A Comparison Study of EDR Estimates from the NLR and NCAR Algorithms

A comparison was made of two eddy dissipation rate (EDR) estimates based on flight data recorded by commercial flights. The EDR estimates from real-time data using the National Center for Atmospheric Research (NCAR) Algorithm were compared with the EDR estimates derived using the Netherlands Aerospace Centre (NLR) Algorithm using quick assess recorder (QAR) data. The estimates were found to be in good agreement in general, although subtle differences were found. The agreement between the two algorithms was better when the flight was above 10,000 ft. The EDR estimates from the two algorithms were also compared with the vertical acceleration experienced by the aircraft. Both EDR estimates showed good correlation with the vertical acceleration and would effectively capture the turbulence subjectively experienced by pilots.

Updated national emission inventory and comparison with the Emissions Database for Global Atmospheric Research (EDGAR): case of Lebanon

Physically based computational modeling is an effective tool for estimating and predicting the spatial distribution of pollutant concentrations in complex environments. A detailed and up-to-date emission inventory is one of the most important components of atmospheric modeling and a prerequisite for achieving high model performance. Lebanon lacks an accurate inventory of anthropogenic emission fluxes. In the absence of a clear emission standard and standardized activity datasets in Lebanon, this work serves to fill this gap by presenting the first national effort to develop a national emission inventory by exhaustively quantifying detailed multisector, multi-species pollutant emissions in Lebanon for atmospheric pollutants that are internationally monitored and regulated as relevant to air quality. Following the classification of the Emissions Database for Global Atmospheric Research (EDGAR), we present the methodology followed for each subsector based on its characteristics and types of fuels consumed. The estimated emissions encompass gaseous species (CO, NOx, SO2), and particulate matter (PM2.5 and PM10). We compare totals per sector obtained from the newly developed national inventory with the international EDGAR inventory and previously published emission inventories for the country for base year 2010 presenting current discrepancies and analyzing their causes. The observed discrepancies highlight the fact that emission inventories, especially for data-scarce settings, are highly sensitive to the activity data and their underlying assumptions, and to the methodology used to estimate the emissions.

The Leipzig Aerosol and Cloud Remote Observations System LACROS – a mobile infrastructure for aerosol-cloud-interaction observations at hot spots of atmospheric research

<p>The large number of unsolved questions concerning the interaction between aerosol particles and clouds and corresponding indirect effects on precipitation and radiative transfer demand new measurement strategies and systems to resolve the atmospheric processes involved. Obtaining synergistic information about cloud and aerosol properties from multi–instrument and hence multi–sensor observations is a key approach to overcome the current lack of knowledge. Motivated by these needs, the mobile multi–instrument platform Leipzig Aerosol and Cloud Remote Observations System LACROS was set-up in 2011 by Leibniz Institute for Tropospheric Research (TROPOS). LACROS nowadays is the central component of a sophisticated framework of synergistic state-of-the-art measurement techniques and methodologies, embedded into an environment of comprehensive data management.</p> <p>The current setup of LACROS comprises a set of state-of-the-art remote-sensing instruments such as a 35-GHz scanning polarimetric cloud radar, multi-wavelength polarization Raman lidars, Doppler lidar, micro rain radar, microwave radiometer, laser disdrometer, as well as sensors for direct and diffuse downwelling solar and terrestrial radiation. All instruments are installed within customized sea-freight containers. This ensures a highest-possible mobility of the whole set of instruments. LACROS is a central mobile exploratory platform of the European Union Aerosol, Clouds, and Trace Gases Research Infrastructure (ACTRIS, http://www.actris.net). A variety of ways for physical, remote, and virtual access to the LACROS capabilities are provided via the European Union project ATMO-ACCESS (https://www.atmo-access.eu).</p> <p>LACROS measurements focus on three main tasks: (1) Investigation of mixed-phase cloud processes by exploiting co‐located remote-sensing observations of microphysical properties and radiative effects of aerosols and clouds and their interactions. (2) Instrument validation and development of algorithms and new measurement techniques for cloud and aerosol microphysics retrievals such as, i.e., dual‐field‐of‐view lidar to derive cloud droplet size information, or retrievals of aerosol microphysical properties from combined lidar and Sun photometer measurements. (3) Field deployments in key regions of atmospheric research, where the processes under investigation are already naturally constrained and observations can ideally be combined with in-situ observations or model simulations.</p> <p> </p> <p>This contribution will present the current setup of LACROS and its recent deployments in Leipzig, the Netherlands, Cyprus and southern Chile, results of aerosol-cloud-interaction studies by means of both, case studies and multi-site long-term statistics, as well as an overview on the current and future involvement of LACROS in cal/val activities of new methods and satellite missions. </p>

