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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Contrasting spring and summer large-scale environments associated with mesoscale convective systems over the U.S. Great Plains

Mesoscale convective systems (MCSs) are frequently observed over the U.S. Great Plains during boreal spring and summer. Here, four types of synoptically-favorable environments for spring MCSs and two types of synoptically- favorable and unfavorable environments for summer MCSs are identified using self-organizing maps (SOM) with the inputs of observational data. During spring, frontal systems providing a lifting mechanism and an enhanced Great Plains low-level jet (GPLLJ) providing anomalous moisture are important features identified by SOM analysis as they create favorable dynamical and thermodynamic environments for MCS development. During summer, the composite MCS environment shows small positive convective available potential energy (CAPE) and convective inhibition (CIN) anomalies, which are in stark contrast with the large positive CAPE and negative CIN anomalies in spring. This contrast suggests that convection may occur even within weak dynamical and thermodynamic perturbations in summer so that MCSs may be inherently less predictable in summer. The two synoptically-favorable environments identified in summer have frontal characteristics and an enhanced GPLLJ, but both shift north compared to spring. The two synoptically-unfavorable environments feature enhanced upper-level ridges, but differ in the strength of the GPLLJ. In both seasons, MCS precipitation amount, area and rate are much larger in the frontal-related MCSs than non-frontal MCSs. A large-scale index constructed using the pattern correlation between the large-scale environment and the synoptically-favorable SOM types is found to be skillful for predicting MCS number, precipitation rate and area in spring, but its explanatory power decreases significantly in summer. The low predictability of summer MCSs deserves further investigation in the future.

Song, Fengfei↗
DOE OSTI2021

Precipitation Characteristics of Warm Season Weather Types in the Southeastern United States of America

Daily weather types (WTs) over the Southeast United States have been analyzed using 850 hPa winds from reanalysis data from March to October of 1979–2019. Six WTs were obtained. WTs 1–3 represent mid-latitude synoptic systems propagating eastward. WT4 is a summer-type pattern predominantly occurring in June–August, with the center of the North Atlantic Subtropical High (NASH) along the Gulf coast in the southern United States. WT5 is most frequent from August to middle October, with the NASH pushed further north and southerly winds over the northern Great Plains. An anticyclone centered at the Carolina coast characterizes WT6, which occurs in all months but is slightly more frequent in the spring and fall, especially in October, corresponding to fair weather in the region. WTs 1, 2 and 3 can persist for only a few days. WTs 4, 5 and 6 can have long spells of persistence. Besides self-persistence, the most observed progression loop is WT1 to WT2, to WT3, and then back to WT1, corresponding to eastward-propagating waves. WTs 4 and 5 are likely to show persistence, with long periods of consecutive days. WT6 usually persists but can also transfer to WT3, i.e., a change from fair weather in the Southeast U.S. to rainy weather in the Mississippi River Valley. A diurnal cycle of precipitation is apparent for each WT, especially over coastal plains. The nocturnal precipitation in central U.S. is associated with WT3. WTs 1–3 are more frequent in El Niño years, corresponding to stronger westerly wave activities and above normal rainfall in the Southeast U.S. in the spring. The positive rainfall anomaly in the Mississippi and Ohio River valley in El Niño years is also associated with more frequent WT3.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Antarctic Cloud Macrophysical, Thermodynamic Phase, and Atmospheric Inversion Coupling Properties at McMurdo Station—Part II: Radiative Impact During Different Synoptic Regimes

Different cloud types are generated over Antarctica as a result of various synoptic conditions. The cloud characteristics affect their impact on the surface energy budget. In this study, the dominating synoptic regimes over Antarctica (centered on the Ross Ice Shelf) are classified using self-organizing map (SOM) analysis, applied over long-term ERA-Interim 700 hPa geopotential height data. The corresponding cloud properties over McMurdo Station (measured as part of the AWARE campaign) are described and discussed with respect to the synoptic settings and sea-ice extent conditions. Cloud radiative forcing calculations are performed as well, and a particular focus is given to the net longwave “radiatively cloudy/opaque” (RO) regime. These results are compared with measurements performed at the West Antarctic Ice Sheet (WAIS) Divide to examine their variability and applicability to other Antarctic locations. It is found that the McMurdo cloud properties are strongly affected by the regional mesoscale cyclonic activity, which counterweights the larger-scale synoptic regime influence, while the WAIS clouds are more susceptible to the varying synoptic settings. In addition, it is suggested that the positive trend in the (frequent) cyclonic activity near the Antarctic coastal regions makes ice-clouds an increasing prominent contributor for the RO cases, especially during freeze-up and maximum sea-ice conditions.

