JGR–Atmospheres

This study quantifies the contribution of individual cloud feedbacks to the total short-term cloud feedback in satellite observations over the period 2002–2014 and evaluates how they are represented in climate models. The observed positive total cloud feedback is primarily due to positive high-cloud altitude, extratropical high- and low-cloud optical depth, and land cloud amount feedbacks partially offset by negative tropical marine low-cloud feedback. Seventeen models from the Atmosphere Model Intercomparison Project of the sixth Coupled Model Intercomparison Project are analyzed. The models generally reproduce the observed moderate positive short-term cloud feedback. However, compared to satellite estimates, the models are systematically high-biased in tropical marine low-cloud and land cloud amount feedbacks and systematically low-biased in high-cloud altitude and extratropical high- and low-cloud optical depth feedbacks. Errors in modeled short-term cloud feedback components identified in this analysis highlight the need for improvements in model simulations of the response of high clouds and tropical marine low clouds. Our results suggest that skill in simulating interannual cloud feedback components may not indicate skill in simulating long-term cloud feedback components.

The Early Eocene Climatic Optimum (EECO) may be a potentially useful analog for future global warming under high CO2 concentrations. However, a paucity of orbital-scale terrestrial records limits our understanding of how the hydrological cycle responded during this protracted (∼4 Myr) interval of global warmth. In this study, we combine zircon U-Pb dating and cyclostratigraphy to establish a high-resolution astronomical timescale spanning the EECO (∼52.9 Ma to ∼49.9 Ma) through a >1 km fluviolacustrine succession from the Gonjo Basin, Southeast Tibet. Our results suggest that hydroclimate variability in the region during this interval was strongly controlled by eccentricity forcing (∼405 Kyr, ∼135–100 Kyr, and possibly ∼200 Kyr cycles). The dominance of eccentricity forcing in our record is consistent with coeval marine records, and indicates that modulation of low-latitude summer insolation through nonlinear interactions with the global carbon cycle likely controlled hydroclimate and paleolake level in the Gonjo basin during the EECO. Our study offers new perspectives for the forcing mechanisms of terrestrial hydroclimate changes of East Asia in response to subtle changes in insolation during the EECO.

Large reductions in anthropogenic emissions of particulate matter and its precursor emissions have occurred since the enactment of the Clean Air Act Amendments of 1990. The Interagency Monitoring of Protected Visual Environments network has measured PM2.5 gravimetric mass (mass of particles with aerodynamic diameters less than 2.5 μm, also referred to here as fine mass, “FM”) and speciated PM2.5 aerosol composition at remote sites since 1988. Measured species include inorganic anions such as sulfate, nitrate, and chloride, carbonaceous aerosols such as organic (OC) and elemental carbon (EC), and elemental concentrations used to estimate fine dust (FD). Trends in seasonal and annual mean mass concentrations were calculated from 2000 through 2021, a period that includes the largest reductions in emissions. On average, annual mean FM at remote sites in the continental United States has decreased at a rate of −1.8% yr−1. This reduction is largely due to annual mean trends in sulfate (−6.1% yr−1), nitrate (−2.7% yr−1), EC (−2.2% yr−1), FD (−1.3% yr−1), and OC (−0.9% yr−1), although the OC annual mean trend was insignificant. Seasonal and regional mean FM trends varied significantly, with strong reductions in the East in all seasons due to sulfate reductions, and flat and insignificant trends in summer and fall in the West due to the influence of biomass burning emissions on OC trends. Evaluating regional and seasonal mean trends in aerosol composition helps identify sources that continue to adversely impact air quality and hinder progress in FM reductions due to successful regulatory activity.

Spatial climate data sets that extend back in time over many decades are an important resource for climate monitoring. The long-term consistency of such data sets is, however, compromised by changes in the measurement systems over time. In this paper, we introduce a data set of monthly precipitation on a 5-km grid over the European Alps that extends back to the late 19th century. In deriving the “long-term Alpine precipitation reconstruction” (LAPrec), special care is taken of variations in the station network, in order for the data set to satisfy high standards in long-term consistency. LAPrec builds on a reconstruction method that integrates the available information in two portions: The first is a set of high-quality homogenized station series, taken from the HISTALP data archive, covering the entire period almost continuously. The second is a high-resolution gridded precipitation analysis, taken from the “Alpine Precipitation Grid Data Set,” constructed from thousands of rain-gauges but covering a few decades only. We demonstrate how the reconstruction approach successfully introduces mesoscale structures that are not resolved by the available long-term station series, more plausibly so than a predecessor data set using conventional interpolation. We also illustrate that LAPrec reveals long-term precipitation trends that are spatially more consistent and more detailed than the trends in popular climate monitoring data sets. Over the period 1871–2017 a statistically significant increase is found in winter over the northern parts of the Alps (1%–2% per 10 years). LAPrec is available in two versions (back until 1871 and 1901 respectively) from the Copernicus climate data store.

