ALBERT

Description: Owing to their extensive spatial coverage, stratocumulus clouds play a crucial role in the radiation budget of the earth. Climate models need an accurate characterisation of stratocumulus in order to provide an accurate forecast. However, remote sensing as well as in-situ observations reveal that on several occasions, cumulus clouds present below the stratocumulus, often have a significant impact on the main stratocumulus microphysical properties. This was observed during the ACE-2 (Aerosol Characterisation Experiment-2) campaign designed to study the impact of polluted continental air on stratocumulus formation. In this paper we used a detailed micro-physical chemical parcel model to quantify the extent of this cumulus-stratocumuls coupling. In addition, we made extensive use of microphysical observations from the C-130 aircraft that was operated during ACE-2. For the ACE-2 case studies considered in this paper, our analysis revealed that the chemical, microphysical and optical characteristics of the main stratocumulus cloud deck had significant contributions from cumulus clouds that often penetrated the stratocumulus deck. The amount of fine mode ionic species, the average droplet number concentrations, the effective radii and the optical depths during the flight A562 (when cumulus clouds interacted with the main stratocumulus) were estimated and model runs that included this effect yielded microphysical and optical properties which compared more favourably with the observations than the runs which did not. This study highlights the importance of including these cumulus effects in stratocumulus related modelling studies.

Description: Extreme events such as heat waves, cold spells, floods, droughts, tropical cyclones, and tornadoes have potentially devastating impacts on natural and engineered systems, and human communities, worldwide. Stakeholder decisions about critical infrastructures, natural resources, emergency preparedness and humanitarian aid typically need to be made at local to regional scales over seasonal to decadal planning horizons. However, credible climate change attribution and reliable projections at more localized and shorter time scales remain grand challenges. Long-standing gaps include inadequate understanding of processes such as cloud physics and ocean-land-atmosphere interactions, limitations of physics-based computer models, and the importance of intrinsic climate system variability at decadal horizons. Meanwhile, the growing size and complexity of climate data from model simulations and remote sensors increases opportunities to address these scientific gaps. This perspectives article explores the possibility that physically cognizant mining of massive climate data may lead to significant advances in generating credible predictive insights about climate extremes and in turn translating them to actionable metrics and information for adaptation and policy. Specifically, we propose that data mining techniques geared towards extremes can help tackle the grand challenges in the development of interpretable climate projections, predictability, and uncertainty assessments. To be successful, scalable methods will need to handle what has been called "Big Data" to tease out elusive but robust statistics of extremes and change from what is ultimately small data. Physically-based relationships (where available) and conceptual understanding (where appropriate) are needed to guide methods development and interpretation of results. Such approaches may be especially relevant in situations where computer models may not be able to fully encapsulate current process understanding, yet the wealth of data may offer additional insights. Large-scale interdisciplinary team efforts, involving domain experts and individual researchers who span disciplines, will be necessary to address the challenge.

Description: Electrostatic Solitary Waves (ESWs) have been observed by several spacecraft in the current layers of Earth's magnetosphere since 1982. ESWs are manifested as isolated pulses (one wave period) in the high time resolution waveform data obtained on these spacecraft. They are thus nonlinear structures generated out of nonlinear instabilities and processes. We report the first observations of ESWs associated with the onset of a super-substorm that occurred on 24 August 2005 while the Cluster spacecraft were located in the magnetotail at around 18–19 RE and moving northward from the plasma sheet to the lobes. These ESWs were detected in the waveform data of the WBD plasma wave receiver on three of the Cluster spacecraft. The majority of the ESWs were detected about 5 min after the super-substorm onset during which time 1) the PEACE electron instrument detected significant field-aligned electron fluxes from a few 100 eV to 3.5 keV, 2) the EDI instrument detected bursts of field-aligned electron currents, 3) the FGM instrument detected substantial magnetic fluctuations and the presence of Alfvén waves, 4) the STAFF experiment detected broadband electric and magnetic waves, ion cyclotron waves and whistler mode waves, and 5) CIS detected nearly comparable densities of H+ and O+ ions and a large tailward H+ velocity. We compare the characteristics of the ESWs observed during this event to those created in the laboratory at the University of California-Los Angeles Plasma Device (LAPD) with an electron beam. We find that the time durations of both space and LAPD ESWs are only slightly larger than the respective local electron plasma periods, indicating that electron, and not ion, dynamics are responsible for generation of the ESWs. We have discussed possible mechanisms for generating the ESWs in space, including the beam and kinetic Buneman type instabilities and the acoustic instabilities. Future studies will examine these mechanisms in more detail using the space measurements as inputs to models, and better relate the ESW space measurements to the laboratory through PIC code models.