antarctic clouds↗
DOE OSTI2017

Tropical circulation and precipitation response to ozone depletion and recovery

Among the few well established changes in atmospheric circulation in recent decades are those caused by stratospheric ozone depletion. They include a strengthening and poleward contraction of the westerly atmospheric circulation over the Southern extratropics, i.e. a strengthening Southern Annular Mode (SAM), in austral spring and summer. Associated effects on extratropical temperature and precipitation and more recently subtropical precipitation have been documented and are understood in a zonal mean framework. We present zonally asymmetric effects of ozone depletion that reach into the tropics and affect atmospheric circulation and precipitation, including the South Pacific Convergence Zone (SPCZ), the most important rainband of the Southern Hemisphere. Using observation-based analyses and model simulations we show that over the 1961–1996 period, ozone depletion led to increased precipitation at the northern flank of the SPCZ and to decreased precipitation to the south. The effects originate from a flow pattern over the southwestern Pacific that extends equatorward and alters the propagation of synoptic waves and thus the position of the SPCZ. Model simulations suggest that anticipated stratospheric ozone recovery over the next decades will reverse these effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Large-scale meteorological control on the spatial pattern of wintertime PM 2.5 pollution over China

The frequent episodes of severe air pollution over China during recent years have posed serious health threats to densely populated eastern China. Although several studies investigated the linkage between enhanced severity and frequency of air pol-lution and the large-scale weather patterns over China, the day-to-day covariability between them, as well as its local and remote mechanisms, has not been systemati-cally documented. The wintertime synoptic covariability between PM 2.5 and large-scale meteorological fields is studied using surface observations of PM 2.5 in 2013/2014–2016/2017 and ERA-Interim meteorological fields through maximum covariance analysis (MCA). The first MCA mode (MCA1) suggests a consistent accumulation of ambient PM 2.5 as a result of weakened winds that block the pollut-ant removal passage in heavily polluted areas of eastern China, as well as moist air from southeast coast favoring haze formation. A northeast–southwest belt that extends into northeastern China and central China on each end is more sensitive to MCA1. The second MCA mode (MCA2) shows a north–south dipole in PM 2.5 linked to the contrast of boundary layer height and surface wind speed between northern and southern regions of China. Spatial patterns of both modes are supported by the GEOS-Chem chemistry transport model with realistic emission inventory. The spatial patterns of the two modes are robust on the interannual time scales. Based on that, we investigate the variability of the first two modes of the identified modes on the multidecadal scale by projecting GPM_500 pattern to 1981–2010. Correlation analysis of the projected time series and climate indices over 30 years indicates the possible linkage of Arctic oscillation, ENSO indices, Pacific decadal oscillation and east Atlantic/western Russia to regional air pollution patterns over China.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Connecting Large‐Scale Meteorological Patterns to Extratropical Cyclones in CMIP6 Climate Models Using Self‐Organizing Maps

Abstract Extratropical cyclones (ETCs) are responsible for the majority of cool‐season extreme events in the northeastern United States (NEUS), often leading to high‐impact weather conditions that can have wide‐ranging socioeconomic impacts. Evaluating the ability of climate models to adequately simulate ETC dynamics is essential for improving model performance and increasing confidence in future projections used by stakeholders and policymakers. ETCs are traditionally studied using techniques such as case studies and synoptic typing, however, these approaches can be time‐consuming, require subjective analysis, and do not necessarily identify the coincident large‐scale meteorological patterns (LSMPs). Here, we apply self‐organizing maps (SOMs) as an automated machine‐learning approach to characterize the LSMPs and associated frequency and intensity of discrete ETC events over NEUS. The dominant patterns of geopotential height variability are identified through SOM analysis of five reanalysis products during the last four decades. ETC events are tracked using TempestExtremes and are integrated with SOMs to classify the accumulated cyclone activity (ACA) associated with each pattern. We then evaluate the skill of CMIP6 historical experiments in simulating the LSMPs and ETC events identified in the SOM. Our results identify a robust bias toward more zonal patterns, with models struggling to reproduce the more amplified patterns typically associated with the highest cyclone activity. While model resolution has some impact on simulation credibility, model configuration appears to be more important in LSMP representation. The vast majority of CMIP6 models produce too few ETCs, although model errors are distributed around historical reanalyses when ACA is normalized by storm frequency.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Application of PRIM for understanding patterns in carbon dioxide model-observation differences

