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At least 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Erroneous Attribution of Deep Convective Invigoration to Aerosol Concentration

Abstract Contiguous time–height cloud objects at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains (SGP) site are matched with surface condensation nuclei (CN) concentrations and retrieved thermodynamic and kinematic vertical profiles for warm-cloud-base, cold-cloud-top systems in convectively unstable environments. Statistical analyses show that previously published conclusions that increasing CN concentrations cause a decrease in minimum cloud-top temperature (CTT) at the SGP site through the aerosol convective invigoration effect are unfounded. The CN–CTT relationship is statistically insignificant, while correlations between convective available potential energy (CAPE), level of neutral buoyancy (LNB), and CN concentration account for most of the change in the CN–CTT positive correlation. Removal of clouds with minimum CTTs > −36°C from the analysis eliminates the CN–CTT correlation. Composited dirty conditions at the SGP have ~1°C-warmer low levels and ~1°C-cooler upper levels than clean conditions. This correlation between aerosol concentrations and thermodynamic profiles may be caused by an increase in regional rainfall preceding deep convective conditions as CN concentration decreases. Increased rainfall can be expected to increase wet deposition of aerosols, cool low-level temperatures, and warm upper-level temperatures. The masking of a potential aerosol effect by such small thermodynamic changes implies that the strategy of analyzing subsets of aerosol data by binned meteorological factor values is not a valid method for discerning an aerosol effect in some situations. These findings highlight the need for more careful, detailed, and strategic observations to confidently isolate and quantify an aerosol deep convective invigoration effect.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

The Diurnal and Microphysical Characteristics of MJO Rain Events during DYNAMO

The Madden–Julian oscillation (MJO) dominates the intraseasonal variability of cloud populations of the tropical Indian and Paci?c Oceans. Suppressed MJO periods consist primarily of shallow and isolated deep convection. During the transition to an active MJO, the shallow and isolated deep clouds grow upscale into the overnight hours. During active MJO periods, mesoscale convective systems occur mostly during 2–4-day bursts of rainfall activity with a statistically signi?cant early morning peak. Yet when these rain events are separated into individual active periods, some periods do not follow the mean pattern, with the November events in particular exhibiting an afternoon peak. The radar-observed microphysical processes producing the precipitation during the major rain events of active MJO periods evolve in connection with synoptic-scale wave passages with varying in?uences of diurnal forcing. MJO studies that do not account for the in-termittency of rainfall during active MJO phases through averaging over multiple events can lead to the misimpression that the primary rain-producing clouds of the MJO are modulated solely by the diurnal cycle.

Rowe, Angela K.↗
DOE OSTI2019

Diurnal Forcing and Phase Locking of Gravity Waves in the Maritime Continent

Abstract An unfiltered zonal Hovmöller depiction of rainfall in the Maritime Continent (MC) reveals remarkable spatiotemporal continuity of zonally propagating disturbances with a diurnal period, which endure over multiple days and propagate faster than the individual convective storms they coupled with. This phenomenon and its sensitivity to the Madden–Julian oscillation (MJO) during the 2011/12 Dynamics of the MJO (DYNAMO) field campaign is examined here through a well-validated, convection-permitting model simulation conducted on a large domain. We find that these disturbances are zonally propagating diurnal gravity waves excited by vigorous nocturnal mesoscale convective systems over Sumatra and Borneo. These gravity waves are diurnally phase locked: their wavelength very closely matches the distance between these two islands (~1500 km), while their particular zonal phase speed (~±17 m s−1) allows them to propagate this distance in one diurnal cycle. We therefore hypothesize that these waves are amplified by resonant interaction due to diurnal phase locking. While these zonal gravity waves decouple from convection once beyond the MC, their divergent flow signature endures well across the Indian Ocean, provoking the notion that they may influence rainfall at far remote locations. The exact controls over this zonal phase speed remain uncertain; we note, however, that it is roughly consistent with diurnal offshore-propagating modes documented previously. Further study is required to tie this down, and more generally, to understand the sensitivity of these modes to background flow strength and the geography of the MC.

