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1. Trends in the Airglow Temperatures in the MLT Region—Part 3: Ground-Based and SABER Measurements

   https://doi.org/10.3390/atmos12091161  

   Huang, Tai-Yin; Vanyo, Michael (September 2021, Atmosphere)

   Ground-based temperature measurements at Svalbard, Wuppertal, and Hohenpeissenberg were analyzed to obtain F10.7, Ap index, and Dst index trends. The trends were then compared to those obtained from Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) temperature measurements at the same locations. Trend analysis was carried out for overlapped time periods, full range of available data, and the CO2-detrended full range of available data. The Svalbard meteor radar (SABER) temperature showed a weak (moderate) correlation with F10.7 and a moderate (weak) correlation with Ap and Dst indices. The trends in the Wuppertal OH* temperature compare well with the SABER temperature when a full range of data is used in the analysis. Both temperatures had a similar F10.7 trend with the same level of correlation coefficient. The F10.7 trend in the Hohenpeissenberg OH* temperature compared well with that obtained by SABER, but the former displayed a weak correlation. The Hohenpeissenberg data displayed a very weak correlation with Ap and Dst indices. Our study clearly shows that a longer dataset would better capture trends in temperature, as was evidenced by the results of Wuppertal data. The CO2-detrended temperatures overall showed slightly larger trend values with a slightly better correlation. 

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2. Trends in the Airglow Temperatures in the MLT Region—Part 1: Model Simulations

   https://doi.org/10.3390/atmos11050468  

   Huang, Tai-Yin; Vanyo, Michael (May 2020, Atmosphere)

   Airglow intensity-weighted temperature variations induced by the CO2 increase, solar cycle variation (F10.7 as a proxy) and geomagnetic activity (Ap index as a proxy) in the Mesosphere and Lower Thermosphere (MLT) region were simulated to quantitatively assess their influences on airglow temperatures. Two airglow models, MACD-00 and OHCD-00, were used to simulate the O(1S) greenline, O2(0,1) atmospheric band, and OH(8,3) airglow temperature variations induced by these influences to deduce the trends. Our results show that all three airglow temperatures display a linear trend of ~−0.5 K/decade, in response to the increase of CO2 gas concentration. The airglow temperatures were found to be highly correlated with Ap index, and moderately correlated with F10.7, with the OH temperature showing an anti-correlation. The F10.7 and Ap index trends were found to be ~−0.7 ± 0.28 K/100SFU and ~−0.1 ± 0.02 K/nT in the OH temperature, 4.1 ± 0.7 K/100SFU and ~0.6 ± 0.03 K/nT in the O2 temperature and ~2.0 ± 0.6 K/100SFU and ~0.4 ± 0.03 K/nT in the O1S temperature. These results indicate that geomagnetic activity can have a rather significant effect on the temperatures that had not been looked at previously. 

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3. Historical Trends in New Mexico Forage Crop Production in Relation to Climate, Energy, and Rangelands

   https://doi.org/10.3390/su12052051  

   Zaied, Ashraf J.; Geli, Hatim M.; Sawalhah, Mohammed N.; Holechek, Jerry L.; Cibils, Andres F.; Gard, Charlotte C. (March 2020, Sustainability)

   This study was conducted within the context of providing an improved understanding of New Mexico’s food, energy, water systems (FEWS) and their behavior under variable climate and socioeconomic conditions. The goal of this paper was to characterize the relationships between production and prices of some forage crops (hay, grain sorghum, and corn) that can be used as feed supplements for beef cattle production and the potential impacts from a changing climate (precipitation, temperature) and energy inputs (crude oil production and prices). The analysis was based on 60 years of data (1958–2017) using generalized autoregressive conditional heteroscedasticity models. Hay production showed a declining trend since 2000 and in 2017, it dropped by ~33% compared to that of 2000. Crude oil production (R2 = 0.83) and beef cattle population (R2 = 0.85) were negatively correlated with hay production. A moderate declining trend in mean annual hay prices was also observed. Mean annual range conditions (R2 = 0.60) was negatively correlated with mean annual hay prices, whereas mean annual crude oil prices (R2 = 0.48) showed a positive relationship. Grain sorghum production showed a consistent declining trend since 1971 and in 2017, it dropped by ~91% compared to that of 1971. Mean annual temperature (R2 = 0.58) was negatively correlated with grain sorghum production, while beef cattle population (R2 = 0.61) and range conditions (R2 = 0.51) showed positive linear relationships. Mean annual grain sorghum prices decreased since the peak of 1974 and in 2017, they dropped by ~77% compared to those of 1974. Crude oil prices (R2 = 0.72) and beef cattle population (R2 = 0.73) were positively correlated with mean annual grain sorghum prices. Corn production in 2017 dropped by ~61% compared to the peak that occurred in 1999. Crude oil production (R2 = 0.85) and beef cattle population (R2 = 0.86) were negatively correlated with corn production. Mean annual corn prices showed a declining trend since 1974 and in 2017, they dropped by ~75% compared to those of 1974. Mean annual corn prices were positively correlated with mean annual precipitation (R2 = 0.83) and negatively correlated with crude oil production (R2 = 0.84). These finding can particularly help in developing a more holistic model that integrates FEWS components to explain their response to internal (i.e., management practices) and external (i.e., environmental) stressors. Such holistic modeling can further inform the development and adoption of more sustainable production and resource use practices. 