Reducing uncertainties in regional carbon balances requires a better understanding of CO 2 transport in synoptic weather systems. Here, we apply the Patient Rule Induction Method (PRIM), a data-mining method to identify high-density regions for a target-class within an input parameter space, to airborne observations of potential temperature, wind speed, water vapor mixing ratio, and CO 2 dry mol fraction gathered during the Atmospheric Carbon and Transport (ACT)-America Summer 2016 and Winter 2017 campaigns. ACT observations were targeted at expert-designated cases of fair weather and near-frontal warm and cold sector air at atmospheric boundary-layer, lower-, and higher free tropospheric levels (ABL, LFT, and HFT, respectively). We investigate atmospheric characteristics of these pre-defined cases and associated CO 2 model-observation-differences in the mesoscale WRF-Chem model. PRIM results separate winter- and summertime observations as well as observations from ABL, LFT, and HFT with enrichment factors of 4.0–20.5 inside the PRIM box compared to the entire dataset but cannot distinguish between near-frontal warm and cold sector observations in the higher free troposphere. Analyzing of the parameter space constrained by PRIM, we find that large magnitude model observation differences preferentially associated with times when atmospheric conditions are less typical. This association suggests that PRIM could provide a useful tool for isolating atmospheric conditions with large-magnitude and non-Gaussian CO 2 -residuals for targeted transport model evaluation and to potentially improve inversion results during synoptically active periods.

Gerken, Tobias [James Madison Univ., Harrisonburg,↗
DOE OSTI2019

Evidence of Specific MJO Phase Occurrence with Summertime California Central Valley Extreme Hot Weather

This study examines associations between California Central Valley (CCV) heat waves and the Madden Julian Oscillation (MJO). These heat waves have major economic impact. Our prior work showed that CCV heat waves are frequently preceded by convection over the tropical Indian and eastern Pacific oceans, in patterns identifiable with MJO phases. The main analysis method is lagged composites (formed after each MJO phase pair) of CCV synoptic station temperature, outgoing longwave radiation (OLR), and velocity potential (VP). Over the CCV, positive temperature anomalies occur only after the Indian Ocean (phases 2–3) or eastern Pacific Ocean (phases 8–1) convection (implied by OLR and VP fields). The largest fractions of CCV hot days occur in the two weeks after onset of those two phase pairs. OLR and VP composites have significant subsidence and convergence above divergence over the CCV during heat waves, and these structures are each part of larger patterns having significant areas over the Indian and Pacific Oceans. Prior studies showed that CCV heat waves can be roughly grouped into two clusters: Cluster 2 is preceded by a heat wave over northwestern North America, while Cluster 1 is not. OLR and VP composite analyses are applied separately to these two clusters. However, for Cluster 2, the subsidence and VP over the CCV are not significant, and the large-scale VP pattern has low correlation with the MJO lagged composite field. Therefore, the association between the MJO convection and subsequent CCV heat wave is more evident in Cluster 1 than Cluster 2.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Joint Synoptic and Cloud Variability over the Northeast Atlantic near the Azores

Abstract Marine boundary layer clouds are modified by processes at different spatial and temporal scales. To isolate the processes governing aerosol–cloud–precipitation interactions, multiday synoptic variability of the environment must be accounted for. Information on the location of low clouds relative to the ridge–trough pattern gives insight into how cloud properties vary as a function of environmental subsidence and stability. The technique of self-organizing maps (SOMs) is employed to objectively classify the 500-hPa geopotential height patterns for 33 years of reanalysis fields (ERA-Interim) into pretrough, trough, posttrough, ridge, and zonal-flow categories. The SOM technique is applied to a region of prevalent marine low cloudiness over the eastern North Atlantic Ocean that is centered on the Azores island chain, the location of a long-term U.S. Department of Energy observation site. The Azores consistently lie in an area of substantial variability in synoptic configuration, thermodynamic environment, and cloud properties. The SOM method was run in two ways to emphasize multiday and seasonal variability separately. Over and near the Azores, there is an east-to-west sloshing back and forth of the western edge of marine low clouds associated with different synoptic states. The different synoptic states also exhibit substantial north–south variability in the position of high clouds. For any given month of the year, there is large year-to-year variability in the occurrence of different synoptic states. Hence, estimating the climatological behavior of clouds from short-term field campaigns has large uncertainties. This SOM approach is a robust method that is broadly applicable to characterizing synoptic regimes for any location.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The Influence of Shallow Cloud Populations on Transitions to Deep Convection in the Amazon

