The Effect of Carburetor-air Temperature on the Cooling Characteristics of a Typical Air-cooled Engine Cylinder
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Detailed studies of the energy and water cycles require accurate estimation of the turbulent fluxes of moisture and heat across the atmosphere-ocean interface at regional to basin scale. Providing estimates of these latent and sensible heat fluxes over the global ocean necessitates the use of satellite or reanalysis-based estimates of near surface variables. Recent studies have shown that errors in the surface (10 meter)estimates of humidity and temperature are currently the largest sources of uncertainty in the production of turbulent fluxes from satellite observations. Therefore, emphasis has been placed on reducing the systematic errors in the retrieval of these parameters from microwave radiometers. This study discusses recent improvements in the retrieval of air temperature and humidity through improvements in the choice of algorithms (linear vs. nonlinear) and the choice of microwave sensors. Particular focus is placed on improvements using a neural network approach with a single sensor (Special Sensor Microwave/Imager) and the use of combined sensors from the NASA AQUA satellite platform. The latter algorithm utilizes the unique sampling available on AQUA from the Advanced Microwave Scanning Radiometer (AMSR-E) and the Advanced Microwave Sounding Unit (AMSU-A). Current estimates of uncertainty in the near-surface humidity and temperature from single and multi-sensor approaches are discussed and used to estimate errors in the turbulent fluxes.
The dataset contains "ecosys" model outputs reported in Mekonnen et al. (2021) to examine the importance of heat transfer from precipitation on permafrost degradation. The study highlighted the importance of mechanistically representing this process in earth system models (ESMs) and demonstrated that precipitation is as important an environmental control on permafrost degradation as surface air temperature. Included are (1) the modeled spatially averaged annual active layer depth (ALD) and daily maximum soil temperature across the North Slope of Alaska from 1980 to 2100, and (2) 25 km resolution modeled ALD for averaged for two time intervals, 2006 - 2010 and 2096 - 2100. The results are provided for two "ecosys" simulations: S1 with precipitation heat transfer and S2 without precipitation heat transfer across the North Slope of Alaska. These data are available in a NetCDF and csv data formats. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
As noted by Gray et al., Sir William Herschel was the first to suggest a possible close connection between the Sun and the Earth’s climate. The Sun, being the source of energy that impacts and drives the Earth’s climate system, displays a variety of changes over both short and long term time scales, the most obvious examples being the somewhat regular waxing and waning of sunspots with time (i.e., the sunspot cycle (SC)), first described by Samuel Heinrich Schwabe, a German apothecary and amateur astronomer who observed the Sun from Dessau, Germany, and the now well established variation of the Sun’s irradiance over the SC. Other factors related to the SC have been linked to changes in climate as well. Some of these other factors include the role of cosmic rays and the solar wind (i.e., the geomagnetic cycle) on climate, as well as the apparent close association between trends in global and northern hemispheric temperature and the length of the SC, although some investigators have described the inferred association between climate and, in particular, SC length as now being weak. More recently, Solheim et al. have reported on the relation between SC length and the average temperature in the same and immediately following SC for a number of meteorological stations in Norway and in the North Atlantic region. They noted that while they found no significant trend (correlation) between SC length and the average temperature when measured for the same cycle, in contrast, they found a significant negative trend when SC length was compared with the following cycle’s average temperature. From this observation, they suggested that average northern hemispheric temperature during the present ongoing SC (SC24) will be lower by about 0.9 °C than was seen in SC23 (spanning 1996–2007, based on yearly averages of sunspot number (SSN), and onset for SC24 occurring in 2008). The purpose of this Technical Publication (TP) is to examine the annual variations of the Armagh surface air temperature (ASAT) and the Global Land-Ocean Temperature Index (GLOTI) in relation to SSN and the SC in order to determine their likely values during SC24. Hence, it may provide insight as to whether solar forcing of global temperature is now lessening as a contributor to global warming, thereby indicating a possible cooling in the near term immediate future that potentially could ameliorate the effect of increased anthropogenic warming.