Ruppert, Jr., James H.↗
DOE OSTI2020

Kelvin Waves during GOAmazon and Their Relationship to Deep Convection

The 2014–15 Observations and Modeling of the Green Ocean Amazon (GOAmazon) field campaign over the central Amazon near Manaus, Brazil, occurred in coordination with the larger Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud-Resolving Modeling and to the Global Precipitation Measurement (CHUVA) project across Brazil. These programs provide observations of convection over the central Amazon on diurnal to annual time scales. Here, we address the question of how Kelvin waves, observed in satellite observations of deep cloud cover over the GOAmazon region during the 2014–15 time period, modulate the growth, type, and organization of convection over the central Amazon. The answer to this question has implications for improved predictability of organized systems over the region and representation of convection and its growth on local to synoptic scales in global models. Our results demonstrate that Kelvin waves are strong modulators of synoptic-scale low- to midlevel free-tropospheric moisture, integrated moisture convergence, and surface heat fluxes. These regional modifications of the environment impact the local diurnal cycle of convection, favoring the development of mesoscale convective systems. As a result, localized rainfall is also strongly modulated, with the majority of rainfall in the GOAmazon region occurring during the passage of these systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Climatological Characteristics of Typical Daily Precipitation

Precipitation is often quantified by the amount that falls over a given period of time but not the rate at which most of it falls or the rate associated with the most frequent events. Here, three metrics are introduced to distill salient characteristics of typical daily precipitation accumulation based on the full distribution of rainfall: rain amount peak (the rain rate at which the most rain falls), rain frequency peak (the most frequent nonzero rain rate), and rain amount width (a measure of the variability of typical precipitation accumulation). These metrics are applied to two observational datasets to describe the climatology of typical daily precipitation accumulation: GPCP 1° daily (October 1996–October 2015) and TMPA 3B42 (January 1998–October 2015). Results show that the rain frequency peak is similar to total rainfall in terms of geographical pattern and seasonal cycle and varies inversely with rain amount width. In contrast, the rain amount peak varies distinctly, reaching maxima on the outer edges of the regions of high total precipitation, and with less seasonal variation. Despite that GPCP and TMPA 3B42 are both merged satellite–gauge precipitation products, they show substantial differences. In particular, the rain amount peak and rain amount width are uniformly greater in TMPA 3B42 compared to GPCP, and there are large discrepancies in their rain frequency distributions (peak and width). Issues relating to model evaluation are highlighted using CESM1 as an illustrative example and underscore the need for observational datasets incorporating measurements of light rain.

Meteorology & Atmospheric Sciences↗
DOE OSTI2019

Separating Dynamic and Thermodynamic Impacts of Climate Change on Daytime Convective Development over Land

Climate change affects the dynamics and thermodynamics of moist convection. Changes in the dynamics concern, for instance, an increase of convection strength due to increases of convective available potential energy (CAPE). Thermodynamics involve increases in water vapor that the warmer atmosphere can hold and convection can work with. Small-scale simulations are conducted to separate these two components for daytime development of unorganized convection over land. The simulations apply a novel modeling technique referred to as the piggybacking (or master–slave) approach and consider the global climate model (GCM)-predicted change of atmospheric temperature and moisture profiles in the Amazon region at the end of the century under a business-as-usual scenario. The simulations show that the dynamic impact dominates because changes in cloudiness and rainfall come from cloud dynamics considerations, such as the change in CAPE and convective inhibition (CIN) combined with the impact of environmental relative humidity (RH) on deep convection. The small RH reduction between the current and future climate significantly affects the mean surface rain accumulation as it changes from a small reduction to a small increase when the RH decrease is eliminated. The thermodynamic impact on cloudiness and precipitation is generally small, with the extreme rainfall intensifying much less than expected from an atmospheric moisture increase. These results are discussed in the context of previous studies concerning climate change–induced modifications of moist convection. Future research directions applying the piggybacking method are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Influence of Spatial Dipole Pattern in Asian Aerosol Changes on East Asian Summer Monsoon

Since China implemented the Air Pollution Prevention and Control Action Plan in 2013, the aerosol emissions in East Asia have been greatly reduced, while emissions in South Asia have continued to increase. This has led to a dipole pattern of aerosol emissions between South Asia and East Asia. We report the East Asian summer monsoon (EASM) responses to the dipole changes in aerosol emissions during 2013–17 are investigated using the atmosphere model of Community Earth System Model version 2 (CESM2). We show that decreases in East Asian emissions alone lead to a positive aerosol effective radiative forcing (ERF) of 1.59 (±0.97) W m -2 over central-eastern China (25°–40°N, 105°–122.5°E), along with a 0.09 (±0.07)°C warming in summer during 2013–17. The warming intensified the land–sea thermal contrast and increased the rainfall by 0.32 (±0.16) mm day -1 . When considering both the emission reductions in East Asia and increases in South Asia, the ERF is increased to 3.39 (±0.89) W m -2 , along with an enhanced warming of 0.20 (±0.08)°C over central-eastern China, while the rainfall insignificant decreased by 0.07 (±0.16) mm day -1 . It is due to the westward shift of the strengthened western Pacific subtropical high, linked to the increase in black carbon in South Asia. Based on multiple EASM indices, the reductions in aerosol emissions from East Asia alone increased the EASM strength by almost 5%. Considering the effect of the westward shift of WPSH, the dipole changes in emissions together increased the EASM by 5%–15% during 2013–17, revealing an important role of South Asian aerosols in changing the East Asian climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Influence of Spatial Dipole Pattern in Asian Aerosol Changes on East Asian Summer Monsoon

