Propagation of Uncertainty in Model Inputs for Reactive Braze Run-Out Simulations
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The paper reports on a general circulation model being developed with the ultimate objective of assessing the effect of SST operations on the atmospheric ozone distribution. The model variables are represented in the spectral domain using 79 spherical harmonics and 26 vertical levels between the ground and 70 km. Initial calculations have attempted to simulate the seasonal variations of the unperturbed global ozone distribution. The model shows the presence of a westerly stratospheric jet in the winter hemisphere with amplitudes similar to those observed in the polar night jet. Easterlies dominate in the summer hemisphere. The model also shows ozone to be transported polewards and downwards. Furthermore the annual cycle in ozone concentrations at mid-latitudes has been simulated. Preliminary comparisons are also made with other features of the dynamics and the ozone distribution in the stratosphere.
We have developed a new empirically-based transport algorithm for use in our GSFC two-dimensional transport and chemistry assessment model. The new algorithm contains planetary wave statistics, and parameterizations to account for the effects due to gravity waves and equatorial Kelvin waves. We will present an overview of the new algorithm, and show various model-data comparisons of long-lived tracers as part of the model validation. We will also show how the new algorithm gives substantially better agreement with observations compared to our previous model transport. The new model captures much of the qualitative structure and seasonal variability observed methane, water vapor, and total ozone. These include: isolation of the tropics and winter polar vortex, the well mixed surf-zone region of the winter sub-tropics and mid-latitudes, and the propagation of seasonal signals in the tropical lower stratosphere. Model simulations of carbon-14 and strontium-90 compare fairly well with observations in reproducing the peak in mixing ratio at 20-25 km, and the decrease with altitude in mixing ratio above 25 km. We also ran time dependent simulations of SF6 from which the model mean age of air values were derived. The oldest air (5.5 to 6 years) occurred in the high latitude upper stratosphere during fall and early winter of both hemispheres, and in the southern hemisphere lower stratosphere during late winter and early spring. The latitudinal gradient of the mean ages also compare well with ER-2 aircraft observations in the lower stratosphere.
Assessing local climate change impacts often requires downscaling coarse global climate model (GCM) output to finer resolution. Two main approaches exist: dynamical downscaling using high-resolution regional climate models, and statistical downscaling based on historical relationships between large-scale and local variables. In a recent analysis of five dynamically downscaled simulations over the western United States, Koszuta et al. (2024, https://doi.org/10.1029/2023gl107298) found that warming weakens orographic influence on winter precipitation, damping increases on windward slopes and amplifying them in rain-shadowed regions. Here we show that this effect is robust across seasons and multiple dynamically downscaled ensembles, and is more pronounced at higher model resolutions. However, it is absent in projections from a widely used statistical model (LOCA2), even when trained on high-resolution future simulations (LOCA2-Hybrid). This highlights a key limitation of many statistical downscaling methods: their preservation of parent GCM trends, which usually fail to capture emergent changes in orographic precipitation patterns.
Observations of the seasonal mean precipitation averaged over a sub-region of the U.S. mid-Atlantic show significant increases in summer but no changes in winter during 1979–2019. Clarifying the drivers of these observed changes is important for understanding and interpreting future projections of regional precipitation by climate models. Herein, this study examines the relative effects of external forcing and internal variability in the observed multi-decadal changes using the historical and RCP8.5/SSP585 simulations from 37 models in the Coupled Model Intercomparison Project phase 5 (CMIP5), 35 models in CMIP6, as well as large ensemble simulations from 6 models, each including more than 20 members. During 1979–2019, enhanced warming over land relative to ocean due to external forcing induces low pressure anomalies over land that contribute to the wetting summer. While similar wetting also occurs during winter, such effect is offset by the drying associated with the positive phase of the North Atlantic Oscillation (NAO) in recent decades. Internal variability produces large uncertainty in the multi-decadal precipitation changes simulated by climate models through changes in large-scale circulation associated with the NAO in winter and the North Atlantic Subtropical High in summer. These multi-decadal relationships between precipitation and large-scale circulation under internal variability also manifest on inter-annual timescale. These relationships highlight enhanced moisture transport from the Gulf of Mexico and North Atlantic in winter and near the mid-Atlantic coast in summer that modulates precipitation change in the study region.