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4. Quasi‐Biennial Oscillation of Short‐Period Planetary Waves and Polar Night Jet in Winter Antarctica Observed in SABER and MERRA‐2 and Mechanism Study With a Quasi‐Geostrophic Model

   https://doi.org/10.1029/2019GL084759  

   Lu, Xian; Wu, Haonan; Chu, Xinzhao; Oberheide, Jens; Mlynczak, Martin G.; Russell, III, James M. (November 2019, Geophysical Research Letters)

   Abstract Analyzing Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) observations from 2003 to 2018, the interannual variability of 2–5d eastward propagating planetary waves is found to correlate positively with zonal‐mean zonal winds averaged over 67.5°±10°S but negatively with the quasi‐biennial oscillation (QBO) index in austral winter. The composite‐mean wave amplitudes are ~20% larger in QBOe than in QBOw. On statistical average, the poleward flank strengthening and the equatorward flank weakening of polar night jet (PNJ) during QBOe form a dipole‐cell pattern. In contrast, only a single negative cell is seen in the Northern Hemisphere zonal‐mean zonal winds (January) previously explained by the Holton‐Tan theory. Such difference implies an interhemispheric asymmetry and other processes needed to explain the additional positive cell in Antarctica. Mechanistic modeling illustrates that the stronger PNJ generates eastward propagating planetary waves with larger growth rates (stronger waves) in QBOe than QBOw, explaining the QBO‐like signal in the Antarctic planetary waves. 

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5. Independent validation of downscaled climate estimates from a coastal Alaska watershed using local historical weather journals

   https://doi.org/10.7717/peerj.12055  

   Williamson, Emily R.; Sergeant, Christopher J. (January 2021, PeerJ)

   Downscaling coarse global and regional climate models allows researchers to access weather and climate data at finer temporal and spatial resolution, but there remains a need to compare these models with empirical data sources to assess model accuracy. Here, we validate a widely used software for generating North American downscaled climate data, ClimateNA, with a novel empirical data source, 20th century weather journals kept by Admiralty Island, Alaska homesteader, Allen Hasselborg. Using Hasselborg’s journals, we calculated monthly precipitation and monthly mean of the maximum daily air temperature across the years 1926 to 1954 and compared these to ClimateNA data generated from the Hasselborg homestead location and adjacent areas. To demonstrate the utility and potential implications of this validation for other disciplines such as hydrology, we used an established regression equation to generate time series of 95% low duration flow estimates for the month of August using mean annual precipitation from ClimateNA predictions and Hasselborg data. Across 279 months, we found strong correlation between modeled and observed measurements of monthly precipitation ( ρ  = 0.74) and monthly mean of the maximum daily air temperature ( ρ  = 0.98). Monthly precipitation residuals (calculated as ClimateNA data - Hasselborg data) generally demonstrated heteroscedasticity around zero, but a negative trend in residual values starting during the last decade of observations may have been due to a shift to the cold-phase Pacific Decadal Oscillation. Air temperature residuals demonstrated a consistent but small positive bias, with ClimateNA tending to overestimate air temperature relative to Hasselborg’s journals. The degree of correlation between weather patterns observed at the Hasselborg homestead site and ClimateNA data extracted from spatial grid cells across the region varied by wet and dry climate years. Monthly precipitation from both data sources tended to be more similar across a larger area during wet years (mean ρ across grid cells = 0.73) compared to dry years (mean ρ across grid cells = 0.65). The time series of annual 95% low duration flow estimates for the month of August generated using ClimateNA and Hasselborg data were moderately correlated ( ρ  = 0.55). Our analysis supports previous research in other regions which also found ClimateNA to be a robust source for past climate data estimates. 

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