Numerical study of western disturbances over western Himalayas using mesoscale model

Hkkjrh; {ks= esa ’khr _rq ds nkSjku if’peh fo{kksHkksa ¼MCY;w-Mh-½ dh egRoiw.kZ fo’ks"krkvksa dks izfr:fir djus ds fy, isu LVsV ;wfuoflZVh&us’kuy lsUVj Qksj ,V~eksLQsfjd fjlpZ ¼ih-,l-;w-&,u-lh-,-vkj-½ la;qDr jkT; vejhdk ds xSj ty LFkSfrd :ikUrj ds rkSj ij eslksLdsy ekWMy ¼,e- ,e- 5½ dk mi;ksx fd;k x;k gSA bl v/;;u esa nks xzgh; ifjlhek Lrj i)fr;ksa uker%&CySdknj ,oa gkSax&iSu rFkk pkj laogu izkpyhdj.k i)fr;ksa uker% dqvks] xzsy] dSufÝz’k ,oa csV~l&feYyj ds 60 fd- eh- ds {kSfrt foHksnu ekWMy dk mi;ksx djds vkB lqxzkfgrk iz;ksx fd, x, gaSA blesa {kSfrt foHksnu ekWMy rFkk LFkykÑfr ds egRo ds nks dkjdksa&30 fd-eh-] 60 fd-eh- ,oa 90 fd- eh- ds {kSfrt foHksnu ekWMy ftlesa ,d fLFkfr esa LFkykÑfr ij fopkj ugha fd;k x;k gS rFkk nwljh esa lkekU; LFkykÑfr ij fopkj fd;k x;k gS] ds vk/kkj ij N% iz;ksx djds v/;;u fd;k x;k gSA bl v/;;u ds fy, nks lfØ; if’peh fo{kksHkksa dk p;u fd;k x;k gS ftlds dkj.k if’peh fgeky; {ks= esa Hkkjh o`f"V gqbZA izFke v/;;u ds fy, 18 tuojh ls 21 tuojh] 1997 rd dh vof/k ds nkSjku ds if’peh fo{kksHk dk p;u fd;k x;k gS rFkk nwljs iz;ksx ds fy, 20 tuojh ls 25 tuojh] 1999 dh vof/k ds nkSjku ds if’peh fo{kksHk dk p;u fd;k x;k gSA blesa vkjafHkd rFkk lhekar fLFkfr;ksa ds fy, us’kuy lsUVj QkWj bu~okbjWuesUV fizMhD’ku&us’kuy lsUVj QkWj ,V~eksLQsfjd fjlpZ ¼,u- lh- b- ih-&,u- lh- , - vkj-½ la;qDr jkT; vejhdk }kjk iqufoZ’ysf"kr vkaadM+ksa dk mi;ksx fd;k x;k gSA bl v/;;u ls ;g irk pyk gS fd gkSax&iSu vkSj csV~l feYyj dh Øe’k% xzgh; ifjlhek Lrj rFkk es?k laogu izkpyhdj.k i)fr ds la;kstu dk izn’kZu mi;ksx dh xbZ vU; la;kstu i)fr;ksa ds rqyuk esa lcls vPNk jgk gSA vkn’kZ HkkSfrdh ¼ekWMy fQftDl½ vU; la;kstu i)fr;ksa dh rqyuk esa bl la;kstu ds }kjk leqnz ry dk nkc T;knk lgh izfr:fir djus esa l{ke jgh gSA blds vykok LFkykÑfr jfgr {ks= esa if’peh fo{kksHk dk izfr:i.k lkekU; LFkykÑfr esa izfr:fIkr if’peh fo{kksHk dh rqyuk esa de o"kkZ dh ek=k dks n’kkZrk gSA tc blesa lkekU; LFkykÑfr dks ’kkfey fd;k x;k rks fgeky; {ks= ds vkl&ikl Hkkjh o"kkZ gqbZA o"kkZ ds {ks=ksa ds ,dhÑr ekWMy lR;kfir fo’ys"k.k ds vuq:Ik ik, x, gaSA o"kkZ {ks=ksa ds lqxzkfgrk v/;;u ls irk pyk gS fd NksVs izHkko& {ks= ¼30 fd-eh-½ ds izfr:fir ekWMy vPNs ifj.kke nsrs gSaA ” A non-hydrostatic version of the Penn State University - National Center for Atmospheric Research (PSU-NCAR), US, Mesoscale Model (MM5) is used to simulate the characteristic features of the Western Disturbances (WDs) occurred over the Indian region during winter. In the present study sensitivity eight experiments are carried out by using two planetary boundary layer schemes, viz., Blackadar and Hong-Pan, and four convection parameterization schemes, viz., Kuo, Grell, Kain-Fristch and Betts-Miller, with 60 km horizontal model resolution. And also the role of horizontal model resolution and topography is studied by carrying out six experiments based on two factors: horizontal model resolution of 30 km, 60 km and 90 km with assumed no topography and normal topography. For this study two active WDs are chosen which yielded extensive precipitation over western Himalayas. WD from 18 to 21 January 1997 is chosen for study one and WD from 20 to 25 January 1999 is chosen for experiment two. National Center for Environmental Prediction – National Center for Atmospheric Research (NCEP-NCAR), US, reanalyzed data is used for initial and boundary conditions. It is found that the performance of combination of the Hong-Pan and Betts-Miller as planetary boundary layer and cloud convection parameterization schemes respectively is best compared to the other combinations of schemes used in this study. The model physics could able to simulate sea level pressure better with this combination as compared to the combinations with other schemes. Further, WD simulations with assumed no topography shows lesser amount of precipitation compared to WD simulations with normal topography. When normal topography is included, intense localized of precipitation was observed along the Himalayan range. Model integrations of precipitation fields are found close to the corresponding verification analysis. Sensitivity studies of precipitation field shows that finer domain (30 km) of the model simulation gives better results.

