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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Modeling Spatial Heterogeneity in Surface Turbulent Heat Flux in the U.S. Southern Great Plains

Advances in numerical modeling of cloud dynamics are driving a need for improved land model prediction at convective storm scales. Here, satellite and ground-based vegetation remote sensing data were combined with land model experiments to more accurately characterize land surface spatial heterogeneity in the Community Land Model (CLM4.0). The new subgrid classification of plant functional types (PFT) and leaf area index (LAI) enables consistent comparison between models and ground-based flux measurements in the U.S. southern Great Plains. Errors in vegetation data sets (inferred from comparison between 250 m satellite and ground-based LAI), while large, had less impact on the simulated characteristics of spatial heterogeneity compared to errors in model representation of surface energy partitioning (between latent and sensible heat flux) and its relationship to LAI. Predicted spatial heterogeneity in surface energy partitioning was enhanced after replacing soil and stomatal resistance parameters with a new set that better predicts the observed relationship to LAI. These modifications increase the number of smaller (mesoscale) dry land patches having higher sensible heat flux. The parameter experiments suggest that vegetation state and processes (transpiration) act to broaden the size spectrum of surface heat flux heterogeneity, which can influence clouds and convective initiation. Moreover, improvements in vegetation input data and model parameters had partially compensating effects on surface flux heterogeneity, indicating the importance of evaluating input data and parameterizations together to improve prediction at higher spatial resolutions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Microbial Community Composition in Deep‐Subsurface Reservoir Fluids Reveals Natural Interwell Connectivity

Abstract The identification of natural fractures and the wells they connect is crucial for the development of geological reservoirs because it may have an important impact on reservoir model construction and hydraulic fracture propagation. In this study we investigated the use of a novel data source, the microbial community composition in the reservoir formation fluids, for identification of interwell connectivity caused by natural fractures. We verified this concept at a newly developed mesoscale enhanced geothermal system (EGS) field testbed located 4,850 ft (1,478 m) beneath ground surface at the Sanford Underground Research Facility in Lead, SD. Fluids produced at or near the EGS testbed were sampled and subjected to high‐throughput 16S rRNA gene amplicon sequencing to analyze the microbial community profile therein. Despite the typically substantial heterogeneity across the community profiles of samples spatially distributed (10 m to 1.9 km apart) throughout the site, samples from two wells at the EGS testbed showed highly similar microbial community composition, suggesting the two wells intersected the same natural fracture. This evidence of natural connectivity between the two wells at the EGS testbed was later corroborated by core log analysis and sewer camera surveys into the boreholes. Besides the field case described in this study, microbial community composition as a reservoir diagnostic tool would be applicable in a much broader context such as unconventional hydrocarbon exploitation, groundwater reservoir characterization, and environmental remediation, adding valuable “hard” data capable of pinpointing the origins of fluids unambiguously.

Zhang, Yuran↗
DOE OSTI2021

Enhance Low Level Temperature and Moisture Profiles Through Combining NUCAPS, ABI Observations, and RTMA Analysis

Thermodynamic information from low levels in the atmosphere is crucial for operational weather forecasts and meteorological researchers. The NOAA Unique Combined Atmospheric Processing System (NUCAPS) sounding products have been proven beneficial to fill the data gap between synoptic radiosonde observations (RAOBs). However, compared with the upper troposphere, the accuracy of NUCAPS soundings in the low levels still needs improvement. In this study, a deep neural network (DNN) is applied to fuse multiple data sources to enhance the NUCAPS temperature and moisture profiles in the lower atmosphere. The network is developed by combining satellite observations, including NUCAPS sounding retrievals and high resolution geostationary satellite observations from the Advanced Baseline Imager, and surface analysis from the Real-Time Mesoscale Analysis (RTMA) as inputs, while collocated soundings from ECMWF re-analysis version 5 are used as the benchmark for the training. The performance of the model is evaluated by using the independent testing data set, data from a different year, as well as collocated RAOBs, showing improvement to the temperature and moisture profiles by reducing the root-mean-squared-error (RMSE) by more than 30% in the lower atmosphere (from 700 hPa to surface) in both clear sky and partially cloudy conditions. A convective event from June 18, 2017 is presented to illustrate the application of the enhanced low level soundings on high impact weather events. The enhanced soundings from fused data capture the large surface-based convective available potential energy structures in the preconvection environment, which is very useful for severe storm nowcasting and forecasting applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