Abstract In this study, a pair of convection-permitting (2-km grid spacing), month-long, wet-season Weather Research and Forecasting (WRF) Model simulations with and without the eddy-diffusivity mass-flux (EDMF) scheme are performed for a portion of the Green Ocean Amazon (GoAmazon) 2014/15 field campaign period. EDMF produces an ensemble of subgrid-scale convective plumes that evolve in response to the boundary layer meteorological conditions and can develop into shallow clouds. The objective of this study is to determine how different treatments of shallow cumulus clouds (i.e., with and without EDMF) impact the total cloud population and precipitation across the Amazonian rain forest, with emphasis on impacts on the likelihood of shallow-to-deep convection transitions. Results indicate that the large-scale synoptic conditions in the EDMF and control simulations are nearly identical; however, on the local scale their rainfall patterns diverge drastically and the biases decrease in EDMF. The EDMF scheme significantly increases the frequency of shallow clouds, but the frequencies of deep clouds are similar between the simulations. Deep convective clouds are tracked using a cloud-tracking algorithm to examine the impact of shallow cumulus on the surrounding ambient environment where deep convective clouds initiate. Results suggest that a rapid increase of low-level cloudiness acts to cool and moisten the low to midtroposphere during the day, favoring the transition to deep convection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Stream Chemistry, Synoptic Surveys, East Fork Poplar Creek Watershed, TN, USA; April 2023 to February 2025

Impacts of developed land cover on stream chemistry can be difficult to discern from natural variability, particularly in carbonate watersheds where weathering of urban infrastructure and lithology generate similar signatures. We evaluated how spatial patterns of stream chemistry varied across perennial and non-perennial tributaries spanning an urban-to-forested gradient in a mid-order, carbonate-dominated watershed. This data package contains a processed and compiled summary of stream chemistry and properties obtained from 12 synoptic surveys of 54 stream sites across the East Fork Poplar Creek watershed located near Oak Ridge, TN, United States. The sites include non-perennial tributaries, perennial tributaries, and the main stem and span forested to urban (highly developed) land cover gradients. The data package includes the processed and flagged chemical data (WaDE_SynopticSummary_FinalChemistry), metadata describing data flagging and analysis (WaDE_SynopticSummary_Metadata), information about each site and its contributing subcatchment (WaDE_SynopticSummary_SiteInformation), and a comparison of instrument and field detection limits used to determine method detection limits for the study (WaDE_SynopticSummary_DetectionLimitComparison). Stream chemistry includes stream parameters measured in situ using multiparameter probes (dissolved oxygen, pH, specific conductance, temperature) and solutes including nutrients (nitrate, ammonium, soluble reactive phosphorus), dissolved organic carbon, dissolved inorganic carbon, major cations (calcium, magnesium, potassium, sodium), major anions (chloride, sulfate), and a broad suite of minor and trace elements.

EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SURFACE ↗
DOE OSTI2022

First Synoptic Images of FUV Discrete Aurora and Discovery of Sinuous Aurora at Mars by EMM EMUS

Abstract We present the first measurements of Mars discrete aurora in the extreme ultraviolet (<110 nm) and the first synoptic aurora images in the far ultraviolet (110–180 nm). Auroral emission is detected in >75% of nightside images, with patterns shifting visibly over 15–20 min. Aurora is observed most frequently in regions of open magnetic topology (where crustal magnetic fields are very weak and/or vertical), with the brightest aurora where crustal fields are strongest. We present the first disk‐averaged spectrum of discrete aurora, with several O, C, and CO features as expected for electron impact primarily on CO 2 . We categorize discrete auroral morphology into three types: crustal field aurora, non‐crustal field patchy aurora, and a new type we call “sinuous” aurora, an elongated serpentine structure that stretches thousands of kilometers into the nightside from near midnight in the northern hemisphere. These observations point to a highly dynamic environment in Mars' magnetotail.

