NASA's Terra Satellite Research Articles

Modeling insect population fluctuations with satellite land surface temperature

The simulation of insect pest populations in agricultural and forest ecosystems is an important and useful tool for integrated pest management (IPM). Insect population models are mainly driven by environmental temperature data, which are usually collected from agrometeorological stations or derived from geographic statistical extrapolations. The present study describes the modeling of olive fly (Bactrocera oleae) populations in the Eastern Mediterranean region using the MODIS (Moderate Resolution Image Spectro Radiometer) land surface temperature (LST) product from NASA TERRA satellite. These data, together with in situ temperature data, were used to estimate the tree-canopy temperatures at the pixel resolution (1km). The estimated canopy temperature was used as input for the olive fly population model. Our main aim was to demonstrate the use of satellite-acquired information for modelling biological and ecological phenomena. Eleven years (2001–2012) of olive fly population fluctuations were simulated for three different geographic locations, representing different geo-climatic conditions. The model successfully simulated the seasonal population fluctuations throughout the 11-year period and did a good job of connecting all of the life stages of the insect. To evaluate the validity of these findings, we compared them with adult olive-fly trapping data. We observed a high degree of correlation between the trapping data and our model's predictions. Here, we demonstrate that satellite thermal data can be used to predict insect pest population fluctuations for IPM purposes. The study also advances some new modelling concepts, such as the “window of opportunity” which links physiological development with chronological age.

Evolution of the 2011 Mt. Etna ash and SO2 lava fountain episodes using SEVIRI data and VPR retrieval approach

In this paper an estimation is made of the temporal evolution of volcanic ash and sulfur dioxide (SO2) emissions from Mt. Etna during its eruption phases. The retrieval is performed using MSG-SEVIRI (Meteosat Second Generation — Spinning Enhanced Visible and Infra Red Imager) images in the TIR (Thermal InfraRed) spectral range. The ash and SO2 plume abundance maps are computed using the Volcanic Plume Removal (VPR) procedure originally applied to MODIS (Moderate Resolution Imaging Spectroradiometer) sensors on board the NASA Terra and Aqua satellites. As test cases, two 2011 lava fountain episodes were considered. The set of parameters required by VPR for the Mt. Etna volcano, Volz type particles, and the SEVIRI sensor are presented. Once the parameters have been computed, the VPR approach requires as input only the SEVIRI-TIR radiances of the bands centered at 8.7, 10.8, and 12.0μm, together with the plume temperature and altitude. The VPR returns maps of plume particles' effective radius, aerosol optical depth at 550nm, and columnar abundance of ash and SO2. A new procedure for estimating wind speed and direction is also presented. Since the ash and SO2 abundance maps, and wind speed at the plume altitude are known, it is possible to reconstruct the ash and SO2 fluxes emitted during the eruption through time. The VPR procedure, applied to TIR SEVIRI data, allows for fast and reliable ash and SO2 retrieval with high temporal resolution during both day and night, and is thus suitable for operational use during a volcanic crisis.

A hydrologic routing model suitable for climate‐scale simulations of arctic rivers: application to the Mackenzie River Basin

AbstractIn this study, the Hillslope River Routing (HRR) model was modified for arctic river basin applications and used to route surface and subsurface run‐off from the Community Land Model (CLM) in the Mackenzie River Basin (MRB) for the period 2000–2004. The HRR modelling framework performs lateral surface and subsurface run‐off routing from hillslopes and channel/floodplain routing. The HRR model was modified here to include a variable subsurface active layer thickness (ALT; permafrost) to enable subsurface water to resurface, a distributed surface storage component to store and attenuate the rapid generation of snowmelt water, compound hillslopes to account for the low relief near rivers and floodplains, and reservoir routing to complete the total surface and subsurface water storage accounting. To illustrate the new HRR model components, a case study is presented for the MRB. The basin is discretized into 5077 sub‐basins based on a drainage network derived from the global digital elevation model (DEM) developed from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor on board NASA's Terra satellite and river widths extracted from LandSat images. The median hillslope land area is 68.5 km2 with a flow length of 2.8 km. Gridded CLM surface and subsurface run‐offs are remapped to the HRR model's irregular sub‐basins. The role of each new model component is quantified in terms of peak annual streamflow (magnitude and timing) at select locations and basin‐wide total water storage anomalies. The role of distributed surface storage is shown to attenuate the relatively rapid generation of snowmelt water, impact the annual peak hydrograph (reduced peaks by >30% and detailed peak by >20 days), and account for 20% of the monthly total water storage anomalies averaged over the year and ranging from 14 to 25% (−10 to 30 mm) throughout the year. Although additional research is needed to dynamically link spatially distributed ALT to HRR, the role of ALT is shown to be important. A basin‐wide, uniform 1 m ALT impacts the annual peak hydrograph (reduced peaks by 9% and detailed peak by 8 days) and trends in total water storage anomalies. Copyright © 2014 John Wiley & Sons, Ltd.

