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Results for “Moisture transport”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Development of an Advanced Clothing Model that Considers Heat and Moisture Transport

Despite recent advancements in the development of human thermal physiology models, clothing is often considered in only a rudimentary manner, that is, as a boundary condition at the skin characterized by its bulk thermal and evaporative impedances. While such an approach may be sufficient for thermoregulation modeling of humans operating in relatively low thermal burden scenarios, e.g., within an office environment, a clothing thermal model that does not explicitly consider the layer-to-layer transport of vapor can yield incorrect results, especially under conditions corresponding to high thermal stress or extreme environments. For example, vapor diffusing through layers of clothing can reach its dew point, in which case a phase change will occur that can fundamentally affect the transport of moisture and heat within the clothing ensemble. Specifically, the evaporation and condensation of moisture within the fabric layers can affect liquid content and temperature and, ultimately, affect thermo-physiological response and thermal comfort perception. Development of an advanced clothing model that considers heat and moisture transport within the fabric layers can improve the accuracy of human thermal predictions in scenarios where clothing-based condensation and evaporation occur. This paper describes how a general heat transfer software modeling tool was modified to consider the transport of vapor, the storage of liquid, and the thermal effects of phase change within a clothing ensemble. The advanced clothing moisture model was tested by comparing its predictions to measurements derived from sweating hot plate experiments and human physiological experiments. The model was able to reproduce the thermal and moisture results from tests performed under conditions in which condensation within the clothing layers was known to occur. This study demonstrates the importance of considering layer-to-layer vapor transport in clothing models and its impact on human thermal modeling predictions.

Human thermal modeling↗
DOE OSTI2025

Atmospheric and oceanic energy transport during North Atlantic freshening events: influences of moisture transport and hydrologic cycle feedbacks

Analogs of present-day rapid ice melt can be found in episodic discharges of icebergs that occurred during glacial periods called Heinrich events. This introduces excess meltwater into the North Atlantic and weakens the Atlantic thermohaline circulation (AMOC), triggering a hydrologic cycle–AMOC collapse feedback as the atmospheric energy transport compensates for reduced northward heat transport. Here we employ a novel series of 100-year North Atlantic “hosing” simulations to investigate atmospheric and oceanic energy transport response from freshwater forcing, focusing in particular on the role of atmospheric rivers (ARs) within atmospheric energy transport. Importantly, we use an “overwriting” methodology that allow us to attribute AMOC weakening to added North Atlantic meltwater and subsequent hydrologic cycle responses, respectively. In contrast to far-reaching response of transient eddies, our results show a substantial increase in moisture convergence from ARs that is geographically constrained to the North Atlantic midlatitudes. Such AR changes nevertheless comprise an important component of net precipitation changes over the Euro-Atlantic sector, with the amount being comparable to that from transient eddies over the subpolar Atlantic. Over the course of the century-long simulations, we demonstrate that hydrologic cycle responses to North Atlantic freshening and subsequent feedbacks, including those from ARs, account for approximately half of the simulated AMOC collapse. Furthermore, our work highlights the dynamics of atmospheric moisture transport response to North Atlantic freshening events and elucidates how intensifying moisture transport may accelerate AMOC collapse in the future.

Atmospheric Science↗
NASA NTRS1986

Moisture transports and budgets of 'moisture bursts'

The paper discusses moisture fluxes and budgets associated with a pair of 'moisture bursts' in the eastern North Pacific Ocean area, described by Smith et al. (1985). The moisture fluxes were calculated using data obtained during the first Special Observing Period (SOP-1) of the FGGE. The area specifically examined extended from the equator to the latitude 20 deg N and from longitude 180 deg to 100 deg W, with concentration on the region south and southeast of the Hawaiian Islands. From the comparison of the calculations based on dropwindsonde and radiosonde data and reports from commercial and military aircraft, it is concluded that the calculations of water vapor flow across latitude lines probably provide a fair representation of reality, especially when based on the dropwindsonde data. However, water vapor flow out of small volumes is not well represented by the results from either data.

