Dynamical constraints on the Local Group from the CMB and 2MRS dipoles

We place constraints on the dynamics of the Local Group (LG) by comparing the dipole of the cosmic microwave background (CMB) with the peculiar velocity induced by the Two Micron All-Sky Redshift Survey galaxy sample. The analysis is limited by the lack of surveyed galaxies behind the zone of avoidance (ZoA). We therefore allow for a component of the LG velocity due to unknown mass concentrations behind the ZoA, as well as for an unknown transverse velocity of the Milky Way relative to the Andromeda galaxy. We infer extra motion along the direction of the Galactic Centre (where Galactic confusion and dust obscuration peaks) at the 95 per cent significance level. With a future survey of the ZoA it might be possible to constrain the transverse velocity of the Milky Way relative to Andromeda.     

Methane and nitrous oxide fluxes in the polluted Adyar River and estuary, SE India

We measured dissolved N(2)O, CH(4), O(2), NH(4)(+), NO(3)(-) and NO(2)(-) on 7 transects along the polluted Adyar River-estuary, SE India and estimated N(2)O and CH(4) emissions using a gas exchange relation and a floating chamber. High NO(2)(-) implied some nitrification of a large anthropogenic NH(4)(+) pool. In the lower catchment CH(4) was maximal (6.3+/-4.3 x 10(4)nM), exceeding the ebullition threshold, whereas strong undersaturation of N(2)O and O(2) implied intense denitrification. Emissions fluxes for the whole Adyar system approximately 2.5 x 10(8) g CH(4)yr(-1) and approximately 2.4 x 10(6)gN(2)O yr(-1) estimated with a gas exchange relation and approximately 2 x 10(9) g CH(4)yr(-1) derived with a floating chamber illustrate the importance of CH(4) ebullition. An equivalent CO(2) flux approximately 1-10 x 10(10)gy r(-1) derived using global warming potentials is equivalent to total Chennai motor vehicle CO(2) emissions in one month. Studies such as this may inform more effective waste management and future compliance with international emissions agreements.     

Evaluation of hydrologic impact of an irrigation curtailment program using Landsat satellite data

Upper Klamath Lake (UKL) is the source of the Klamath River that flows through southern Oregon and northern California. The UKL Basin provides water for 81,000+ ha (200,000+ acres) of irrigation on the U.S. Bureau of Reclamation Klamath Project located downstream of the UKL Basin. Irrigated agriculture also occurs along the tributaries to UKL. During 2013–2016, water rights calls resulted in various levels of curtailment of irrigation diversions from the tributaries to UKL. However, information on the extent of curtailment, how much irrigation water was saved, and its impact on the UKL is unknown. In this study, we combined Landsat-based actual evapotranspiration (ETa) data obtained from the Operational Simplified Surface Energy Balance model with gridded precipitation and U.S. Geological Survey station discharge data to evaluate the hydrologic impact of the curtailment program. Analysis was performed for 2004, 2006, 2008–2010 (base years), and 2013–2016 (target years) over irrigated areas above UKL. Our results indicate that the savings from the curtailment program over the June to September time period were highest during 2013 and declined in each of the following years. The total on-field water savings was approximately 60 hm³ in 2013 and 2014, 44 hm³ in 2015, and 32 hm³ in 2016 (1 hm3 = 10,000 m³ or 810.7 ac-ft). The instream water flow changes or extra water available were 92, 68, 45, and 26 hm³, respectively, for 2013, 2014, 2015, and 2016. Highest water savings came from pasture and wetlands. Alfalfa showed the most decline in water use among grain crops. The resulting extra water available from the curtailment contributed to a maximum of 19% of the lake inflows and 50% of the lake volume. The Landsat-based ETa and other remote sensing datasets used in this study can be used to monitor crop water use at the irrigation district scale and to quantify water savings as a result of land-water management changes.     