Understanding the climatic effect of vegetation in different regions is important for understanding the climate impact of vegetation change in both the past and future. Here we quantify the climate response to vegetation removal on each continent, except Antarctica, using CESM1.2.2 under pre-industrial climate condition, and the associated mechanisms are analyzed. Results show that removing the global vegetation lowers the global mean surface temperature (GMST) by 3.65°C. Removing vegetation over Eurasia and North America lowers GMST by 1.83°C and 0.88°C, respectively. They also reduce the global precipitation, but at a much slower rate than that would be caused in the CO2 perturbation experiments. Removing vegetation on all other continents has negligible influence on global climate, but has significant local warming effect due to weakening of evapotranspiration. The removal of low-latitude vegetation tends to reduce the local precipitation, but increase the precipitation over nearby oceans, especially to the west. The feedbacks of thermodynamic sea ice and oceans amplify the initial direct cooling due to vegetation removal by a factor of >5. The response of ocean circulation has a negligible impact on GMST, but has a significant influence on the pattern of temperature changes by redistributing heat. Without the ocean-circulation feedback, the Northern Hemisphere would be 1.30°C colder while the Southern Hemisphere 1.17°C warmer when the global vegetation is removed.

Nitrogen dioxide (NO2) and formaldehyde (HCHO) play vital roles in atmospheric photochemical processes. Their tropospheric vertical column density (TVCD) distributions have been monitored by satellite instruments. Evaluation of these observations is essential for applying these observations to study photochemistry. Assessing satellite products using observations at rural sites, where local emissions are minimal, is particularly useful due in part to the spatial homogeneity of trace gases. In this study, we evaluate OMI and TROPOMI NO2 and HCHO TVCDs using multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements at a rural site in the east coast of the Shandong province, China in spring 2018 during the Ozone Photochemistry and Export from China Experiment (OPECE) measurement campaign. On days not affected by local burning, we found generally good agreement of NO2 data after using consistent a priori profiles in satellite and MAX-DOAS retrievals and accounting for low biases in scattering weights in one of the OMI products. In comparison, satellite HCHO products exhibited weaker correlations with MAX-DOAS data, in contrast to satellite NO2 products. However, TROPOMI HCHO products showed significantly better agreement with MAX-DOAS measurements compared to OMI data. Furthermore, case studies of the vertical profiles measured by MAX-DOAS on burning days revealed large enhancements of nitrous acid (HONO), NO2, and HCHO in the upper boundary layer, accompanied with considerable variability, particularly in HONO enhancements.

Starting from point sources, wildfire smoke is important in the global aerosol system. The ability to characterize smoke near-source is key to modeling smoke dispersion and predicting air quality. With hemispheric views and 10-min refresh, imagers in Geostationary (GEO) orbit have advantages monitoring smoke over once-per-day sensors in low-earth orbit (LEO). However, both can be inadequate in capturing the characteristics of smoke plumes close to their sources due to too-coarse spatial resolution (both detector and product resolution), too-sparse temporal resolution (from LEO sensors), and too-conservative masking. In addition to satellite observations, the Fire Influence on Regional to Global Environments and Air Quality experiment offered sub-orbital enhanced-MODIS Airborne Simulator (eMAS) imagery at 50 m pixel resolution—including multiple eMAS flight tracks over individual fires in short time periods. It provided opportunity to explore smoke plume characterization at various spatial and temporal scales and quantify the limitations of space sensors for describing smoke magnitude near source as well as its temporal evolution. Here we applied modified aerosol algorithm to different imagers, relaxing its masking to estimate smoke's aerosol optical depth (AOD) as close as possible to its source. We found that GEO sensors with nominal 1 km spatial resolution can match the much finer resolution eMAS retrieved mean plume AOD, as long as the retrieval spatial resolution is finer than the width of the plumes. However, the plume's maximum AOD may be drastically underestimated by satellite products.

