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DOE OSTI2026

Upper ocean mixing, surface heat fluxes, and heat content variability in the upper 150 m during Hurricane Laura (2020)

Observations (from thermistor sensors and a hurricane glider) and model-based temperature were used to answer questions including the following: 1) What physical and environmental conditions explain the rapid intensification of Hurricane Laura? 2) How did the pre-existing warm mixed layer at Stone mooring (StM) influence the degree of cooling in the mixed layer? 3) How did vertical mixing, surface heat fluxes, and advective processes collectively shape the mixed layer heat evolution at StM? Observations measured by thermistor sensors showed that Hurricane Laura induced a cooling of -1.2oC in the mixed layer when Hurricane Laura’s wind speed increased to 47 m/s on 26 August. This contrasts with the -1.04oC mixed layer temperature change estimated from model-based temperature. At StM, the presence of a 31oC warm mixed layer and elevated heat content (60-80kJ/cm2) effectively preconditioned the upper ocean ahead of Hurricane Laura’s passage. After Hurricane Laura passed, turbulent mixing associated with the storm transported the heat anomalies downward into subsurface layers. In addition, this study shows that a surface heat flux of 5.04 kJ/cm2 supported the intensity of Hurricane Laura as it traversed over the StM. Using a mixed layer heat balance model, this study shows that entrainment flux and surface flux mostly contributed to the observed change in the mixed layer temperature.

Tsai, Senam↗

DOE OSTI2024

Modeled estimates of permafrost hydrology and related fields for pan-Arctic region over the period 1980-2100

This dataset contains gridded estimates of total runoff (mm/day); subsurface runoff (mm/day); snow water equivalent (SWE, mm/day); vertical upward water flux of combined surface evaporation, evapotranspiration, and snow sublimation (mm/day); and soil temperature (C) across the pan-Arctic basin from simulations of the Permafrost Water Balance Model (PWBM v4). These data were generated to allow researchers to advance understanding of the changes unfolding in the Arctic's terrestrial water cycle under the influences of climate warming, hydrological cycle intensification, and permafrost thaw. The dataset will enable researchers to address important questions spanning multiple disciplines. For example, how will rising river flows exported to the coast impact critical zone ecosystems, near-shore ice dynamics, and ocean biogeochemical processes. Spatial resolution is 25x25 km with N=39926 grid cells spanning the domain. Three forcing datasets were used to drive simulations at an implicit daily time step over the period 1980-2100. Daily air temperature, precipitation, and wind speed data from the WATCH Forcing Data methodology applied to ERA5 reanalysis (W5E5) were used for meteorological forcings over the period 1980-2019. Simulations for the period 1980-2100 used meteorological data from two global climate models; IPSL-CM6A-LR and MPI-ESM1-2-HR. The PWBM hydrological outputs are organized by grid and month in gzipped ASCII text files within each archived tar file. Soil temperature is organized by grid cell and day of year from DOY 205 to DOY 260. No special software is required to work with these data. The package contains spatial domain and river basin information files. These data are most useful for analyses of the spatial and temporal variations in terrestrial hydrology and soil thermal dynamics. A manuscript describing the model simulations and associated analysis has been accepted for publication in The Cryosphere (Rawlins and Karmalkar, 2024).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Assimilating Scanning Radar Data into Cloud-Scale Models

The aim of this project is to improve the initial conditions of large eddy simulations (LES) of deep convective storms by assimilating scanning radar reflectivity and radial velocity data as well as local environmental observations. Accomplishing this goal often results in more accurate numerical forecasts of clouds and precipitation than if the background initial meteorological conditions are solely relied upon for convection initiation and intensification, as is typical of most operational and research models. Conducted in a storm-scale LES framework, these more accurate numerical analyses can serve as tool to better understand and parameterize land-atmosphere coupling, boundary layer turbulence, and cloud processes, each used for model parameterization development of convection. Our work examined the sensitivity of the numerical representation of cloud-scale wind and microphysical structures to: i) the assimilation of radiosonde observations characterizing the near-storm inflow, ii) the assimilation of radar data of varying resolution for model simulations with grid spacings of 1-km and 0.25-km, and iii) to the assimilation of three-dimensional plan-projection-indicator (PPI) and range-height indicator (RHI) radar volumes. Few studies have explored deep convective storm analyses and forecasts produced by assimilation of radar observations to cloud-scale LES. Furthermore, to our knowledge, no storm-scale DA study has explored the value of assimilating high-resolution sector RHI volumes to determine if they can improve the retrieval of the vertical kinematic and microphysical storm structure aloft over the use of traditionally utilized PPI scans.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1984