Abstract The maximum supersaturation ( S x ) in clouds is a key parameter affecting the cloud's microphysical and radiative properties. We investigate the S x of the marine boundary layer clouds by combining airborne and surface observations in the Eastern North Atlantic. The cloud droplet number concentration ( N c ) in the least diluted cloud cores agrees well with the number concentration of particles larger than the Hoppel Minimum (HM) ( N >HM ) below clouds, indicating that the HM represents the average size threshold above which particles are activated to form cloud droplets. The S x values derived from surface observations vary from 0.10% to 0.50% from June 2017 to June 2018, with a clear seasonal variation exhibiting higher values during winter. Most of the S x variance (∼60%) can be explained by the cloud condensation nuclei (CCN) concentration and updraft velocity ( w ), with the CCN concentration playing a more important role than w in explaining the variation of S x . The influence of CCN concentration on S x leads to a buffered response of N c to aerosol perturbations. The response of N c to low aerosol concentration during winter is further buffered by the high w . The global Community Earth System Model (CESM) simulated S x values in the Azores have a positive bias compared to measured S x , likely due to overestimated w and underestimated CCN concentration. The CESM simulated S x exhibits higher values further north over the North Atlantic Ocean, which is attributed to stronger w . The suppression of S x by aerosol is also evident in regions with high CCN concentrations.
Abstract The impact of convective closure on the double‐ITCZ bias in the NCAR CESM2.2 is investigated in this study. The standard CESM2.2 simulates a remarkable double‐ITCZ bias in the central and eastern Pacific, especially in boreal winter and spring. Modifications to the closure in convection parameterization scheme greatly reduce the double‐ITCZ bias in all seasons, demonstrating that convection parameterization can substantially influence the double‐ITCZ bias in CESM2.2. Further analyses suggest that convection parameterization can modulate the tropical atmosphere‐ocean feedback processes, through which it influences the SST in the southern ITCZ region and hence the double‐ITCZ bias. The changes in the upper ocean temperature advection induced by modified convective closure plays important roles in reducing the warm SST bias and double‐ITCZ precipitation bias in the southern ITCZ region. The modified convective closure improves the low‐level cloud and shortwave cloud radiative forcing in the southeastern Pacific. However, surface heat flux plays only a limited role in reducing warm SST bias and double ITCZ bias because the impacts of shortwave radiation changes are largely canceled by changes in longwave radiation and latent heat flux.
Forced convection heat transfer from flat plate and cylinder in cross flow to simulated Mars atmosphere
Abstract. The spatial heterogeneity related to complex topography in California demands high-resolution (< 5 km) modeling, but global convection-permitting climate models are computationally too expensive to run multi-decadal simulations. We developed a 3.25 km California climate modeling framework by leveraging regional mesh refinement (CARRM) using the U.S. Department of Energy (DOE)'s global Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) version 0. Four 5-year time periods (2015–2020, 2029–2034, 2044–2049, and 2094–2099) were simulated by nudging CARRM outside California to 1° coupled simulation of E3SMv1 under the Shared Socioeconomic Pathways (SSP)5-8.5 future scenario. The 3.25 km grid spacing adds considerable value to the prediction of the California climate changes, including more realistic high temperatures in the Central Valley and much improved spatial distributions of precipitation and snowpack in the Sierra Nevada and coastal stratocumulus. Under the SSP5-8.5 scenario, CARRM simulation predicts widespread warming of 6–10 °C over most of California, a 38 % increase in statewide average 30 d winter–spring precipitation, a near-complete loss of the alpine snowpack, and a sharp reduction in shortwave cloud radiative forcing associated with marine stratocumulus by the end of the 21st century. We note a climatological wet precipitation bias for the CARRM and discuss possible reasons. We conclude that SCREAM RRM is a technically feasible and scientifically valid tool for climate simulations in regions of interest, providing an excellent bridge to global convection-permitting simulations.
Identifying the contributions of chemistry and transport to observed ozone pollution using regional‐to‐global models relies on accurate representation of ozone dry deposition. We use a recently developed configuration of the NOAA GFDL chemistry‐climate model – in which the atmosphere and land are coupled through dry deposition—to investigate the influence of ozone dry deposition on ozone pollution over northern midlatitudes. In our model, deposition pathways are tied to dynamic terrestrial processes, such as photosynthesis and water cycling through the canopy and soil. Small increases in winter deposition due to more process‐based representation of snow and deposition to surfaces reduce hemispheric‐scale ozone throughout the lower troposphere by 5–12 ppb, improving agreement with observations relative to a simulation with the standard configuration for ozone dry deposition. Declining snow cover by the end of the 21st‐century tempers the previously identified influence of rising methane on winter ozone. Dynamic dry deposition changes summer surface ozone by −4 to +7 ppb. While previous studies emphasize the importance of uptake by plant stomata, new diagnostic tracking of depositional pathways reveals a widespread impact of nonstomatal deposition on ozone pollution. Daily variability in both stomatal and nonstomatal deposition contribute to daily variability in ozone pollution. Twenty‐first century changes in summer deposition result from a balance among changes in individual pathways, reflecting differing responses to both high carbon dioxide (through plant physiology versus biomass accumulation) and water availability. Our findings highlight a need for constraints on the processes driving ozone dry deposition to test representation in regional‐to‐global models.