Eurasian teleconnection pattern (EU) and its two variants (EU1 and EU2) are the representative wintertime atmospheric teleconnections over Eurasian continent. They are mainly indicative of the local features and closely related to other teleconnection patterns. What are the major interannual climate modes over mid-high latitude Eurasia in boreal winter is still an open question. With the ERA5 reanalysis data sets after removing the linear impact of El Niño-Southern Oscillation (ENSO), three wintertime climate modes over mid-high latitude Eurasia are identified by the first three empirical orthogonal function (EOF) modes of the anomalous relative tendency (ART) of 500 hPa geopotential height. They approximately explain 75% of the interannual variance in total. The three climate modes have combined features of EU-like patterns with Arctic Oscillation (AO), North Atlantic Oscillation (NAO) and West Atlantic (WA) teleconnections, respectively, and they are named EU-AO, EU-NAO and EU-WA climate modes accordingly. All the three climate modes originate mainly from the North Atlantic and demonstrate clear Rossby wave trains downstream to East Asia along the great circle route, and they can be primarily stimulated and maintained by positive air-sea feedback over North Atlantic regarding to the obvious North Atlantic tripole-like sea surface temperature patterns. Interannual climate variations over the most Eurasian continent are strongly linked to and well reproduced by the three ENSO-independent climate modes, which can be applied as the important signals for monitoring and predicting winter interannual climate variabilities over mid-high latitude Eurasia.

The aromatic components with strong light-absorbing capacity in HULIS mainly originated from coal combustion, enhancing light-absorbing capacity of HULIS-C and making it more recalcitrant to oxidative aging.

Humic-like substances (HULIS) are significant contributor to the light absorption of water-soluble brown carbon (WSBrC), which contains certain strong light-absorbing chemical components that are not well understood, impeding the assessment of WSBrC's climate impact. China as the hotspot regions with high loading of WSBrC characterized by high light-absorbing capacity, here, we investigated the sources and atmospheric processes (δ13C–Δ14C), molecular composition (Fourier transform ion cyclotron resonance mass spectrometry), and light absorption properties (UV spectrophotometry) of HULIS in PM2.5 from 10 Chinese cities. HULIS-C was major contributor to the light absorption coefficient (70.5 ± 6.6%) of WSBrC at 365 nm, which was more enriched with fossil sources (48.0 ± 9.0% vs. 30.3 ± 13.9%) but depleted in 13C (δ13C: −25.6 ± 0.9‰ vs. −22.4 ± 1.0‰) relative to non-HULIS-C. This suggests that the fossil components in HULIS are more recalcitrant to oxidative aging and exhibit higher light-absorbing capacity, while the non-fossil organic carbon is more likely to be oxidatively bleached into small, colorless, and highly polar molecules (i.e., non-HULIS). Aromatic components are the major strong light-absorbing fossil components in HULIS, dominantly originating from coal combustion (>77%). Non-negative matrix factorization model showed that aromatic molecules from coal combustion have higher molecular weight and lower oxidation levels than biomass burning, potentially making them to be photo-recalcitrant compounds. Our finding that coal combustion-derived BrC maybe more persistent in the atmosphere and has greater long-term impact on climate than BrC derived from biomass burning is an important consideration in climate models and mitigation policies.

