nasa-gesdisc/es-publications-researchareas huggingface dataset:
Large-Scale Geographic Variation in Distribution and Abundance of Australian Deep-Water Kelp Forests (2015)

Despite the significance of marine habitat-forming organisms, little is known about their large-scale distribution and abundance in deeper waters, where they are difficult to access. Such information is necessary to develop sound conservation and management strategies. Kelps are main habitat-formers in temperate reefs worldwide; however, these habitats are highly sensitive to environmental change. The kelp Ecklonia radiate is the major habitat-forming organism on subtidal reefs in temperate Australia. Here, we provide large-scale ecological data encompassing the latitudinal distribution along the continent of these kelp forests, which is a necessary first step towards quantitative inferences about the effects of climatic change and other stressors on these valuable habitats. We used the Autonomous Underwater Vehicle (AUV) facility of Australias Integrated Marine Observing System (IMOS) to survey 157,000 m2 of seabed, of which ca 13,000 m2 were used to quantify kelp covers at multiple spatial scales (10100 m to 1001,000 km) and depths (1560 m) across several regions ca 26 latitude apart along the East and West coast of Australia. We investigated the large-scale geographic variation in distribution and abundance of deep-water kelp (>15 m depth) and their relationships with physical variables. Kelp cover generally increased with latitude despite great variability at smaller spatial scales. Maximum depth of kelp occurrence was 4050 m. Kelp latitudinal distribution along the continent was most strongly related to water temperature and substratum availability. This extensive survey data, coupled with ongoing AUV missions, will allow for the detection of long-term shifts in the distribution and abundance of habitat-forming kelp and the organisms they support on a continental scale, and provide information necessary for successful implementation and management of conservation reserves.

Research areas: Ecosystems
Lagrangian analysis of microphysical and chemical processes in the Antarctic stratosphere: a case study (2015)

Abstract. We investigated chemical and microphysical processes in the late winter in the Antarctic lower stratosphere, after the first chlorine activation and initial ozone depletion. We focused on a time interval when both further chlorine activation and ozone loss, but also chlorine deactivation, occur.  We performed a comprehensive Lagrangian analysis to simulate the evolution of an air mass along a 10-day trajectory, coupling a detailed microphysical box model to a chemistry model. Model results have been compared with in situ and remote sensing measurements of particles and ozone at the start and end points of the trajectory, and satellite measurements of key chemical species and clouds along it.  Different model runs have been performed to understand the relative role of solid and liquid polar stratospheric cloud (PSC) particles for the heterogeneous chemistry, and for the denitrification caused by particle sedimentation. According to model results, under the conditions investigated, ozone depletion is not affected significantly by the presence of nitric acid trihydrate (NAT) particles, as the observed depletion rate can equally well be reproduced by heterogeneous chemistry on cold liquid aerosol, with a surface area density close to background values.  Under the conditions investigated, the impact of denitrification is important for the abundances of chlorine reservoirs after PSC evaporation, thus stressing the need to use appropriate microphysical models in the simulation of chlorine deactivation. We found that the effect of particle sedimentation and denitrification on the amount of ozone depletion is rather small in the case investigated. In the first part of the analyzed period, when a PSC was present in the air mass, sedimentation led to a smaller available particle surface area and less chlorine activation, and thus less ozone depletion. After the PSC evaporation, in the last 3 days of the simulation, denitrification increases ozone loss by hampering chlorine deactivation.

Research areas: Validation
Investigation of sea-breeze convergence in Salento Peninsula (southeastern Italy) (2015)