Since China implemented the Air Pollution Prevention and Control Action Plan in 2013, the aerosol emissions in East Asia have been greatly reduced, while emissions in South Asia have continued to increase. This has led to a dipole pattern of aerosol emissions between South Asia and East Asia. Here, the East Asian summer monsoon (EASM) responses to the dipole changes in aerosol emissions during 2013–17 are investigated using the atmosphere model of Community Earth System Model version 2 (CESM2). We show that decreases in East Asian emissions alone lead to a positive aerosol effective radiative forcing (ERF) of 1.59 (±0.97) W m -2 over central-eastern China (25°–40°N, 105°–122.5°E), along with a 0.09 (±0.07)°C warming in summer during 2013–17. The warming intensified the land–sea thermal contrast and increased the rainfall by 0.32 (±0.16) mm day -1 . When considering both the emission reductions in East Asia and increases in South Asia, the ERF is increased to 3.39 (±0.89) W m -2 , along with an enhanced warming of 0.20 (±0.08)°C over central-eastern China, while the rainfall insignificant decreased by 0.07 (±0.16) mm day -1 . It is due to the westward shift of the strengthened western Pacific subtropical high, linked to the increase in black carbon in South Asia. Based on multiple EASM indices, the reductions in aerosol emissions from East Asia alone increased the EASM strength by almost 5%. Finally, considering the effect of the westward shift of WPSH, the dipole changes in emissions together increased the EASM by 5%–15% during 2013–17, revealing an important role of South Asian aerosols in changing the East Asian climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Investigating the Relative Contribution from Tropical Indo-Pacific SST to Asian Monsoon Precipitation Variability Using LIM

Abstract A critical issue is determining the factors that control the year-to-year variability in precipitation over southern Asia. In this study, we employ a cyclostationary linear inverse model (CS-LIM) to quantify the relative contribution of tropical Pacific and Indian Ocean sea surface temperature anomalies (SSTAs) to the interannual variability of the Asian monsoon, especially Indian summer monsoon rainfall (ISMR). Through a series of CS-LIM experiments, we isolate the impacts of the direct forcing from Pacific SSTAs, Indian Ocean SSTAs, and their interaction on Asian monsoon rainfall variability. Our results reveal distinct patterns of influence with the direct forcing from the Pacific (Indian) Ocean tending to enhance (reduce) the magnitude of precipitation variability, while the Indo-Pacific interaction acts to strongly damp the variability of Asian monsoon precipitation, especially over India. We further investigate these specific impacts on ISMR by analyzing the relationship between tropical Indo-Pacific SSTAs and the leading three empirical orthogonal functions (EOFs) of ISMR. The results from our CS-LIM experiments indicate that the direct forcing from El Niño–Southern Oscillation (ENSO) enhances the variability of the first and third EOFs, while the Indian Ocean SSTA opposes ENSO’s effects, which is consistent with previous studies. Our new results show that the tropical Indo-Pacific interaction strongly damps ISMR variability, which is due to the ENSO-induced Indian Ocean dipole (IOD) opposing the direct impacts from ENSO on ISMR. Additionally, reduced ENSO amplitude and duration associated with the Indo-Pacific interaction may also contribute to the damping effect on ISMR, but this requires further study to understand the relevant mechanisms.

