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At least 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Water Vapor Transport Over the Tropical Oceans During ENSO as Diagnosed from TRMM and SSM/I Data

Traditionally, large-scale water vapor transport [div Q] has been derived directly from circulation statistics in which transport processes are often depicted by mean and eddy motions. Thus detailed and accurate calculations of moisture transport terms over the globe are required. Notably, the lack of systematically spaced conventional measurements of meteorological variables over oceans has hindered understanding of the distribution and transport of water vapor. This motivates the use of indirect calculation methods in which horizontal divergence of water vapor is balanced by the evaporation minus precipitation, assuming the rate of changes of precipitable water and condensates is small over a sufficiently long time period. In order to obtain the water vapor transport, we need evaporation rate minus precipitation (E-P). Focussing on the differences in water vapor transport between El Nino and La Nina periods and their influences on atmospheric circulations, we study January, February, and March of 1998 and 1999 periods which represent El Nino and La Nina respectively. SSM/I-derived precipitation and evaporation rate from SSM/I wind and total precipitable water, in conjunction with NCEP SST and surface air temperature, are used for the calculation of the transport potential function. For the retrieval of evaporation we use a stability-dependent aerodynamic bulk scheme developed by Chou (1993). It was tested against aircraft covariance fluxes measured during cold air outbreaks over the North Atlantic Ocean. Chou et al. (1997) reported that the SSM/I retrieved latent heat flux over the western Pacific warm pool area were found to be comparable with daily mean fluxes of a ship measurements during TOGA/COARE.

Robertson, Franklin R.↗
DOE OSTI2023

More Frequent and Persistent Heatwaves Due To Increased Temperature Skewness Projected by a High‐Resolution Earth System Model

Abstract Heatwaves are strongly associated with temperature distributions, but the mechanisms by which distributions are influenced by climate change remains unclear. Comparing simulations from a high‐spatial resolution Community Earth System Model (CESM‐HR) with those from low‐resolution models, we identify substantial improvements by CESM‐HR in reproducing observed Northern Hemisphere summer temperature skewness, as well as the frequency, intensity, persistence, and total heatwave days. Temperature skewness is strongly linked to land‐atmosphere interactions and atmospheric circulation. Under global warming projections, some regions exhibit enhanced temperature skewness, along with more frequent and persistent heatwaves of greater intensity. We find that in energy‐limited regimes, such as India, negative skewness in latent heat flux facilitates large positive skewness in sensible heat flux, which modulates near‐surface air temperatures. Skewness differences of latent and sensible heat fluxes are amplified under global warming, increasing the temperature skewness. We find that this contrasting flux mechanism is active in several heatwave‐prone regions.

Gao, Yang↗
NASA NTRS2015

Spatial and Temporal Variation in Primary Productivity (NDVI) of Coastal Alaskan Tundra: Decreased Vegetation Growth Following Earlier Snowmelt

In the Arctic, earlier snowmelt and longer growing seasons due to warming have been hypothesized to increase vegetation productivity. Using the Normalized Difference Vegetation Index (NDVI) from both field and satellite measurements as an indicator of vegetation phenology and productivity, we monitored spatial and temporal patterns of vegetation growth for a coastal wet sedge tundra site near Barrow, Alaska over three growing seasons (2000-2002). Contrary to expectation, earlier snowmelt did not lead to increased productivity. Instead, productivity was associated primarily with precipitation and soil moisture, and secondarily with growing degree days, which, during this period, led to reduced growth in years with earlier snowmelt. Additional moisture effects on productivity and species distribution, operating over a longer time scale, were evident in spatial NDVI patterns associated with microtopography. Lower, wetter regions dominated by graminoids were more productive than higher, drier locations having a higher percentage of lichens and mosses, despite the earlier snowmelt at the more elevated sites. These results call into question the oft-stated hypothesis that earlier arctic growing seasons will lead to greater vegetation productivity. Rather, they agree with an emerging body of evidence from recent field studies indicating that early-season, local environmental conditions, notably moisture and temperature, are primary factors determining arctic vegetation productivity. For this coastal arctic site, early growing season conditions are strongly influenced by microtopography, hydrology, and regional sea ice dynamics, and may not be easily predicted from snowmelt date or seasonal average air temperatures alone. Our comparison of field to satellite NDVI also highlights the value of in-situ monitoring of actual vegetation responses using field optical sampling to obtain detailed information on surface conditions not possible from satellite observations alone.