Description: Extreme events such as heat waves, cold spells, floods, droughts, tropical cyclones, and tornadoes have potentially devastating impacts on natural and engineered systems and human communities worldwide. Stakeholder decisions about critical infrastructures, natural resources, emergency preparedness and humanitarian aid typically need to be made at local to regional scales over seasonal to decadal planning horizons. However, credible climate change attribution and reliable projections at more localized and shorter time scales remain grand challenges. Long-standing gaps include inadequate understanding of processes such as cloud physics and ocean–land–atmosphere interactions, limitations of physics-based computer models, and the importance of intrinsic climate system variability at decadal horizons. Meanwhile, the growing size and complexity of climate data from model simulations and remote sensors increases opportunities to address these scientific gaps. This perspectives article explores the possibility that physically cognizant mining of massive climate data may lead to significant advances in generating credible predictive insights about climate extremes and in turn translating them to actionable metrics and information for adaptation and policy. Specifically, we propose that data mining techniques geared towards extremes can help tackle the grand challenges in the development of interpretable climate projections, predictability, and uncertainty assessments. To be successful, scalable methods will need to handle what has been called "big data" to tease out elusive but robust statistics of extremes and change from what is ultimately small data. Physically based relationships (where available) and conceptual understanding (where appropriate) are needed to guide methods development and interpretation of results. Such approaches may be especially relevant in situations where computer models may not be able to fully encapsulate current process understanding, yet the wealth of data may offer additional insights. Large-scale interdisciplinary team efforts, involving domain experts and individual researchers who span disciplines, will be necessary to address the challenge.

Description: Recent high resolution measurements of POLAR and FAST satellites have revealed two-dimensional coherent structures in the polar cap boundary layer (PCBL) region. Since the ion temperature is often observed to be greater than the electron temperature in this region, electron acoustic waves can exist as a normal mode of the plasma system. It is shown that the nonlinear evolution of such waves can be modelled by the coupled Davey-Stewartson I equations. These equations, which are a generalization of the nonlinear Schrödinger equation to two dimensions, admit exponentially localized solutions called dromions. A detailed parametric characterization of the regions of existence of such solutions is presented in the context of the PCBL region.

Description: The presence of dynamic, large amplitude solitary waves in the auroral regions of space is well known. Since their velocities are of the order of the ion acoustic speed, they may well be considered as being generated from the nonlinear evolution of ion acoustic waves. However, they do not show the expected width-amplitude correlation for K-dV solitons. Recent POLAR observations have actually revealed that the low altitude rarefactive ion acoustic solitary waves are associated with an increase in the width with increasing amplitude. This indicates that a weakly nonlinear theory is not appropriate to describe the solitary structures in the auroral regions. In the present work, a fully nonlinear analysis based on Sagdeev pseudopotential technique has been adopted for both parallel and oblique propagation of rarefactive solitary waves in a two electron temperature multi-ion plasma. The large amplitude solutions have consistently shown an increase in the width with increasing amplitude. The width-amplitude variation profile of obliquely propagating rarefactive solitary waves in a magnetized plasma have been compared with the recent POLAR observations. The width-amplitude variation pattern is found to fit well with the analytical results. It indicates that a fully nonlinear theory of ion acoustic solitary waves may well explain the observed anomalous width variations of large amplitude structures in the auroral region.

