Assessing the Influence of Inter Tropical Discontinuity on Total Column Ozone Variation Over West Africa

The focus of this study is to evaluate the influence of Intertropical Discontinuity (ITD) on the variation of Total column ozone (TCO). Relevant information is supplied on the temporal and spatial variability of TCO along the ITD zone, which is an important factor influencing the earth's atmosphere. Several studies over the years have established the relationship and influence several atmospheric processes have on TCO. However, the relationship between Intertropical discontinuity and TCO over West Africa has a gap. This study tends to examine the influence ITD has on TCO variation using the West Africa region as a case study. The study used Wind, ozone and dewpoint temperature data for the period between 1980-2019. To assess the variability and trend over the study region, several statistical methods were used, including Pearson correlation, Mann-Kendall, and linear regression model. The Mann-Kendall test shows an increasing trend throughout the months over the study region. Spatial analysis also revealed that regions North of the ITD has a higher concentration of TCO that the southern region of the ITD. however, ITD influence was more visible during the wet month of June to August (JJA) as the highest concentration of TCO was observed during this period across all latitude but more deviation was observed between latitude 100N to 180N, while the least occurrence is observed when ITD is at its minimum position in the month of December to February (DJF). The ACRV shows that 140N exhibit the highest variation with a value of 4.84, while the deviation is also at its highest with value of 13.65. The monthly position of ITD for Forty years was also analysed to observe the monthly deviation along the ITD region forty years and the spatial distribution of TCO was analysed from January to December. It’s of note that during the cause of this study, ozone hole which is designated by concentration less than or equal to 220DU was not recorded. The highest and the lowest value of TCO is 295DU and 227DU respectively with an average range of 68DU.

The Impact of Assimilating GPS Precipitable Water Vapor in Convective-Permitting WRF-ARW on North American Monsoon Precipitation Forecasts over Northwest Mexico

We assess the impact of GPS precipitable water vapor (GPS-PWV) data assimilation (DA) on short-range North American monsoon (NAM) precipitation forecasts, across 38 days with weak synoptic forcing, during the NAM GPS Hydrometeorological Network field campaign in 2017 over northwest Mexico. Utilizing an ensemble-based data assimilation technique, the GPS-PWV data retrieved from 18 observation sites are assimilated every hour for 12 hours into a 30-member ensemble convective-permitting (2.5 km) Advanced Research version of the Weather Research and Forecasting (WRF-ARW) model. As the assimilation of the GPS-PWV improves the initial condition of WRF by reducing the root mean square error and bias of PWV across 1200-1800 UTC, this also leads to an improvement in capturing nocturnal convection of mesoscale convective systems (MCSs; after 0300 UTC) and to an increase by 0.1 mm h-1 in subsequent precipitation during the 0300-0600 UTC period relative to no assimilation of the GPS-PWV (NODA) over the area with relatively more observation sites. This response is consistent with observed precipitation from the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement Final Precipitation product. Moreover, compared to the NODA, we find that the GPS-PWV DA decreases cloud top temperature, increases most unstable convective available energy and surface dewpoint temperature, and thus creates a more favorable condition for convective organization in the region.

Data-driven analysis of climate change in Saudi Arabia: trends in temperature extremes and human comfort indicators

We have analyzed the long-term temperature trends and extreme temperature events in Saudi Arabia between 1979 and 2019. Our study relies on the high resolution, consistent and complete ERA5 reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). We evaluated linear trends in several climate descriptors, including temperature, dewpoint temperature, thermal comfort and extreme event indices. Previous works on this topic used data from weather station observations over limited time intervals and did not include temperature data for recent years. The years 2010-2019 have been the warmest decade ever observed by instrumental temperature monitoring and comprise the eight warmest years on record. Therefore the earlier results may be incomplete and their results no longer relevant. Our findings indicate that over the past four decades, Saudi Arabia has warmed up at a rate that is 50% higher than the rest of land mass in the Northern Hemisphere. Moreover, moisture content of the air has significantly increased in the region. The increases of temperature and humidity have resulted in the soaring of dew point temperature and thermal discomfort across the country. These increases are more substantial during summers, which are already very hot compared to winters. Such changes may be dangerous to people over vast areas of the country. If the current trend persists into the future, human survival in the region will be impossible without continuous access to air conditioning.