Below-cloud scavenging (BS) is often underestimated in chemical transport models (CTMs) due to inaccurate parameterizations of BS coefficient for fine particle (Λ) caused by a shortage of high-time resolution field observations. Rainfall ions and related air pollutants were measured hourly in Central China (CC) during 2019. BS contributed to 37%–68% of wet deposition for SO42– ${\text{SO}}_{4}^{2\mbox{--}}$, NO3– ${\text{NO}}_{3}^{\mbox{--}}$, and NH4+ ${\text{NH}}_{4}^{+}$ (SNA). By a bulk method coupled with brute-force search, the Λ (10−2–10 hr−1) was parameterized for SNA in PM2.5, which was 1–3 orders of magnitudes higher than theoretical calculations in CTMs. These chemical-specific Λ parameterizations were validated by EMEP model. Compared to baselines, updated simulations for annual SNA wet deposition increased by 3.3%–20.4% and for mean PM2.5 SNA concentrations reduced by 1.2%–40%, capturing measurements better. The contributions of scavenged gases to wet deposition below cloud were calculated as 9%–73%, exhibiting discrepancies (2%–17% for HNO3 and 19%–90% for SO2) with previous modeling results as different Λ schemes adopted in CTMs. The nonlinearity between Λ and precipitation intensity causes frequency exerting stronger impact on aerosol burden than intensity and duration. Periodic light rain with a precipitation amount of 1–10 mm per event can eliminate 60% of SNA in PM2.5 and is suggested as a routine procedure to improve local air quality. Analyzing a typical washout process after a haze event in CC, BS could reduce PM2.5 SNA concentrations by 44%–54% derived from improved parameterizations.

Utilizing the Open Integrated Forecasting System, the responses of Ural blocking (UB) to different stratospheric warming scenarios are investigated. Numerical results show that stratospheric warming with moderate strength in minor patterns prolongs the UB duration and enhances its intensity, while strong stratospheric warming in minor patterns tends to shorten its duration and weaken its intensity, even leading to the collapse of the UB events. Further diagnosis reveals that the planetary wave activity flux propagates downward from the stratosphere to the troposphere after stratospheric warming. Moreover, the convergence of planetary wave activity flux is a key factor for UB enhancement and maintenance. In addition, the weakened meridional temperature gradients, decelerated zonal westerly winds, and a reduced meridional potential vorticity gradient (PVy) result in UB enhancement in response to stratospheric warming with moderate strength. As stratospheric warming strengthens, planetary wave activity flux diverges, westerly winds in the tropospheric mid-latitudes accelerate and the PVy in the Ural sector enlarges, which further weakens UB. Regarding the stratospheric perturbations in major patterns, they have similar influences on UB events, that is, UB enhances with moderate stratospheric warming and weakens with strong warming. However, the strengthened warming would trigger UB re-enhancement, which is closely associated with anomalous activities of tropospheric synoptic-scale waves induced by stratospheric perturbations. These results reveal UB events respond differently to stratospheric warming with various intensities and patterns in the short term, which makes a contribution to understanding stratosphere-troposphere coupling.

Nonlinearities and asymmetries of El Niño Southern Oscillation (ENSO) stratospheric pathway to the North Atlantic and Europe are examined in large ensembles conducted with fully coupled climate models during wintertime. The analysis is centered on historical experiments of the Max Planck Institute Grand Ensemble (MPI-GE, 95 members) and expanded to six other ensembles of more limited size. In MPI-GE, significant responses are obtained for each ENSO phase and three different intensities (weak, moderate and strong). Overall, linear relationships are found for either El Niño or La Niña key diagnostics that characterize the pathway. These relationships are generally weaker for the cold La Niña than for the warm El Niño so that asymmetries between them develop as the events intensify. Specifically for strong events, the extra-tropical North Pacific and stratospheric responses are asymmetric, with larger responses for El Niño. In addition, the stratospheric asymmetry in strong events seems to contribute to the asymmetry in strong events in the North Atlantic—Europe response in the troposphere in late winter. The extra-tropical North Pacific response shows general agreement between MPI-GE and the other large ensembles. However, this agreement is not as large when other parts of the pathway are compared. Relatively high inter-model response spread confirms the typical model uncertainty found when examining atmospheric circulation responses which include the stratosphere in state-of-the-art climate models.

Because of the potential similarities of the climate in the mid-Pliocene to the projected conditions in the near future, studying mid-Pliocene dryland aridity can advance our future projections. In this study, we used climate modeling to investigate mid-Pliocene dryland aridity. Our results indicated that, in the mid-Pliocene compared to the preindustrial period, the simulated dryland was substantially less arid in North Africa, the Arabian Peninsula, Australia and Central Asia and more arid in North and South America and Southern Africa. The combined topography, vegetation and lakes (TVL) and atmospheric CO2 concentrations markedly modified this large-scale dryland aridity, mainly by modulating precipitation and potential evapotranspiration, respectively. Moreover, the dryland aridity during the mid-Pliocene varied under different orbital parameter intervals, mainly through precipitation changes. Our results show the important effect of vegetation on dryland aridity in a previous warm period and imply the potential effect of vegetation on future dryland aridity.