Thompson, A. H.↗
NASA NTRS1994

A class of the van Leer-type transport schemes and its application to the moisture transport in a general circulation model

A generalized form of the second-order van Leer transport scheme is derived. Several constraints to the implied subgrid linear distribution are discussed. A very simple positive-definite scheme can be derived directly from the generalized form. A monotonic version of the scheme is applied to the Goddard Laboratory for Atmospheres (GLA) general circulation model (GCM) for the moisture transport calculations, replacing the original fourth-order center-differencing scheme. Comparisons with the original scheme are made in idealized tests as well as in a summer climate simulation using the full GLA GCM. A distinct advantage of the monotonic transport scheme is its ability to transport sharp gradients without producing spurious oscillations and unphysical negative mixing ratio. Within the context of low-resolution climate simulations, the aforementioned characteristics are demonstrated to be very beneficial in regions where cumulus convection is active. The model-produced precipitation pattern using the new transport scheme is more coherently organized both in time and in space, and correlates better with observations. The side effect of the filling algorithm used in conjunction with the original scheme is also discussed, in the context of idealized tests. The major weakness of the proposed transport scheme with a local monotonic constraint is its substantial implicit diffusion at low resolution. Alternative constraints are discussed to counter this problem.

Lin, Shian-Jiann↗
DOE OSTI2025

Regional and Temporal Variability of Atmospheric River Seasonality: Influences of Detection Algorithms and Moisture Transport Dynamics

Abstract Understanding the regional and temporal variability of atmospheric river (AR) seasonality is crucial for preparedness and mitigation of extreme events. While ARs were thought to peak in winter, recent research shows they exhibit region‐specific seasonality and are heavily influenced by the chosen detection algorithm. This study examines the link between the year‐to‐year consistency of peak‐AR activity to the presence of a dominant seasonal pattern, considering both location and algorithm choice. Regions are categorized by their temporal characteristics: consistent patterns (e.g., East Asia), patterns with occasional outliers (e.g., British Columbia coast), and regions lacking a clear dominant peak season (e.g., South Atlantic, parts of Australia). Hence, not all regions display a consistent seasonal cycle of AR activity. This study quantifies the extent to which a region experiences a dominant peak season of AR activity (or lacks one) and offers insights to enhance decision‐making in water management, natural hazard preparedness, and forecasting. Furthermore, given our finding that detection algorithms influence the peak season of AR activity, we also examine two diagnostic variables representative of moisture transport to corroborate our results. Integrated vapor transport, which captures meridional and zonal moisture transport, and Moist Wave Activity, representing moisture intrusions from lower to higher latitudes, are examined. Our analysis indicates that inconsistencies in the seasonal cycle of AR activity are not solely due to discrepancies in detection algorithms but also arise from changes in moisture transport. Plain Language Summary Atmospheric rivers (ARs) are critical weather phenomena that can cause extreme events like heavy rainfall and flooding. Understanding when and where ARs are most likely to occur throughout the year is essential for preparing and responding to these events. Traditionally, ARs were thought to peak in winter, but recent studies show this varies by region. Our study helps address the challenge decision‐makers face in anticipating and preparing for AR events by providing insights into the consistency of peak seasonal patterns across different areas. Some regions, like East Asia, and the British Columbia coast, show a consistent peak season, while others, like the South Atlantic and parts of Australia, have significant year‐to‐year variations, making it hard to identify a dominant season. To better understand these changes over time, the study also examines how moisture moves in the atmosphere, using Integrated Vapor Transport (which looks at moisture movement in various directions) and Moist Wave Activity (which tracks moisture shifts from lower to higher latitudes). The findings suggest that inconsistencies in AR patterns are due not only to detection methods but also due to changes in moisture transport. Key Points The peak season of atmospheric river activity can change depending on the year in some areas Interannual variations in the peak season can make identifying a dominant season challenging for some regions Frequent shifts in peak season across years reflect inconsistencies tied to detection algorithms and to underlying dynamics

Kamnani, Diya↗
DOE OSTI2026

Evaluating Atmospheric River Impacts on Energy and Moisture Transport in the Arctic Using Different Detection Algorithms