Residential Greenness Reduces Depression Risk in a Cohort of Adult Women

Residential Greenness Reduces Depression Risk in a Cohort of Adult WomenAbstract Number:2902 Peter James*, Rachel Banay, Jaime Hart, Olivia Okerere, and Francine Laden Peter James* Harvard School of Public Health, United States, E-mail Address: [email protected] Search for more papers by this author , Rachel Banay Harvard School of Public Health, United States, E-mail Address: [email protected] Search for more papers by this author , Jaime Hart Harvard School of Public Health, United States, E-mail Address: [email protected] Search for more papers by this author , Olivia Okerere Harvard School of Public Health, United States, E-mail Address: [email protected] Search for more papers by this author , and Francine Laden Harvard School of Public Health, United States, E-mail Address: [email protected] Search for more papers by this author AbstractBackground: Emerging evidence indicates that lower levels of residential or neighborhood greenness may be associated with adverse mental health effects. However, to this point, scant research has considered depression specifically, and most research has involved cross-sectional data only. The objective of this study was to examine residential greenness and depression risk prospectively in the Nurses’ Health Study.Methods: A total of 50,222 women (mean age 63 [range 49.5-76.8]) without depression atbaseline (2000) were followed until 2006. Residential greenness was measured using the Normalized Difference Vegetation Index (NDVI) derived from MODerate-resolution Imaging Spectroradiometer on board NASA's Terra satellite imagery, and defined as themean greenness value in July of each year within a 1,250 meter radial buffer of the nurses’ mailing addresses. Depression was defined as having either self-reported physician-diagnosed depression or self-reported use of antidepressants. We used a Coxproportional hazards analysis to examine the relationship between greenness and depression incidence.Results: Over 518,824 person-years, 7,433 incident depression cases were identified. Mean July NDVI levels were 167.7 (range 31.9-233.1). In models adjusted for month of the year of questionnaire return, race, individual socioeconomic status, educationalattainment, marital status, physical activity, BMI, level of social participation, smoking status, mental health at baseline, and Census tract median home value, median income, and population density, living in the highest quintile of residential NDVI was associated with a 14% reduction in depression risk (HR= 0.86 [95% confidence interval (CI) 0.79, 0.93]) compared to the lowest quintile of greenness.Conclusions: In this population of women, we observed an inverse relationship between surrounding summer greenness levels and the risk of self-reported depression.

China Collection 2.0: The aerosol optical depth dataset from the synergetic retrieval of aerosol properties algorithm

A wide range of data products have been published since the operation of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on NASA's TERRA and AQUA satellites. Based on DarkTarget and DeepBlue method, NASA has published Aerosol Optical Depth (AOD) products Collection 5.0 and Collection 5.1 at 10 km spatial resolution. The Collection 6.0 will be published soon with spatial resolution of 3 km. Although validated globally, regional and systematic errors are still found in the MODIS-retrieved AOD products. This is especially remarkable for bright heterogeneous land surface, such as mainland China. In order to solve the aerosol retrieval problem over heterogeneous bright land surface, the Synergetic Retrieval of Aerosol Properties algorithm (SRAP) has been developed based on the synergetic use of the MODIS data of TERRA and AQUA satellites. Using the SRAP algorithm, we produced AOD dataset-China Collection 2.0, dated from August 2002 to August 2012, and compared the AOD results with AErosol Robotic NETwork (AERONET) and Chinese Meteorological Administration Aerosol Remote Sensing Network (CARSNET) measurements. We find that 62% of China Collection 2.0 AOD values are within an expected error (EE) range of ±(0.05 + 20%) and that 56% are within an EE range of ±(0.05 + 15%) when compared with AERONET-observed values. For CARSNET validation, we find that 60% of China Collection 2.0 AOD values are within an expected error (EE) range of ±(0.05 + 20%) and that 53% are within an EE range of ±(0.05 + 15%). In addition, we also compare the AOD results with MODIS aerosol products, the cross validation shows that the two AOD have good consistency. Monthly averaged AOD results show that AOD is generally high in China's eastern coastal region from March to August, and AOD is not more than 0.5 in other months. Season averaged results show that the higher values of AOD are mostly distributed in eastern and southern China.