Aerosols play a key role in polar climate, and are affected by long-range transport from the mid-latitudes, both in the Arctic and Antarctic. This work investigates poleward extreme transport events of aerosols, referred to as polar aerosol atmospheric rivers (p-AAR), leveraging the concept of atmospheric rivers (AR) which signal extreme transport of moisture. Using reanalysis data, we build a detection catalog of p-AARs for black carbon, dust, sea salt and organic carbon aerosols, for the period 1980–2022. First, we describe the detection algorithm, discuss its sensitivity, and evaluate its validity. Then, we present several extreme transport case studies, in the Arctic and in the Antarctic, illustrating the complementarity between ARs and p-AARs. Despite similarities in transport pathways during co-occurring AR/p-AAR events, vertical profiles differ depending on the species, and large-scale transport patterns show that moisture and aerosols do not necessarily originate from the same areas. The complementarity between AR and p-AAR is also evidenced by their long-term characteristics in terms of spatial distribution, seasonality and trends. p-AAR detection, as a complement to AR, can have several important applications for better understanding polar climate and its connections to the mid-latitudes.

Arctic clouds are sensitive to atmospheric particles since these are sometimes in such low concentrations that clouds cannot always form under supersaturated water vapor conditions. This is especially true in the late summer, when aerosol concentrations are generally very low in the high Arctic. The environment changes rapidly around freeze-up as the open waters close and snow starts accumulating on ice. We investigated droplet formation during eight significant fog events in the central Arctic Ocean, north of 80°, from August 12 to 19 September 2018 during the Arctic Ocean 2018 expedition onboard the icebreaker Oden. Calculated hygroscopicity parameters (κ) for the entire study were very high (up to κ = 0.85 ± 0.13), notably after freeze-up, suggesting that atmospheric particles were very cloud condensation nuclei (CCN)-active. At least one of the events showed that surface clouds were able to form and persist for at least a couple hours at aerosol concentrations less than 10 cm−3, which was previously suggested to be the minimum for cloud formation. Among these events that were considered limited in CCN, effective radii were generally larger than in the high CCN cases. In some of the fog events, droplet residuals particles did not reactivate under supersaturations up to 0.95%, suggesting either in-droplet reactions decreased hygroscopicity, or an ambient supersaturation above 1%. These results provide insight into droplet formation during the clean late-summer and fall of the high Arctic with limited influence from continental sources.

Volcanic ash clouds are carefully monitored as they present a significant hazard to humans and aircraft. The primary tool for forecasting the transport of ash from a volcano is dispersion modeling. These models make a number of assumptions about the size, sphericity and density of the ash particles. Few studies have measured the density of ash particles or explored the impact that the assumption of ash density might have on the settling dynamics of ash particles. In this paper, the raw apparent density of 23 samples taken from 15 volcanoes are measured with gas pycnometry, and a negative linear relationship is found between the density and the silica content. For the basaltic ash samples, densities were measured for different particle sizes, showing that the density is approximately constant for particles smaller than 100 μm, beyond which it decreases with size. While this supports the current dispersion model used by the London Volcanic Ash Advisory Centre (VAAC), where the density is held at a constant (2.3 g cm−3), inputting the measured densities into a numerical simulation of settling velocity reveals a primary effect from the silica content changing this constant. The VAAC density overestimates ash removal times by up to 18%. These density variations, including those varying with size beyond 100 μm, also impact short-range particle-size distribution measurements and satellite retrievals of ash.