Sea surface height (SSH) from altimeter observations from 1992 on and from modeling results is investigated to determine the modes of variability and the linkages to the state of oceanic circulation in the North Atlantic. First the altimeter and model simulated SSH are analyzed using the empirical orthogonal function (EOF) analysis. They are found to share a similar leading mode where the center of action is along the Gulf Stream and North Atlantic Current with opposite sign anomalies in the subpolar gyre and in the slope waters along the Eastern Seaboard. The time series of the leading EOF mode from the altimeter data shows that between winters of 1995 and 1996, SSH over the Gulf Stream decreased by about 12cm which change is reproduced by the model simulation. Based on the relationship from the model simulations between the time series of the SSH EOF1 and meridional heat transport, it is suggested that associated with this SSH change in 1995-96, the overturning has slowed down from its heights in the early 90's. Furthermore, it is shown that decadal variability in the leading SSH mode originates from the thermal forcing component. This adds confidence to the qualitative relationship between the state of overturning/meridional heat transport and SSH in the limited area described by the EOF1. SSH variability in the eastern side of the North Atlantic basin, outside the western boundary current region, is determined by local and remote (Rossby waves) wind stress curl forcing.
Realistically representing the present-day characteristics of extreme precipitation has been a challenge for global climate models, which is due in part to deficiencies in model resolution and physics, but is also due to a lack of consistency in gridded observations. In this study, we use three observation datasets, including gridded rain gauge and satellite data, to assess historical simulations from sixteen Coupled Model Intercomparison Project Phase 6 (CMIP6) models. We separately evaluate summer and winter precipitation over the United States (US) with a comprehensive set of extreme precipitation indices, including an assessment of precipitation frequency, intensity and spatial structure. The observations exhibit significant differences in their estimates of area-average intensity distributions and spatial patterns of the mean and extremes of precipitation over the US. In general, the CMIP6 multi-model mean performs better than most individual models at capturing daily precipitation distributions and extreme precipitation indices, particularly in comparison to gauge-based data. Also, the representation of the extreme precipitation indices by the CMIP6 models is better in the summer than winter. Although the ‘standard’ horizontal-resolution can vary significantly across CMIP6 models, from ~0.7° to ~2.8°, we find that resolution is not a good indicator of model performance. Overall, our results highlight common biases in CMIP6 models and demonstrate that no single model is consistently the most reliable across all indices.
A Jan.-Feb. climatology model was constructed from the GLAS general circulation model by averaging eight 30-day means of periods from Jan. 15-Feb. 14. The position and intensity of the Aleutian and Icelandic lows in the winter, the central Arctic pressure distribution during winter and summer, and the summertime North Atlantic and North Pacific high pressure regimes were satisfactorily simulated; sensible and evaporative heat fluxes and radiation budget parameters were reasonable, although a rigorous comparison is difficult due to data deficiencies. The model is less successful in simulating the Southern Hemisphere climatology; the 500 mb circumpolar flow is adequate, but the stationary low pressure centers at the surface around the Antarctic continent are not well reproduced.
Several numerical experiments were conducted with a simplified tracer transport model in order to attempt to examine the poleward transport of Mars atmospheric water during a polar warming like that which occurred during the winter solstice dust storm of 1977. The flow for the transport experiments was taken from numerical simulations with a nonlinear beta-plane dynamical model. Previous studies with this model have demonstrated that a polar warming having essential characteristics like those observed during the 1977 dust storm can be produced by a planetary wave mechanism analogous to that responsible for terrestrial sudden stratospheric warmings. Several numerical experiments intended to simulate water transport in the absence of any condensation were carried out. These experiments indicate that the flow during a polar warming can transport very substantial amounts of water to high northern latitudes, given that the water does not condense and fall out before reaching the polar region.