Lillis, Robert J.↗
DOE OSTI2019

Vertical Structure and Microphysical Characteristics of Frontal Systems Passing over a Three-Dimensional Coastal Mountain Range

As midlatitude cyclones pass over a coastal mountain range, the processes producing their clouds and precipitation are modified, leading to considerable spatial variability in precipitation amount and composition. Statistical diagrams of airborne precipitation radar transects, surface precipitation measurements, and particle size distributions are examined from nine cases observed during the Olympic Mountains Experiment (OLYMPEX). Although the pattern of windward enhancement and leeside diminishment of precipitation was omnipresent, the degree of modulation was largely controlled by the synoptic environment associated with the prefrontal, warm, and postfrontal sectors of midlatitude cyclones. Prefrontal sectors contained homogeneous stratiform precipitation with a slightly enhanced ice layer on the windward slopes and rapid diminishment to a near-complete rain shadow in the lee. Warm sectors contained deep, intense enhancement over both the windward slopes and high terrain and less prominent rain shadows owing to downstream spillover of ice particles generated over terrain. Surface particle size distributions in the warm sector contained a broad spectrum of sizes and concentrations of raindrops on the lower windward side where high precipitation rates were achieved from varying degrees of both liquid and ice precipitation-generating processes. Spillover precipitation was rather homogeneous in nature and lacked the undulations in particle size and concentration that occurred at the windward sites. Postfrontal precipitation transitioned from isolated convective cells over ocean to a shallow, mixed convective–stratiform composition with broader coverage and greater precipitation rates over the sloping terrain.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Wind energy variability and links to regional and synoptic scale weather

The accurate characterization of seasonal and inter-annual site-level wind energy variability is essential during wind project development. Understanding the features and probability of low-wind years is of particular interest to developers and financers. However, a dearth of long-term, hub-height wind observations makes these characterizations challenging, and thus techniques to improve these characterizations are of great value. To improve resource characterization, we explicitly link wind resource variability (at hub-height, and at specific sites) to regional and synoptic scale wind regimes. Our approach involves statistical clustering of high-resolution modeled wind data, and is applied to California for a period covering 1980–2015. With this approach, we investigate the unique meteorological patterns driving low and high wind years at five separate wind project sites. We also find wind regime changes over the 36-year period consistent with global warming: wind regimes associated with anomalously hot summer days increased at half a day per year and stagnant conditions increased at one-third days per year. Despite these changes, the average annual resource potential remained constant at all project sites. Additionally, we identify correlations between climate modes and wind regime frequency, a linkage valuable for resource characterization and forecasting. Our general approach can be applied in any location and may benefit many aspects of wind energy resource evaluation and forecasting.

17 WIND ENERGY↗
DOE OSTI2022

Evaluating seasonal and regional distribution of snowfall in regional climate model simulations in the Arctic

In this study, we investigate how the regional climate model HIRHAM5 reproduces the spatial and temporal distribution of Arctic snowfall when compared to CloudSat satellite observations during the examined period of 2007–2010. For this purpose, both approaches, i.e., the assessments of the surface snowfall rate (observation-to-model) and the radar reflectivity factor profiles (model-to-observation), are carried out considering spatial and temporal sampling differences. The HIRHAM5 model, which is constrained in its synoptic representation by nudging to ERA-Interim, represents the snowfall in the Arctic region well in comparison to CloudSat products. The spatial distribution of the snowfall patterns is similar in both identifying the southeastern coast of Greenland and the North Atlantic corridor as regions gaining more than twice as much snowfall as the Arctic average, defined here for latitudes between 66 and 81°N. Excellent agreement (difference less than 1%) in the Arctic-averaged annual snowfall rate between HIRHAM5 and CloudSat is found, whereas ERA-Interim reanalysis shows an underestimation of 45% and significant deficits in the representation of the snowfall rate distribution. From the spatial analysis, it can be seen that the largest differences in the mean annual snowfall rates are an overestimation near the coastlines of Greenland and other regions with large orographic variations as well as an underestimation in the northern North Atlantic Ocean. To a large extent, the differences can be explained by clutter contamination, blind zone or higher resolution of CloudSat measurements, but clearly HIRHAM5 overestimates the orographic-driven precipitation. The underestimation of HIRHAM5 within the North Atlantic corridor south of Svalbard is likely connected to a poor description of the marine cold air outbreaks which could be identified by separating snowfall into different circulation weather type regimes. By simulating the radar reflectivity factor profiles from HIRHAM5 utilizing the Passive and Active Microwave TRAnsfer (PAMTRA) forward-modeling operator, the contribution of individual hydrometeor types can be assessed. Looking at a latitude band at 72–73°N, snow can be identified as the hydrometeor type dominating radar reflectivity factor values across all seasons. The largest differences between the observed and simulated reflectivity factor values are related to the contribution of cloud ice particles, which is underestimated in the model, most likely due to the small sizes of the particles. The model-to-observation approach offers a promising diagnostic when improving cloud schemes, as illustrated by comparison of different schemes available for HIRHAM5.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Meteorological Drivers and Large-Scale Climate Forcing of West Antarctic Surface Melt

