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At least 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

An Enhanced Global Precipitation Measurement (GPM) Validation Network Prototype

A Validation Network (VN) prototype is currently underway that compares data from the Precipitation Radar (PR) instrument on NASA's Tropical Rainfall Measuring Mission (TRMM) satellite to similar measurements from the U.S. national network of operational weather radars. This prototype is being conducted as part of the ground validation activities of NASA's Global Precipitation Measurement (GPM) mission. GPM will carry a Dual-frequency Precipitation Radar instrument (DPR) with similar characteristics to the TRMM PR. The purpose of the VN is to identify and resolve significant discrepancies between the U.S. national network of ground radar (GR) observations and satellite observations. The ultimate goal of such comparisons is to understand and resolve the first order variability and bias of precipitation retrievals in different meteorological/hydrological regimes at large scales. This paper presents a description of, and results from, an improved algorithm for volume matching and comparison of PR and ground radar observations.

Schwaller, Matthew R.↗
NASA NTRS2010

Electrically-Active Convection and Tropical Cyclogenesis in the Atlantic and East Pacific

It has been hypothesized that deep, intense convective-scale "hot" towers may aid the process of tropical cyclogenesis and intensification through dynamic and thermodynamic feedbacks on the larger meso-to-synoptic scale circulation. In this study, we make use of NCEP Reanalysis data and Tropical Rainfall Measurement Mission (TRMM) lightning imaging sensor (LIS), precipitation radar (PR), and microwave imager (TMI) data to investigate the role that widespread and/or intense lightning-producing convection (i.e., "electrically-hot towers") present in African easterly waves (AEWs) may play in tropical cyclogenesis over the Atlantic, Caribbean, and East Pacific regions. NCEP Reanalysis 700 hPa meridional winds for the months of June to November for the years 2001-2009 were analyzed for the domain of 5degN-20degN and 130degW-20degE in order to partition individual AEWs into northerly, southerly, trough, and ridge phases. Subsequently, information from National Hurricane Center (NHC) storm reports was used to divide the waves into developing and non-developing waves and to further divide the developing waves into those waves that spawned storms that only developed to tropical storm strength and those that spawned storms that reached hurricane strength. The developing waves were also divided by the region in which they developed. To help determine the gross nature of the smaller convective scale, composites were created of all developing and non-developing waves as a function of AEW wave phase over the full analysis domain and over various smaller longitude bands by compositing TRMM PR, TMI, LIS, and IR brightness temperature data extracted from the NASA global-merged IR brightness temperature dataset. Finally, similar composites were created using various NCEP variables to assess the nature of the larger scale environment and circulation. Results suggest a clear distinction between developing and non-developing waves as developing waves near their region of development in terms of the intensity of convection (indicated by lightning flash rate), coverage of cold cloudiness (indicated by the percentage of a 2.5deg by 2.5deg box covered by IR brightness temperatures less than 210 K), and large-scale variables, such as midlevel moisture and upper-level upward motion. For example, waves that developed in the East Pacific longitude band (i.e., 130degW-95degW) were observed in that band to have a flash rate of 56.4 flashes/day, a coverage by brightness temperatures less than 210 K equal to 2.2%, a 700-hPa specific humidity anomaly of 0.4 g/kg, and a 300-hPa omega value of -0.04 Pascals/s in the trough phase compared to the non-developing wave trough values of 22.1 flashes/day, a coverage by brightness temperatures less than 210 K equal to 0.9%, a 700-hPa specific humidity anomaly of -0.3 g/kg, and a 300-hPa omega value of -0.01 Pascals/s.

Leppert, Kenneth D., II↗
DOE OSTI2022

ARM data-oriented metrics and diagnostics package for climate model evaluation (ARM-DIAGS-V3) version 3