Fine particulate matter (PM2.5) poses significant risks to human health and the environment by penetrating the lungs and causing respiratory and cardiovascular diseases, making it crucial to understand its sources and behavior for effective air quality management. The Goddard Earth Observing System (GEOS) Forward Processing (FP) system model, operated by the Global Modeling and Assimilation Office (GMAO) at NASA's Goddard Space Flight Center, provides real-time weather and aerosol analyses and forecasts. In addition to meteorological data assimilation, the GEOS-FP system also assimilates aerosol using Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) and Aerosol Robotic Network (AERONET) AOD data. In this study, the aerosol data assimilation and forecasts performance of the GEOS-FP model were evaluated for predicting PM2.5 in Korea using observations from the Airborne and Satellite Investigation of Asian Air Quality (ASIA-AQ) campaign. The ASIA-AQ campaign, an international collaborative field study initiative, aims to enhance understanding of local air quality issues and address common challenges in interpreting satellite data and air quality modeling. Conducted in South Korea from February 15 to March 13, 2024, during the high PM2.5 concentration winter season, this campaign provided extensive airborne and ground observations for intensive analysis of PM2.5 model simulations. We demonstrate how the assimilation runs and the forecasting performance of PM2.5 at 24-hour and 48-hour intervals vary. Additionally, we analyzed the differences and characteristics of PM2.5 composition in cases of long-range transport and local emissions. Using ASIA-AQ airborne data, we also examined the vertical profile of fine particulate matter. Through the intensive observations of this campaign, the GEOS model was assessed over South Korea using both in situ and airborne measurements to establish a baseline and identify priorities for future development.
POAM solar occultation observations from 1994 to present are studied for the purpose of determining Type I PSC formation characteristics and winter-long evolution. This study examines PSC observations from many years on a common basis to see if characteristics can be identified. The results show that Type Ia PSCs form at the beginning of the winter, within several days of the first drop in temperature below T_NAT, and peak early in the winter. Type Ia PSCs typically out number Ib PSCs over the winter, especially at the beginning of the winter. Type Ia and Ib PSC observations continue throughout the winter. Micro-physical models of PSC formation must match these observed characteristics. Some models predict that temperatures must be more than 5 K below T_NAT for five days before significant freezing can occur. This is not seen in the POAM observations. Differences in PSC characteristics between the first two Arctic winters (1994-1995 and 1995-1996) and later winters also suggest the influence of volcanic perturbations on PSC formation. Type Ia and Ib PSC Characteristics observed by POAM III and SAGE III for the 2002-2003 Arctic winter are compared.
NASA’s Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign gathered data using “satellite-simulating” (albeit with higher-resolution data than satellites currently provide) and in situ aircraft to study snowstorms, with an emphasis on banding. This study used three IMPACTS microwave instruments—two passive and one active—chosen for their sensitivity to precipitation microphysics. The 10–37-GHz passive frequencies were well suited for detecting light precipitation and differentiating rain intensities over water. The 85–183-GHz frequencies were more sensitive to cloud ice, with higher cloud tops manifesting as lower brightness temperatures, but this did not necessarily correspond well to near-surface precipitation. Over land, retrieving precipitation information from radiometer data is more difficult, requiring increased reliance on radar to assess storm structure. A dual-frequency ratio (DFR) derived from the radar’s Ku- and Ka-band frequencies provided greater insight into storm microphysics than reflectivity alone. Areas likely to contain mixed-phase precipitation (often the melting layer/bright band) generally had the highest DFR, and high-altitude regions likely to contain ice usually had the lowest DFR. The DFR of rain columns increased toward the ground, and snowbands appeared as high-DFR anomalies.
Given a rising demand for quality assurance, rather than solely yield, supplemental irrigation plays an important role to ensure the viability and profitability of vegetable crops from unpredictable changes in weather. However, under drought conditions, agricultural irrigation is often given low priority for water allocation. This reduced water availability for agriculture calls for techniques with greater irrigation efficiency, that do not compromise crop quality and yield, and that provide economic benefit for producers. This study developed vegetable growing models for eight different vegetable crops (bush bean, green bean, cabbage, peppermint, spearmint, yellow straight neck squash, zucchini, and bell pepper) based on data from several years of field research. The ALMANAC model accurately simulated yields and water use efficiency (WUE) of all eight vegetables. The developed vegetable models were used to evaluate the effects of various irrigation regimes on vegetable growth and production in several locations in the Winter Garden Region of Texas, under variable weather conditions. Based on our simulation results from 960 scenarios, optimal irrigation amounts that produce high yield as well as reasonable economic profit to producers were determined for each vegetable crop. Overall, yields for all vegetables increased as irrigation amounts increased. However, irrigation amounts did not have a sustainable impact on vegetable yield at high irrigation treatments, and the WUEs of most vegetables were not significantly different among various irrigation regimes. When vegetable yields were compared with water cost, the rate decreased as irrigation amounts increased. Thus, producers will not receive economic benefits when vegetable irrigation water demand is too high.