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The rapid changes occurring in the polar regions require an improved understanding of the processes that are driving these changes. At the same time, increased human activities such as marine navigation, resource exploitation, aviation, commercial fishing, and tourism require reliable and relevant weather information. One of the primary goals of the World Meteorological Organization's Year of Polar Prediction (YOPP) project is to improve the accuracy of numerical weather prediction (NWP) at high latitudes. During YOPP, two Canadian "supersites" were commissioned and equipped with new ground-based instruments for enhanced meteorological and system process observations. Additional pre-existing supersites in Canada, the United States, Norway, Finland, and Russia also provided data from ongoing long-term observing programs. These supersites collected a wealth of observations that are well suited to address YOPP objectives. In order to increase data useability and station interoperability, novel Merged Observatory Data Files (MODFs) were created for the seven supersites over two Special Observing Periods (February to March 2018 and July to September 2018). All observations collected at the supersites were compiled into this standardized NetCDF MODF format, simplifying the process of conducting pan-Arctic NWP verification and process evaluation studies. This paper describes the seven Arctic YOPP supersites, their instrumentation, data collection and processing methods, the novel MODF format, and examples of the observations contained therein. MODFs comprise the observational contribution to the model intercomparison effort, termed YOPP site Model Intercomparison Project (YOPPsiteMIP). All YOPPsiteMIP MODFs are publicly accessible via the YOPP Data Portal (Whitehorse: 10.21343/a33e-j150, Huang et al., 2023a; Iqaluit: 10.21343/yrnf-ck57, Huang et al., 2023b; Sodankylä: 10.21343/m16p-pq17, O'Connor, 2023; Utqiaġvik: 10.21343/a2dx-nq55, Akish and Morris, 2023c; Tiksi: 10.21343/5bwn-w881, Akish and Morris, 2023b; Ny-Ålesund: 10.21343/y89m-6393, Holt, 2023; and Eureka: 10.21343/r85j-tc61, Akish and Morris, 2023a), which is hosted by MET Norway, with corresponding output from NWP models. [ABSTRACT FROM AUTHOR]

Federal law requires states and school districts to institute accountability systems that report disaggregated student data to ensure that all children make academic progress. However, one of the mandated categories for disaggregation -- English Learner (EL) -- is reported as a single group despite representing students who are beginning, intermediate, and advanced in their acquisition of English. We argue that such a disaggregation is not sufficiently nuanced and may inadvertently hurt the very students it seeks to serve. Through the analysis of one large metro-area's accountability framework, this paper finds that there is a statistically significant relationship between EL level of English proficiency and school accountability rating that negatively impacts schools with large Intermediate EL populations.

Language ideologies--the way our ideas about language and accent both reflect and are informed by our ideas about people and society--influence us in subtle, often subconscious ways. They can shape classroom practices and potentially create barriers to student learning. In this article, learn about two especially harmful language ideologies that affect how we view students: language standardization and alingualism. The authors share a number of strategies to support educators as they facilitate conversations with colleagues about language ideologies within school contexts.