A Python-based metrics and diagnostics package is currently being developed by the ARM Infrastructure Team at Lawrence Livermore National Laboratory to facilitate the use of long-term high frequency measurements from the ARM program in evaluating the regional climate simulation of clouds, radiation, precipitation, and aerosols. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The CMIP model data sets are also included in the package to enable model inter-comparison as demonstrated in Zhang et al. (2018) and Zhang et al. (2020). The mean of the CMIP model can be served as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, aerosol optical depth, and radiative fluxes, with plan to extend to more fields, such as the evaluation of model simulated aerosol physicochemical properties and cloud microphysics properties. Process-oriented diagnostics focusing on aerosol, cloud, and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. In addition to the Southern Great Plains (SGP), North Slope of Alaska (NSA) and Tropical Western Pacific (TWP) atmospheric observatories in the ARMDIAGS version 2.0, the version 3.0 package have extended to the data collected at the ARM Eastern North Atlantic (ENA) atmospheric observatory and the Observation and Modeling of the Green Ocean Amazon (GOAMAZON) field campaign. The metrics and diagnostics package are currently built upon standard Python libraries and additional Python packages developed by DOE (CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first provide an overview of major metrics in section 2. The input data, which constitutes the core content of the metrics and diagnostics package, is summarized in section 3. A user's guide documenting the workflow/structure of the version 3.0 codes and including step-by-step instruction for running the package is described in section 4.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Increased exposure of coastal cities to sea-level rise due to internal climate variability

Adaptation to future sea-level rise is based on projections of continuously improving climate models. These projections are accompanied by inherent uncertainties, including those due to internal climate variability (ICV). The ICV arises from complex and unpredictable interactions within and between climate-system components, rendering its impact irreducible. Although neglecting this uncertainty can lead to an underestimation of future sea-level rise, its estimation and impacts have not been fully explored. Combining the Community Earth System Model version 1 Large Ensemble experiments with power-law statistics, we show that, by 2100, if the ICV uncertainty reaches its upper limit, new sea-level-rise hotspots would appear in Southeast Asian megacities (Chennai, Kolkata, Yangon, Bangkok, Ho Chi Minh City and Manila), in western tropical Pacific Islands and the Western Indian Ocean. Here, the better the ICV uncertainty is taken into account and correctly estimated, the more effective adaptation strategies can be elaborated with confidence and actions to follow.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Coupled Land Atmosphere Predictability

We have designed and executed a set of predictability experiments, designed around the driest and wettest June soil moisture anomalies from a CCM3 simulation forced by observed SST for the period from 1958 through 1998. Each set contains an ensemble of five runs, all begun on June I radiation date. One set of these experiments helps to assess the extent to which the wet or dry conditions depend solely on the initial state of the atmosphere. The other set of experiments helps to assess the extent to which the wet or dry conditions depend sole on the initial state of the land surface. Preliminary analysis of these experiments suggests that the initial atmospheric state is more important than the initial state of the surface soil moisture in predicting the occurrence of wet or dry periods. These results suggest that when the atmosphere is inclined to generate dry surface conditions (through reduced moisture availability and increased evaporation) it matters little what initial levels of soil water are at; the soil will rapidly dry out. The ensemble forcing the ensembles with dry soil conditions, but utilizing 'normal' atmospheric conditions show little if any indication of the sharp reduction in soil moisture experienced in the control, indicating that the 'normal' atmospheric state is more important than the initial state of the soil moisture in predicting the occurrence of drought. Our work to date has documented the response of surface hydrologic variability, particularly over North America, to atmospheric forcing. While we have seen some suggestion that pre-existing surface anomalies can affect atmospheric circulation over this region, by far the strongest signal is the atmospheric anomalies leading those of soil moisture and surface energy balance changes. This is not an unexpected result since wintertime NA precipitation links to remote atmospheric forcing by ENSO are known to be statistically significant. While warm season links to remote forcing are more tenuous and not well explored, the present results encourage us to examine in more detail the SST forcing from the tropical and North Pacific.

Roads, John↗
NASA NTRS2002

Prospects for Improved Forecasts of Weather and Short-Term Climate Variability on Subseasonal (2-Week to 2-Month) Times Scales

This workshop, held in April 2002, brought together various Earth Sciences experts to focus on the subseasonal prediction problem. While substantial advances have occurred over the last few decades in both weather and seasonal prediction, progress in improving predictions on these intermediate time scales (time scales ranging from about two weeks to two months) has been slow. The goals of the workshop were to get an assessment of the "state of the art" in predictive skill on these time scales, to determine the potential sources of "untapped" predictive skill, and to make recommendations for a course of action that will accelerate progress in this area. One of the key conclusions of the workshop was that there is compelling evidence for predictability at forecast lead times substantially longer than two weeks. Tropical diabatic heating and soil wetness were singled out as particularly important processes affecting predictability on these time scales. Predictability was also linked to various low-frequency atmospheric "phenomena" such as the annular modes in high latitudes (including their connections to the stratosphere), the Pacific/North American (PNA) pattern, and the Madden Julian Oscillation (MJO). The latter, in particular, was highlighted as a key source of untapped predictability in the tropics and subtropics, including the Asian and Australian monsoon regions.