Consistent large-scale response of hourly extreme precipitation to temperature variability

<p>Hourly precipitation extremes can intensify with higher temperatures at higher rates than theoretically expected from thermodynamic increases explained by the Clausius-Clapeyron (CC) relationship (~6.5%/K), but local scaling with surface air temperature is highly variable. Here, we use daily dewpoint temperature, a direct proxy of absolute humidity, as the scaling variable instead of surface air temperature. Using a global dataset of over 7000 hourly precipitation gauges, we estimate the at-gauge local scaling across six macro-regions; this ranges from CC to 2xCC for more than 60% of gauges. We find positive scaling in subtropical and tropical regions in contrast to previous work. Moreover, regional scaling rates show surprisingly universal behaviour at around CC, with higher scaling rates in Europe. Our results show a much greater consistency of scaling across the globe than previous work, usually at or above the CC rate, suggesting the relevance of dewpoint temperature scaling to understand future changes.   </p>

Assessing Aircraft Performance in a Warming Climate

Increases in maximum and minimum air temperatures resulting from anthropogenic climate change will present challenges to aircraft performance. Elevated density altitude (DA) reduces aircraft and engine performance and has a direct impact on operational capabilities. The frequency of higher DA will increase with the combination of higher air temperatures and higher dewpoint temperatures. The inclusion of dewpoint temperature in DA projections will become increasingly critical as minimum air temperatures rise. High DA impacts aircraft performance in the following ways: reduction in power because the engine takes in less air; reduction in thrust because a propeller is less efficient in less dense air; reduction in lift because less dense air exerts less force on the airfoils. For fixed-wing aircraft, the performance impacts include decreased maximum takeoff weight and increased true airspeed, which results in longer takeoff and landing distance. For rotary-wing aircraft, the performance impacts include reduced power margin, reduced maximum gross weight, reduced hover ceiling, and reduced rate of climb. In this research, downscaled and bias-corrected maximum and minimum air temperatures for future time periods are collected and analyzed for a selected site: Little Rock Air Force Base, Arkansas. Impacts corresponding to DA thresholds are identified and integrated into risk probability matrices enabling quantifiable comparisons. As the magnitude and frequency of high DA occurrences are projected to increase as a result of climate change, it is imperative for military mission planners and acquisition officers to comprehend and utilize these projections in their decision-making processes.

Optimization and Simulation of a CFR Engine Fueled by Dilute Anode Tail-Gas

Recent innovations in Metal Supported Solid Oxide Fuel Cells (MS-SOFC) have increased the longevity and reliability of fuel cells. These innovations drive the desire to create power generating systems that combine different ways of extracting power from a fuel to increase overall thermal efficiency. This investigation assesses the feasibility of operating an internal combustion engine with the anode tail-gas, which is a blend of H2, CO, CO2, H2O, and CH4, exhausted by a MS-SOFC. This engine would be used to support fuel cell balance of plant equipment and produce excess electrical power. Four variations of the expected anode tail-gas blends were determined by varying the dewpoint temperature of the fuel. Gas blends are tested by combining separate flows of each constituent, and combustion is tested using a Cooperative Fuel Research (CFR) engine. Compression ratio, spark timing, inlet manifold temperature, and boost pressure were used to obtain optimal operating conditions. Stable engine operation was obtained on all test blends. A combination of computational fluid dynamics (CFD) and analysis of chemical species and reaction mechanisms is used to develop an engine and combustion model. This model allows for further investigation into anode tail-gas combustion characteristics. Response Surface Method Optimization was used to experimentally optimize operating parameters and determine the maximum achievable efficiency utilizing the CFR engine. All test blends with H2O produced power in the engine although the blend with the most water content caused operational problems with the CFR engine test stand, including large amounts of water entering the oil system. Three chemical kinetic mechanisms were investigated that had the correct species for simulating the fuel with a low number of reactions to facilitate low computational time: San Diego (SD), GRI and Gallway 2017 (NUIG) mechanism. Out of these four mechanisms, the NUIG mechanism results fit the CFR engine experimental data best. Response Surface Method Optimization was performed on the most viable test blends, the steam injections blends at 40°C and 90°C fuel dewpoint temperature. During optimization the 40°C dewpoint temperature blend brake efficiency increased from 20% to 21.6%, and the 90°C dewpoint temperature blend brake efficiency increased from 17% to 22.3%.