Growing↗
NASA NTRS2017

Temperature Changes in the United States

Temperature is among the most important climatic elements used in decision-making. For example, builders and insurers use temperature data for planning and risk management while energy companies and regulators use temperature data to predict demand and set utility rates. Temperature is also a key indicator of climate change: recent increases are apparent over the land, ocean, and troposphere, and substantial changes are expected for this century. This chapter summarizes the major observed and projected changes in near-surface air temperature over the United States, emphasizing new data sets and model projections since the Third National Climate Assessment (NCA3). Changes are depicted using a spectrum of observations, including surface weather stations, moored ocean buoys, polar-orbiting satellites, and temperature-sensitive proxies. Projections are based on global models and downscaled products from CMIP5 (Coupled Model Intercomparison Project Phase 5) using a suite of Representative Concentration Pathways (RCPs; see Ch. 4: Projections for more on RCPs and future scenarios).

Vose, R. S.↗
DOE OSTI2022

Impacts of Lake Surface Temperature on the Summer Climate Over the Great Lakes Region

The surface of the Great Lakes interacts with the atmosphere, influencing the weather and climate over the Great Lakes Region (GLR). However, most climate models were not designed with sufficient emphasis on lake–atmosphere interactions, which could potentially cause model biases over the GLR. To understand how lake surface temperature (LST) affects the regional summer climate over the GLR, we conducted twin experiments using the Weather Research and Forecasting model at a spatial resolution of 4 km using two different LST data sets as the bottom boundary condition over the Great Lakes. In this work, our simulations include 10 ensemble members for the summer of 2018 and a single multiyear run for the summers of 2014–2020. Results show that variations in LST influence atmospheric temperature and moisture at a local scale—while affecting the convective environment and precipitation processes over a much larger spatial scale. In particular, an LST that is only 1°C–3°C warmer (depending on the lake) increases near-surface air temperature by 1.93°C and 0.97°C over Lake Superior and Lake Erie, respectively, and increases evaporation over the lakes by 0.23 and 1.1 mm day –1 . The warmer LST reduces mesoscale convective precipitation upstream of the GLR; however, it increases isolated deep convective precipitation and nonconvective precipitation downstream of GLR due to increased local instability and enhancement of moisture transport. Our analyses confirm the robustness of these impacts, which is at least 2 times larger than the model internal variability and is seen across all simulated summer seasons.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Accuracy requirements

Satellite and surface measurements, if they are to serve as a climate monitoring system, must be accurate enough to permit detection of changes of climate parameters on decadal time scales. The accuracy requirements are difficult to define a priori since they depend on unknown future changes of climate forcings and feedbacks. As a framework for evaluation of candidate Climsat instruments and orbits, we estimate the accuracies that would be needed to measure changes expected over two decades based on theoretical considerations including GCM simulations and on observational evidence in cases where data are available for rates of change. One major climate forcing known with reasonable accuracy is that caused by the anthropogenic homogeneously mixed greenhouse gases (CO2, CFC's, CH4 and N2O). Their net forcing since the industrial revolution began is about 2 W/sq m and it is presently increasing at a rate of about 1 W/sq m per 20 years. Thus for a competing forcing or feedback to be important, it needs to be of the order of 0.25 W/sq m or larger on this time scale. The significance of most climate feedbacks depends on their sensitivity to temperature change. Therefore we begin with an estimate of decadal temperature change. Presented are the transient temperature trends simulated by the GISS GCM when subjected to various scenarios of trace gas concentration increases. Scenario B, which represents the most plausible near-term emission rates and includes intermittent forcing by volcanic aerosols, yields a global mean surface air temperature increase Delta Ts = 0.7 degrees C over the time period 1995-2015. This is consistent with the IPCC projection of about 0.3 degrees C/decade global warming (IPCC, 1990). Several of our estimates below are based on this assumed rate of warming.