Projecting future climate variables is essential for comprehending the potential impacts on hydroclimatic hazards like floods and droughts. Evaluating these impacts is challenging due to the coarse spatial resolution of global climate models (GCMs); therefore, bias correction is widely used. Here, we applied two statistical methods—standard empirical quantile mapping (EQM) and a hybrid approach, EQM with linear correction (EQM-LIN)—to bias correct precipitation and air temperature simulated by nine GCMs. We used historical observations from 20 weather stations across South Florida to project future climate under three shared socioeconomic pathways (SSPs). Compared to the EQM, the hybrid EQM-LIN method improved R 2 of daily quantiles by up to 30% over the historical period and improved MAE up to 70% in months that contain most extreme values. Projected extreme precipitation at the weather stations showed that, compared to the EQM-LIN, the EQM method underestimates the high quantiles by up to 26% in SSP585. The projected changes in annual maximum precipitation from historical period (1985–2014) to near future (2040–2069) and far future (2070–2100) were between 2% and 16% across the study area. Projected future precipitation suggested a slight decrease during summer but an increase in fall. This, along with rising summer temperatures, suggested that South Florida can experience rapid oscillations from warmer summers and increased flooding in fall under future climate. Additionally, our comparative analyses with globally and nationally downscaled studies showed that such coarse scale studies do not represent the climatic extremes well, particularly for high quantile precipitation.
This dataset consists of field measurements of CO2 and CH4 flux, as well as soil properties made during 2013 in Areas A-D of Intensive Site 1 at the Next-Generation Ecosystem Experiments (NGEE) Arctic site near Barrow, Alaska. Included are i) measurements of CO2 and CH4 flux made from June to September (ii) Calculation of corresponding Gross Primary Productivity (GPP) and CH4 exchange (transparent minus opaque) between atmosphere and the ecosystem (ii) Measurements of Los Gatos Research (LGR) chamber air temperature made from June to September (ii) measurements of surface layer depth, type of surface layer, soil temperature and soil moisture from June to September. This data package contains two *.csv files and one *.pdf file. NGEE Arctic Project Summary: The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
Abstract Observations show increases in river discharge to the Arctic Ocean especially in winter over the last decades but the physical mechanisms driving these changes are not yet fully understood. We hypothesize that even in the absence of a precipitation increase, permafrost degradation alone can lead to increased annual river runoff. To test this hypothesis we perform 12 millennium-long simulations over an idealized hypothetical watershed (1 km 2 ) using a distributed, physically based water balance model (Water flow and Balance Simulation Model, WaSiM). The model is forced by both a hypothetical warming defined by an air temperature increase of 7.5 ∘ C over 100 years, and a corresponding cooling scenario. To assess model sensitivity we vary soil saturated hydraulic conductivity and lateral subsurface flow configuration. Under the warming scenario, changes in subsurface water transport due to ground temperature changes result in a 7%–14% increase in annual runoff accompanied by a 6%–20% decrease in evapotranspiration. The increase in runoff is most pronounced in winter. Hence, the simulations demonstrate that changes in permafrost characteristics due to climate warming and associated changes in evapotranspiration provide a plausible mechanism for the observed runoff increases in Arctic watersheds. In addition, our experiments show that when lateral subsurface moisture transport is not included, as commonly done in global-scale Earth System Models, the equilibrium water balance in response to the warming or cooling is similar to the water balance in simulations where lateral subsurface transport is included. However, the transient changes in water balance components prior to reaching equilibrium differ greatly between the two. For example, for high saturated hydraulic conductivity only when lateral subsurface transport is considered, a period of decreased runoff occurs immediately after the warming. This period is characterized by a positive change in soil moisture storage caused by the soil moisture deficit developed during prior cooling.
One of the more viable research techniques into global climate change for the purpose of understanding the consequent environmental impacts is based on the use of general circulation models (GCMs). However, GCMs are currently unable to reliably predict the regional climate change resulting from global warming, and it is at the regional scale that predictions are required for understanding human and environmental responses. Regional climates in the extratropics are in large part governed by the synoptic-scale circulation and the feasibility of using this interscale relationship is explored to provide a way of moving to grid cell and sub-grid cell scales in the model. The relationships between the daily circulation systems and surface air temperature for points across the continental United States are first developed in a quantitative form using a multivariate index based on principal components analysis (PCA) of the surface circulation. These relationships are then validated by predicting daily temperature using observed circulation and comparing the predicted values with the observed temperatures. The relationships predict surface temperature accurately over the major portion of the country in winter, and for half the country in summer. These relationships are then applied to the surface synoptic circulation of the Goddard Institute for Space Studies (GISS) GCM control run, and a set of surface grid cell temperatures are generated. These temperatures, based on the larger-scale validated circulation, may now be used with greater confidence at the regional scale. The generated temperatures are compared to those of the model and show that the model has regional errors of up to 10 C in individual grid cells.
