Spatiotemporal variability of meteorological droughts in southeastern USA

Droughts in the southeast USA have been linked to economic losses and intractable water conflicts. The region has witnessed several severe droughts events during the period from 1901 to 2005. In this study, spatiotemporal variability in meteorological drought characteristics in the southeast were analyzed using two different datasets by the means of standard precipitation index and standard precipitation evapotranspiration index for the period 1901–2005 for agricultural and non-agricultural seasons. The study periods were divided into three epochs 1901–1935, 1936–1970, and 1971–2005 and drought characteristics, in terms of severity, frequency, number, and trends were analyzed. Additionally, areal extent, drought severities and return periods associated with three severe drought years 1904, 1954, and 2000 were analyzed. Except for the state of Florida, results indicate decrease in drought severity during the recent epoch of 1970–2005 in the study domain. Trend analysis confirms that the study domain has become wetter over the last 105 years. Wetting trends were more prominent in the agricultural season. Additionally, droughts seem to have migrated from the western part of the study area encompassing the states of Alabama, Tennessee, Louisiana, and Mississippi to the Florida panhandle region during the recent epoch. Droughts exhibited higher spatiotemporal variability during the agricultural season compared to the non-agricultural seasons. Results also showed that early to mid-1950s experienced some of the most severe droughts in the study domain. Some of the drought events, such as the drought of 1954 and 2000, have been equivalent to a 100-year drought event in the southeast. The results from this study form the benchmark for studying the impacts of future climate change projections on meteorological droughts in the southeast.     

Uncertainty of soil erosion modelling using open source high resolution and aggregated DEMs

Digital Elevation Model (DEM) is one of the important parameters for soil erosion assessment. Notable uncertainties are observed in this study while using three high resolution open source DEMs. The Revised Universal Soil Loss Equation (RUSLE) model has been applied to analysis the assessment of soil erosion uncertainty using open source DEMs (SRTM, ASTER and CARTOSAT) and their increasing grid space (pixel size) from the actual. The study area is a part of the Narmada river basin in Madhya Pradesh state, which is located in the central part of India and the area covered 20,558 km². The actual resolution of DEMs is 30 m and their increasing grid spaces are taken as 90, 150, 210, 270 and 330 m for this study. Vertical accuracy of DEMs has been assessed using actual heights of the sample points that have been taken considering planimetric survey based map (toposheet). Elevations of DEMs are converted to the same vertical datum from WGS 84 to MSL (Mean Sea Level), before the accuracy assessment and modelling. Results indicate that the accuracy of the SRTM DEM with the RMSE of 13.31, 14.51, and 18.19 m in 30, 150 and 330 m resolution respectively, is better than the ASTER and the CARTOSAT DEMs. When the grid space of the DEMs increases, the accuracy of the elevation and calculated soil erosion decreases. This study presents a potential uncertainty introduced by open source high resolution DEMs in the accuracy of the soil erosion assessment models. The research provides an analysis of errors in selecting DEMs using the original and increased grid space for soil erosion modelling.     

Analysis and very short range forecast of cyclone “AILA” with radar data assimilation with rapid intermittent cycle using ARPS 3DVAR and cloud analysis techniques

