G.M. Ariful Islam

Bio: G.M. Ariful Islam is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Monsoon & Holocene. The author has an hindex of 3, co-authored 5 publications receiving 38 citations.

The Dust Deposition Process and Biogeochemical Impacts in the Northern South China Sea

Abstract: Modern dust plays essential roles in marine sediments, providing nutrient and crucial elements for primary productivity and aquatic ecosystems. However, present marine atmospheric dust observational evidence concerning the biogeochemical response to dust deposition process is spared for a long time. Here a total of 147 aerosols samples were collected near the northern South China Sea (SCS) coast between 13 February, 2016, and 12 February, 2017, have been investigated for the grain size distribution, depositional flux, ten-day back trajectories, clusters analysis, combining with primary productivity (Chlorophyll-a concentration) to indicate the present-day dust deposition process and biogeochemical impacts in the northern SCS on the first time. Our results illustrate the deposition flux and grain size distribution change in different season, grain size distribution in winter are coarser particles than that in the summer, while the maximum and minimum dry deposition flux are 12 December, 2016, (60.4 mg m−2 d−1) and 26 August, 2016, (5 mg m−2 d−1), respective. In addition, the back trajectories and three clusters analyze results indicating 53% of air masses originating locally near the coastal areas of China from the marine boundary layer (0–0.5 km) in the summer monsoon, while 48% dust from the northeast wind is prevailing during the winter monsoon over a relatively higher level (0–1.5 km). Furthermore, an apparent Chl-a blooming after aeolian dust input with a period of 1–2 days in the SCS. Therefore, atmospheric dust contains readily bioavailable iron and enhance the biogeochemical impact in the oligotrophic SCS.

Global Warming and the Weakening of the Tropical Circulation

Abstract: This study examines the response of the tropical atmospheric and oceanic circulation to increasing greenhouse gases using a coordinated set of twenty-first-century climate model experiments performed for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). The strength of the atmospheric overturning circulation decreases as the climate warms in all IPCC AR4 models, in a manner consistent with the thermodynamic scaling arguments of Held and Soden. The weakening occurs preferentially in the zonally asymmetric (i.e., Walker) rather than zonal-mean (i.e., Hadley) component of the tropical circulation and is shown to induce substantial changes to the thermal structure and circulation of the tropical oceans. Evidence suggests that the overall circulation weakens by decreasing the frequency of strong updrafts and increasing the frequency of weak updrafts, although the robustness of this behavior across all models cannot be confirmed because of the lack of data. As the cli...

Global dust model intercomparison in AeroCom phase I

Abstract: Abstract. This study presents the results of a broad intercomparison of a total of 15 global aerosol models within the AeroCom project. Each model is compared to observations related to desert dust aerosols, their direct radiative effect, and their impact on the biogeochemical cycle, i.e., aerosol optical depth (AOD) and dust deposition. Additional comparisons to Angstrom exponent (AE), coarse mode AOD and dust surface concentrations are included to extend the assessment of model performance and to identify common biases present in models. These data comprise a benchmark dataset that is proposed for model inspection and future dust model development. There are large differences among the global models that simulate the dust cycle and its impact on climate. In general, models simulate the climatology of vertically integrated parameters (AOD and AE) within a factor of two whereas the total deposition and surface concentration are reproduced within a factor of 10. In addition, smaller mean normalized bias and root mean square errors are obtained for the climatology of AOD and AE than for total deposition and surface concentration. Characteristics of the datasets used and their uncertainties may influence these differences. Large uncertainties still exist with respect to the deposition fluxes in the southern oceans. Further measurements and model studies are necessary to assess the general model performance to reproduce dust deposition in ocean regions sensible to iron contributions. Models overestimate the wet deposition in regions dominated by dry deposition. They generally simulate more realistic surface concentration at stations downwind of the main sources than at remote ones. Most models simulate the gradient in AOD and AE between the different dusty regions. However the seasonality and magnitude of both variables is better simulated at African stations than Middle East ones. The models simulate the offshore transport of West Africa throughout the year but they overestimate the AOD and they transport too fine particles. The models also reproduce the dust transport across the Atlantic in the summer in terms of both AOD and AE but not so well in winter-spring nor the southward displacement of the dust cloud that is responsible of the dust transport into South America. Based on the dependency of AOD on aerosol burden and size distribution we use model bias with respect to AOD and AE to infer the bias of the dust emissions in Africa and the Middle East. According to this analysis we suggest that a range of possible emissions for North Africa is 400 to 2200 Tg yr−1 and in the Middle East 26 to 526 Tg yr−1.

Assessment of land surface temperature and land cover variability during winter: A spatio-temporal analysis of Pabna municipality in Bangladesh

Abstract: Monitoring the change of land use and land cover (LULC) and land surface temperature (LST) at different spatio-temporal scales is vital for evaluating landscape dynamics and thermal environment. This study investigates the decadal change of LULC and winter LST on Pabna municipality over the period between 1990 and 2020 using Landsat images (TM, ETM+ and OLI). The study further explores LST distribution for different LULC classes and the explanatory power of various land surface indicators for change in LST. A supervised maximum likelihood classification (MLC) technique was used for LULC mapping of the study area. The results showed that built-up areas were increasing rapidly while water bodies, bare lands and vegetation decreased. The built-up area expanded by 358% between 1990 and 2020, with the occupied area rising from 1.44 km2 to 6.60 km2. To obtain reliable LST results, average values of LST obtained from multiple Landsat images for each year were used. The mean LST in the winter season has risen by 0.63 °C over the last 30 years. The variation in LST between separate days of the same year increased significantly, although the change in mean LST was small. Statistical analysis of land surface indicators revealed that NDVI, NDBI and NDBaI have significant explanatory power to describe LST scenarios. The explanatory power of NDBI and NDBaI to explain the rise of LST is increasing over time while the cooling capacity of NDVI is declining. LST had a moderate positive correlation with NDBI and NDBI and a weak negative correlation with NDVI.