Delgenio, Anthony↗
NASA NTRS1985

The cryptoendolithic microbial environment in the Antarctic cold desert: temperature variations in nature

In the Antarctic cold desert, cryptoendolithic microorganisms live under the surface of porous sandstone rocks. During the austral summer, the environment of the near-surface rock layers colonized by organisms is characterized by two kinds of temperature oscillations, both occurring across the freezing point. Low-frequency (diurnal) and large-amplitude (up to about 20 degrees C) oscillations on the sunlit surface of rocks result in a daily freeze-thaw cycle. This is a result of the diurnal changes in the sun altitude and angle with respect to the rock surface. The biological effect of this oscillation is the regulation of the onset and cessation of metabolic activity. The high-frequency (few minutes) oscillations occur only under certain weather conditions (sunny days with light winds) and are superimposed on the low-frequency oscillations. They are caused by the cooling effect of wind gusts on rock surfaces that are much warmer than ambient air temperatures. High-frequency oscillations result in a rapid freeze-thaw cycle on the surface, which, however, does not reach the microbial zone. These high-frequency freeze-thaw oscillations are probably the cause of the abiotic nature of the rock surface. Both oscillations seem to have an effect on rock weathering.

Cold Climate↗
DOE OSTI2026

Measuring Climate and Water Risk across the Bulk Power System

As climate impacts increase and power systems transition to renewables, planners and operators need insights into climate risks to power generation and infrastructure to ensure reliable decision-making in the short and long-term. We present a standardized, consistent mechanism for utilities and system operators to evaluate the climate- and water-related risks of their current and future grid assets. Using a risk-based approach on the combined outcomes of high-fidelity climate drivers together with water and power system models, we examine the temperature and water availability impacts within the contiguous United States to power system assets at the water basin level in three different time periods and report resulting outcomes on lost capacity across different expansion scenarios and climate models. The results indicate that air temperature has the highest effect on derating. Changes in streamflow do not have a large impact on generation capacity at the national level. Electric sector buildout scenarios each have a unique regional risk profile, depending on the technology mix and total capacity, although risks from high temperatures are significant for both traditional and renewable energy generation. Stakeholders can use this approach to monitor effects of generation capacity losses and potential impacts as climate, generation mix, and infrastructure change.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Deep Learning Advances Arctic River Water Temperature Predictions

The accelerated warming in the Arctic poses serious risks to freshwater ecosystems by altering streamflow and river thermal regimes. However, limited research on Arctic River water temperatures exists due to data scarcity and the absence of robust methodologies, which often focus on large, major river basins. To address this, we leveraged the newly released, extensive AKTEMP data set and advanced machine learning techniques to develop a Long Short-Term Memory (LSTM) model. By incorporating ERA5-Land reanalysis data and integrating physical understanding into data-driven processes, our model advanced river water temperature predictions in ungauged, snow- and permafrost-affected basins in Alaska. Our model outperformed existing approaches in high-latitude regions, achieving a median Nash-Sutcliffe Efficiency of 0.95 and root mean squared error of 1.0°C. The LSTM model learned air temperature, soil temperature, solar radiation, and thermal radiation—factors associated with energy balance—were the most important drivers of river temperature dynamics. Soil moisture and snow water equivalent were highlighted as critical factors representing key processes such as thawing, melting, and groundwater contributions. Glaciers and permafrost were also identified as important covariates, particularly in seasonal river water temperature predictions. Our LSTM model successfully captured the complex relationships between hydrometeorological factors and river water temperatures across varying timescales and hydrological conditions. This scalable and transferable approach can be potentially applied across the Arctic, offering valuable insights for future conservation and management efforts.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Snowpack ground truth: Radar test site, Steamboat Springs, Colorado, 8-16 April 1976

Ground-truth data taken at Steamboat Springs, Colorado is presented. Data taken during the period April 8, 1976 - April 16, 1976 included the following: (1) snow depths and densities at selected locations (using a Mount Rose snow tube); (2) snow pits for temperature, density, and liquid water determinations using the freezing calorimetry technique and vertical layer classification; (3) snow walls were also constructed of various cross sections and documented with respect to sizes and snow characteristics; (4) soil moisture at selected locations; and (5) appropriate air temperature and weather data.

Howell, S.↗
NASA NTRS1979

Importance of temperature control for HEFLEX, a biological experiment for Spacelab 1

The importance of temperature control to HEFLEX, a Spacelab experiment designed to measure kinetic properties of Helianthis nutation in a low-g environment, is discussed. It is argued that the development of the HEFLEX experiment has been severely hampered by the inadequate control of ambient air temperature provided by the spacecraft module design. A worst case calculation shows that delivery of only 69% of the maximum yield of useful data from the HEFLEX system is guaranteed; significant data losses from inadequate temperature control are expected. The magnitude of the expected data losses indicates that the cost reductions associated with imprecise temperature controls may prove to be a false economy in the long term.