The frequency, the location and the characteristics of convective rainfall events induced by the convergence of different sea breeze systems on a Mediterranean peninsula (Salento, in southeastern Italy) are analyzed. Such events have been studied considering satellite/radar images and output fields from two Limited Area Models in the summer period of 20112013. A total of 20days have been detected in which the precipitation due to sea-breeze convergence was clearly observed in satellite and radar images. The synoptic conditions associated with these events have been identified considering the averages of some relevant meteorological parameters in the selected days and the anomaly with respect to the climate. The presence of a cold trough in the central Mediterranean basin appears as a fundamental ingredient for the occurrence of sea breeze convergence and associated precipitation. High-resolution simulations with two state-of-art numerical models have revealed that both of them are generally able to simulate a convergence pattern correctly, apart from a couple of cases for each model. The higher rainfall amounts occur with weak synoptic wind, and weak-to-moderate values of Convective Available Potential Energy (CAPE). When the synoptic wind is of moderate intensity, the region of convergence moves toward the Adriatic coast for a prevailing southerly component, and toward the Ionian coast for a prevailing northerly component. On the opposite, the skin sea surface temperature is relatively uniform and the difference between the Ionian and the Adriatic Seas, surrounding the peninsula on the east and west side, is generally smaller than 1K, having only a marginal effect on the sea breeze patterns. Similarly, the value of CAPE before the occurrence of rainfall has low prognostic value. The results shows that limited area models with a grid spacing of few km appear as appropriate tools for the simulation for such relatively small scale phenomena.

Research areas: Atmospheric/Ocean Indicators
Interannual variability in chlorophyll-a on the southern Queensland continental shelf and its relationship to ENSO (2015)

Coastal phytoplankton blooms can result from upwelling of colder nutrient-rich water, seasonal fluvial or anthropogenic point sources of nutrient. Here we analyze 15-year time series of monthly mean and 8-day satellite-derived chlorophyll-a (Chl-a) and sea surface temperature (SST) on the southern Queensland continental shelf (24.2528.25S) from March 2000 to February 2015. We examine the interannual variability in these parameters and its relationship to algal bloom dynamics. Seasonal climatological means are computed and analyzed. Empirical orthogonal function (EOF) analysis is applied to these time series. Cross-correlation and spatial correlation analyses are used to investigate the relationship between the multivariate ENSO index (MEI), Chl-a and SST. Computed eigenvectors of the time series of Chl-a and SST present a strong seasonal variability on the first EOF modes. Thus, the seasonal variability was removed by computing monthly and 8-day Chl-a and SST anomalies. The EOF analysis was then applied to the anomaly time series. Correlation analysis results show a positive correlation between MEI and the eigenvector of the first EOF of the monthly Chl-a anomaly with time lag of three to four months. We find a negative correlation between MEI and the eigenvector of the second EOF of the monthly Chl-a anomaly with time lag of three to four months. There is no correlation between MEI and eigenvectors of the monthly SST anomaly. There are significant correlations between eigenvectors of the first and second EOF modes of 8-day Chl-a and the first and second EOF modes of 8-day SST respectively. Negative correlation coefficients between 8-day anomalies of Chl-a and SST are found on the continental shelf to the east of Fraser Island and Stradbroke Island. Analysis of a particular algal bloom event indicates a negative SST anomaly and negative curl of wind stress in the waters to the southeast of Fraser Island suggesting that wind stress is possibly a secondary but significant physical driver of the upwelling system. Our results suggest that variability in phytoplankton biomass on the southern Queensland continental shelf is driven by upwelling of nutrients during the spring dry season and fluvial nutrient loads during the summer and autumn wet seasons. Seasonal change is the primary factor controlling the variability of Chl-a and SST while climate variability (ENSO) and upwelling are secondary but significant factors.

Research areas: Ecosystems, Atmospheric/Ocean Indicators
Influence of air mass origin on aerosol properties at a remote Michigan forest site (2015)

The northern Great Lakes region of North America is a large, relatively pristine area. To date, there has only been limited study of the atmospheric aerosol in this region. During summer 2009, a detailed characterization of the atmospheric aerosol was conducted at the University of Michigan Biological Station (UMBS) as part of the Community AtmosphereBiosphere Interactions Experiment (CABINEX). Measurements included particle size distribution, water-soluble composition, and CCN activity. Aerosol properties were strongly dependent on the origin of the air masses reaching the site. For 60% of the study period, air was transported from sparsely populated regions to the northwest. During these times aerosol loadings were low, with mean number and volume concentrations of 1630 cm3 and 1.91 m3 cm3, respectively. The aerosol during clean periods was dominated by organics, and exhibited low hygroscopicities (mean  = 0.18 at s = 0.3%). When air was from more populated regions to the east and south (29% of the time), aerosol properties reflected a stronger anthropogenic influence, with 85% greater particle number concentrations, 2.5 times greater aerosol volume, six times more sulfate mass, and increased hygroscopicity (mean  = 0.24 at s = 0.3%). These trends are have the potential to influence forestatmosphere interactions and should be targeted for future study.