New World Meteorological Organization Certified Megaflash Lightning Extremes for Flash Distance (709 km) and Duration (16.73 s) Recorded From Space

Identification and validation of atmospheric extremes are essential to monitoring climate change, to addressing engineering and safety concerns, and to promoting technological advancement. An international World Meteorological Organization evaluation committee has critically adjudicated and recommended acceptance of two lightning megaflash events (horizontal mesoscale lightning discharges of >100 km in length) as new global extremes using analysis of Geostationary Lightning Mapper data. The world's greatest extent for an individual lightning flash is a single flash that covered a horizontal distance of 709 ± 8 km (441 ± 5 mi) across parts of southern Brazil on 31 October 2018. Furthermore, the greatest duration for a single lightning flash is 16.730 ± 0.002 s from a flash that developed continuously over northern Argentina on 4 March 2019.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Observations and Modeling of Ocean Circulation in the Seychelles Plateau Region

The ocean circulation around and over the Seychelles Plateau is characterized using 35 months of temperature and velocity measurements along with a numerical model. The results here provide the first documented description of the ocean circulation atop the Seychelles Plateau. The Seychelles Plateau is an unusually broad (~200 km), shallow (~50 m) plateau, dropping off steeply to the abyss. It is situated in a dynamic location (3.5-5.5S, 54-57E) in the south-western tropical Indian Ocean where northwesterly winds are present during austral summer and become southeasterly in austral winter, following the reversal of the western Indian Ocean monsoon winds. Measurements around the Inner Islands, on the Seychelles Plateau, have been carried out since 2015. Velocity measurements show that most of the depth-averaged current variance on the Seychelles Plateau arises from near-inertial oscillations and lower-frequency variability. Lower-frequency variability encompasses seasonal and intraseasonal variability, the latter of which includes the effects of mixed Rossby-gravity waves and mesoscale eddies. Here, a global 0.1-degree numerical ocean simulation is used in conjunction with these observations to describe the regional circulation around the Seychelles Plateau. Atop the Seychelles Plateau, circulation is dominated by ageostrophic processes consistent with Ekman dynamics, while around the Seychelles Plateau, both geostrophic and ageostrophic processes are important and vary seasonally. Stratification responds to the sea surface height semi-annual signal which is due to Ekman pumping-driven upwelling (related to the Seychelles-Chagos Thermocline Ridge) and the arrival of an annual downwelling Rossby wave.

58 GEOSCIENCES↗
DOE OSTI2020

Simulating the Effects of Surface Energy Partitioning on Convective Organization: Case Study and Observations in the US Southern Great Plains

Realistic cloud-resolving simulations were performed to study the effects of surface energy partitioning (surface sensible and latent heat fluxes) on the organization of isolated convection into larger mesoscale convective systems (MCSs) near the US Southern Great Plains. The role of cold pools in mediating surface-convection interactions was explored. Better organized MCSs tended to occur in the experiments with perturbed wetter soil (and more active vegetation), regardless of the effects of soil moisture on the diurnal timing of convective triggering. Wetter soil led to shallower boundary layers and more convective available potential energy than drier soil. The roles of cold pools on convection are lifecycle-stage dependent: A dry surface allows more numerous colliding cold pools, thereby aiding in convective triggering by reducing entrainment in the early stages, and providing gust-front uplift in later stages. However, horizontal propagation of the cold-pool density current can outrun the convective system, creating a slantwise updraft and thus weakening the gust front uplift in later stages. This effect calls into question previous cold pool parameterizations, in which the gust front uplift is mainly proportional to the negative buoyancy of cold air. Finally, both the model and observation show an enhancement of surface latent heat flux during the passage of a gust front at night, suggesting that a positive feedback between the surface and convection helps MCSs to persist into the nighttime.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Combined Optical and Radio-Frequency Measurements of a Lightning Megaflash by the FORTE Satellite