This study explores the role of snowpack in polar boundary layer chemistry, especially as a direct source of reactive bromine (BrOx = BrO + Br) and nitrogen (NOx = NO + NO2) in the Arctic springtime. Surface snow samples were collected daily from a Canadian high Arctic location at Eureka, Nunavut (80° N, 86° W) from the end of February to the end of March in 2018 and 2019. The snow was sampled at several sites representing distinct environments: sea ice, inland close to sea level, and a hilltop ∼ 600 m above sea level (a.s.l.). At the inland sites, surface snow salinity has a double-peak distribution with the first and lowest peak at 0.001–0.002 practical salinity unit (psu), which corresponds to the precipitation effect, and the second peak at 0.01–0.04 psu , which is likely related to the salt accumulation effect (due to loss of water vapour by sublimation). Snow salinity on sea ice has a triple-peak distribution; its first and second peaks overlap with the inland peaks, and the third peak at 0.2–0.4 psu is likely due to the sea water effect (a result of upward migration of brine). At all sites, snow sodium and chloride concentrations increase by almost 10-fold from the top 0.2 to ∼ 1.5 cm. Surface snow bromide at sea level is significantly enriched, indicating a net sink of atmospheric bromine. Moreover, surface snow bromide at sea level has an increasing trend over the measurement period, with mean slopes of 0.024 µMd-1 in the 0–0.2 cm layer and 0.016 µMd-1 in the 0.2–0.5 cm layer. Surface snow nitrate at sea level also shows a significant increasing trend, with mean slopes of 0.27, 0.20, and 0.07 µMd-1 in the top 0.2, 0.2–0.5, and 0.5–1.5 cm layers, respectively. Using these trends, an integrated net deposition flux of bromide of (1.01 ± 0.48) × 10 7 molec.cm-2s-1 and an integrated net deposition flux of nitrate of (2.6 ± 0.37) × 10 8 molec.cm-2s-1 were derived. In addition, the surface snow nitrate and bromide at inland sites were found to be significantly correlated (R = 0.48–0.76) with the [NO3-]/[Br-] ratio of 4–7 indicating a possible acceleration effect of reactive bromine in atmospheric NOx -to-nitrate conversion. This is the first time such an effect has been seen in snow chemistry data obtained with a sampling frequency as short as 1 d. BrO partial column (0–4 km) data measured by MAX-DOAS show a decreasing trend in early spring, which generally agrees with the derived surface snow bromide deposition flux indicating that bromine in Eureka atmosphere and surface snow did not reach a photochemical equilibrium state. Through mass balance analysis, we conclude that the average release flux of reactive bromine from snow over the campaign period must be smaller than the derived bromide deposition flux of ∼ 1 × 10 7 molec.cm-2s-1. Note that the net mean fluxes observed do not completely rule out larger bidirectional fluxes over shorter timescales. [ABSTRACT FROM AUTHOR]

This study evaluates tropospheric columns of methane, carbon monoxide, and ozone in the Arctic simulated by 11 models. The Arctic is warming at nearly 4 times the global average rate, and with changing emissions in and near the region, it is important to understand Arctic atmospheric composition and how it is changing. Both measurements and modelling of air pollution in the Arctic are difficult, making model validation with local measurements valuable. Evaluations are performed using data from five high-latitude ground-based Fourier transform infrared (FTIR) spectrometers in the Network for the Detection of Atmospheric Composition Change (NDACC). The models were selected as part of the 2021 Arctic Monitoring and Assessment Programme (AMAP) report on short-lived climate forcers. This work augments the model–measurement comparisons presented in that report by including a new data source: column-integrated FTIR measurements, whose spatial and temporal footprint is more representative of the free troposphere than in situ and satellite measurements. Mixing ratios of trace gases are modelled at 3-hourly intervals by CESM, CMAM, DEHM, EMEP MSC-W, GEM-MACH, GEOS-Chem, MATCH, MATCH-SALSA, MRI-ESM2, UKESM1, and WRF-Chem for the years 2008, 2009, 2014, and 2015. The comparisons focus on the troposphere (0–7 km partial columns) at Eureka, Canada; Thule, Greenland; Ny Ålesund, Norway; Kiruna, Sweden; and Harestua, Norway. Overall, the models are biased low in the tropospheric column, on average by - 9.7 % for CH 4 , - 21 % for CO, and - 18 % for O 3. Results for CH 4 are relatively consistent across the 4 years, whereas CO has a maximum negative bias in the spring and minimum in the summer and O 3 has a maximum difference centered around the summer. The average differences for the models are within the FTIR uncertainties for approximately 15 % of the model–location comparisons. [ABSTRACT FROM AUTHOR]