Description: A first ever study on the characterization of volatile organic compounds (VOCs) has been made over a Himalayan high altitude station in India. A total of 18 VOCs (mono aromatics-BTEX (benzene, toluene, ethylbenzene, xylene), non-BTEX substituted aromatics and halocarbon) have been measured over Darjeeling (27.01° N, 88.15° E, 2200 m a.s.l.) in the eastern Himalaya in India during the period of July 2011–June 2012. The annual average concentration of the sum of 18 target VOCs (TVOC) was 376.3 ± 857.2 μg m−3. Monoaromatics had the highest contribution (72%) followed by other substituted aromatics (22%) and halocarbon (6%) compounds. Toluene was the most abundant VOC in the atmosphere of Darjeeling with the contribution of ~37% to TVOC followed by benzene (~21%), ethylbenzene (~9%) and xylenes (~6%). TVOC concentrations were highest during the postmonsoon season with minimum solar radiation and lowest during the premonsoon season with maximum solar radiation. Anthropogenic activities related mainly to tourists like diesel and gasoline emissions, biomass and coal burning, use of solvent and solid waste emissions were almost equal in both the seasons. Seasonal variation in TVOCs over Darjeeling was mainly governed by the incoming solar radiation rather than the emission sources. Source apportionment study using Positive Matrix Factorization (PMF) model indicated that major fraction of (~60%) TVOC were contributed by diesel and gasoline exhausts followed by solvent evaporation (18%) and other sources. Diesel exhaust was also found to have the maximum potential in tropospheric ozone formation. The atmospheric loading of BTEX over Darjeeling was found to be comparable with several Indian metro cities and much higher than other cities around the world.

Description: Owing to their extensive spatial coverage, stratocumulus clouds play a crucial role in the radiation budget of the earth. Climate models need an accurate characterisation of stratocumulus in order to provide an accurate forecast. However, remote sensing as well as in-situ observations reveal that on several occasions, cumulus clouds present below the stratocumulus, often have a significant impact on the main stratocumulus microphysical properties. This was observed during the ACE-2 (Aerosol Characterisation Experiment 2) campaign designed to study the impact of polluted continental air on stratocumulus formation. In this paper we used a detailed micro-physical chemical parcel model to quantify the extent of this cumulus-stratocumuls coupling. In addition, we made extensive use of microphysical observations from the C-130 aircraft that was operated during ACE-2. For the ACE-2 case studies considered in this paper, our analysis revealed that the chemical, microphysical and optical characteristics of the main stratocumulus cloud deck had significant contributions from cumulus clouds that often penetrated the stratocumulus deck. The amount of fine mode ionic species, the average droplet number concentrations, the effective radii and the optical depths during the flight A562 (when cumulus clouds interacted with the main stratocumulus) were estimated and model runs that included this effect yielded microphysical and optical properties which compared more favourably with the observations than the runs which did not. This study highlights the importance of including these cumulus effects in stratocumulus related modelling studies.

Description: Concentrations of ambient NH3, NO, NO2 and SO2 were measured over Bay of Bengal (BoB) during 28 December 2008 to 25 January 2009 to study their diurnal variation and relationship of NH3 with other trace gases over BoB. The measurements were done under the winter phase of Integrated Campaign on Aerosols and Radiation Budget (W_ICARB). For the first time, ambient NH3 was monitored precisely over BoB based on chemiluminescence method, having estimation efficiency more precise than the chemical trap method. The average concentration of ambient NH3, NO, NO2 and SO2 were recorded as 4.78 ± 1.68, 1.89 ± 1.26, 0.31 ± 0.14 and 0.80 ± 0.30 μg m−3, respectively, over BoB. The prominent latitudinal and longitudinal variations of the trace gases were observed over BoB, whereas NH3 and NO showed the non-significant diurnal variation. Results reveal that the concentration of ambient NH3 negatively correlated with ambient NO2 (r2 = −0.56), SO2 (r2 = −0.58) and ambient temperature (r2 = −0.27) during the study.

Description: The Neyveli Lignite Corporation (NLC) is among the largest lignite based power plants in South East Asia. The four elevated stacks from this power plant emanate a substantial amount of sulphur dioxide into a tropical boundary layer. Sulphur dioxide being a soluble pollutant gas is absorbed by falling raindrops. This is a first study that quantifies the scavenging action of the North Eastern monsoonal rains from a lignite based power plant. We find that although the North Eastern monsoonal rains have a preponderance of very large droplets, the contribution of the small droplets cannot be neglected. We expect that the estimated scavenging coefficients can be used by large eddy and climate models.