Research areas: Air Quality, Environmental Impacts
Influence of acquisition time and resolution on wheat yield estimation at the field scale from canopy biophysical variables retrieved from SPOT satellite data (2015)

Detailed information about the prediction of within-field potential in terms of yield at the field scale is an attractive goal that would allow useful applications in precision agriculture. Biophysical variables characterizing crop canopies, such as the leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), fractional ground cover (Fcover) and the concentration of chlorophyll-a and -b (Cab), can be estimated from satellite remote-sensing data through the application of a neural network inversion of a radiative transfer model, such as PROSAIL. The knowledge of the temporal and spatial variability of these variables can enhance the possibilities of estimating yield at the field scale. The aim of this study is to investigate the influence of acquisition time and spatial resolution of biophysical variables estimated from satellite data on the grain yield estimation of wheat crops. We used SPOT 4 (spatial resolution: 20 m) and SPOT 5 (spatial resolution: 10 m) images, acquired at six different dates during the wheat growing season in 2012, to obtain LAI, Fcover, FAPAR, and Cab on five fields in Maccarese (Central Italy). A preliminary survey was carried out to correlate spatially biophysical variables with the final grain yield at each acquisition date. Biophysical variables estimated at a spatial resolution of 10 m during the stem elongation stage showed the best simple and spatial correlation with yield. At this stage, all the biophysical variables showed the highest correlation values as compared to the other dates. Subsequently, we used the variables estimated from SPOT data at each growth stage to calibrate multiple linear regression (MLR) and cubist regression (CR) models for two fields, which were then validated on five independent fields. Although the CR calibration models provided better accuracy than MLR, the best validation statistics were gained from MLR models, obtaining a root mean square error (RMSE) of about 1 t ha1 for three of these fields, using remote data having a spatial resolution of 10 metres and acquired between steam elongation and booting stage. The optimal acquisition time is affected, ceteris paribus, by the agricultural management and in particular by the variety that can influence the trend of crop growth. However, the optimal growth stage for yield estimation seems to be quite similar over the study area during a growth season. The validation of models on field data collected in another growing season is mainly affected by the climate conditions. These results highlight the importance of spatial resolution and the influence of acquisition time of satellite images on the estimation of yield at the field scale by remote-sensing data.

Research areas: Agriculture
In situ response of bay productivity to nutrient loading from a small tributary: The Delaware Bay-Murderkill Estuary tidally-coupled biogeochemical reactor (2015)

A small, turbid and nutrient-rich tributary, the Murderkill Estuary, and a large estuarine ecosystem, the Delaware Bay, are tightly linked and form an efficient, tidally-coupled biogeochemical reactor during the summer. Nitrate loading from the Murderkill Estuary generates an instantaneous increase in biological oxygen production in the adjacent Delaware Bay. We are able to capture this primary production response with continuous hourly measurements of dissolved oxygen, chlorophyll, and nitrate. The nitrate influxes from the Murderkill support primary production rates in the Delaware Bay margins that are twice as high as the average production rates measured in the central Bay regions. This elevates chlorophyll in the Bay margins in the summer and fuels metabolism. Tidal transport of the newly produced autochthonous chlorophyll particles from the Bay into the Estuary could also provide a source of labile material to the marshes surrounding the Murderkill, thus perhaps fueling marsh respiration. As a consequence of the tidal coupling between Delaware Bay and the Murderkill Estuary, ecosystem productivity and metabolism in the Bay and Estuary are linked, generating an ecosystem feedback mechanism. Storms modulate this tidally-coupled biogeochemical reactor, by generating significant nitrate and salinity changes. Depending on their magnitude and duration, storms induce large phytoplankton blooms in the Delaware Bay. Such large phytoplankton blooms may occur more often with climate change, since century-long discharge records document an increase in storm frequency.