Schubert, Siegfried↗
NASA NTRS2003

Estimating the Tropospheric Ozone Distribution by the Assimilation of Satellite Data

Tropospheric ozone is important to the environment, because it acts as a strong oxidant to control the concentrations of many reduced gases (methane, carbon monoxide, ... ), its radiative forcing plays a significant role in the greenhouse effect, and direct contact with ozone is harmful to human health. Tropospheric ozone, whose main sources are intrusion from the stratosphere and chemical production from source gases associated with urban pollution or biomass burning, varies on a wide range of spatial and temporal scales. Its transport and chemistry can be influenced by weather, seasonal, or multiannual variability. Despite the importance of tropospheric ozone, it contributes only about 10% of the total ozone loading in the atmosphere. Consequently, satellite instruments lose sensitivity below the stratospheric ozone peak, and provide little information about middle and lower tropospheric ozone. This talk will discuss recent modifications made to the satellite ozone data assimilation system at NASA's Data Assimilation Office (DAO) in order to provide better tropospheric ozone columns and profiles. We use a version of the system that assimilates only the data from the Solar Backscatter UltraViolet/2 (SBUV/2) instrument. The quality of the assimilated ozone in the tropical troposphere is evaluated by comparison with independent observations obtained from the Southern Hemispheric Additional Ozonesondes (SHADOZ) network. It is shown that the quality of ozone fields is sensitive to the winds used in the transport model. Increasing the vertical resolution of the model also has a beneficial impact. The assimilated ozone in the lower troposphere was substantially improved by inclusion of tropospheric ozone production, loss, and dry deposition rates from the Harvard GEOS-CHEM model. The mechanisms behind these results will be examined and the implications for our understanding of tropospheric ozone will be discussed.

Hayashi, Hiroo↗
NASA NTRS2005

Simulation of Water Sources and Precipitation Recycling for the MacKenzie, Mississippi and Amazon River Basins

An atmospheric general circulation model simulation for 1948-1997 of the water budgets for the MacKenzie, Mississippi and Amazon River basins is presented. In addition to the water budget, we include passive tracers to identify the geographic sources of water for the basins, and the analysis focuses on the mechanisms contributing to precipitation recycling in each basin. While each basin s precipitation recycling has a strong dependency on evaporation during the mean annual cycle, the interannual variability of the recycling shows important relationships with the atmospheric circulation. The MacKenzie River basin has only a weak interannual dependency on evaporation, where the variations in zonal moisture transport from the Pacific Ocean can affect the basin water cycle. On the other hand, the Mississippi River basin has strong interannual dependencies on evaporation. While the precipitation recycling weakens with increased low level jet intensity, the evaporation variations exert stronger influence in providing water vapor for convective precipitation at the convective cloud base. High precipitation recycling is also found to be partly connected to warm SSTs in the tropical Pacific Ocean. The Amazon River basin evaporation exhibits small interannual variations, so that the interannual variations of precipitation recycling are related to atmospheric moisture transport from the tropical south Atlantic Ocean. Increasing SSTs over the 50-year period are causing increased easterly transport across the basin. As moisture transport increases, the Amazon precipitation recycling decreases (without real time varying vegetation changes). In addition, precipitation recycling from a bulk diagnostic method is compared to the passive tracer method used in the analysis. While the mean values are different, the interannual variations are comparable between each method. The methods also exhibit similar relationships to the terms of the basin scale water budgets.

Bosilovich, Michael G.↗
NASA NTRS2006

Optically Thin Liquid Water Clouds: Their Importance and Our Challenge

Many of the clouds important to the Earth's energy balance, from the tropics to the Arctic, are optically thin and contain liquid water. Longwave and shortwave radiative fluxes are very sensitive to small perturbations of the cloud liquid water path (LWP) when the liquid water path is small (i.e., < g/sq m) and, thus, the radiative properties of these clouds must be well understood to capture them correctly in climate models. We review the importance of these thin clouds to the Earth's energy balance, and explain the difficulties in observing them. In particular, because these clouds are optically thin, potentially mixed-phase, and often (i.e., have large 3-D variability), it is challenging to retrieve their microphysical properties accurately. We describe a retrieval algorithm intercomparison that was conducted to evaluate the issues involved. The intercomparison included eighteen different algorithms to evaluate their retrieved LWP, optical depth, and effective radii. Surprisingly, evaluation of the simplest case, a single-layer overcast cloud, revealed that huge discrepancies exist among the various techniques, even among different algorithms that are in the same general classification. This suggests that, despite considerable advances that have occurred in the field, much more work must be done, and we discuss potential avenues for future work.