Numerical Prediction of the President's Day Cyclone

Numerical-diagnostic studies of major anomalous weather events are being conducted in order to investigate the relevant physical processes associated with the events and the role of satellite observing systems in the analysis and prediction of these phenomena. One component of this study is concerned with the numerical prediction of intense coastal and oceanic cyclogenesis. The specific objectives of this research are: (1) to assess the accuracy of Goddard Laboratory for Atmospheric Sciences model predictions of cyclogenesis, (2) to determine the importance of large scale dynamical processes and diabatic heating to the prediction, and (3) to evaluate the sensitivity of the model predictions to the initial conditions. It was shown that diabatic heating resulting from oceanic fluxes significantly contributed to the generation of low level cyclonic vorticity and the intensification and slow rate movement of an upper level ridge over the western Atlantic. As an upper level short-wave trough approached this ridge, diabatic heating associated with the release of latent heat intensified, and the gradient of vorticity, vorticity advection, upper level divergence, and upward vertical motion in advance of the trough were greatly increased, providing strong large-scale forcing for the surface cyclogenesis.

Atlas, R.↗

DOE OSTI2024

Regime shifts in Arctic terrestrial hydrology manifested from impacts of climate warming

Abstract. Anthropogenic warming in the Arctic is causing hydrological cycle intensification and permafrost thaw, with implications for flows of water, carbon, and energy from terrestrial biomes to coastal zones. To better understand the likely impacts of these changes, we used a hydrology model driven by meteorological data from atmospheric reanalysis and two global climate models for the period 1980–2100. The hydrology model accounts for soil freeze–thaw processes and was applied across the pan-Arctic drainage basin. The simulations point to greater changes over northernmost areas of the basin underlain by permafrost and to the western Arctic. An acceleration of simulated river discharge over the recent past is commensurate with trends drawn from observations and reported in other studies. Between early-century (2000–2019) and late-century (2080–2099) periods, the model simulations indicate an increase in annual total runoff of 17 %–25 %, while the proportion of runoff emanating from subsurface pathways is projected to increase by 13 %–30 %, with the largest changes noted in summer and autumn and across areas with permafrost. Most notably, runoff contributions to river discharge shift to northern parts of the Arctic Basin that contain greater amounts of soil carbon. Each season sees an increase in subsurface runoff; spring is the only season where surface runoff dominates the rise in total runoff, and summer experiences a decline in total runoff despite an increase in the subsurface component. The greater changes that are seen in areas where permafrost exists support the notion that increased soil thaw is shifting hydrological contributions to more subsurface flow. The manifestations of warming, hydrological cycle intensification, and permafrost thaw will impact Arctic terrestrial and coastal environments through altered river flows and the materials they transport.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Strategic roadmap to assess forest vulnerability under air pollution and climate change

Abstract Although it is an integral part of global change, most of the research addressing the effects of climate change on forests have overlooked the role of environmental pollution. Similarly, most studies investigating the effects of air pollutants on forests have generally neglected the impacts of climate change. We review the current knowledge on combined air pollution and climate change effects on global forest ecosystems and identify several key research priorities as a roadmap for the future. Specifically, we recommend (1) the establishment of much denser array of monitoring sites, particularly in the South Hemisphere; (2) further integration of ground and satellite monitoring; (3) generation of flux‐based standards and critical levels taking into account the sensitivity of dominant forest tree species; (4) long‐term monitoring of N, S, P cycles and base cations deposition together at global scale; (5) intensification of experimental studies, addressing the combined effects of different abiotic factors on forests by assuring a better representation of taxonomic and functional diversity across the ~73,000 tree species on Earth; (6) more experimental focus on phenomics and genomics; (7) improved knowledge on key processes regulating the dynamics of radionuclides in forest systems; and (8) development of models integrating air pollution and climate change data from long‐term monitoring programs.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2006

The Effect of the Saharan Air Layer on the Formation of Hurricane Isabel (2003) Simulated with AIRS Data