Research areas: Water Quality, Ecosystems
Implications of MODIS impression of aerosol loading over urban and rural settlements in Nigeria: Possible links to energy consumption patterns in the country (2015)

A study of aerosol loading patterns in some selected cities in Nigeria was carried out using MODIS, TOMS/OMI AND AIRS satellite imageries for a period of 10 years. The results showed that an aerosol optical depth (AOD) loading obtained ranged from 0.020.9, UV aerosol index (AI) and carbon monoxide (CO) results ranged from 1.32 2.43 and 2.222.6 molecule/cm2, respectively. The CO data was used to infer the presence of carbonecous aerosols from biomass, fossil combustion and industrial activities. This result indicates that areas with higher AOD and AI do not correspond in high CO loading. From the HYSPLIT and HAT analysis conducted it showed that advection plays important role in the dispersion of aerosols. This implies that aerosols can reside in a place remote from where they are generated. Also, the high concentration of CO aerosol in the southern cities suggests a high rate of industrial pollution as a result of fossil fuel burning, vehicular emissions, high population density and gas flaring. Therefore, emphasis should be on the need to switch to renewable energy options as an alternative to fossil fuel. Furthermore, plans for mitigations should not be limited to industrialized cities only but extended to other cities which might be bearing the real brunt of industrial emissions as shown in this work.

Research areas: Air Quality, Environmental Impacts, Energy Production/Use
Impacts of Amazonia biomass burning aerosols assessed from short-range weather forecasts (2015)

Abstract. The direct radiative impacts of biomass burning aerosols (BBA) on meteorology are investigated using short-range forecasts from the Met Office Unified Model (MetUM) over South America during the South American Biomass Burning Analysis (SAMBBA). The impacts are evaluated using a set of three simulations: (i) no aerosols, (ii) with monthly mean aerosol climatologies and (iii) with prognostic aerosols modelled using the Coupled Large-scale Aerosol Simulator for Studies In Climate (CLASSIC) scheme. Comparison with observations show that the prognostic CLASSIC scheme provides the best representation of BBA. The impacts of BBA are quantified over central and southern Amazonia from the first and second day of 2-day forecasts during 14 September3 October 2012. On average, during the first day of the forecast, including prognostic BBA reduces the clear-sky net radiation at the surface by 15  1 W m2 and reduces net top-of-atmosphere (TOA) radiation by 8  1 W m2, with a direct atmospheric warming of 7  1 W m2. BBA-induced reductions in all-sky radiation are smaller in magnitude: 9.0  1 W m2 at the surface and 4.0  1 W m2 at TOA. In this modelling study the BBA therefore exert an overall cooling influence on the Earthatmosphere system, although some levels of the atmosphere are directly warmed by the absorption of solar radiation. Due to the reduction of net radiative flux at the surface, the mean 2 m air temperature is reduced by around 0.1  0.02 C. The BBA also cools the boundary layer (BL) but warms air above by around 0.2 C due to the absorption of shortwave radiation. The overall impact is to reduce the BL depth by around 19  8 m. These differences in heating lead to a more anticyclonic circulation at 700 hPa, with winds changing by around 0.6 m s1. Inclusion of climatological or prognostic BBA in the MetUM makes a small but significant improvement in forecasts of temperature and relative humidity, but improvements were small compare with model error and the relative increase in forecast skill from the prognostic aerosol simulation over the aerosol climatology was also small. Locally, on a 150 km scale, changes in precipitation reach around 4 mm day1 due to changes in the location of convection. Over Amazonia, including BBA in the simulation led to fewer rain events that were more intense. This change may be linked to the BBA changing the vertical profile of stability in the lower atmosphere. The localised changes in rainfall tend to average out to give a 5 % (0.06 mm day1) decrease in total precipitation over the Amazonian region (except on day 2 with prognostic BBA). The change in water budget from BBA is, however, dominated by decreased evapotranspiration from the reduced net surface fluxes (0.2 to 0.3 mm day1), since this term is larger than the corresponding changes in precipitation and water vapour convergence.