Meteorology & Atmospheric Sciences↗
DOE OSTI2024

West African Monsoon System’s Responses to Global Ocean–Regional Atmosphere Coupling

This study explores the added value (AV) of a regional Earth system model (ESM) compared to an atmosphere-only regional climate model (RCM) in simulating West African monsoon (WAM) rainfall. The primary goals are to foster discussions on the suitability of coupled RCMs for WAM projections and deepen our understanding of ocean–atmosphere coupling’s influence on the WAM system. The study employs results from dynamical downscaling of the ERA-Interim reanalysis and Max Plank Institute ESM, low resolution (MPI-ESM-LR), by two RCMs, atmosphere only (REMO) and REMO coupled with Max Planck Institute Ocean Model (MPIOM) (ROM), at ~25-km horizontal resolution. Results show that in regions distant from coupling domain boundaries such as West Africa (WA), constraint conditions from ERA-Interim are more beneficial than coupling effects. REMO, reliant on oceanic sea surface temperatures (SSTs) from observations and influenced by ERA-Interim, is biased under coupling conditions, although coupling offers potential advantages in representing heat and mass fluxes. Contrastingly, as intended, coupling improves SSTs and monsoon fluxes’ relationships under ESM-forced conditions. In this latter case, the coupling features a dipole-like spatial structure of AV, improving precipitation over the Guinea Coast but degrading precipitation over half of the Sahel. Our extensive examination of physical processes and mechanisms underpinning the WAM system supports the plausibility of AV. Additionally, we found that the monsoonal dynamics over the ocean respond to convective activity, with the Sahara–Sahel surface temperature gradient serving as the maintenance mechanism. While further efforts are needed to enhance the coupled RCM, we advocate for its use in the context of WAM rainfall forecasts and projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

On the controls of daytime precipitation in the Amazonian dry season

The Amazon plays an important role in the global energy and hydrological budgets. The precipitation during the dry season (June–September) plays a critical role in maintaining the extent of the rain forest. The deployment of the first Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF-1) in the context of the Green Ocean Amazon (GOAmazon) field campaign at Manacapuru, Brazil, provided comprehensive measurements of surface, cloud, precipitation, radiation, and thermodynamic properties for two complete dry seasons (2014 and 2015). The precipitation events occurring during the nighttime were associated with propagating storm systems (nonlocal effects), while the daytime precipitation events were primarily a result of local land–atmosphere interactions. During the two dry seasons, precipitation was recorded at the surface on 106 days (43%) from 158 rain events with 82 daytime precipitation events occurring on 64 days (60.37%). Detailed comparisons between the diurnal cycles of surface and profile properties between days with and without daytime precipitation suggested the increased moisture at low and midlevels to be responsible for lowering the lifting condensation level, reducing convective inhibition and entrainment, and thus triggering the transition from shallow to deep convection. Although the monthly accumulated rainfall decreased during the progression of the dry season, the contribution of daytime precipitation to it increased, suggesting the decrease to be mainly due to reduction in propagating squall lines. Lastly, the control of daytime precipitation during the dry season on large-scale moisture advection above the boundary layer and the total rainfall on propagating squall lines suggests that coarse-resolution models should be able to accurately simulate the dry season precipitation over the Amazon basin.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

PERSIANN-CNN: Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Convolutional Neural Networks

Abstract Accurate and timely precipitation estimates are critical for monitoring and forecasting natural disasters such as floods. Despite having high-resolution satellite information, precipitation estimation from remotely sensed data still suffers from methodological limitations. State-of-the-art deep learning algorithms, renowned for their skill in learning accurate patterns within large and complex datasets, appear well suited to the task of precipitation estimation, given the ample amount of high-resolution satellite data. In this study, the effectiveness of applying convolutional neural networks (CNNs) together with the infrared (IR) and water vapor (WV) channels from geostationary satellites for estimating precipitation rate is explored. The proposed model performances are evaluated during summer 2012 and 2013 over central CONUS at the spatial resolution of 0.08° and at an hourly time scale. Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN)–Cloud Classification System (CCS), which is an operational satellite-based product, and PERSIANN–Stacked Denoising Autoencoder (PERSIANN-SDAE) are employed as baseline models. Results demonstrate that the proposed model (PERSIANN-CNN) provides more accurate rainfall estimates compared to the baseline models at various temporal and spatial scales. Specifically, PERSIANN-CNN outperforms PERSIANN-CCS (and PERSIANN-SDAE) by 54% (and 23%) in the critical success index (CSI), demonstrating the detection skills of the model. Furthermore, the root-mean-square error (RMSE) of the rainfall estimates with respect to the National Centers for Environmental Prediction (NCEP) Stage IV gauge–radar data, for PERSIANN-CNN was lower than that of PERSIANN-CCS (PERSIANN-SDAE) by 37% (14%), showing the estimation accuracy of the proposed model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Can the GPM IMERG Final Product Accurately Represent MCSs’ Precipitation Characteristics over the Central and Eastern United States?