Aerosols emitted in densely populated and industrialized Indo-Gangetic Plain, one of the most polluted regions in the world, modulate regional climate, monsoon, and Himalayan glacier retreat. Thus, this region is important for understanding aerosol perturbations and their resulting impacts on atmospheric changes during COVID-19 lockdown period, a natural experimental condition created by the pandemic. By analyzing 5 years (2016–2020) data of aerosols and performing a radiative transfer calculation, we found that columnar and near-surface aerosol loadings decreased, leading to reductions in radiative cooling at the surface and top of the atmosphere and atmospheric warming during lockdown period. Further, satellite data analyses showed increases in cloud optical thickness and cloud-particle effective radius and decrease in lower tropospheric air temperature during lockdown period. These results indicate critical influences of COVID-19 lockdown on regional climate and water cycle over Indo-Gangetic Plain, emphasizing need for further studies from modeling perspectives.
A high temperature solar receiver was fabricated and tested in excess of 1370 C on an 11-meter-diameter test bed concentrator at the Jet Propulsion Laboratory Parabolic Dish Test Site, Edwards, California. The 60-kilowatt thermal receiver design utilizes state-of-the-art silicon carbide honeycomb matrix panels to receive and transfer the solar energy and mullite elements for thermal buffer storage. Solar tests were conducted with indicated air exit temperatures ranging from 885 C (1625 F) to 1427 C (2600 F), mass flow rates of 75 to 105 g/sec (0.16 to 0.23 lbm/sec), and pressures up to 265 kPa absolute (38.4 psia). Estimates of efficiency are 59.7% at 1120 C (2048 F) to 80.6% at 885 C (1625 F) when aperture spillage losses are considered separately. Results are presented which demonstrate the feasibility of this innovative receiver concept for point-focusing parabolic dish applications over a wide temperature range.
The results of an analytical investigation of the theoretical air specific impulse performance and adiabatic combustion temperatures of several possible ram-jet fuels over a range of equivalence ratios, inlet-air temperatures, and combustion pressures, is presented herein. The fuels include octane-1, 50-percent-magnesium slurry, boron, pentaborane, diborane, hydrogen, carbon, and aluminum. Thermal effects from high combustion temperatures were found to effect considerably the combustion performance of all the fuels. An increase in combustion pressure was beneficial to air specific impulse at high combustion temperatures. The use of these theoretical data in engine operation and in the evaluation of experimental data is described.
We have previously conducted a number of data assimilation experiments using AIRS Version-5 quality controlled temperature profiles as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The data assimilation and forecast system we used was the Goddard Earth Observing System Model , Version-5 (GEOS-5) Data Assimilation System (DAS), which represents a combination of the NASA GEOS-5 forecast model with the National Centers for Environmental Prediction (NCEP) operational Grid Point Statistical Interpolation (GSI) global analysis scheme. All analyses and forecasts were run at a 0.5deg x 0.625deg spatial resolution. Data assimilation experiments were conducted in four different seasons, each in a different year. Three different sets of data assimilation experiments were run during each time period: Control; AIRS T(p); and AIRS Radiance. In the "Control" analysis, all the data used operationally by NCEP was assimilated, but no AIRS data was assimilated. Radiances from the Aqua AMSU-A instrument were also assimilated operationally by NCEP and are included in the "Control". The AIRS Radiance assimilation adds AIRS observed radiance observations for a select set of channels to the data set being assimilated, as done operationally by NCEP. In the AIRS T(p) assimilation, all information used in the Control was assimilated as well as Quality Controlled AIRS Version-5 temperature profiles, i.e., AIRS T(p) information was substituted for AIRS radiance information. The AIRS Version-5 temperature profiles were presented to the GSI analysis as rawinsonde profiles, assimilated down to a case-by-case appropriate pressure level p(sub best) determined using the Quality Control procedure. Version-5 also determines case-by-case, level-by-level error estimates of the temperature profiles, which were used as the uncertainty of each temperature measurement. These experiments using GEOS-5 have shown that forecasts resulting from analyses using the AIRS T(p) assimilation system were superior to those from the Radiance assimilation system, both with regard to global 7 day forecast skill and also the ability to predict storm tracks and intensity.