Chapman, D. K.↗
NASA NTRS1980

A short-range objective nocturnal temperature forecasting model

A relatively simple, objective, nocturnal temperature forecasting model suitable for freezing and near-freezing conditions has been designed so that a user, presumably a weather forecaster, can put in standard meteorological data at a particular location and receive an hour-by-hour prediction of surface and air temperatures for that location for an entire night. The user has the option of putting in his own estimates of wind speeds and background sky radiation which are treated as independent variables. An analysis of 141 test runs show that 57.4% of the time the model predicts to within 1 C for the best cases and to within 3 C for 98.0% of all cases.

Sutherland, R. A.↗
NASA NTRS1959

Exploratory Investigation of Aerodynamic Flameholders for Afterburner Application

An investigation was conducted to determine the flameholding capabilities of aerodynamic jets at afterburner operating conditions. Stability data for a number of aerodynamic flameholders were obtained in a 5- by 5-inch test section at inlet-air reference velocities up to 600 feet per second, an inlet-air temperature of 1250 F, and a combustor-inlet pressure of 15 inches of mercury absolute. Combustion efficiency and stability data of the more promising combinations were then obtained in a 10- by 12-inch test section at the same test conditions. Both air and stoichiometric mixtures of fuel and air were used in the jets; mixture flow rates were approximately 1 percent by weight of the total air-flow rate. Injection pressures were limited to values that might be available from compressor-bleed air. At a reference velocity of 600 feet per second, aerodynamic flame-holders alone were unable to maintain a stable flame at injection pressures up to 70 pounds per square inches large reductions in velocity were required to achieve flame stabilization. When the aerodynamic jets were used in combination with a V-gutter flameholder with approximately a 30 percent blocked area, flame stabilization was attained at a velocity of 600 feet per second; however, the combustion efficiencies of the various combinations were no greater than that obtained with the V-gutter alone.

Butze, Helmut F.↗
DOE OSTI2024

Integration and validation of some modules for modelling of high-speed chemically reactive flows in two-phase gas-droplet mixtures

Three modules are integrated into the built-in OpenFOAM rhoCentralFoam solver towards accurate and efficient modelling of high-speed chemically reactive flows in two-phase gas-droplet mixtures within the OpenFOAM 10.0 framework. The first module is the mixture-averaged diffusion model. The second module is the built-in OpenFOAM Lagrangian solver coupled with optimised droplet drag coefficient and convective heat transfer coefficient sub-models. The last module is a sparse stiff chemistry solver based on dynamic adaptive hybrid integration (AHI-S). The optimised droplet sub-models are first verified in correct implementation for subsequent simulations in this work. Further, they show good accuracy against experimental and analytical data in the modelling of ammonia droplet acceleration and cooling in the flowing and/or low-temperature air. The accuracy and efficiency gains related to the mixture-averaged diffusion model and the AHI-S chemistry solver are examined by simulating 1-D detonation propagation in ammonia droplet-free/laden ammoniaoxygen mixtures. Numerical results of detonation propagation speed, gaseous temperature, density, and species distributions around the induction zone show good agreement with experimental data and analytical solutions. Compared to the built-in OpenFOAM diffusion model, the mixture-averaged diffusion model provides different numerical predictions of pulsating instabilities in detonation propagation. It shows better accuracy in depicting the detonation structure within the droplet-free section attributed to improved multi-component diffusion modelling. Compared to the built-in OpenFOAM solver EulerImplicit (backward Euler), the AHI-S chemistry solver reduces the computational cost by around 50%. It achieves satisfactory accuracy in calculating detonation propagation speed within the droplet-free section with the optimal efficiency when the safety factor, β, equals 0.5.