Atmospheric rivers (ARs) significantly impact the Arctic climate system by enhancing atmospheric heat and moisture transport and altering the local energy budget. Developing AR detection tools (ARDTs) is critical yet challenging. This study evaluates 12 ARDTs in the Arctic to assess their performance in representing atmospheric heat (represented by moist static energy) and moisture transport, as well as surface downward longwave radiation (LWD) and precipitation impacts, spanning 2000 to 2019 using ERA5 reanalysis. We find that AR occurrence frequency in the Arctic varies widely, from less than 1% to over 13%, depending on the ARDT. This variability leads to differences in contributions to poleward atmospheric heat (<1%–33%) and moisture (<1%–49%) transport. The highest AR frequency, and corresponding contributions to atmospheric heat and moisture transport, occurs over the Atlantic sector during non-summer seasons for most ARDTs. This region aligns with the primary poleward moisture pathway and the end of climatological mid-latitude storm tracks, highlighting strong connections between Arctic ARs and mid-latitude cyclones. ARs induce significant LWD anomalies, largest in winter, smallest in summer, and also substantially contribute to the seasonal precipitation. Global ARDTs detect fewer ARs with larger anomalies (>100 W m−2 in higher Arctic), but contribute <1% to seasonal climatological LWD and precipitation. In contrast, polar-specific ARDTs detect higher AR occurrences and account for up to 16% of seasonal LWD and 41% precipitation. This suggests that algorithms emphasizing extreme events with large anomalies do not necessarily indicate a large climate radiative and precipitation impact.

Zhang, Chen [University of Colorado, Boulder, CO (↗
NASA NTRSDate not supplied

Multi-source Estimates of Land / Ocean Moisture Transport Variability over the Satellite Era

It is widely appreciated that atmospheric transport of water from the world’s oceans is a process key to planetary energy balance as well as Earth's habitability. What is not yet clear is the extent of variability in moisture transports, the relative importance of interdecadal variability versus climate change signals, and importantly, our ability to quantify these changes. This work assesses variations in moisture transport variability during the satellite era (~1980 to present) by comparing several different estimates. (i) The most direct estimate is the vertically integrated flux convergence of moisture from reanalyses which use observed wind and moisture information. (ii) One alternative estimate comes from P-ET over land taken from global hydrologic models constrained with precipitation and near-surface meteorology. Here we use an ensemble of six models. An adjunct to this method is to employ satellite derive ET (e.g., GLEAM or DOLCE). (iii) Complementary to this is E-P over the global oceans derived from satellite estimates of P such as TRMM, GPM and GPCP and SeaFlux V3 or J-OFURO3 estimates of E, all relying heavily upon microwave measurements. Transport between land and oceans must essentially balance at monthly scales, i.e., vanish globally. (iv) a fourth perspective comes from estimate of terrestrial RO + storage rate, delta S. G-RUN Ensemble which uses observed streamflow and P measurements to calibrate a statistical model provides the former while GRACE, GRACE-FO provide total water storage anomalies used to calculate storage rate changes. GRACE REC uses GRACE data to train a precipitation-driven statistical model to extend storage estimates before the GRACE era. (All of these alternatives to reanalysis estimates also consider the small atmospheric column water vapor contribution.) We examine the transport changes from these three different methodologies, their relative accuracies and discuss the origin of their differences. Regional trends in moisture flux divergence and their role in multi-decadal trends are considered. Interannual variability arising in connection with ENSO variability is a dominant signal, driven largely by P changes. Trends since 1980 include reductions in moisture delivery to the western U.S., eastern Brazil, and central Africa with recovery of moisture convergence to the Sahel and parts of eastern North America.

Franklin Robertson↗
NASA NTRS2005

Estimating moisture transport over oceans using space-based observations

The moisture transport integrated over the depth of the atmosphere (0) is estimated over oceans using satellite data. The transport is the product of the precipitable water and an equivalent velocity (ue), which, by definition, is the depth-averaged wind velocity weighted by humidity. An artificial neural network is employed to construct a relation between the surface wind velocity measured by the spaceborne scatterometer and coincident ue derived using humidity and wind profiles measured by rawinsondes and produced by reanalysis of operational numerical weather prediction (NWP). On the basis of this relation, 0 fields are produced over global tropical and subtropical oceans (40_N- 40_S) at 0.25_ latitude-longitude and twice daily resolutions from August 1999 to December 2003 using surface wind vector from QuikSCAT and precipitable water from the Tropical Rain Measuring Mission. The derived ue were found to capture the major temporal variability when compared with radiosonde measurements. The average error over global oceans, when compared with NWP data, was comparable with the instrument accuracy specification of space-based scatterometers. The global distribution exhibits the known characteristics of, and reveals more detailed variability than in, previous data.