In this study, both reflectivity and radial velocity are assimilated into the Weather Research and Forecasting (WRF) model using ARPS 3DVAR technique and cloud analysis procedure for analysis and very short range forecast of cyclone ÁILA. Doppler weather radar (DWR) data from Kolkata radar are assimilated for numerical simulation of landfalling tropical cyclone. Results show that the structure of cyclone AILA has significantly improved when radar data is assimilated. Radar reflectivity data assimilation has strong influence on hydrometeor structures of the initial vortex and precipitation pattern and relatively less influence is observed on the wind fields. Divergence/convergence conditions over cyclone inner-core area in the low-to-middle troposphere (600–900 hPa) are significantly improved when wind data are assimilated. However, less impact is observed on the moisture field. Analysed minimum sea level pressure (SLP) is improved significantly when both reflectivity and wind data assimilated simultaneously (RAD-ZVr experiment), using ARPS 3DVAR technique. In this experiment, the centre of cyclone is relocated very close to the observed position and the system maintains its intensity for longer duration. As compared to other experiments track errors are much reduced and predicted track is very much closer to the best track in RAD-ZVr experiment. Rainfall pattern and amount of rainfall are better captured in this experiment. The study also reveals that cyclone structure, intensification, direction of movement, speed and location of cyclone are significantly improved and different stages of system are best captured when both radar reflectivity and wind data are assimilated using ARPS 3DVAR technique and cloud analysis procedure. Thus optimal impact of radar data is realized in RAD-ZVr experiment. The impact of DWR data reduces after 12 h forecast and it is due to the dominance of the flow from large-scale global forecast system model. Successful coupling of data assimilation package ARPS 3DVAR with WRF model for Indian DWR data is also demonstrated.     

Numerical simulation by a stretched-coordinate Ocean General Circulation Model: A preliminary results

Summary ?A three-dimensional Ocean General Circulation Model has been developed in stretched coordinate from scratch. The same model has been used to perform some numerical experiments to simulate the basic circulation pattern and the model variability to atmospheric forcing. For numerical simulations 72 × 25 grid points in the horizontal directions and nine (10, 30, 75, 250, 500, 1000, 1500, 2000 and 3000 m) vertical levels are considered. The lateral boundaries are set at 60° N and 60° S. The basic focus of the paper is on the demonstration of the performance of the model and its assessment by employing appropriate forcing from the outputs of an atmospheric general circulation model. Hence, the model was forced with the forcing (wind and thermodynamic) derived from the ECMWF runs from the AMIP archives. The preliminary results show the realistic simulation of basic pattern of different fields. The model simulations show that the model is able to reproduce some of the general features of the ocean, such as surface currents, surface temperature and salinity, mass transport and meridional heat transport. It is also to be noted that the model is capable to capture the El-Ni?o and La-Ni?a type events. Received April 3, 2002; revised June 6, 2002; accepted July 24, 2002 Published online: February 20, 2003     

Assessment of PM<Subscript>2.5</Subscript> chemical compositions in Delhi: primary vs secondary emissions and contribution to light extinction coefficient and visibility degradation

Haze-fog conditions over northern India are associated with visibility degradation and severe attenuation of solar radiation by airborne particles with various chemical compositions. PM_2.5 samples have been collected in Delhi, India from December 2011 to November 2012 and analyzed for carbonaceous and inorganic species. PM₁₀ measurements were made simultaneously such that PM_10–2.5 could be estimated by difference. This study analyzes the temporal variation of PM_2.5 and carbonaceous particles (CP), focusing on identification of the primary and secondary aerosol emissions, estimations of light extinction coefficient (b_ext) and the contributions by the major PM_2.5 chemical components. The annual mean concentrations of PM_2.5, organic carbon (OC), elemental carbon (EC) and PM_10–2.5 were found to be 153.6 ± 59.8, 33.5 ± 15.9, 6.9 ± 3.9 and 91.1 ± 99.9 μg m^?3, respectively. Total CP, secondary organic aerosols and major anions (e.g., SO₄ ^2? and NO₃ ^?) maximize during the post-monsoon and winter due to fossil fuel combustion and biomass burning. PM_10–2.5 is more abundant during the pre-monsoon and post-monsoon. The OC/EC varies from 2.45 to 9.26 (mean of 5.18 ± 1.47), indicating the influence of multiple combustion sources. The b_ext exhibits highest values (910 ± 280 and 1221 ± 371 Mm^?1) in post-monsoon and winter and lowest in monsoon (363 ± 110 and 457 ± 133 Mm^?1) as estimated via the original and revised IMPROVE algorithms, respectively. Organic matter (OM =1.6 × OC) accounts for ~39 % and ~48 % of the b_ext, followed by (NH₄)₂SO₄ (~21 % and ~24 %) and EC (~13 % and ~10 %), according to the original and revised algorithms, respectively. The b_ext estimates via the two IMPROVE versions are highly correlated (R² = 0.95, root mean square error = 38 % and mean bias error = 28 %) and are strongly related to visibility impairment (r = ?0.72), mostly associated with anthropogenic rather than natural PM contributions. Therefore, reduction of CP and precursor gas emissions represents an urgent opportunity for air quality improvement across Delhi.     