This study explores the role of snowpack in polar boundary layer chemistry, especially as a direct source of reactive bromine (BrOX=BrO+Br) and nitrogen (NOX=NO+NO2) in the Arctic springtime. Surface snow samples were collected daily from a Canadian high Arctic location at Eureka, Nunavut (80° N, 86° W) from the end of February to the end of March in 2018 and 2019. The snow was sampled at several sites representing distinct environments: sea ice, inland close to sea level, and a hilltop ~600 m above sea level (asl). At the inland sites, surface snow salinity has a double-peak distribution with the first and lowest peak at 0.001–0.002 practical salinity unit (psu), which corresponds to the precipitation effect, and the second peak at 0.01–0.04 psu, which is likely related to the salt accumulation effect (due to loss of water vapour by sublimation). Snow salinity on sea ice has a triple-peak distribution; its first and second peaks overlap with the inland peaks, and the third peak at 0.2–0.4 psu is likely due to the sea water effect (due to upward migration of brine on sea ice). At all sites, snow sodium and chloride concentrations increase by almost 10-fold from the top 0.2 cm to ~1.5 cm in depth. Surface snow bromide at sea level is significantly enriched, indicating a net sink of atmospheric bromine. Moreover, surface snow bromide at sea level has an increasing trend over the measurement time period, with mean slopes of 0.024 in the 0–0.2 cm layer and 0.016 μM d-1 in the 0.2–0.5 cm layer. Surface snow nitrate at sea level also shows a significant increasing trend, with mean slopes of 0.27, 0.20, and 0.07 μM d-1 in the top 0.2 cm, 0.2–0.5 cm, and 0.5–1.5 cm layers, respectively. Using these trends, an integrated net deposition flux of bromide of 1.01×107 molecules cm-2 s-1 and an integrated net deposition flux of nitrate of 2.6×108 molecules cm-2 s-1 were derived. In addition, nitrate and bromide in the morning samples are significantly higher than the afternoon samples, indicating a strong photochemistry effect. However, the mean bromide loss rate (0.027–0.040 μM) is smaller than the nitrate loss rate (0.23–0.362 μM) by an order of magnitude, implying the reactive bromine emission flux from snowpack is significantly smaller than the reactive nitrogen emission flux, which is consistent with the large difference between their derived net deposition fluxes. After considering the photochemical loss effect, the corrected bromide deposition flux at sea level is 2.73×107 molecules cm-2 s-1; for nitrate, the corrected deposition flux is 5.98×108 molecules cm-2 s-1. In addition, the surface snow nitrate and bromide at inland sites were found to be significantly correlated (R=0.48–0.76), and the [NO3-]/[Br-] ratio of 4–7 indicates a possible acceleration effect of reactive bromine in atmospheric NOX-to-nitrate conversion. This is the first time such an effect has been seen in snow chemistry data obtained with a sampling frequency as short as one day. [ABSTRACT FROM AUTHOR]

This study explores the role of snowpack in polar boundary layer chemistry, especially as a direct source of reactive bromine (BrOX=BrO+Br) and nitrogen (NOX=NO+NO2) in the Arctic springtime. Surface snow samples were collected daily from a Canadian high Arctic location at Eureka, Nunavut (80°N, 86°W) from the end of February to the end of March in 2018 and 2019. The snow was sampled at several sites representing distinct environments: sea ice, inland close to sea level, and a hilltop ~600 m above sea level (asl). At the inland sites, surface snow salinity has a double-peak distribution with the first and lowest peak at 0.001-0.002 practical salinity unit (psu), which corresponds to the precipitation effect, and the second peak at 0.01-0.04 psu, which is likely related to the salt accumulation effect (due to loss of water vapour by sublimation). Snow salinity on sea ice has a triple-peak distribution; its first and second peaks overlap with the inland peaks, and the third peak at 0.2-0.4 psu is likely due to the sea water effect (due to upward migration of brine on sea ice). At all sites, snow sodium and chloride concentrations increase by almost 10-fold from the top 0.2 cm to ~1.5 cm in depth. Surface snow bromide at sea level is significantly enriched, indicating a net sink of atmospheric bromine. Moreover, surface snow bromide at sea level has an increasing trend over the measurement time period, with mean slopes of 0.024 in the 0-0.2 cm layer and 0.016 μM d-1 in the 0.2-0.5 cm layer. Surface snow nitrate at sea level also shows a significant increasing trend, with mean slopes of 0.27, 0.20, and 0.07 μM d-1 in the top 0.2 cm, 0.2-0.5 cm, and 0.5-1.5 cm layers, respectively. Using these trends, an integrated net deposition flux of bromide of 1.01×107 molecules cm-2 s-1 and an integrated net deposition flux of nitrate of 2.6×108 molecules cm-2 s-1 were derived. In addition, nitrate and bromide in the morning samples are significantly higher than the afternoon samples, indicating a strong photochemistry effect. However, the mean bromide loss rate (0.027-0.040 μM) is smaller than the nitrate loss rate (0.23-0.362 μM) by an order of magnitude, implying the reactive bromine emission flux from snowpack is significantly smaller than the reactive nitrogen emission flux, which is consistent with the large difference between their derived net deposition fluxes. After considering the photochemical loss effect, the corrected bromide deposition flux at sea level is 2.73×107 molecules cm-2 s-1; for nitrate, the corrected deposition flux is 5.98×108 molecules cm-2 s-1. In addition, the surface snow nitrate and bromide at inland sites were found to be significantly correlated (R=0.48-0.76), and the [NO3-]/[Br-] ratio of 4-7 indicates a possible acceleration effect of reactive bromine in atmospheric NOX-to-nitrate conversion. This is the first time such an effect has been seen in snow chemistry data obtained with a sampling frequency as short as one day. [ABSTRACT FROM AUTHOR]