The optical and VHF instrumentation on the Fast On-Orbit Recording of Transient Events (FORTE) satellite is used to document the combined phenomenology evolution of a lightning “megaflash” – mesoscale lightning that propagates laterally over exceptional distances. We identify a FORTE flash whose maximum extent was 82 km and inferred length over multiple distinct branches exceeded 100 km. This flash lasted 1.2 s and produced 250 optical and 591 RF events. We find that the channel development mapped by FORTE’s pixelated lightning imager (LLS) occurred at a typical speed of 2.6x10 5 m s -1 and was accompanied by sustained periods of VHF emission that could individually exceed 100 ms in duration. The impulsive IC events generated by the flash indicate that this development occurred at altitudes between 3 and 8 km. Four +CG strokes were identified in the VHF waveform data that are responsible for two of the three highly-radiant LLS groups (two of the +CGs were not as optically bright as the others). These strokes occurred at different locations throughout the flash footprint with the most distant strokes separated by approximately 50 km. These space-based observations match previous observations of megaflashes as well as ground-based measurements of negative leader development during “spider” lightning, suggesting that FORTE is sensing the same phenomena.

Peterson, Michael Jay↗
DOE OSTI2020

Predictive Inverse Model for Advective Heat Transfer in a Short–Circuited Fracture: Dimensional Analysis, Machine Learning, and Field Demonstration

Identifying fluid flow maldistribution in planar geometries is a well–established problem in subsurface science/engineering. Of particular importance to the thermal performance of enhanced (or “engineered”) geothermal systems is identifying the existence of nonuniform (i.e., heterogeneous) permeability and subsequently predicting advective heat transfer. Here, machine learning via a genetic algorithm (GA) identifies the spatial distribution of an unknown permeability field in a two–dimensional Hele–Shaw geometry (i.e., parallel plates). The inverse problem is solved by minimizing the L2 norm between simulated residence time distribution (RTD) and measurements of an inert tracer breakthrough curve (BTC) (C–Dot nanoparticle). Principal component analysis (PCA) of spatially correlated permeability fields enabled reduction of the parameter space by more than a factor of 10 and restricted the inverse search to reservoir–scale permeability variations. Thermal experiments and tracer tests conducted at the mesoscale Altona Field Laboratory (AFL) demonstrate that the method accurately predicts the effects of extreme flow channeling on heat transfer in a single bedding–plane rock fracture. However, this is only true when the permeability distributions provide adequate matches to both tracer RTD and frictional pressure loss. Without good agreement to frictional pressure loss, it is still possible to match a simulated RTD to measurements, but subsequent predictions of heat transfer are grossly inaccurate. Here, the results of this study suggest that it is possible to anticipate the thermal effects of flow maldistribution, but only if both simulated RTDs and frictional pressure loss between fluid inlets and outlets are in good agreement with measurements.

42 ENGINEERING↗
DOE OSTI2021

Multilayer Network Clarifies Prevailing Water Consumption Telecouplings in the United States

Virtual water flows are used to map the indirect water consumption connections implied by the supply chain of a city, region, or country. This information can be used to manage supply chains to achieve environmental policy objectives and mitigate environmental risks to critical supply chains. A limitation of prior work is that these flows are typically analyzed using monolayer networks, which ignores crucial intersectoral or interlayer couplings. Here, in this study, we use a multilayer network to account for such couplings when analyzing blue virtual water flows in the United States. Our multilayer network consists of 115 different regions (nodes), covering the entire conterminous United States; 41 coupled economic sectors (layers); and ∼2 × 10 7 possible links. To analyze the multilayer network, we focus on three fundamental network properties: topological connectivity, mesoscale structure, and node centrality. The network has a high connectivity, with each node being on average connected to roughly 2/3 of the network's nodes. Interlayer flows are a major driver of connectivity, representing ∼54% of all the network's connections. Five different groups of tightly connected nodes (communities) characterize the network. Each community represents a preferred spatial mode of long-range virtual water interaction within the United States. We find that large (populous) cities have a stronger influence than small ones on network functioning because they attract and recirculate more virtual water through their supply chains. Our results also highlight differences between the multilayer and monolayer virtual water network, which overall show that the former provides a more realistic representation of virtual water flows.