The empirical relationship between satellite-derived tropospheric NO<sub>2</sub> and fire radiative power and possible implications for fire emission rates of NO<sub>x</sub>

Abstract. Nitrogen oxides (NOx) play key roles in atmospheric chemistry, air pollution, and climate. While the largest fraction of these reactive gases is released by anthropogenic emission sources, a significant amount can be attributed to vegetation fires. In this study, NO2 from GOME-2 on board EUMETSAT's MetOp-A and OMI on board NASA's Aura as well as fire radiative power (FRP) from the measurements of MODIS on board NASA's Terra and Aqua satellites are used to derive fire emission rates (FERs) of NOx for different types of vegetation using a simple statistical approach. Monthly means of tropospheric NO2 vertical columns (TVC NO2) have been analyzed for their temporal correlation with the monthly means of FRP for five consecutive years from 2007 to 2011 on a horizontal 1° × 1° grid. The strongest correlation is found to be largely confined to tropical and subtropical regions, which account for more than 80% of yearly burned area, on average, globally. In these regions, the seasonal variation of fire intensity, expressed by the FRP data, is similar to the pattern of TVC NO2. As chemical models typically require values for the amount of NOx being released as a function of time, we have converted the retrieved TVC NO2 into production rates of NOx from fire (Pf) by assuming a constant lifetime of NOx. The comparison between Pf and NOx emissions from the Global Fire Emissions Database (GFEDv3.1) over 5 characteristic biomass burning regions in the tropics and subtropics shows good agreement. By separating the monthly means of Pf and FRP according to land cover type, FERs of NOx could be derived for different biomes. The estimated FERs for the dominating types of vegetation burned are lowest for open shrublands and savannas (0.28–1.03 g NOx s−1 MW−1) and highest for croplands and woody savannas (0.82–1.56 g NOx s−1 MW−1). This analysis demonstrates that the strong empirical relationship between TVC NO2 and FRP and the following simplified assumptions are a useful tool for the characterization of NOx emission rates from vegetation fires in the tropics and subtropics. Possible factors affecting the magnitude of the obtained values are discussed.

Assessing new remote sensing aerosol detection algorithms

Atmospheric aerosols affect the weather and climate by changing cloud formation and the energy balance and, depending on their type and concentration, can negatively affect air quality. Important atmospheric aerosols include dust, ash, volcanic sulfate aerosols, sea salt, biogenic particles, urban/industrial pollution, and smoke. For more than a decade, the twin Moderate Resolution Imaging Spectroradiometers (MODIS) aboard NASA's Aqua and Terra satellites have provided regular global assessments of aerosol loading, and now, following its 2011 launch, the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar‐orbiting Partnership (Suomi‐NPP) satellite is ready to contribute to that assessment.

Arctic Diurnal Land-Surface Temperature Range Changes Derived by NASA MODIS-Terra and -Aqua 2000 through 2012

The diurnal variation of surface temperature is a fundamental parameter as it is a driver of physical processes of atmosphere-land and -ocean energy and mass cycles playing a key role in meteorology and climatology. Our investigation focus is on the diurnal variation of land-surface temperature derived by the Moderate Resolution Imaging Spectroradiometer (MODIS) deployed on the NASA Terra and Aqua satellites. We key our investigation on the ascending and descending mode equator crossing times for daytime and nighttime land-surface temperature variations from March 2000 through 2010 (MODIS-Terra) and July 2002 through 2012 (MODIS-Aqua) and assess the diurnal land-surface temperature range changes at those sampling times. Our investigation shows non-stationary changes in the trends of land-surface temperature diurnal range. We identify changes in the diurnal range trends linked to increase of daytime and nighttime land-surface temperatures from March 2000 through 2010 and decrease in daytime and nighttime land-surface temperatures from July 2002 through 2012. The most recent decrease in daytime and nighttime land-surface temperatures and diurnal range will affect Arctic and other associated energy and mass cycles.