Turner, D. D.↗
NASA NTRS2007

Intraseasonal Variations of the Tropical Total Ozone and their Connection to the Madden-Julian Oscillation

We investigate the intraseasonal (30-90 day) variations in satellite-observed tropical total ozone (O3) and their connection to the Madden-Julian Oscillation (MJO). Tropical total O3 intraseasonal variations are large (approximately +/- 10 DU) and comparable to those in annual and interannual time scales. These O3 anomalies are mainly evident in the subtropics over the Pacific an eastern; hemisphere and propagate slowly eastward (approximately 5 m s-1). The subtropical negative (positive) O3 anomalies are typically collocated with the subtropical upper troposphere anticyclones (cyclones) generated by equatorial MJO convection and flank or lie to the west of the equatorial enhanced (suppressed) MJO convection. The subtropical O3 are anticorrelated with geopotential height anomalies near the tropopause and thus mainly associated with the O3 variability in the stratosphere rather the troposphere. Over the equatorial regions, total O3 anomalies are small.

Atmospheric Infrared Sounder (AIRS)↗
NASA NTRSDate not supplied

A Framework for Evaluating Climate Model Performance Metrics

The CMIP5 archive contains future climate projections from over 50 models provided by dozens of modeling centers from around the world. Individual model projections, however, are subject to biases created by structural model uncertainties. As a result, ensemble averaging of multiple models is often used to add value to model projections: consensus projections have been shown to consistently outperform individual models. Previous reports for the IPCC establish climate change projections based on an equal-weighted average of all model projections. However, certain models reproduce climate processes better than other models. Should models be weighted based on performance? Unequal ensemble averages have previously been constructed using a variety of mean state metrics. What metrics are most relevant for constraining future climate projections? This project develops a framework for systematically testing metrics in models to identify optimal metrics for unequal weighting multi-model ensembles. A unique aspect of this project is the construction and testing of climate process-based model evaluation metrics. A climate process-based metric is defined as a metric based on the relationship between two physically related climate variables?e.g., outgoing longwave radiation and surface temperature. Metrics are constructed using high-quality Earth radiation budget data from NASA's Clouds and Earth's Radiant Energy System (CERES) instrument and surface temperature data sets. It is found that regional values of tested quantities can vary significantly when comparing weighted and unweighted model ensembles. For example, one tested metric weights the ensemble by how well models reproduce the time-series probability distribution of the cloud forcing component of reflected shortwave radiation. The weighted ensemble for this metric indicates lower simulated precipitation (up to .7 mm/day) in tropical regions than the unweighted ensemble: since CMIP5 models have been shown to overproduce precipitation, this result could indicate that the metric is effective in identifying models which simulate more realistic precipitation. Ultimately, the goal of the framework is to identify performance metrics for advising better methods for ensemble averaging models and create better climate predictions.

Noel C Baker↗
DOE OSTI2023

An Open‐Source, Physics‐Based, Tropical Cyclone Downscaling Model With Intensity‐Dependent Steering

Abstract An open‐source, physics‐based tropical cyclone (TC) downscaling model is developed, in order to generate a large climatology of TCs. The model is composed of three primary components: (a) a random seeding process that determines genesis, (b) an intensity‐dependent beta‐advection model that determines the track, and (c) a non‐linear differential equation set that determines the intensification rate. The model is entirely forced by the large‐scale environment. Downscaling ERA5 reanalysis data shows that the model is generally able to reproduce observed TC climatology, such as the global seasonal cycle, genesis locations, track density, and lifetime maximum intensity distributions. Inter‐annual variability in TC count and power‐dissipation is also well captured, on both basin‐wide and global scales. Regional TC hazard estimated by this model is also analyzed using return period maps and curves. In particular, the model is able to reasonably capture the observed return period curves of landfall intensity in various sub‐basins around the globe. The incorporation of an intensity‐dependent steering flow is shown to lead to regionally dependent changes in power dissipation and return periods. Advantages and disadvantages of this model, compared to other downscaling models, are also discussed.