Garcia Gonzalez, Susana↗
DOE OSTI2022

Baroclinic Control of Southern Ocean Eddy Upwelling Near Topography

In the Southern Ocean, mesoscale eddies contribute to the upwelling of deep waters along sloping isopycnals, helping to close the upper branch of the meridional overturning circulation. Eddy energy (EE) is not uniformly distributed along the Antarctic Circumpolar Current (ACC). Instead, “hotspots” of EE that are associated with enhanced eddy-induced upwelling exist downstream of topographic features. This study shows that, in idealized eddy-resolved simulations, a topographic feature in the ACC path can enhance and localize eddy-induced upwelling. However, the upwelling systematically occurs in regions where eddies grow through baroclinic instability, rather than in regions where EE is large. Across a range of parameters, along-stream eddy growth rate is a more reliable indicator of eddy upwelling than traditional parameterizations such as eddy kinetic energy, eddy potential energy, or isopycnal slope. Ocean eddy parameterizations should consider metrics specific to the growth of baroclinic instability to accurately model eddy upwelling near topography.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Crucial roles of eastward propagating environments in the summer MCS initiation over the U.S. Great Plains

Mesoscale convective systems (MCSs) frequently occur over the U.S. Great Plains during summer. An analysis using self-organizing map is conducted to identify four types of summer MCS initiation environments during 2004-2017. The first two types feature favorable large-scale environments at both upper and low levels, while Type-3 has favorable lower-level and surface conditions but unfavorable upper-level circulation, and Type-4 features the most unfavorable large-scale environments for MCS initiation. Despite the unfavorable large-scale environment, the convection-centered environments in Type-4 are favorable for MCS initiation and similar to the first two types, suggesting a role of sub-synoptic disturbances as an MCS precursor. All four types of the MCS initiation delineate a clear eastward propagating feature in many fields, such as upper-level potential vorticity/geopotential height, surface pressure and surface equivalent potential temperature, upstream up to 25°-longitude west of and ~36 hours before the MCS initiation. The propagating environments and local, non-propagating low-level moisture are found to be important in MCS initiation at the foothill of the Rocky Mountains, but over the central Great Plains, it is the coupling of dynamical and moisture anomalies associated with propagating waves that results in the MCS initiation. By tracking MCSs and mid-tropospheric perturbations (MPs), a type of sub-synoptic disturbances with Rocky Mountains origin, ~30% of MPs is associated with MCS initiation, mostly in Type-4. Although MPs are related to a small fraction of MCS initiation, MCSs that are associated with MPs tend to produce more rainfall in a larger area with a stronger convective intensity, suggesting MPs to be a source of intense MCSs in summer.

Song, Fengfei↗
DOE OSTI2021

Ice Nucleating Particle Connections to Regional Argentinian Land Surface Emissions and Weather During the Cloud, Aerosol, and Complex Terrain Interactions Experiment

Abstract Here, we present a multi‐season study of ice‐nucleating particles (INPs) active via the immersion freezing mechanism, which took place in north‐central Argentina, a worldwide hotspot for mesoscale convective storms. INPs were measured untreated, after heating to 95°C, and after hydrogen peroxide digestion. No seasonal cycle of INP concentrations was observed. Heat labile INPs, which we define as “biological” herein, dominated the population active at −5 to −20°C, while non‐heat‐labile organic INPs (decomposed by peroxide) dominated at lower temperatures, from −20 to −28°C. Inorganic INPs (remaining after peroxide digestion), were minor contributors to the overall INP activity. Biological INP concentration active around −12°C peaked during rain events and under high relative humidity, reflecting emission mechanisms independent of the background aerosol concentration. The ratio of non‐heat‐labile organic and inorganic INPs was generally constant, suggesting they originated from the same source, presumably from regional arable topsoil based on air mass histories. Single particle mass spectrometry showed that soil particles aerosolized from a regionally common agricultural topsoil contained known mineral INP sources (K‐feldspar and illite) as well as a significant organic component. The INP activity observed in this study correlates well with agricultural soil INP activities from this and other regions of the world, suggesting that the observed INP spectra might be typical of many arable landscapes. These results demonstrate the strong influence of regional continental landscapes, emitting INPs of types that are not yet well represented in global models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Climatology of the Vertical Profiles of Polarimetric Radar Variables and Retrieved Microphysical Parameters in Continental/Tropical MCSs and Landfalling Hurricanes