The crucial physics of how the atmosphere really accomplishes the tropical cyclogenesis process is still poorly understood. The presence of the Saharan Air Layer (SAL), an elevated mixed layer of warm and dry air that extends from Africa to the tropical Atlantic and contains a substantial amount of mineral dust, adds more complexity to the tropical cyclogenesis process in the Atlantic basin. The impact of the SAL on tropical cyclogenesis is still uncertain. Karyampudi and Carlson (1988) conclude that a strong SAL can potentially aid tropical cyclone development while Dunion and Velden (2004) argue that the SAL generally inhibits tropical cyclogenesis and intensification. Advancing our understanding of the physical mechanisms of tropical cyclogenesis and the associated roles of the SAL strongly depends on the improvement in the observations over the data-sparse ocean areas. After the Atmospheric Infrared Sounder (AIRS), the Advanced Microwave Sounding Unit (AMSU), and the microwave Humidity Sounder of Brazil (HSB) were launched with the NASA Aqua satellite in 2002, new data products retrieved from the AIRS suite became available for studying the effect of the warm, dry air mass associated with the SAL (referred to as the thermodynamic effect). The vertical profiles of the AIRS retrieved temperature and humidity provide an unprecedented opportunity to examine the thermodynamic effect of the SAL. The observational data can be analyzed and assimilated into numerical models, in which the model thermodynamic state is allowed to relax to the observed state from AIRS data. The objective of this study is to numerically demonstrate that the thermodynamic effect of the SAL on the formation of Hurricane Isabel (2003) can be largely simulated through nudging of the AIRS data.

Wu, iguang↗

DOE OSTI2020

Impacts of directed evolution and soil management legacy on the maize rhizobiome

Domestication and agricultural intensification dramatically altered maize and its cultivation environment. Changes in maize genetics (G) and environmental (E) conditions increased productivity under high-synthetic-input conditions. However, novel selective pressures on the rhizobiome may have incurred undesirable tradeoffs in organic agroecosystems, where plants obtain nutrients via microbially mediated processes including mineralization of organic matter. Using twelve maize genotypes representing an evolutionary transect (teosintes, landraces, inbred parents of modern elite germplasm, and modern hybrids) and two agricultural soils with contrasting long-term management, here we integrated analyses of rhizobiome community structure, potential microbe-microbe interactions, and N-cycling functional genes to better understand the impacts of maize evolution and soil management legacy on rhizobiome recruitment. We show complex shifts in rhizobiome communities during directed evolution of maize (defined as the transition from teosinte to modern hybrids), with a larger effect of domestication (teosinte to landraces) than modern breeding (inbreds to hybrids) on rhizobiome structure and greater impacts of modern breeding on potential microbe-microbe interactions. Rhizobiome structure was significantly correlated with plant nutrient composition. Furthermore, plant biomass and nutrient content were affected by G x E interactions in which teosinte and landrace genotypes had better relative performance in the organic legacy soil than inbred and modern genotypes. The abundance of six N-cycling genes of relevance for plant nutrition and N loss pathways did not significantly differ between teosinte and modern rhizospheres in either soil management legacy. These results provide insight into the potential for improving maize adaptation to organic systems and contribute to interdisciplinary efforts toward developing resource-efficient, biologically based agroecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2000

Global Remote Sensing of Precipitating Electron Energies: A Comparison of Substorms and Pressure Pulse Related Intensifications

The Polar Ultraviolet Imager (UVI) observes aurora responses to incident solar wind pressure pulses and interplanetary shocks such its those associated with coronal mass ejections. Previous observations have demonstrated that the arrival of it pressure pulse at the front of the magnetosphere results in highly disturbed geomagnetic conditions and a substantial increase in both dayside and nightside aurora precipitations. Our observations show it simultaneous brightening over bread areas of the dayside and nightside auroral in response to a pressure pulse, indicating that more magnetospheric regions participate as sources for auroral precipitation than during isolate substorm. We estimate the characteristic energies of incident auroral electrons using Polar UVI images and compare the precipitation energies during pressure pulse associated event to those during isolated substorms. We estimate the characteristic energies of incident auroral electrons using Polar UVI images and compare the precipitation energies during pressure pulse associated events to those during isolated auroral substorms. Electron precipitation during substorms has characteristic energies greater than 10 KeV and is structured both in local time and in magnetic latitude. For auroral intensifications following the arrival of'a pressure pulse or interplanetary shock. Electron precipitation is less spatially structured and has greater flux of lower characteristic energy electrons (Echar less than 7 KeV) than during isolated substorm onsets. These observations quantify the differences between global and local auroral precipitation processes and will provide a valuable experimental check for models of sudden storm commencements and magnetospheric response to perturbations in the solar wind.