42 ENGINEERING↗
DOE OSTI2022

Effects of Vegetation on Fluxes of Nitric Oxide, Nitrogen Dioxide, and Nitrous Oxide in a Mixed Deciduous Forest Clearing

Atmosphere-terrestrial exchange of nitrogen oxides, such as nitric oxide (NO), nitrogen dioxide (NO2) and nitrous oxide (N2O), plays an important role in controlling atmospheric composition and the radiative forcing of Earth’s atmosphere. In this study, the impact of vegetation ground cover on NOx (NOx = NO + NO2) and N2O fluxes in a deciduous forest clearing was studied using dynamic flow chambers located on three experimental plots with differing vegetation ground cover. Microbial emissions of NO and N2O were observed throughout the measurement period, while NO2 was exclusively deposited. Vegetation had no observable impact on NO2 deposition. Under dry conditions, total measured nitrogen emissions were numerically similar across all plots, although the N2O:NO ratio was higher for plots containing plants. Vegetation elevates soil water content through enhanced water retention, a condition that favors denitrification and more N2O production, relative to NO. Two rain events induced pulses of NO and N2O that were higher for bare soil compared to the vegetated plots. Lower NO and N2O emissions in plant-containing chambers stemmed from enhanced root uptake of N following rewetting, which diminished the amount of N substrate available for microbial NO and N2O production. The sensitivity of soil N emissions to vegetation ground cover highlights the need for more studies that investigate this effect over a wide range of ecosystems and to include vegetation effects in future parameterizations of soil NOx and N2O used in atmospheric models. This dataset includes processed data collected from 4 dynamic flux chambers and 17 sensors. Data includes ambient gas measurements made 1 m from the surface and soil flux measurements of NO, NO2, N2O, ozone (O3) and carbon dioxide (CO2). Also included is a suite of meteorological (air temperature, humidity, pressure) and soil parameters (water filled pore space, soil temperature). Refer to the readme for more information about each of the data sets.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1977

Development of spiral-groove self-acting face seals

An experimental evaluation and a 100-hour endurance test were performed on a spiral groove geometry, self-acting face seal. The seal was tested and operated successfully at maximum conditions of 243.8 m/s surface speed, 199.9 N/sq cm air pressure, and 645.4K (702 F) air temperature. The maximum speed condition of 243.8 m/s was obtained at a shaft speed of 72,500 rpm. Seal wear, gas leakage, and sealing element temperature were monitored during the test. Condition of the seal at the completion of the test was documented and found acceptable for further use. The spiral groove wear rate measured during the endurance test indicates a minimum potential seal life of over 2700 hours. Seal air leakage measured during the test program is within the range considered acceptable for consideration for use in a small gas turbine engine.

Obrien, M.↗
DOE OSTI2023

Performance analysis and comparison of data-driven models for predicting indoor temperature in multi-zone commercial buildings

Building thermal models, which characterize the properties of a building’s envelope and thermal mass, are essential for accurate indoor temperature and cooling/heating demand prediction. Because of their flexibility and ease of use, data-driven models are increasingly used. Here, this study compared and analyzed the performance of gray-box (resistance-capacitance) and black-box (recurrent neural network) models for predicting indoor air temperature in a real multi-zone commercial building. The developed resistance-capacitance model served as a benchmark model for which full sets of temporal data and building information were used as inputs. The recurrent neural network models were trained and tested assuming various available types and amounts of temporal data and known building physical information to investigate the effects of data and information availability. Feature importance analysis was conducted to select the key variables for different prediction targets under different scenarios. This research provides guidance in selecting an appropriate building thermal response modeling method based on the measured data availability, building physical information, and application.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1955

Ideal Temperature Rise Due to Constant-pressure Combustion of a JP-4 Fuel

The ideal temperature rise due to the constant-pressure combustion of a methylene (CH sub 2) fuel was calculated. CH sub 2 fuel closely approximates MIL-F-5624 grade JP-4 fuel presently used in most turbojet and ram-jet engines. Charts are presented from which the ideal temperature rise or the ideal quantity of fuel required to obtain a specified combustion temperature may be obtained for any flight condition likely to be encountered with turbojet or ram-jet engines using this fuel. The charts are applicable only to a fuel having a hydrogen-carbon mass ratio of 0.168. They include a range of fuel-air ratios from 0 to 1.2 fraction of stoichiometric fuel-air ratio with dissociation taken into account, inlet-air temperatures from 400 degrees to 1600 degrees R, and combustion pressures from 1/16 to 64 atmospheres. The use of the charts is illustrated by several examples.

Huntley, S C↗