Long term (2003–2012) spatio-temporal MODIS (Terra/Aqua level 3) derived climatic variations of aerosol optical depth and cloud properties over a semi arid urban tropical region of Northern India

Aerosol optical depth (AOD) values at 550 nm derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA's Terra and Aqua satellites, for the 10 years period of 2003–2012 have been analyzed in the present study. The retrieved satellite data (Terra/Aqua) has been used to investigate the temporal heterogeneity in columnar aerosol characteristics over a semi arid urban tropical Delhi zone (28° 34′, 77° 07′, 233 m ASL) of Northern India with a resolution of 1° × 1° grid in magnitude. Aerosol optical depths have found to be increased >25% across Delhi region of India during the study period of 2003–2012. Yearly mean Terra/Aqua AOD values have shown an increasing trend at a rate of 0.005/0.009 per year respectively. However, seasonally winter means Terra/Aqua AOD values exhibit an increasing trend at a rate of ∼0.012/0.007 per year respectively. In order to provide a better understanding of aerosol–cloud interaction, a single paired one tailed distribution student's t-Test has been applied to the Terra AOD values and cloud parameters. The results extracted in the present study are compared with the earlier studies as well as with the AOD values over various other Indian regions.

An Analysis of the Short-Term Cloud Feedback Using MODIS Data

AbstractThe cloud feedback in response to short-term climate variations is estimated from cloud measurements combined with offline radiative transfer calculations. The cloud measurements are made by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra satellite and cover the period 2000–10. Low clouds provide a strong negative cloud feedback, mainly because of their impact in the shortwave (SW) portion of the spectrum. Midlevel clouds provide a positive net cloud feedback that is a combination of a positive SW feedback partially canceled by a negative feedback in the longwave (LW). High clouds have only a small impact on the net cloud feedback because of a close cancellation between large LW and SW cloud feedbacks. Segregating the clouds by optical depth, it is found that the net cloud feedback is set by a positive cloud feedback due to reductions in the thickest clouds (mainly in the SW) and a cancelling negative feedback from increases in clouds with moderate optical depths (also mainly in the SW). The global average SW, LW, and net cloud feedbacks are +0.30 ±1.10, −0.46 ±0.74, and −0.16 ±0.83 W m−2 K−1, respectively. The SW feedback is consistent with previous work; the MODIS LW feedback is lower than previous calculations and there are reasons to suspect it may be biased low. Finally, it is shown that the apparently small control that global mean surface temperature exerts on clouds, which leads to the large uncertainty in the short-term cloud feedback, arises from statistically significant but offsetting relationships between individual cloud types and global mean surface temperature.

Surface ozone photolysis rate trends in the Eastern Mediterranean: Modeling the effects of aerosols and total column ozone based on Terra MODIS data

The surface ozone photolysis rate (J(O1D)) was computed on a daily basis and on a 50 km × 50 km resolution for the 11-year period 2000–2010 at Finokalia meteorological station in Crete, Greece. A radiative transfer model was used, with climatological data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board NASA's Terra satellite. The area is representative of the Eastern Mediterranean, a region with high variability in aerosol loads and total column ozone. Instantaneous values of J(O1D) computed from the model were validated against corresponding station measurements available during the 5-year period 2002–2006. Monthly mean values of J(O1D) during the 11-year period examined, reveal a statistically significant decreasing trend, based on Terra MODIS data, which shows an overall 13% decrease. The aerosol effect on J(O1D) varies on a daily basis, depending on the aerosol load, and can exceed −10% during dust events, with a median value of −2.3% over the whole period examined. On a seasonal basis, the aerosol effect on J(O1D) follows the seasonal pattern of the aerosol load, with higher values in spring and autumn, due to the increased Saharan dust episodes during these seasons. Linear regression analysis on monthly mean values of total column ozone revealed a statistically significant increasing trend in both Finokalia and Thessaloniki stations. Total column ozone MODIS data were validated against spectroradiometric (columnar) measurements at Thessaloniki station. Sensitivity analysis on the effect of total column ozone on J(O1D) showed that a 10% variation in total ozone causes a corresponding 15–17% change in J(O1D). These results suggest that the decreasing trend in J(O1D) found in the case of Terra MODIS should be attributed mainly to the corresponding increasing trend in total column ozone.