Mixed layer heat budget of the El Niño in NCEP climate forecast system

The mechanisms controlling the El Niño have been studied by analyzing mixed layer heat budget of daily outputs from a free coupled simulation with the Climate Forecast System (CFS). The CFS is operational at National Centers for Environmental Prediction, and is used by Climate Prediction Center for seasonal-to-interannual prediction, particularly for the prediction of the El Niño and Southern Oscillation (ENSO) in the tropical Pacific. Our analysis shows that the development and decay of El Niño can be attributed to ocean advection in which all three components contribute. Temperature advection associated with anomalous zonal current and mean vertical upwelling contributes to the El Niño during its entire evolutionary cycle in accordance with many observational, theoretical, and modeling studies. The impact of anomalous vertical current is found to be comparable to that of mean upwelling. Temperature advection associated with mean (anomalous) meridional current in the CFS also contributes to the El Niño cycle due to strong meridional gradient of anomalous (mean) temperature. The surface heat flux, non-linearity of temperature advection, and eddies associated with tropical instabilities waves (TIW) have the tendency to damp the El Niño. Possible degradation in the analysis and closure of the heat budget based on the monthly mean (instead of daily) data is also quantified.     

Microstructures and compositional variation in the intravolcanic bole clays from the eastern Deccan volcanic province: Palaeoenvironmental implications and duration of volcanism

Clay minerals associated with intra-volcanic bole horizons of varied colours and thicknesses contain montmorillonite, halloysite and kaolinite, show distinct microstructures and microaggregates. In kaolinite, Fe³⁺ ions substitute for Al³⁺ at octahedral sites. Most of these clays are dioctahedral type, show balance between net layer and interlayer charges. The interstratified illite — smectite (I/S) mixed layers containing variable proportions of montmorillonite. Illite contains sheet-like, well oriented microaggregates. The parallel stacks of chlorite sheets show chlorite/smectite (C/S) mixed layers. Progressive enrichment of Fe and depletion of Al ions with the advancement of kaolinization process is observed. High order of structural and compositional maturity observed in these bole clays, indicate long hiatus between the two volcanic episodes.     

Clay Minerals in Soils as Evidence of Holocene Climatic Change, Central Indo-Gangetic Plains, North-Central India

Clay mineral assemblages of a soil chrono-association comprising five fluvial surface members (QGH1 to QGH5) of the Indo-Gangetic Plains between the Ramganga and Rapti rivers, north-central India, demonstrate that pedogenic interstratified smectite–kaolin (Sm/K) can be considered as a potential indicator for paleoclimatic changes during the Holocene from arid to humid climates. On the basis of available radiocarbon dates, thermoluminescence dates, and historical evidence, tentative ages assigned to QGH1 to QGH5 are <500 yr B.P., >500 yr B.P., >2500 yr B.P., 8000 TL yr B.P., and 13,500 TL yr B.P., respectively. During pedogenesis two major regional climatic cycles are recorded: relatively arid climates between 10,000–6500 yr B.P. and 3800–? yr B.P. were punctuated by a warm and humid climate. Biotite weathered to trioctahedral vermiculite and smectite in the soils during arid conditions, and smectite was unstable and transformed to Sm/K during the warm and humid climatic phase (7400–4150 cal yr B.P.). When the humid climate terminated, vermiculite, smectite, and Sm/K were preserved to the present day. The study suggests that during the development of soils in the Holocene in alluvium of the Indo-Gangetic Plains, climatic fluctuations appear to be more important than realized hitherto. The soils older than 2500 yr B.P. are relict paleosols, but they are polygenetic because of their subsequent alterations.