Clustering and Classification in Fisheries

<p>This goal of this research is to investigate associations between presences of fish species, space, and time in a selected set of areas in New Zealand waters. In particular we use fish abundance indices on the Chatham Rise from scientific surveys in 2002, 2011, 2012, and 2013. The data are collected in annual bottom trawl surveys carried out by the National Institute of Water and Atmospheric Research (NIWA). This research applies clustering via finite mixture models that gives a likelihood-based foundation for the analysis. We use the methods developed by Pledger and Arnold (2014) to cluster species into common groups, conditional on the measured covariates (body size, depth, and water temperature). The project for the first time applies these methods incorporating covariates, and we use simple binary presence/absence data rather than abundances. The models are fitted using the Expectation-Maximization (EM) algorithm. The performance of the models is evaluated by a simulation study. We discuss the advantages and the disadvantages of the EM algorithm. We then introduce a newly developed function clustglm (Pledger et al., 2015) in R, which implements this clustering methodology, and perform our analysis using this function on the real-life presence/absence data. The results are analysed and interpreted from a biological point of view. We present a variety of visualisations of the models to assist in their interpretation. We found that depth is the most important factor to explain the data.</p>

Clustering and Classification in Fisheries

<p>This goal of this research is to investigate associations between presences of fish species, space, and time in a selected set of areas in New Zealand waters. In particular we use fish abundance indices on the Chatham Rise from scientific surveys in 2002, 2011, 2012, and 2013. The data are collected in annual bottom trawl surveys carried out by the National Institute of Water and Atmospheric Research (NIWA). This research applies clustering via finite mixture models that gives a likelihood-based foundation for the analysis. We use the methods developed by Pledger and Arnold (2014) to cluster species into common groups, conditional on the measured covariates (body size, depth, and water temperature). The project for the first time applies these methods incorporating covariates, and we use simple binary presence/absence data rather than abundances. The models are fitted using the Expectation-Maximization (EM) algorithm. The performance of the models is evaluated by a simulation study. We discuss the advantages and the disadvantages of the EM algorithm. We then introduce a newly developed function clustglm (Pledger et al., 2015) in R, which implements this clustering methodology, and perform our analysis using this function on the real-life presence/absence data. The results are analysed and interpreted from a biological point of view. We present a variety of visualisations of the models to assist in their interpretation. We found that depth is the most important factor to explain the data.</p>