Understanding the drivers of surface melting in West Antarctica is crucial for understanding future ice loss and global sea level rise. This study identifies atmospheric drivers of surface melt on West Antarctic ice shelves and ice sheet margins and relationships with tropical Pacific and high-latitude climate forcing using multidecadal reanalysis and satellite datasets. Physical drivers of ice melt are diagnosed by comparing satellite-observed melt patterns to anomalies of reanalysis near-surface air temperature, winds, and satellite-derived cloud cover, radiative fluxes, and sea ice concentration based on an Antarctic summer synoptic climatology spanning 1979–2017. Summer warming in West Antarctica is favored by Amundsen Sea (AS) blocking activity and a negative phase of the southern annular mode (SAM), which both correlate with El Niño conditions in the tropical Pacific Ocean. Extensive melt events on the Ross–Amundsen sector of the West Antarctic Ice Sheet (WAIS) are linked to persistent, intense AS blocking anticyclones, which force intrusions of marine air over the ice sheet. Surface melting is primarily driven by enhanced downwelling longwave radiation from clouds and a warm, moist atmosphere and by turbulent mixing of sensible heat to the surface by föhn winds. Since the late 1990s, concurrent with ocean-driven WAIS mass loss, summer surface melt occurrence has increased from the Amundsen Sea Embayment to the eastern Ross Ice Shelf. We link this change to increasing anticyclonic advection of marine air into West Antarctica, amplified by increasing air–sea fluxes associated with declining sea ice concentration in the coastal Ross–Amundsen Seas.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Spatial modeling of daily concentrations of ground-level ozone in Montreal, Canada: A comparison of geostatistical approaches

Highlights: • The KED model with road and vegetation density as covariates showed good performance for all six synoptic classes. • The model using KED demonstrated the best results (R{sup 2} = 0.92; RMSE = 3.14 ppb). • The model using OK demonstrated a R{sup 2} = 0.85 and RMSE = 4 ppb. • Our results showed that errors appear to be substantially reduced with the KED model. • When measurements at numerous monitoring stations in a region are available, it may be better to use KED. • The BME may be more useful for prediction when data is not available. Ground-level ozone (O{sub 3}) is a powerful oxidizing agent and a harmful pollutant affecting human health, forests and crops. Estimating O{sub 3} exposure is a challenge because it exhibits complex spatiotemporal patterns. The aim in this study was to provide high-resolution maps (100 × 100 m) of O{sub 3} for the metropolitan area of Montreal, Canada. We assessed the kriging with external drift (KED) model to estimate O{sub 3} concentration by synoptic weather classes for 2010. We compared these results with ordinary kriging (OK), and a simple average of 12 monitoring stations. We also compared the estimates obtained for the 2010 summer with those from a Bayesian maximum entropy (BME) model reported in the literature (Adam-Poupart et al., 2014). The KED model with road and vegetation density as covariates showed good performance for all six synoptic classes (daily R{sup 2} estimates ranging from 0.77 to 0.92 and RMSE from 2.79 to 3.37 ppb). For the summer of 2010, the model using KED demonstrated the best results (R{sup 2} = 0.92; RMSE = 3.14 ppb), followed by the OK model (R{sup 2} = 0.85, RMSE = 4 ppb). Our results showed that errors appear to be substantially reduced with the KED model. This may increase our capacity of linking O{sub 3} levels to health problems by means of improved assessments of ambient exposures. However, future work integrating the temporal dependency in the data is needed to not overstate the performance of the KED model.

54 ENVIRONMENTAL SCIENCES↗