We investigate the benefit of assimilating high spatial-temporal resolution nitrogen dioxide (NO2) measurements from a geostationary (GEO) instrument such as Tropospheric Emissions: Monitoring of Pollution (TEMPO) versus a low-earth orbit (LEO) platform like TROPOspheric Monitoring Instrument (TROPOMI) on the inverse modeling of nitrogen oxides (NOx) emissions. We generated synthetic TEMPO and TROPOMI NO2 measurements based on emissions from the COVID-19 lockdown period. Starting with emissions levels prior to the lockdown, we use the Weather Research and Forecasting Model coupled with Chemistry/Data Assimilation Research Testbed (WRF-Chem/DART) to assimilate these pseudo-observations in Observing System Simulation Experiments to adjust NOx emissions and quantify how well the assimilation of TEMPO versus TROPOMI measurements recovers the lockdown-induced emissions changes. We find that NOx emission biases can be ameliorated using half as many simulation days when assimilating GEO observations, and the estimated NOx emissions in 23 out of 29 major urban regions in the US are more accurate. The root mean square error and coefficient of determination of posterior NOx emissions are reduced by 12.5%–41.5% and 1.5%–17.1%, respectively, across different regions. We conduct sensitivity experiments that use different data assimilation (DA) configurations to assimilate synthetic GEO observations. Results demonstrate that the temporal width of the DA window introduces −10% to −20% biases in the emissions inversion and constraining both NOx concentrations and emissions simultaneously yields the most accurate NOx emissions estimates. Our work serves as a valuable reference on how to appropriately assimilate GEO observations for constraining NOx emissions in future studies.

Poor air quality is often experienced in densely populated areas located alongside large rivers. The presence of a river valley can modify local meteorology, potentially interfering with the formation of air pollutants such as PM2.5. However, the mechanisms behind PM2.5 formation in river valleys and its impacts on surrounding regions remain poorly understood. This study investigates the formation mechanisms of PM2.5 in the Nanjing reach of the Yangtze River, considering its complex terrain and anthropogenic emissions, through numerical simulation. Simulated results revealed higher PM2.5 concentrations along the Yangtze River compared to the average concentrations in Nanjing, primarily driven by elevated nitrate level. Factors such as higher humidity, wind speed, ageostrophic wind field, and shallow boundary layer were identified as key contributors to the increased PM2.5 concentrations along the river. Our study demonstrates significant impact of local thermal circulations on PM2.5 formation, resulting from the interaction between the large water body of the Yangtze River and the urban area. This phenomenon was confirmed through sensitivity experiments, which showed attenuated local thermal circulations in the absence of the Yangtze River. Source apportionment and process analysis results confirm the dominant roles of local thermal circulation related horizontal and vertical advections, with diurnal fluctuations, in shaping PM2.5 variations along the river. Inorganic chemistry processes also played a non-negligible role, particularly during polluted conditions. Local thermal circulations in river valleys are crucial for PM2.5 formation, highlighting the need for comprehensive strategies to tackle air pollution in similar regions.

Supercooled liquid clouds are ubiquitous over the Southern Ocean (SO), even to temperatures below −20°C, and comprise a large fraction of the marine boundary layer (MBL) clouds. Earth system models and reanalysis products have struggled to reproduce the observed cloud phase distribution and occurrence of cloud ice in the region. Recent simulations found the microphysical representation of ice nucleation and growth has a large impact on these properties, however, measurements of SO ice nucleating particles (INPs) to validate simulations are sparse. This study presents measurements of INPs from simultaneous aircraft and ship campaigns conducted over the SO in austral summer 2018, which include the first in situ observations in and above cloud in the region. Our results confirm recent observations that INP concentrations are uniformly lower than measurements made in the late 1960s. While INP concentrations below and above cloud are similar, higher ice nucleation efficiency above cloud supports model simulations that the dominant INP composition varies with height. Model parameterizations based solely on aerosol properties capture the mean relationship between INP concentration and temperature but not the observed variability, which is likely related to the only modest correlations observed between INPs and environmental or aerosol metrics. Including wind speed in addition to activation temperature in a marine INP parameterization reduces bias but does not explain the large range of observed INP concentrations. Direct and indirect inference of marine INP size suggests MBL INPs, at least during Austral summer, are dominated by particles with diameters smaller than 500 nm.

We observed two Terrestrial Gamma-ray Flashes (TGFs) in Uchinada, Japan associated with negative cloud-to-ground lightning strokes exactly 1 year apart on 18 December 2020 and 2021. The events were remarkable for their lateral distance from the associated strokes—each about 5 km away from the detector site. Not only was that lateral distance remarkable on its own for a ground based detection, but the low-altitude profile of winter thunderstorms in Japan would suggest the detections occurred at unprecedented nadir angles—73.3° off axis for the 2020 event with the standard assumption of a vertically oriented TGF. Unsurprisingly, Monte Carlo simulations of the straightforward interpretation of these events yield fluences 2 orders of magnitude lower than observed data. We investigate a variety of ways to attempt to resolve the contradiction between expected and observed behavior.