Mesoscale convective systems (MCSs) play an important role in water and energy cycles as they produce heavy rainfall and modify the radiative profile in the tropics and midlatitudes. An accurate representation of MCSs’ rainfall is therefore crucial in understanding their impact on the climate system. The V06B Integrated Multisatellite Retrievals from Global Precipitation Measurement (IMERG) half-hourly precipitation final product is a useful tool to study the precipitation characteristics of MCSs because of its global coverage and fine spatiotemporal resolutions. However, errors and uncertainties in IMERG should be quantified before applying it to hydrology and climate applications. This study evaluates IMERG performance on capturing and detecting MCSs’ precipitation in the central and eastern United States during a 3-yr study period against the radar-based Stage IV product. The tracked MCSs are divided into four seasons and are analyzed separately for both datasets. IMERG shows a wet bias in total precipitation but a dry bias in hourly mean precipitation during all seasons due to the false classification of nonprecipitating pixels as precipitating. These false alarm events are possibly caused by evaporation under the cloud base or the misrepresentation of MCS cold anvil regions as precipitating clouds by the algorithm. IMERG agrees reasonably well with Stage IV in terms of the seasonal spatial distribution and diurnal cycle of MCSs precipitation. A relative humidity (RH)-based correction has been applied to the IMERG precipitation product, which helps reduce the number of false alarm pixels and improves the overall performance of IMERG with respect to Stage IV.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The 1996 Mid-Atlantic Winter Flood: Exploring Climate Risk through a Storyline Approach

Abstract This article explores the application of thermodynamic perturbations to a historical midlatitude, wintertime, rain-on-snow flood event to evaluate how similar events may evolve under different climate forcings. In particular, we generate a hindcast of the 1996 Mid-Atlantic flood using an ensemble of 14-km variable-resolution simulations completed with the U.S. Department of Energy’s global Energy Exascale Earth System Model (E3SM). We show that the event is skillfully reproduced over the Susquehanna River Basin (SRB) by E3SM when benchmarked against in situ observational data and high-resolution reanalyses. In addition, we perform five counterfactual experiments to simulate the flood under preindustrial conditions and four different levels of warming as projected by the Community Earth System Model Large Ensemble. We find a nonlinear response in simulated surface runoff and streamflow as a function of atmospheric warming. This is attributed to changing contributions of liquid water input from a shallower initial snowpack (decreased snowmelt), increased surface temperatures and rainfall rates, and increased soil water storage. Flooding associated with this event peaks from around +1 to +2 K of global average surface warming and decreases with additional warming beyond this. There are noticeable timing shifts in peak runoff and streamflow associated with changes in the flashiness of the event. This work highlights the utility of using storyline approaches for communicating climate risk and demonstrates the potential nonlinearities associated with hydrologic extremes in areas that experience ephemeral snowpack, such as the SRB.

Meteorology & Atmospheric Sciences↗
DOE OSTI2016

Sensitivity of a Cumulus Parameterization Scheme to Precipitation Production Representation and Its Impact on a Heavy Rain Event over Korea

The sensitivity of a cumulus parameterization scheme (CPS) to a representation of precipitation production is examined. To do this, the parameter that determines the fraction of cloud condensate converted to precipitation in the simplified Arakawa–Schubert (SAS) convection scheme is modified following the results from a cloud-resolving simulation. While the original conversion parameter is assumed to be constant, the revised parameter includes a temperature dependency above the freezing level, whichleadstolessproductionoffrozenprecipitating condensate with height. The revised CPS has been evaluated for a heavy rainfall event over Korea as well as medium-range forecasts using the Global/Regional Integrated Model system (GRIMs). The inefficient conversion of cloud condensate to convective precipitation at colder temperatures generally leads to a decrease in pre-cipitation, especially in the category of heavy rainfall. The resultant increase of detrained moisture induces moistening and cooling at the top of clouds. A statistical evaluation of the medium-range forecasts with the revised precipitation conversion parameter shows an overall improvement of the forecast skill in precipitation and large-scale fields, indicating importance of more realistic representation of microphysical processes in CPSs.