Chua, D.↗

NASA NTRS2020

Using GLM Flash Density, Flash Area, and Flash Energy to Diagnose Tropical Cyclone Structure and Intensification

Increased lightning in tropical cyclones (TCs) is typically associated with intensification, but significant lightning outbreaks are also observed in weakening storms. The total number of lightning flashes in a TC is not always a reliable indicator of TC intensity evolution. Issues with the range and detection efficiency of ground-based networks, particularly for intracloud lightning. Physical processes such as vertical wind shear can intensify asymmetric convection while also weakening the TC. The commissioning of the Geostationary Lightning Mapper (GLM) aboard GOES-16 and GOES-17 marked, for the first time, the presence of an operational lightning detector in geostationary orbit. In addition to flash density (the number of flashes per unit area per unit time), GLM also provides continuous observations of flash area and total optical energy.

Duran, Patrick↗

NASA NTRS2010

The Impact of Microphysical Schemes on Intensity and Track of Hurricane

During the past decade, both research and operational numerical weather prediction models [e.g. Weather Research and Forecasting Model (WRF)] have started using more complex microphysical schemes originally developed for high-resolution cloud resolving models (CRMs) with a 1-2 km or less horizontal resolutions. The WRF is a next-generation meso-scale forecast model and assimilation system that has incorporated a modern software framework, advanced dynamics, numeric and data assimilation techniques, a multiple moveable nesting capability, and improved physical packages. The WRF model can be used for a wide range of applications, from idealized research to operational forecasting, with an emphasis on horizontal grid sizes in the range of 1-10 km. The current WRF includes several different microphysics options. At Goddard, four different cloud microphysics schemes (warm rain only, two-class of ice, two three-class of ice with either graupel or hail) are implemented into the WRF. The performances of these schemes have been compared to those from other WRF microphysics scheme options for an Atlantic hurricane case. In addition, a brief review and comparison on the previous modeling studies on the impact of microphysics schemes and microphysical processes on intensity and track of hurricane will be presented. Generally, almost all modeling studies found that the microphysics schemes did not have major impacts on track forecast, but did have more effect on the intensity. All modeling studies found that the simulated hurricane has rapid deepening and/or intensification for the warm rain-only case. It is because all hydrometeors were very large raindrops, and they fell out quickly at and near the eye-wall region. This would hydrostatically produce the lowest pressure. In addition, these modeling studies suggested that the simulated hurricane becomes unrealistically strong by removing the evaporative cooling of cloud droplets and melting of ice particles. This is due to the much weaker downdraft simulated. However, there are many differences between different modeling studies and these differences were identified and discussed.

Tao, W. K.↗

NASA NTRS2003

Seasonal Evolution and Variability Associated with the West African Monsoon System

In this study, we investigate the seasonal variations in surface rainfall and associated large-scale processes in the tropical eastern Atlantic and West African region. The 5-yr (1998-2002) high-quality TRMM rainfall, sea surface temperature (SST), water vapor and cloud liquid water observations are applied along with the NCEP/NCAR reanalysis wind components and a 3-yr (2000-2002) Quickscat satellite-observed surface wind product. Major mean rainfall over West Africa tends to be concentrated in two regions and is observed in two different seasons, manifesting an abrupt shift of the mean rainfall zone during June-July. (i) Near the Gulf of Guinea (about 5 degN), intense convection and rainfall are seen during April-June and roughly follow the seasonality of SST in the tropical eastern Atlantic. (ii) Along the latitudes of about 10 deg. N over the interior West African continent, a second intense rain belt begins to develop from July and remains there during the later summer season. This belt co-exists with a northwardmoved African Easterly Jet (AEJ) and its accompanying horizonal and vertical shear zones, the appearance and intensification of an upper tropospheric Tropical Easterly Jet (TEJ), and a strong low-level westerly flow. Westward-propagating wave signals [ i e . , African easterly waves (AEWs)] dominate the synoptic-scale variability during July-September, in contrast to the evident eastward-propagating wave signals during May- June. The abrupt shift of mean rainfall zone thus turns out to be a combination of two different physical processes: (i) Evident seasonal cycles in the tropical eastern Atlantic ocean which modulate convection and rainfall in the Gulf of Guinea by means of SST thermal forcing and SST-related meridional gradient; (ii) The interaction among the AEJ, TEJ, low-level westerly flow, moist convection and AEWs during July-September which modulates rainfall variability in the interior West Africa, primarily within the ITCZ rain band. Evident seasonality in synoptic-scale wave signals is shown to be a good evidence for this seasonal evolution.