Research areas: Atmospheric/Ocean Indicators
Impact of Meteorological Parameters and Gaseous Pollutants on PM2.5 and PM10 Mass Concentrations during 2010 in Xian, China (2015)

ABSTRACTMass concentrations of PM2.5 and PM10 from the six urban/rural sampling sites of Xian were obtained during two weeks of every month corresponding to January, April, July and October during 2010, together with the six meteorological parameters and the data of two precursors. The result showed that the average annual mass concentrations of PM2.5 and PM10 were 140.9  108.9 g m3 and 257.8  194.7 g m3, respectively. Basin terrain constrains the diffusion of PM2.5 and PM10 concentration spatially. High concentrations in wintertime and low concentrations in summertime are due to seasonal variations of meteorological parameters and cyclic changes of precursors (SO2 and NO2). Stepwise Multiple Linear Regression (MLR) analysis indicates that relative humidity is the main factor influencing on meteorological parameter. Entry MLR analysis suggests that SO2 from local coal-burning power plants is still the primary pollutant. Trajectory cluster results of PM2.5 at BRR indicate that the entrained urban pollutants carried by the westerly or winter monsoon forms the dominant regional pollution sources in winter and spring. Ultraviolet (UV) aerosol index verified the source and pathway of dust storm in spring.

Research areas: Air Quality, Environmental Impacts
Identifying fire plumes in the Arctic with tropospheric FTIR measurements and transport models (2015)

Abstract. We investigate Arctic tropospheric composition using ground-based Fourier transform infrared (FTIR) solar absorption spectra, recorded at the Polar Environment Atmospheric Research Laboratory (PEARL, Eureka, Nunavut, Canada, 8005' N, 8642' W) and at Thule (Greenland, 7653' N, 6874' W) from 2008 to 2012. The target species, carbon monoxide (CO), hydrogen cyanide (HCN), ethane (C2H6), acetylene (C2H2), formic acid (HCOOH), and formaldehyde (H2CO) are emitted by biomass burning and can be transported from mid-latitudes to the Arctic.  By detecting simultaneous enhancements of three biomass burning tracers (HCN, CO, and C2H6), ten and eight fire events are identified at Eureka and Thule, respectively, within the 5-year FTIR time series. Analyses of Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model back-trajectories coupled with Moderate Resolution Imaging Spectroradiometer (MODIS) fire hotspot data, Stochastic Time-Inverted Lagrangian Transport (STILT) model footprints, and Ozone Monitoring Instrument (OMI) UV aerosol index maps, are used to attribute burning source regions and travel time durations of the plumes. By taking into account the effect of aging of the smoke plumes, measured FTIR enhancement ratios were corrected to obtain emission ratios and equivalent emission factors. The means of emission factors for extratropical forest estimated with the two FTIR data sets are 0.40  0.21 g kg1 for HCN, 1.24  0.71 g kg1 for C2H6, 0.34  0.21 g kg1 for C2H2, and 2.92  1.30 g kg1 for HCOOH. The emission factor for CH3OH estimated at Eureka is 3.44  1.68 g kg1.  To improve our knowledge concerning the dynamical and chemical processes associated with Arctic pollution from fires, the two sets of FTIR measurements were compared to the Model for OZone And Related chemical Tracers, version 4 (MOZART-4). Seasonal cycles and day-to-day variabilities were compared to assess the ability of the model to reproduce emissions from fires and their transport. Good agreement in winter confirms that transport is well implemented in the model. For C2H6, however, the lower wintertime concentration estimated by the model as compared to the FTIR observations highlights an underestimation of its emission. Results show that modeled and measured total columns are correlated (linear correlation coefficient r > 0.6 for all gases except for H2CO at Eureka and HCOOH at Thule), but suggest a general underestimation of the concentrations in the model for all seven tropospheric species in the high Arctic.

Research areas: Wildfires, Air Quality