Geospatial Techniques for the Assessment and Analysis of Flood Risk along the Niger-Benue Basin in Nigeria

River flooding has become a widely distributed and devastating natural disaster that has caused significant damages both economically and socially. Recently, it displaced millions of people in Nigeria and submerged several square kilometres of landed area in general and farmlands in particular. Although, the National Emergency Management Agency (NEMA) predicted the occurrence of the flood disaster and advised the relocation of residence from the floodplain to the high ground, but spatial information pertaining to the areal extent vulnerable to the hazard was not made available. This study attempted to assess the spatial impact of the October 2012 flooding of the Niger-Benue basin on the surrounding areas using the moderate resolution imaging Spectroradiometre (MODIS) data of NASA Terra satellite and developed a geospatial methodology for detecting and extracting the flood risk areas and the vulnerable population to flooding within the basin. The integration of remotely sensed data and other spatial and non-spatial data within the GIS platform was able to produce series of thematic maps which was used to generate a geospatial database for flood risk analysis and assessment. The result of the analysis effectively demonstrated the contribution of geospatial methods in mitigating and monitoring the effect of flooding along the Niger-Benue basin. It was therefore, suggested that government agencies and policy makers should adopt this powerful technique for reliable and well synthesized information which is a vital component of flood risk assessment and planning.

FraRI: an algorithm to account for the discontinuity at 60° N in MODIS temperature products

The Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra and Aqua satellites conducts continuous monitoring of the Earth's land surface and oceans. Recently, a sharp discontinuity (averaging 1.9°C) has been noticed at 60° N in both MODIS daytime and night-time land surface temperature (LST) products. This linear artefact arises because the CO2 high cloud test in the operational code for the generation of the MODIS cloud mask product is used only in the non-polar region (between 60° N and 60° S). The resulting discontinuity clearly has negative implications for any statistical applications of these temperature data. In this technical note we present a new algorithm, which minimizes this discontinuity. The method uses edge detection and elimination based on a mixture of Sobel and non-linear Laplacian filters (edge detection and quantification), cubic splines (edge modelling), and a controllable power function for image restoration. The implementation of this algorithm is demonstrated on an image of average minimum night-time LST between 2001 and 2008.

Aerosol optical depth increase in partly cloudy conditions

Remote sensing observations of aerosol from surface and satellite instruments are extensively used for atmospheric and climate research. From passive sensors, the apparent cloud‐free atmosphere in the vicinity of clouds often appears to be brighter than further away from the clouds, leading to an increase in the retrieved aerosol optical depth (τ). Mechanisms contributing to this enhancement or increase, including contamination by undetected clouds, hygroscopic growth of aerosol particles, and meteorological conditions, have been debated in recent literature, but the extent to which each of these factors influence the observed enhancement (Δτ) is poorly known. Here we used 11 years of daily global observations at 10 × 10 km2 resolution from the MODIS on the NASA Terra satellite to quantify τ as a function of cloud fraction (CF). Our analysis reveals that, averaged over the globe, the clear sky τ is enhanced by Δτ = 0.05 in cloudy conditions (CF = 0.8–0.9). This enhancement in Δτ corresponds to relative enhancement of 25% in cloudy conditions (CF = 0.8–0.9) compared with relatively clear conditions (CF = 0.1–0.2). Unlike the absolute enhancement Δτ, the relative increase in τis rather consistent in all seasons and is 25–35% in the subtropics and 15–25% at mid and higher latitudes. Using a simple Gaussian probability density function model to connect cloud cover and the distribution of relative humidity, we argue that much of the enhancement is consistent with aerosol hygroscopic growth in the humid environment surrounding clouds. Consideration of these cloud‐dependentτeffects will facilitate understanding aerosol‐cloud interactions and reduce the uncertainty in estimates of aerosol radiative forcing by global climate models.