The thermal state of women during the effect of high air temperature and relative humidity with a varying degree of physical loads was studied. Parameters for air temperature, relative humidity, and air movement were established. It was established that in women the thermo-regulatory stress occurs at lower air temperatures and with lower physical loads than in men. The accumulation of heat in women was revealed with lower air temperature than in men. It is concluded that to preserve the normal physiological state of the female organism it is necessary to create more favorable microclimate conditions and decrease the physical loads.
Using a high-temperature optically based displacement measurement system, a foil air bearing's stiffness and damping characteristics were experimentally determined. Results were obtained over a range of modified Sommerfeld Number from 1.5E6 to 1.5E7, and at temperatures from 25 to 538 C. An Experimental procedure was developed comparing the error in two curve fitting functions to reveal different modes of physical behavior throughout the operating domain. The maximum change in dimensionless stiffness was 3.0E-2 to 6.5E-2 over the Sommerfeld Number range tested. Stiffness decreased with temperature by as much as a factor of two from 25 to 538 C. Dimensionless damping was a stronger function of Sommerfeld Number ranging from 20 to 300. The temperature effect on damping being more qualitative, showed the damping mechanism shifted from viscous type damping to frictional type as temperature increased.
In this presentation we address several fundamental issues in the measurement of temperature and water vapor by AIRS: accuracy, precision, vertical resolution and biases as a function of cloud amount. We use two correlative data sources. First we compare AIRS total water vapor with that from the Advanced microwave Sounding Radiometer for EOS (AMSR-E) instrument, also onboard the Aqua spacecraft. AMSRE uses a mature methodology with a heritage including the operational Special Sensor Microwave Imager (SSM/I) instruments. AIRS and AMSR-E observations are collocated and simultaneous, providing a very large data set for comparison: about 200,000 over-ocean matches daily. We show small cloud-dependent biases between AIRS and AMSR-E total water vapor for several oceanic regions. Our second correlative data source is several hundred dedicated radiosondes launched during AIRS overpasses.
We conducted a new set of Data Assimilation Experiments covering the period January 1 to February 29, 2016 using the GEOS-5 DAS. Our experiments assimilate all data used operationally by GMAO (Control) with some modifications. Significant improvement in Global and Southern Hemisphere Extra-tropical 7-day forecast skill was obtained when: We assimilated AIRS Quality Controlled temperature profiles in place of observed AIRS radiances, and also did not assimilate CrISATMS radiances, nor did we assimilate radiosonde temperature profiles or aircraft temperatures. This new methodology did not improve or degrade 7-day Northern Hemispheric Extra-tropical forecast skill. We are conducting experiments aimed at further improving of Northern Hemisphere Extra-tropical forecast skill.
The molar mass of water vapor is less than that of dry air, making humid air lighter than dry air at the same temperature and pressure. This effect is known as vapor buoyancy and has been considered negligibly small in large-scale climate dynamics. Here we use theory, reanalysis data, and a hierarchy of climate models to show that vapor buoyancy has a similar magnitude to thermal buoyancy in the tropical free troposphere. We further show that vapor buoyancy makes cold air rise and increases subtropical stratiform low clouds by up to 70% of its climatological value. However, some widely used climate models fail to represent vapor buoyancy in the governing equations. Further, this flaw leads to inaccurate simulations of cloud distributions—the largest uncertainty in predicting climate change.
Abstract Surface energy budgets of high-latitude permafrost systems are poorly represented in Earth system models (ESMs), yet permafrost is rapidly degrading and these dynamics are critical to future carbon-climate feedback predictions. A potentially important factor in permafrost degradation neglected so far by ESMs is heat transfer from precipitation, although increases in soil temperature and thaw depth have been observed following increases in precipitation. Using observations and a mechanistic ecosystem model, we show here that increases in precipitation hasten active layer development beyond that caused by surface air warming across the North Slope of Alaska (NSA) under recent and 21st century climate (RCP8.5). Modeled active layer depth (ALD) in simulations that allow precipitation heat transfer agreed very well with observations from 28 Circumpolar Active Layer Monitoring sites (R 2 = 0.63; RMSE = 10 cm). Simulations that ignored precipitation heat transfer resulted in lower spatially-averaged soil temperatures and a 39 cm shallower ALD by 2100 across the NSA. The results from our sensitivity analysis show that projected increases in 21st century precipitation deepen the active layer by enhancing precipitation heat transfer and ground thermal conductivity, suggesting that precipitation is as important an environmental control on permafrost degradation as surface air temperature. We conclude that ESMs that do not account for precipitation heat transfer likely underestimate ALD rates of change, and thus likely predict biased ecosystem responses.