Tree Crown Detection,Delineation and Counting in UAV Remote Sensed Images: A Neural Network Based Spectral–Spatial Method

UAVs are fast emerging as a remote sensing platform to complement satellite based remote sensing. Agriculture and ecology is one of the important applications of UAV remote sensing, also known as low altitude remote sensing (LARS). This work demonstrates the use and potential of LARS in agriculture, particularly small holder open field agriculture. Two UAVs are used for remote sensing. The first UAV is a fixed wing aircraft with a high spatial resolution visible spectrum also known as RGB camera as a payload. The second UAV is a quadrotor UAV with an RGB camera interfaced to an on-board single board computer as the payload. LARS was carried out to acquire aerial high spatial resolution RGB images of different farms. Spectral–spatial classification of high spatial resolution RGB images for detection, delineation and counting of tree crowns in the image is presented. Supervised classification is carried out using extreme learning machine (ELM), a single hidden layer feed forward network neural network classifier. ELM was modelled for RGB values as input feature vectors and binary (tree and non-tree pixels) output class. Due to similarities in spectral intensities, some of the non-tree pixels were classified as tree pixels and in order to remove them, spatial classification was performed on the image. Spatial classification was carried out using thresholded geometrical property filtering techniques. Threshold values chosen for carrying out spatial classification were analysed to obtain optimal values. Finally in the delineation and counting, the connected tree crowns were segmented using Watershed algorithm performed on the image after marking individual tree crowns using Distance Transform method. Five representative UAV images captured at different altitudes with different crowns of banana plant, mango trees and coconut trees were used to demonstrate the performance of the proposed method. The performance was compared with the traditional KMeans spectral–spatial method of clustering. Results and comparison of performance parameters of KMeans spectral–spatial and ELM spectral–spatial classification methods are presented. Results indicate that ELM performed better than KMeans.     

Benthic coverage and bottom topography of coral reef environment over Pirotan reef,Gulf of Kachchh region,India

Remote sensing measurements in coral reef environments commonly confront the problem of overlying atmosphere and modification of spectral signal due to water column over the bottom substrates. In order to correct these problems, hyperspectral observations offer an advantage over multispectral observations. Airborne hyperspectral remote sensing data from Airborne Visible Infrared Imaging Spectrometer- Next Generation (AVIRIS-NG) sensor was acquired during low tidal condition on 14 February 2016 at Pirotan reef, Gulf of Kachchh region, India. The objective of this study is to map benthic coverage and bottom topography over Pirotan reef. The methodology involved atmospheric correction, simultaneous retrieval of water parameters, bathymetry, water column correction and mapping. Atmospheric correction was performed by removing path radiance and aerosol contribution and dividing by atmospheric transmittance and incoming solar irradiance to obtain remote sensing reflectance. Model derived error minimization technique was used for simultaneous retrieval of water parameters and bathymetry. Derived water parameters were used to account for water column attenuation and retrieve concomitant true bottom signature.     

A class of hidden Markov models for regional average rainfall

Abstract

Basic hidden Markov models are very useful in stochastic environmental research but their ability to accommodate sufficient dependence between observations is somewhat limited. However, they can be modified in several ways to form a rich class of flexible models that are useful in many environmental applications. We consider a class of hidden Markov models that incorporate additional dependence among observations to model average regional rainfall time series. The focus of the study is on models that introduce additional dependence between the state level and the observation level of the process and also on models that incorporate dependence at observation level. Construction of the likelihood function of the models is described along with the usual second-order properties of the process. The maximum likelihood method is used to estimate the parameters of the models. Application of the proposed class of models is illustrated in an analysis of daily regional average rainfall time series from southeast and southwest England for the winter season during 1931 to 2010. Models incorporating additional dependence between the state level and the observation level of the process captured the distributional properties of the daily rainfall well, while the models that incorporate dependence at the observation level showed their ability to reproduce the autocorrelation structure. Changes in some of the regional rainfall properties during the time period are also studied.

Editor D. Koutsoyiannis     

Barotropic instability of weakly non-parallel zonal flows

Abstract

Barotropic instability of weakly non-parallel zonal flows with localized intense shear regions is investigated numerically. The numerical integrations of the linear stability problem reveal the existence of unstable localized wave packets whose spatial structure and eigenfrequencies depend on two parameters which measure the degree of supercriticality and the zonal length-scale of the shear region. The results indicate that the structure of the instability is determined by conditions that ensure the decay of the wave packet at infinity and the transition from long to short waves across a turning point (critical layer) region which is controlled by non-parallel effects. The controlling influence exerted by the weak non-parallel effects on the evolution of the instability underlines the weakness of the parallel flow assumption which can be used locally, away from critical layers, as a diagnostic tool only.     