VALIDATION STUDY ON ALOS PRISM DSM MOSAIC AND ASTER GDEM 2

Abstract. This study aims to evaluate height accuracy of two datasets obtained by spaceborne optical instruments of a digital elevation data for a large-scale area. The digital surface model (DSM) was generated by the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) onboard the Advanced Land Observing Satellite (ALOS, nicknamed 'Daichi'), and the global digital elevation model (DEM) version 2 (GDEM-2) was derived from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) onboard NASA's TERRA satellite. The test site of this study was the entire country of Bhutan, which is located on the southern slopes of the eastern Himalayas. Bhutan is not a large country, covering about 330 km from east to west, and 170 km from north to south; however, it has large height variation from 200 m to more than 7,000 m. This therefore makes it very interesting for validating digital topographic information in terms of national scale generation as well as wide height range. Regarding the reference data, field surveys were conducted in 2010 and 2011, and collected ground control points by a global positioning system were used for evaluating precise height accuracies in point scale as check points (CPs), with a 3 arc-sec DEM created by the Shuttle Radar Topography Mission (SRTM-3) used to validate the wide region. The results confirmed a root mean square error of 8.1 m for PRISM DSM and 29.4 m for GDEM-2 by CPs.

Satellite and surface-based remote sensing of Southeast Asian aerosols and their radiative effects

Using one year (December 2006–November 2007) of the Moderate Resolution Imaging SpectroRadiometer (MODIS), Multi-Angle Imaging SpectroRadiometer (MISR), and Clouds and the Earth's Radiant Energy System (CERES) data sets from NASA's Terra satellite, we assess the spatial and temporal distributions of aerosol properties (Aerosol Optical Depth, Fine Mode Fraction, and Single Scattering albedo) in the Southeast Asian region (SEA, 10°S–25°N, 90°E–150°E). We also provide a quantitative evaluation of regional cloud-free diurnally averaged shortwave aerosol radiative effects (SWARE) at the top of atmosphere (TOA) over both land and ocean. Our results indicate that the diurnally averaged shortwave radiative effects at the TOA over land and ocean are (−6.4±1.2Wm−2) and (−5.9±1.3Wm−2) with corresponding 550nm aerosol optical depths of 0.27±0.24 and 0.12±0.10. Fine aerosol particles (<0.6μm) dominate the continental areas during the whole study period, which represents large fractions of biomass burning aerosols and anthropogenic pollutant aerosols. Our results also indicate that the monthly averaged cloud cover fractions over this region are above 60%. Therefore, further sampling of aerosols underneath these cloud layers is needed in future field campaigns.

Effect of absorbing aerosols on snow albedo reduction in the Sierra Nevada

This paper investigates snow albedo changes in the Sierra Nevada Mountain area associated with potential deposition of absorbing aerosols in spring by using the snow albedo, aerosol optical depth, land surface temperature, and other relevant parameters available from the Moderate-Resolution Imaging Spectroradiometer (MODIS) onboard the NASA Terra satellite during 2000–2009. Satellite pixels with 100% snow cover have been selected to derive the monthly mean snow albedo value, along with aerosol optical depth, surface temperature, and days after snowfall in March and April to perform multiple regression analysis. We show that aerosol optical depth, which generally includes dust and black carbon over the Sierra Nevada as a result of the transpacific transport from East Asia and local sources, represents a significant parameter affecting snow albedo variation, second only to the land surface temperature change. The regression analysis illustrates that a one standard deviation increase in land surface temperature (2.2 K) and aerosol optical depth (0.044) can lead to decreases in snow albedo by 0.038 and 0.026, respectively. This study also shows that approximately 26% of snow albedo reduction from March to April over the Sierra Nevada is caused by an increase in aerosol optical depth, which has a profound impact on available water resources in California. However, the results show that there are no significant trends for snow albedo, surface temperature, and aerosol optical depth of snow-covered areas over the Sierra Nevada Mountain area in this 10-year period.