Both measurements and modelling of air pollution in the Arctic are difficult. Yet with the Arctic warming at nearly four times the global average rate, and changing emissions in and near the region, it is important to understand Arctic atmospheric composition and how it is changing. This study examines the simulations of atmospheric concentrations of methane, carbon monoxide and ozone in the Arctic by 11 models. Evaluations are performed using data from five high-latitude ground-based Fourier transform infrared (FTIR) spectrometers in the Network for the Detection of Atmospheric Composition Change (NDACC). Mixing ratios of trace gases are modelled at three-hourly intervals by CESM, CMAM, DEHM, EMEP MSC-W, GEM-MACH, GEOS-Chem, MATCH, MATCH-SALSA, MRI-ESM2, UKESM1 and WRF-Chem for the years 2008, 2009, 2014, and 2015. The comparisons focus on the troposphere (0–7 km partial columns) at Eureka, Canada; Thule, Greenland; Ny Ålesund, Norway; Kiruna, Sweden; and Harestua, Norway. Overall, the models are biased low in the tropospheric column, on average by -9.6 % for CH4, -21 % for CO and -18 % for O3. Results for CH4 are relatively consistent across the four years, whereas CO has a maximum negative bias in the spring and minimum in the summer, and O3 has a maximum difference centred around the summer. The average differences for the models are within the FTIR uncertainties for approximately 15 % of the model-location comparisons. [ABSTRACT FROM AUTHOR]

Ozone depletion over the polar regions is monitored each year by satellite and ground-based instruments. In this study, the vortex-averaged ozone loss over the last three decades is evaluated for both polar regions using the passive ozone tracer of the chemical transport model TOMCAT/SLIMCAT and total ozone observations from Systεave;me d'Analyse par Observation Zénithale (SAOZ) ground-based instruments and Multi-Sensor Reanalysis (MSR2). The passive tracer method allows us to determine the evolution of the daily rate of column ozone destruction, and the magnitude of the cumulative loss at the end of the winter. Three metrics are used to estimate the linear trend since 2000 and to assess the current situation of ozone recovery over both polar regions: 1) The maximum ozone loss at the end of the winter; 2) the onset day of ozone loss at a specific threshold and 3) the ozone loss residuals computed from the differences between annual ozone loss and ozone loss values regressed with respect to sunlit volume of polar stratospheric clouds (VPSC). This latter metric is based on linear and parabolic regressions for ozone loss in the Northern and Southern Hemispheres, respectively. In the Antarctic, metrics 1, and 3, yield trends of -2.3 and -1.8 % dec-1 for the 2000–2021 period, significant at 1 and 2 standard error (σ), respectively. For metric 2, various thresholds were considered, all of them showing a time delay for when they are reached. The trends are significant at the 2σ level and vary from 3.5 to 4.2 day dec-1 between the various thresholds. In the Arctic, metric 1 exhibits large interannual variability and no significant trend is detected; this result is highly influenced by the record ozone losses in 2011 and 2020. Metric 2 is not applied in the Northern Hemisphere due to the difficulty of finding a threshold value in a consistent number of winters. Metric 3 shows a negative trend in Arctic ozone loss residuals of -1.7 ±1 % dec-1, significant at 1σ level. This is therefore the first quantitative detection of ozone recovery in the Arctic springtime lower stratosphere. [ABSTRACT FROM AUTHOR]