Gu, Guojun↗

DOE OSTI2021

Anthropogenic influence on extreme precipitation over global land areas seen in multiple observational datasets

The intensification of extreme precipitation under anthropogenic forcing is robustly projected by global climate models, but highly challenging to detect in the observational record. Large internal variability distorts this anthropogenic signal. Models produce diverse magnitudes of precipitation response to anthropogenic forcing, largely due to differing schemes for parameterizing subgrid-scale processes. Meanwhile, multiple global observational datasets of daily precipitation exist, developed using varying techniques and inhomogeneously sampled data in space and time. Previous attempts to detect human influence on extreme precipitation have not incorporated model uncertainty, and have been limited to specific regions and observational datasets. Using machine learning methods that can account for these uncertainties and capable of identifying the time evolution of the spatial patterns, we find a physically interpretable anthropogenic signal that is detectable in all global observational datasets. Machine learning efficiently generates multiple lines of evidence supporting detection of an anthropogenic signal in global extreme precipitation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

A Process Model for ITCZ Narrowing under Warming Highlights Clear-Sky Water Vapor Feedbacks and Gross Moist Stability Changes in AMIP Models

Tropical areas with mean upward motion—and as such the zonal-mean intertropical convergence zone (ITCZ)—are projected to contract under global warming. To understand this process, a simple model based on dry static energy and moisture equations is introduced for zonally symmetric overturning driven by sea surface temperature (SST). Processes governing ascent area fraction and zonal mean precipitation are examined for insight into Atmospheric Model Intercomparison Project (AMIP) simulations. Bulk parameters governing radiative feedbacks and moist static energy transport in the simple model are estimated from the AMIP ensemble. Uniform warming in the simple model produces ascent area contraction and precipitation intensification—similar to observations and climate models. Contributing effects include stronger water vapor radiative feedbacks, weaker cloud-radiative feedbacks, stronger convection-circulation feedbacks, and greater poleward moisture export. The simple model identifies parameters consequential for the inter-AMIP-model spread; an ensemble generated by perturbing parameters governing shortwave water vapor feedbacks and gross moist stability changes under warming tracks inter-AMIP-model variations with a correlation coefficient ~0.46. Here, the simple model also predicts the multimodel mean changes in tropical ascent area and precipitation with reasonable accuracy. Furthermore, the simple model reproduces relationships among ascent area precipitation, ascent strength, and ascent area fraction observed in AMIP models. A substantial portion of the inter-AMIP-model spread is traced to the spread in how moist static energy and vertical velocity profiles change under warming, which in turn impact the gross moist stability in deep convective regions—highlighting the need for observational constraints on these quantities.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1996

Moderate Geomagnetic Storms: Interplanetary Origins and Coupling Functions (ISEE3 Data)

Geomagnetic storms are related to the ring current intensification, which is driven by energy injection primarily during energetic solar wind-magnetosphere coupling due to reconnection at the magnetopause. This work identified the interplanetary origins of moderate geomagnetic storms (-100nT is less or equal to Dst(sub peak) is less than or equal to -50 nT) and analyzed the coupling processes during the storm main phase at solar maximum (1978-1979).

Mendes, Odim, Jr.↗

NASA NTRS1976

Photographic image intensification by autoradiography

Images on developed photographic emulsions can be significantly intensified by making the image silver radioactive and exposing a second emulsion to this radiation. Because the print, an autoradiograph, reproduces the original with significant increases in density and contrast, the method can be used to enhance underexposed emulsions and to increase the limits of photographic detection. This paper reports a new, practical chemical method for activating the silver, using thiourea labeled with sulfur-35, a process convenient for use in photographic laboratories. Speed increases of 13 and contrast increases of 18 were achieved with Kodak Plus-X film in this initial phase.