Most existing cloud models tend to overestimate the size of cloud ice particles and underestimate their concentration. This emphasizes the need to provide a reliable observational reference to optimize cloud model performance, particularly in areas of high concentration of ice at high altitudes. The dual-polarization radars give the community a unique opportunity to quantify cloud ice with a good accuracy using polarimetric radar retrievals. Here, in this study, we utilize the network of operational WSR-88D radars to build a climatology of the vertical profiles of radar variables, such as radar reflectivity Z, differential reflectivity Z DR , and specific differential phase K DP as well as the radar-retrieved vertical profiles of ice water content (IWC) above the melting layer and liquid water content below it, mean volume diameter D m , and total number concentration N t of ice and liquid particles. Such climatology was created for continental/marine mesoscale convective systems (MCSs) and tropical cyclones including hurricanes. The dataset includes 13 continental MCSs, 10 marine MCSs, and 11 tropical cyclones. Separate statistics of the “background” vertical profiles and the ones associated with high IWC aloft have been obtained in the course of this study. It is shown that continental MCSs exhibit larger size of ice in lower concentration aloft compared to the marine MCSs and especially tropical cyclones/hurricanes. A combination of high KDP and low Z aloft signifies lower D m , higher N t , and often substantial IWC.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The Behaviors of Intraseasonal Cloud Organization During DYNAMO/AMIE

This study investigates the organization of tropical convection associated with the Madden-Julian Oscillation (MJO) during the Dynamics of the MJO/Atmospheric Radiation Measurement MJO Investigation Experiment field campaign. While it is known that tropical clouds can organize and impact the large-scale environment, how this occurs, and its underlying mechanism are not fully understood. Application of several existing cloud organization indices showed inconsistent evolutions in the measured degree of organization with the MJO. The inconsistency arises from the varying definitions and assumptions of cloud organization behaviors that are applied to each index. While these indices often combine different properties of clouds, such as their number density, size, and distance between them, the analysis of these properties separately provided further understanding of how clouds organize with the MJO. Using the rainfall clusters identified from the S-Polka radar, we find that deep convective rainfall clusters begin to increase their number density before the arrival of MJO enhanced convective center, which is accompanied by increased proximity (shorter distance to each other) and followed by growth in their size. However, the nonrandomness in the spatial distribution of rainfall clusters maximizes as MJO convection decays. Deep convective clusters become the least randomly distributed as the clusters decay because of the suppression and decay of isolated deep convective cells, while clustered deep convective cells exist longer. This evolution of cloud organization is analogous to mesoscale convective systems, indicating that the duration and frequency of their organization stages are altered by the large-scale environmental perturbations associated with the MJO.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Cloud Morphology Evolution in Arctic Cold‐Air Outbreak: Two Cases During COMBLE Period

Abstract Cloud feedbacks play an important role in Arctic warming. Cloud morphology, for example, cloud size and spatial distributions, is among key factors that directly impact their radiative effects. In this work, we use two cases observed during the Cold‐air Outbreak (CAO) in the Marine Boundary Layer Experiment (COMBLE) to study the evolution of cloud size distributions as an air mass is advected from the Arctic over a comparatively warm ocean and cloud mesoscale organization changes from rolls to cells. Cloud objects are identified from Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance images through an object segmentation procedure and roll breakup is identified by homogeneities in cloud water path (CWP). Roll breakup is found to be accompanied by a local minimum in wind shear and local maxima in cloud size and marine cold air outbreak index. The mean cloud horizontal aspect ratio has weak fetch dependency and is around 2 in roll, transition, and cell regimes. Regardless of distance from the ice edge, smaller clouds (<10 km 2 ) dominate the population number but not cloud cover. Cloud size distributions show bimodality in transition and cell regimes. For clouds with comparable sizes, mean nearest neighbor distances normalized by equivalent cloud radius converge to a single value for all regimes and for all but the smallest clouds, suggesting that clouds of comparable sizes in CAOs are separated by distance proportional to their sizes. The presented statistical results pave the way to evaluating model simulated cloud organizations during CAO events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Impacts of Lake Surface Temperature on the Summer Climate Over the Great Lakes Region