Effects of Water Level Decline in Lake Urmia, Iran, on Local Climate Conditions

Lake Urmia in northwestern Iran is the largest lake in Iran and the second largest saltwater lake in the world. The water level in Lake Urmia has decreased dramatically in recent years, due to drought, climate change, and the overuse of water resources for irrigation. This shrinking of the lake may affect local climate conditions, assuming that the lake itself affects the local climate. In this study, we quantified the lake’s impact on the local climate by analyzing hourly time series of data on climate variables (temperature, vapor pressure, relative humidity, evaporation, and dewpoint temperature for all seasons, and local lake/land breezes in summer) for the period 1961–2016. For this, we compared high quality, long-term climate data obtained from Urmia and Saqez meteorological stations, located 30 km and 185 km from the lake center, respectively. We then investigated the effect of lake level decrease on the climate variables by dividing the data into periods 1961–1995 (normal lake level) and 1996–2016 (low lake level). The results showed that at Urmia station (close to the lake), climate parameters displayed fewer fluctuations and were evidently affected by Lake Urmia compared with those at Saqez station. The effects of the lake on the local climate increased with increasing temperature, with the most significant impact in summer and the least in winter. The results also indicated that, despite decreasing lake level, local climate conditions are still influenced by Lake Urmia, but to a lesser extent.

Effects of Water Level Decline in Lake Urmia, Iran, on Local Climate Conditions

Lake Urmia in northwestern Iran is the largest lake in Iran and the second largest saltwater lake in the world. The water level in Lake Urmia has decreased dramatically in recent years, due to drought, climate change, and overuse of water resources for irrigation. This shrinking of the lake may affect local climate conditions, assuming that the lake itself affects the local climate. In this study, we quantified the lake’s impact on the local climate by analyzing hourly time series of data on climate variables (temperature, vapor pressure, relative humidity, evaporation, and dewpoint temperature for all seasons, and local lake/land breezes in summer) for the period 1961-2016. For this, we compared high quality, long-term climate data obtained from Urmia and Saqez meteorological stations, located 30 km and 185 km from the lake center, respectively. We then investigated the effect of lake level decrease on the climate variables by dividing the data into 1961-1995 (normal lake level) and 1996-2016 (low lake level). The results showed that at Urmia station (close to the lake), climate parameters displayed fewer fluctuations and were evidently affected by Lake Urmia compared with those at Saqez station. The effects of the lake on the local climate increased with increasing temperature, with the most significant impact in summer and the least in winter. The results also indicated that, despite decreasing lake level, local climate conditions are still influenced by Lake Urmia, but to a lesser extent.

Comparison of WBGTs over Different Surfaces within an Athletic Complex

Many athletic governing bodies are adopting on-site measurement of the wet-bulb globe temperature (WBGT) as part of their heat safety policies. It is well known, however, that microclimatic conditions can vary over different surface types and a question is whether more than one WBGT sensor is needed to accurately capture local environmental conditions. Our study collected matched WBGT data over three commonly used athletic surfaces (grass, artificial turf, and hardcourt tennis) across an athletic complex on the campus of the University of Georgia in Athens, GA. Data were collected every 10 min from 9:00 a.m. to 6:00 p.m. over a four-day period during July 2019. Results indicate that there is no difference in WBGT among the three surfaces, even when considered over morning, midday, and afternoon practice periods. We did observe microclimatic differences in dry-bulb temperature and dewpoint temperature among the sites. Greater dry-bulb and lower dewpoint temperatures occurred over the tennis and artificial turf surfaces compared with the grass field because of reduced evapotranspiration and increase convective transfers of sensible heat over these surfaces. The lack of difference in WBGT among the surfaces is attributed to the counterbalancing influences of the different components that comprise the index. We conclude that, in a humid, subtropical climate over well-watered grass, there is no difference in WBGT among the three athletic surfaces and that, under these circumstances, a single monitoring site can provide representative WBGTs for nearby athletic surfaces.