Askins, B. S.↗

DOE OSTI2024

Uncertainty characterization in a coupled human-natural system: Modeling agricultural adaptation in the Great Lakes Region

The Great Lakes Region's water quality and ecological health are threatened by the export of nutrients from agricultural lands, which causes eutrophication, hypoxia, and destructive algal blooms. The intensification of hydrologic cycles brought about by climate change is expected to exacerbate nutrient loading in the region, and, at the same time, agricultural adaptation to changing conditions is also expected to affect loading through shifting amounts and timing of fertilization. Quantifying these future effects and their interactions necessitates modeling both the human and natural processes as a coupled system, by pairing land use and agricultural management with hydrologic modeling. At the same time, compounding uncertainties arising from the complex interactions in both systems significantly limit our predictive understanding of the region's impacts. This study utilizes the Soil and Water Assessment Tool (SWAT), developed for simulating the impact of various farmer decisions on watershed functions in Western Lake Erie watersheds, and an under-development agent-based model (ABM) for agricultural management decisions. The aim of this study is to use global sensitivity analysis on the coupled ABM and SWAT models to quantify how uncertainty in both models interactively affects nutrient loading. To do so, we will conduct Sobol sensitivity analysis experiments at different levels of coupling assumptions to quantify how various uncertain factors (e.g., soil moisture and crop choice) and their interactions affect our estimates of nutrient loading. The results of this analysis will allow us to quantify how complex interactions and dependencies between both systems amplify the effect of uncertainties. Insights gained from this study will have broader implications for modeling the adaptive co-evolution of human and natural systems under climate change and can inform effective management of nutrient loading in the Great Lakes Region.

Climate Change↗

DOE OSTI2024

Urban morphology and urban water demand evolution in the Los Angeles region

Detailed description of the dataset sources used in this study, the experimental workflow, and plotting for the paper figures provided at the associated GitHub Meta Repo: https://github.com/IMMM-SFA/Ferencz_et_al_2024_ERL The future water demand projections from this study are hypothetical future water demands that reflect the population and urban land cover changes represented by the scenarios considered. The intent and emphasis of this work is investigating the interactions between population change, evolution of urban morphology, and water demand. These projections are not meant to be likely future demands for specific water providers or the LA region and should not be interpreted as such. The folders contain input and output data for each step of the "Recreate my Experiment" workflow described in the associated GitHub meta-repository as well as data used for plotting Figures for the paper that this dataset supports. Description of each folder's contents and use: Step_1a: All necessary inputs to the associated python script provided on the GitHub repo. Step_1b: All necessary inputs (downscaled population rasters) used by the associated python script provided on the GitHub repo. Original 1-km squared rasters that were downscaled also provided. Step_1c: Urban growth projection rasters corresponding to SSP3 and SSP5 population scenarios are provided in separate subfolders as well as the water provider boundaries used for analysis. Outputs of data processing also provided. Associated python script provided on GitHub. Step_1d: Description of Inputs used by the QGIS Model Builder GUI that automates geospatial processing and clipping the of the high resolution land cover data for each urban land class footprint within a defined polygon boundary. The Model Builder is provided on the GitHub repo and can be used by QGIS. The outputs of this step are in "Clipped Provider Hi Res Landcover". If the user wants to use The Model Builder for different regions of LA or two test our outputs, they will need to download the hi resolution landcover raster listed in the Readme and in Ref [2] of the GitHub Page. Step_1e: All necessary inputs to generate average monthly demand for each water provider. Associated python script on GitHub. Step 2: Output data about land cover metrics (areas and fractions) for each urban land class for each water provider. Associated python script on GitHub. Uses outputs from Step 1d "Clipped Provider Hi Res Landcover" Step 3: Inputs for and Outputs from the urban projection raster analysis Python script on GitHub. The outputs are rasters of urban pixels that were converted to a higher land class and the number of land class units that changed (Values of 1, 2, or 3). For example, a value of 2 could be LC 21 -> 23 or LC 22 -> 24. These maps are label "intensification." The other outputs are "urban growth" rasters showing the conversion of non urban to urban land, which are indicated by pixel values of 1. Step 4: Output projections of indoor and outdoor annual and monthly demands for each water provider. These are used for Figures 4 - 7 of the paper. Figures: This folder has data used for plotting Figures 1 through 5. Data for Figures 6 and 7 are sourced directly from folders associated with the Processing and Analysis Steps 1 - 4 and the plotting scripts for Figures 6 and 7 are commented with what folder paths are needed to generate the figures. The GitHub page provides descriptions of how each figure was made and the associated plotting scripts used.

Los Angeles↗