The surface of the Great Lakes interacts with the atmosphere, influencing the weather and climate over the Great Lakes Region (GLR). However, most climate models were not designed with sufficient emphasis on lake–atmosphere interactions, which could potentially cause model biases over the GLR. To understand how lake surface temperature (LST) affects the regional summer climate over the GLR, we conducted twin experiments using the Weather Research and Forecasting model at a spatial resolution of 4 km using two different LST data sets as the bottom boundary condition over the Great Lakes. In this work, our simulations include 10 ensemble members for the summer of 2018 and a single multiyear run for the summers of 2014–2020. Results show that variations in LST influence atmospheric temperature and moisture at a local scale—while affecting the convective environment and precipitation processes over a much larger spatial scale. In particular, an LST that is only 1°C–3°C warmer (depending on the lake) increases near-surface air temperature by 1.93°C and 0.97°C over Lake Superior and Lake Erie, respectively, and increases evaporation over the lakes by 0.23 and 1.1 mm day –1 . The warmer LST reduces mesoscale convective precipitation upstream of the GLR; however, it increases isolated deep convective precipitation and nonconvective precipitation downstream of GLR due to increased local instability and enhancement of moisture transport. Our analyses confirm the robustness of these impacts, which is at least 2 times larger than the model internal variability and is seen across all simulated summer seasons.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Predicting Thermal Performance of an Enhanced Geothermal System From Tracer Tests in a Data Assimilation Framework

Abstract Predicting the thermal performance of an enhanced geothermal system (EGS) requires a comprehensive characterization of the underlying fracture flow patterns from practically available data such as tracer data. However, due to the inherent complexities of subsurface fractures and the generally insufficient geological/geophysical data, interpreting tracer data for fracture flow characterization and thermal prediction remains a challenging task. The present study aims to tackle the challenge by leveraging a data assimilation method to maximize the utilization of information inherently contained in tracer data, and meanwhile maintain the flexibility to handle various uncertainties. A tracer data interpretation framework was proposed with the following three components integrated: (a) We use principal component analysis (PCA) to reduce the dimensionality of model parameter space. (b) We use ES‐MDA (ensemble smoother with multiple data assimilation) to invert for fracture aperture/flow fields and obtain posterior model ensembles for uncertainty quantification. Various data types are assimilated jointly to improve the predictive ability of the posterior ensemble. (c) The inverted fracture aperture fields are then incorporated into reservoir models to predict thermal performance. We developed a field‐scale EGS model to verify the ability of the framework to characterize highly heterogeneous fracture aperture/flow fields and predicting thermal performance. We also applied the framework to a mesoscale field experiment to demonstrate its potential application in real‐world geothermal reservoirs. The results indicate that the proposed framework can effectively retrieve fracture flow information from tracer data for thermal prediction and uncertainty quantification, and thus provide informative guidance for EGS optimization and risk management.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Impacts of Large-Scale Urbanization and Irrigation on Summer Precipitation in the Mid-Atlantic Region of the United States

This study investigates how urbanization and irrigation in the United States east of the Rocky Mountains affect summer precipitation in the Mid-Atlantic region (MAR) using convection-permitting Weather Research and Forecasting model simulations with/without urbanization or irrigation. In this work, a feature tracking algorithm is used to identify precipitation from mesoscale convective systems (MCSs), isolated deep convection (IDC), and non-convective systems (NC). Overall, urbanization suppresses all three types of precipitation in the MAR by reducing water vapor content and convective available potential energy, while irrigation enhances IDC and NC precipitation but suppresses MCS precipitation. Examination of the MCS and IDC initiation locations indicates that irrigation suppresses MAR precipitation that is produced by MCSs initiated in the Great Plains and Midwest (GP) but enhances MAR precipitation from MCSs initiated locally within the region. Irrigation induces a mid-level cyclonic circulation anomaly centering in the Southeast, hindering the eastward propagation and development of MCSs from the GP.

54 ENVIRONMENTAL SCIENCES↗