Artificial Neural Network↗
DOE OSTI2025

Downward Convective Moisture Transport Dominated by a Few Overshooting Clouds in Marine and Continental Shallow Convection

Abstract In a previous study (Xiao et al., 2023, https://doi.org/10.1029/2022ms003526 ), we found that ignoring the moist convective downdrafts associated with overshooting clouds in parameterizations can lead to significant biases in the simulated depth and liquid water content of a shallow cloud layer. In this study, we seek to better quantify the properties of the clouds responsible for these moist downdrafts to help improve shallow convection parameterizations. We apply a 3‐D cloud‐tracking algorithm to large‐eddy simulations (LESs) of marine and continental shallow convection. We find that top 1% and 2% of the tracked cloud population ranked by lifetime‐mean cloud‐base mass flux can explain 90%–95% of the total downward moisture transport in the upper cloud layer whereas top 10%–20% is required to explain 90%–95% of the total upward moisture transport near mean cloud base. The vertical structure of the clouds in the top 1% and 2% (the overshooting “deep mode”) is also distinctively different from that of the rest of the cloud population (the “shallow mode”). Shallow convection parameterizations need to capture accurately the properties and convective transports of the clouds in both the deep and shallow modes. To do that, our results suggest that mass‐flux parameterizations need to (a) accurately predict the size and number of the deep‐mode clouds and (b) explicitly represent overshooting cloud updrafts and associated moist downdrafts.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Moisture transport in composites

The moisture distribution and moisture content of composite materials exposed to humid air or to water are discussed. Expressions are presented for estimating the weight gain of both single and multilayered composites when the moisture content and the temperature of the environment are constant. The parameters needed for solving problems in the time varying environmental conditions are specified, and a numerical approach for the solution of such problems is indicated.

Springer, G. S.↗
DOE OSTI2020

Fast Advective Water Flow through Nanochannels in Clay Interlayers: Implications for Moisture Transport in Soils and Unconventional Oil/Gas Production

Water flow in nanometer or sub-nanometer hydrophilic channels bears special importance in diverse fields of science and engineering. However, the nature of such water flow remains elusive. In this work, we report our molecular-modeling results on water flow in a sub-nanometer clay interlayer between two montmorillonite layers. We show that a fast advective flow can be induced by evaporation at one end of the interlayer channel, that is, a large suction pressure created by evaporation (~818 MPa) is able to drive the fast water flow through the channel (~0.88 m/s for a 46 Å-long channel). Scaled up for the pressure gradient to a 2 μm particle, the velocity of water is estimated to be about 95 μm/s, indicating that water can quickly flow through a μm-sized clay particle within seconds. The prediction seems to be confirmed by our thermogravimetric analysis of bentonite hydration and dehydration processes, which indicates that water transport at the early stage of the dehydration is a fast advective process, followed by a slow diffusion process. The possible occurrence of a fast advective water flow in clay interlayers prompts us to reassess water transport in a broad set of natural and engineered systems such as clay swelling/shrinking, moisture transport in soils, water uptake by plants, water imbibition/release in unconventional hydrocarbon reservoirs, and cap rock integrity of supercritical CO 2 storage.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2007

Spacebased Estimation of Moisture Transport in Marine Atmosphere Using Support Vector Regression

An improved algorithm is developed based on support vector regression (SVR) to estimate horizonal water vapor transport integrated through the depth of the atmosphere ((Theta)) over the global ocean from observations of surface wind-stress vector by QuikSCAT, cloud drift wind vector derived from the Multi-angle Imaging SpectroRadiometer (MISR) and geostationary satellites, and precipitable water from the Special Sensor Microwave/Imager (SSM/I). The statistical relation is established between the input parameters (the surface wind stress, the 850 mb wind, the precipitable water, time and location) and the target data ((Theta) calculated from rawinsondes and reanalysis of numerical weather prediction model). The results are validated with independent daily rawinsonde observations, monthly mean reanalysis data, and through regional water balance. This study clearly demonstrates the improvement of (Theta) derived from satellite data using SVR over previous data sets based on linear regression and neural network. The SVR methodology reduces both mean bias and standard deviation comparedwith rawinsonde observations. It agrees better with observations from synoptic to seasonal time scales, and compare more favorably with the reanalysis data on seasonal variations. Only the SVR result can achieve the water balance over South America. The rationale of the advantage by SVR method and the impact of adding the upper level wind will also be discussed.