Meteorology & Atmospheric Sciences↗
NASA NTRS1994

Accuracy assessment of the large-scale dynamic ocean topography from TOPEX/POSEIDON altimetry

The quality of TOPEX/POSEIDON determinations of the global scale dynamic ocean topography have been assessed by determining mean topography solutions for successive 10-day repeat cycles and by examining the temporal changes in the sea surface topography to identify known features. The assessment is based on the analysis of TOPEX altimeter data cycles 1 through 36. Important errors in the tide model used to correct the altimeter data have been identified. The errors were reduced significantly by use of a new tide model derived with the TOPEX/POSEIDON measurements. Maps of the global 1-year mean topography, produced using four of the most accurate of the marine geoid, show that the largest error in the dynamic ocean topography show expected features, such as the known annual hemispherical sea surface rise and fall and the seasonal variability due to monsoon influence in the Indian Ocean. Changes in the sequence of 10-day topography maps show the development and propagation of an equatorial Kelvin wave in the Pacific beginning in December 1992 with a propagation velocity of approximately 3 m/s. The observations are consistent with observed changes in the equatorial trade winds, and with tide gauge and other in situ observations of the strengthening of the El Nino. Comparison of TOPEX-determine sea surface height at points near oceanic tide gauges shows agreement at the 4 cm root-mean-square (RMS) level over the tropical Pacific. The results show that the TOPEX altimeter data set can be used to map the ocean surface with a temporal resolution of 10 days and an accuracy which is insonsistent with traditional in situ methods for the determination of sea level variations.

Tapley, B. D.↗
NASA NTRS1999

Seasonal Variability of Middle Latitude Ozone in the Lowermost Stratosphere Derived from Probability Distribution Functions

We present a study of the distribution of ozone in the lowermost stratosphere with the goal of understanding the relative contribution to the observations of air of either distinctly tropospheric or stratospheric origin. The air in the lowermost stratosphere is divided into two population groups based on Ertel's potential vorticity at 300 hPa. High [low] potential vorticity at 300 hPa suggests that the tropopause is low [high], and the identification of the two groups helps to account for dynamic variability. Conditional probability distribution functions are used to define the statistics of the mix from both observations and model simulations. Two data sources are chosen. First, several years of ozonesonde observations are used to exploit the high vertical resolution. Second, observations made by the Halogen Occultation Experiment [HALOE] on the Upper Atmosphere Research Satellite [UARS] are used to understand the impact on the results of the spatial limitations of the ozonesonde network. The conditional probability distribution functions are calculated at a series of potential temperature surfaces spanning the domain from the midlatitude tropopause to surfaces higher than the mean tropical tropopause [about 380K]. Despite the differences in spatial and temporal sampling, the probability distribution functions are similar for the two data sources. Comparisons with the model demonstrate that the model maintains a mix of air in the lowermost stratosphere similar to the observations. The model also simulates a realistic annual cycle. By using the model, possible mechanisms for the maintenance of mix of air in the lowermost stratosphere are revealed. The relevance of the results to the assessment of the environmental impact of aircraft effluence is discussed.

Cerniglia, M. C.↗
NASA NTRS1999

Seasonal Variability of Middle Latitude Ozone in the Lowermost Stratosphere Derived from Probability Distribution Functions

We present a study of the distribution of ozone in the lowermost stratosphere with the goal of understanding the relative contribution to the observations of air of either distinctly tropospheric or stratospheric origin. The air in the lowermost stratosphere is divided into two population groups based on Ertel's potential vorticity at 300 hPa. High [low] potential vorticity at 300 hPa suggests that the tropopause is low [high], and the identification of the two groups helps to account for dynamic variability. Conditional probability distribution functions are used to define the statistics of the mix from both observations and model simulations. Two data sources are chosen. First, several years of ozonesonde observations are used to exploit the high vertical resolution. Second, observations made by the Halogen Occultation Experiment [HALOE) on the Upper Atmosphere Research Satellite [UARS] are used to understand the impact on the results of the spatial limitations of the ozonesonde network. The conditional probability distribution functions are calculated at a series of potential temperature surfaces spanning the domain from the midlatitude tropopause to surfaces higher than the mean tropical tropopause [approximately 380K]. Despite the differences in spatial and temporal sampling, the probability distribution functions are similar for the two data sources. Comparisons with the model demonstrate that the model maintains a mix of air in the lowermost stratosphere similar to the observations. The model also simulates a realistic annual cycle. By using the model, possible mechanisms for the maintenance of mix of air in the lowermost stratosphere are revealed. The relevance of the results to the assessment of the environmental impact of aircraft effluence is discussed.