Han, Ji-Young↗
DOE OSTI2024

On CCN Effects upon Convective Cold Pool Timing and Features

Abstract Cold pools produced by deep convection can initiate new convection, and their representation in larger-scale weather and climate models could improve prediction of the extent and timing of upscale growth. Cold pools originate from latent cooling from precipitation changing phase, but little attention has been paid to microphysical influences on cold pool characteristics, particularly CCN effects. Datasets obtained from the CACTI and RELAMPAGO field campaigns, along with idealized numerical modeling, are utilized to investigate the hypothesis that convective storms forming in higher-CCN environments generate their first surface rainfall later, delaying cold pool initiation. Aircraft observations of CCN and shallow convection on 9 days do suggest a CCN effect. Those ingesting more CCN contained fewer drizzle drops, although a decreased cloud depth with increasing CCN was also likely a limiting factor. In three of those cases that later developed into deep convection, the timing of cold pool onset was not ubiquitously delayed in environments with more CCN. Idealized numerical simulations suggest that an ordinary thunderstorm can experience small delays in cold pool onset with increasing CCN due to changes in graupel production, but CCN effects on the cold pool from a supercell thunderstorm can be easily overpowered by its unique dynamics. A strong inverse relationship between cold pool strength, expansion rate, and depth with increasing CCN is suggested by the results of the ordinary thunderstorm simulation. Further consideration of CCN appears warranted for future cold pool parameterization development, but other environmental factors affecting storm morphology and precipitation cannot be ignored.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

Modern analogs for understanding pollen-vegetation dynamics in a Mediterranean mosaic landscape (Balearic Islands, Western Mediterranean)

This paper presents the study of modern pollen analogs from the Balearic Islands. While similar studies have been largely applied to mainland areas, research focused on modern vegetation dynamics on Mediterranean islands remains very rare. In this research, we combine vegetation surveys, pollen analysis and multivariate statistics to understand landscape composition. The main objectives of are: (1) to examine pollen-vegetation relationships in relation to environmental and land-use variables; (2) to understand modern pollen representation in a mosaic landscape structure; and (3) to propose pollen indicators that characterize the primary vegetation types from the Balearic Islands to better interpret past pollen records in Mediterranean island environments. Pollen results and Redundancy Analysis (RDA) distinguish three major groups: (a) Holm oak and box formations; (b) maquis and garrigues; and (c) anthropogenic and open habitats. Landscape form, mean decadal rainfall, mean decadal temperature, fire activity, trampling, slope percentage, wet/flooded soil, saline soil, distance to agropastoral cells, gHM index, domestic herbivory presence, agropastoral use, and soil type are the major variables explaining modern pollen assemblage variation in our research. Poaceae undiff., Plantago sp., Apiaceae undiff., Cerealia-t, and Cichorieae are highly correlated to human activities but should be interpreted cautiously when occurring in low values. Quercus ilex-t, Hypericum, and Buxus are correlated to humid locations while Pistacia, Pinus, Juniperus-t, and Olea to high mean decadal temperatures. Our study indicates how pollen analysis and multivariate analysis are powerful tools for characterizing the mosaic landscape, with special focus on the main vegetation types of the Balearic Islands.

Geology↗
DOE OSTI2017

Spatial Analysis of Stover Moisture Content During Harvest Season in the U.S.

The moisture content of a maturing crop varies as the harvest season progresses. For crop residues such as corn stover, moisture content at the time of harvest can be as high as 75% (wet mass basis) to less than 20% depending on the geographic location (climate conditions) and stage of harvest. Biomass moisture content is critical for baling and extended storage. It is therefore essential to have an estimate of the quantities of corn stover available as wet or dry for various parts of the U.S. To this end, we analyzed hourly weather data (temperature, humidity, and rainfall) from the Typical Meteorological Year v.3 (TMY3) dataset developed by the National Renewable Energy Laboratory. A recently published set of equations for calculating the moisture content of stover as a function of hourly temperature, humidity, and rainfall were used. The annual start and end of corn grain harvest along with annual grain production (in bushels) for each state were extracted from USDA National Agricultural Statistics Service reports. Using these datasets and moisture sorption equations, the percentage of corn stover tonnage with moisture content less than 20%, between 20% and 40%, or greater than 40% was estimated from the length of time that the biomass was in these moisture content ranges. These calculations were carried out for several locations within each of the states for which TMY data were available. It was concluded that about 37.2% of corn stover is dry (<20% moisture content), whereas 36.5% is wet (>40% moisture content) nationwide. The remaining 27.0% of corn stover is between 20% and 40% moisture content. Keywords: Corn stover, Equilibrium moisture content, Field drying, Moisture content, Stover harvest, Typical Meteorological Year data.

09 BIOMASS FUELS↗