Support vector regression↗
NASA NTRS2001

Numerical Study of the Role of Shallow Convection in Moisture Transport and Climate

The objective of this investigation was to study the role of shallow convection on the regional water cycle of the Mississippi and Little Washita Basins of the Southern Great Plains (SGP) using a 3-D mesoscale model, the PSU/NCAR MM5. The underlying premise of the project was that current modeling of regional-scale climate and moisture cycles over the continents is deficient without adequate treatment of shallow convection. At the beginning of the study, it was hypothesized that an improved treatment of the regional water cycle can be achieved by using a 3-D mesoscale numerical model having high-quality parameterizations for the key physical processes controlling the water cycle. These included a detailed land-surface parameterization (the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) sub-model of Wetzel and Boone), an advanced boundary-layer parameterization (the 1.5-order turbulent kinetic energy (TKE) predictive scheme of Shafran et al.), and a more complete shallow convection parameterization (the hybrid-closure scheme of Deng et al.) than are available in most current models. PLACE is a product of researchers working at NASA's Goddard Space Flight Center in Greenbelt, MD. The TKE and shallow-convection schemes are the result of model development at Penn State. The long-range goal is to develop an integrated suite of physical sub-models that can be used for regional and perhaps global climate studies of the water budget. Therefore, the work plan focused on integrating, improving, and testing these parameterizations in the MM5 and applying them to study water-cycle processes over the SGP. These schemes have been tested extensively through the course of this study and the latter two have been improved significantly as a consequence.

Seaman, Nelson L.↗
NASA NTRS2014

How Accurate is Land/Ocean Moisture Transport Variability in Reanalyses?

Quantifying the global hydrological cycle and its variability across various time scales remains a challenge to the climate community. Direct measurements of evaporation (E), evapotranspiration (ET), and precipitation (P) are not feasible on a global scale, nor is the transport of water vapor over the global oceans and sparsely populated land areas. Expanding satellite data streams have enabled development of various water (and energy) flux products, complementing reanalyses and facilitating observationally constrained modeling. But the evolution of the global observing system has produced additional complications--improvements in satellite sensor resolution and accuracy have resulted in "epochs" of observational quasi-uniformity that can adversely affect reanalysis trends. In this work we focus on vertically integrated moisture flux convergence (VMFC) variations within the period 1979 - present integrated over global land. We show that VMFC in recent reanalyses (e.g. ERA-I, NASA MERRA, NOAA CFSR and JRA55) suffers from observing system changes, though differently in each product. Land Surface Models (LSMs) forced with observations-based precipitation, radiation and near-surface meteorology share closely the interannual P-ET variations of the reanalyses associated with ENSO events. (VMFC over land and P-ET estimates are equivalent quantities since atmospheric storage changes are small on these scales.) But the long-term LSM trend over the period since 1979 is approximately one-fourth that of the reanalyses. Additional reduced observation reanalyses assimilating only surface pressure and /or specifying seasurface temperature also have a much smaller trend in P-ET like the LSMs. We explore the regional manifestation of the reanalysis P-ET / VMFC problems, particularly over land. Both principal component analysis and a simple time series changepoint analysis highlight problems associated with data poor regions such as Equatorial Africa and, for one reanalysis, the Equatorial Andes region. Onset of the availability of passive microwave Special Sensor Microwave Imager (SSMI) moisture data in July 1987 and the transition from the Microwave Sounder Unit (MSU) to an advanced version (AMSU) have significant impacts on VMFC variability. Simple accounting for these errors of leading importance results in modified reanalysis VMFC estimates that agree much better with the LSM results. Regional details of the modified reanalysis VMFC and LSM P-ET are related to changes in Pacific Decadal Variability as manifest in SST changes after the late 1990s.

Robertson, F. R.↗