Experimental investigation of runoff reduction and sediment removal by vegetated filter strips

The impact of vegetated filter strips (VFS) on sediment removal from runoff has been studied extensively in recent years. Vegetation is believed to increase water infiltration and decrease water turbulence thus enhancing sediment deposition within filter media. In the study reported here, field experiments have been conducted to examine the efficiency of vegetated filter strips for sediment removal from cropland runoff. Twenty filters with varying length, slope and vegetated cover were used under simulated runoff conditions with an average sediment concentration of 2700 mg/L. The filters were 2, 5, 10 and 15 m long with a slope of 2·3 and 5% and three types of vegetation. Three other strips with bare soil were used as a control. The experimental results showed that the average sediment trapping efficiency of all filters was 84% and ranging from 68% in a 2‐m filter to as high as 98% in a 15‐m long filter compared with only 25% for the control. The length of filter has been found to be the predominant factor affecting sediment deposition in VFS up to 10 m. Increasing filter length to 15 m did not improve sediment trapping efficiency under the present experimental conditions. The rate of incoming flow and vegetation cover percentage has a secondary effect on sediment deposition in VFS. Copyright © 2004 John Wiley & Sons, Ltd.     

Indian Summer Monsoon Rainfall Characteristics During Contrasting Monsoon Years

The present paper presents a diagnostic study of two recent monsoon years, of which one is dry monsoon year (2009) and the other is wet monsoon year (2010). The study utilized the IMD gridded rainfall data set in addition to the Reynolds SST, NCEP-NCAR reanalysis wind and temperature products, and NOAA OLR. The study revealed that the months July and August are the most crucial months to decide whether the ISMR is wet or dry. However, during July 2009, most of the Indian subcontinent received more than 60 % in the central and western coastal regions. In a wet monsoon year, about 35–45 % of rainfall is contributed during June and July in most parts of India. During these years, the influence of features in the Pacific Ocean played vital role on the Indian summer monsoon rainfall. During 2009, Pacific SST was above normal in nino regions, characteristic of the El Nino structure; however, during 2010, the nino regions were clearly below normal temperature, indicating the La Nina pattern. The associated atmospheric general circulation through equatorial Walker and regional Hadley circulation modulates the tropospheric temperature, and hence the organized convective cloud bands. These cloud bands show different characteristics in northward propagation during dry and wet years of ISMR. During a dry year, the propagation speed and magnitudes are considerably higher than during a wet monsoon year.     

A Study on the Performance of the NCMRWF Analysis and Forecasting System During Asian Summer Monsoon: Thermodynamic Aspects

—The thermodynamic characteristics of the Asian summer monsoon are examined with a global analysis-forecast system. In this study, we investigated the large-scale balances of heat and moisture by making use of operational analyses as well as forecast fields for June, July and August (JJA), 1994. Apart from elucidating systematic errors in the temperature and moisture fields, the study expounds the influence of these errors on the large-scale budgets of heat and moisture over the monsoon region. The temperature forecasts of the model delineate predominant cooling in the middle and lower tropospheres over the monsoon region. Similarly, the moisture forecasts evince a drying tendency in the lower troposphere. However, certain sectors of moderate moistening exist over the peninsular India and adjoining oceanic sectors of the Arabian Sea and Bay of Bengal.¶The broad features of the large-scale heat and moisture budgets represented by the analysis/forecast fields indicate good agreement with the observed aspects of the summer monsoon circulation. The model forecasts fail to retain the analyzed atmospheric variability in terms of the mean circulation, which is indicated by underestimation of various terms of heat and moisture budgets with an increase in the forecast period. Further, the forecasts depict an anomalous diabatic cooling layer in the lower middle troposphere of the monsoon region which inhibits vertical transfer of heat and moisture from the mixed layer of the atmospheric boundary layer to the middle troposphere. In effect, the monsoon circulation is considerably weakened with an increase in the forecast period. The treatment of shallow convection and the use of interactive clouds in the model can reduce the cooling bias considerably.