Cerniglia, M. C.↗
NASA NTRS2020

Subseasonal-to-Seasonal Hindcast Skill Assessment of Ridging Events Related to Drought Over the Western United States

Persistent atmospheric ridging events centered near the western United States are associated with widespread precipitation deficits and meteorological drought. Due to the relatively low skill of- dynamical models in forecasting precipitation on subseasonal‐to‐seasonal (S2S) time scales across this region, forecasts of ridging are explored in this study as a potential bridge for early warning drought prediction. To assess skill, we evaluate deterministic and probabilistic S2S hindcasts (out to 6 week lead time) of ridging events and geopotential height anomalies over the western United States in five ensemble hindcast systems. Prediction skill for ridging events is shown to be highly variable across models. For some models, longer‐time‐averaged patterns of geopotential height anomalies across the first 6 weeks can be skillfully simulated, when evaluated probabilistically against climatology. The most skillful models show modest skill in forecasting above normal ridging occurrences at lead times of Weeks 3–4 and Weeks 5–6,with some sensitivity to the specific ridge location and method for determining skill. Using the European Centre for Medium‐Range Weather Forecasts (ECMWF) model as a case study, longer lead time forecast busts are shown to often occur under extended periods of highly active La Nina‐like tropical convection. Model errors at simulating these tropical convection features may have a disproportionately large impact and degrade downstream forecasts over the western United States. Despite the documented model shortcomings, our results highlight an opportunity to target skillful ridging forecasts from dynamical models for improving early warning drought forecasting at S2S lead times.

S2S↗
DOE OSTI2021

Tracking Extremes in Exascale Simulations Utilizing Exascale Platforms

There is a growing recognition in the literature that understanding variability and trends in hydrometeorological extremes relies on understanding variability and trends in the meteorological phenomena that drive these extremes. Such phenomenon-focused understanding relies critically on a robust methodology for identifying the occurrence of these phenomena in observations and model output, but a robust methodology does not currently exist. There are a variety of heuristic methods reported in the literature for identifying, and in some cases temporally tracking, meteorological phenomena. However, there have been several intercomparison projects (and resulting papers) indicating that there is a large uncertainty associated with choices in the identification methods; this is the case for extratropical cyclones (ETCs), atmospheric rivers (ARs), and even tropical cyclones (TCs); and we hypothesize that this is a general issue with heuristic identification methods altogether. These studies clearly show that this identification uncertainty leads to a large, and previously under-recognized, quantitative and even qualitative uncertainty in our understanding of these phenomena. In light of these issues, we suggest that the field could be advanced by addressing two overarching questions. First, can we explicitly quantify uncertainty associated with detecting hydrometeorological phenomena? Second, can we decompose detection uncertainty into reducible and irreducible parts?

58 GEOSCIENCES↗
DOE OSTI2020

Subseasonal Variability of Elevated Dust Concentrations Over South Florida

Dust mass concentrations have been measured daily at Miami, Florida, in the summer months, and biweekly throughout the remaining months, since 1974. The 43-year record of dust mass concentrations indicate large daily, seasonal, and interannual variations, with most of the dust arriving within 5–8 episodes each summer. On average, dust arrives to Miami, Florida, 10 days after emission from North Africa, with measured concentrations depending on characteristics of the lower free-tropospheric winds due to the vast travel distance. Daily dust mass concentrations from July and August, the months that contribute the most to the annual mean, are used to characterize the synoptic conditions most favorable for dust transport. Two key regions are linked with the highest daily dust mass concentrations above Miami: (i) easterly winds, averaged over 850–500 mb, over the Tropical West Atlantic [15–25°N, 45–80°W], and (ii) southerly winds, similarly averaged, over the Florida Peninsula [20–30°N,75–80°W]. Winds within these two regions are enhanced when the North Atlantic subtropical high is displaced south and zonally elongated, relocating the western edge over Florida. A dust-transport-efficiency index, based on the maximum potential for dust to arrive above Miami with limited loss to deposition or mixing, identifies high-dust loading cases on the subseasonal scale. Monthly dust-transport-efficiency values agree well with the monthly dust trends over the 43-year time span. While seasonal dust loadings have been decreasing over Florida in the past decade, the transport efficiency has been increasing, possibly due to trends in the North Atlantic subtropical high.

54 ENVIRONMENTAL SCIENCES↗