Interannual variation in the fine-mode MODIS aerosol optical depth and its relationship to the changes in sulfur dioxide emissions in China between 2000 and 2010

Abstract. Anthropogenic SO2 emissions increased alongside economic development in China at a rate of 12.7% yr−1 from 2000 to 2005. However, under new Chinese government policy, SO2 emissions declined by 3.9% yr−1 between 2005 and 2009. Between 2000 and 2010, we found that the variability in the fine-mode (submicron) aerosol optical depth (AOD) over the oceans adjacent to East Asia increased by 3–8% yr−1 to a peak around 2005–2006 and subsequently decreased by 2–7% yr−1, based on observations by the Moderate Resolution Imaging Spectroradiometer (MODIS) on board NASA's Terra satellite and simulations by a chemical transport model. This trend is consistent with ground-based observations of aerosol particles at a mountainous background observation site in central Japan. These fluctuations in SO2 emission intensity and fine-mode AOD are thought to reflect the widespread installation of fuel-gas desulfurization (FGD) devices in power plants in China, because aerosol sulfate is a major determinant of the fine-mode AOD in East Asia. Using a chemical transport model, we confirmed that the contribution of particulate sulfate to the fine-mode AOD is more than 70% of the annual mean and that the abovementioned fluctuation in fine-mode AOD is caused mainly by changes in SO2 emission rather than by other factors such as varying meteorological conditions in East Asia. A strong correlation was also found between satellite-retrieved SO2 vertical column density and bottom-up SO2 emissions, both of which were also consistent with observed fine-mode AOD trends. We propose a simplified approach for evaluating changes in SO2 emissions in China, combining the use of modeled sensitivity coefficients that describe the variation of fine-mode AOD with changes in SO2 emissions and satellite retrieval. Satellite measurements of fine-mode AOD above the Sea of Japan marked a 4.1% yr−1 decline between 2007 and 2010, which corresponded to the 9% yr−1 decline in SO2 emissions from China during the same period.

Predominant transport paths of Saharan dust over the Mediterranean Sea to Europe

We use monthly data of aerosol optical thickness (AOT) from the Moderate Resolution Imaging Spectroradiometer on board the seven NASA Terra and Aqua satellites for a 10 year period (2001–2010) in order to determine seasonal variations of Saharan dust transport over the Mediterranean toward Europe. The maxima of AOT are used to visualize the transport paths. Saharan dust reaches Europe over the Mediterranean and also by looping back over the Atlantic. In spring, aerosols are observed within a wide range of longitudes in Europe, with the highest AOT over western Europe. This may be partially explained by dust transport to western Europe via the Atlantic route, while to central and eastern Europe, dust is transported over the Mediterranean. During all seasons, dust is transported over the Mediterranean to Europe. In the summer months, aerosols are observed predominantly in central Europe. In autumn, aerosol activity is strongest in eastern Europe. We show that there are local AOT maxima over north Italy, in the Alps, in Spain, southeast of the Pyrenees and Sierra Nevada, and in the Rila Mountains in Bulgaria. We suggest that these maxima of aerosol concentration appear as the dust‐carrying airflow reaches the mountains and slows.

Aerosol shortwave direct radiative effect and forcing based on MODIS Level 2 data in the Eastern Mediterranean (Crete)

Abstract. The shortwave (SW) radiation budget was computed on a 10 km × 10 km resolution above FORTH-CRETE AERONET station in Crete, Greece, for the 11-year period from 2000 to 2010. The area is representative of the Eastern Mediterranean region, where air pollution and diminishing water resources are exacerbated by high aerosol loads and climate change. The present study aims to quantify the aerosol direct effect and forcing on the local surface and atmospheric energy budget. A radiative transfer model was used, with climatological data from the Moderate Resolution Imaging Spectroradiometer (MODIS), on board NASA's Terra and Aqua satellites. The instantaneous radiative fluxes were computed for satellite overpass times at the surface, within the atmosphere and at the top of atmosphere (TOA). Downward surface fluxes and aerosol input data were validated against ground measurements. Output fluxes reveal the direct radiative effects of dust events, with instantaneous values reaching up to −215, 139 and −46 Wm−2 at the surface (cooling), within the atmosphere (warming) and at TOA (cooling), respectively. Mean monthly values show a decreasing trend of the aerosol direct radiative effect, in agreement with a similar trend in AOT. The analysis of the contribution of anthropogenic and natural aerosol show major peaks of natural aerosol direct effect occurring mainly in spring, while a summer maximum is attributed to anthropogenic aerosol. During their peaks, anthropogenic aerosol forcing can reach values of −24 Wm−2 at the surface, 19 Wm−2 in the atmosphere and over −4 Wm−2 at TOA (monthly mean instantaneous values). The corresponding monthly peak values for natural aerosol are over −20 Wm−2, 12 Wm−2 and −9 Wm−2.