Can't see the science for the solicitors: judicial review of scientific research in light of NIWA's case

<p>The existence of climate change remains an unjustifiably vexed issue worldwide. In New Zealand Climate Science Education Trust v National Institute of Water and Atmospheric Research Ltd, sceptics’ attempts to challenge NIWA’s temperature records allowed the Court to extend its reach into the heart of the scientific research process. Whilst this paper supports Venning J’s determination that NIWA’s decisions were within the Court’s jurisdiction for review, his finding that individuals might suffer harm as a result of them is shown to be unjustified. Furthermore, the Court’s inherent unsuitability to addressing matters with high scientific contents, due to its adversarial nature and judges’ lack of scientific training, supports a finding of non- or partial justiciability. Non-justiciability is here rejected for allowing scientists behaving fraudulently to escape rebuke. The standard of deference Venning J attempts to introduce is similarly flawed as it allows unwary judges to unintentionally judge matters of science. Concerns are also raised that research might stagnate if scientists must worry about judicial scrutiny of their work. Thus, a standard of flagrant impropriety, or “fraud, corruption or bad faith”, is argued to be the ideal threshold for permitting judicial review of scientific research.</p>

Can't see the science for the solicitors: judicial review of scientific research in light of NIWA's case

<p>The existence of climate change remains an unjustifiably vexed issue worldwide. In New Zealand Climate Science Education Trust v National Institute of Water and Atmospheric Research Ltd, sceptics’ attempts to challenge NIWA’s temperature records allowed the Court to extend its reach into the heart of the scientific research process. Whilst this paper supports Venning J’s determination that NIWA’s decisions were within the Court’s jurisdiction for review, his finding that individuals might suffer harm as a result of them is shown to be unjustified. Furthermore, the Court’s inherent unsuitability to addressing matters with high scientific contents, due to its adversarial nature and judges’ lack of scientific training, supports a finding of non- or partial justiciability. Non-justiciability is here rejected for allowing scientists behaving fraudulently to escape rebuke. The standard of deference Venning J attempts to introduce is similarly flawed as it allows unwary judges to unintentionally judge matters of science. Concerns are also raised that research might stagnate if scientists must worry about judicial scrutiny of their work. Thus, a standard of flagrant impropriety, or “fraud, corruption or bad faith”, is argued to be the ideal threshold for permitting judicial review of scientific research.</p>

Drone measurements of surface-based winter temperature inversions in the High Arctic at Eureka

The absence of sunlight during the winter in the High Arctic results in a strong surface-based atmospheric temperature inversion, especially during clear skies and light surface wind conditions. The inversion suppresses turbulent heat transfer between the ground and the boundary layer. As a result, the difference between the surface air temperature, measured at a height of 2 m, and the ground skin temperature can exceed several degrees Celsius. Such inversions occur very frequently in polar regions, are of interest to understand the mechanisms responsible for surface–atmosphere heat, mass, and momentum exchanges, and are critical for satellite validation studies. In this paper we present the results of operations of two commercial remotely piloted aircraft systems, or drones, at the Polar Environment Atmospheric Research Laboratory, Eureka, Nunavut, Canada, at 80∘ N latitude. The drones are the Matrice 100 and Matrice 210 RTK quadcopters manufactured by DJI and were flown over Eureka during the February–March field campaigns in 2017 and 2020. They were equipped with a temperature measurement system built on a Raspberry Pi single-board computer, three platinum-wire temperature sensors, a Global Navigation Satellite System receiver, and a barometric altimeter. We demonstrate that the drones can be effectively used in the extremely challenging High Arctic conditions to measure vertical temperature profiles up to 75 m above the ground and sea ice surface at ambient temperatures down to −46 ∘C. Our results indicate that the inversion lapse rates within the 0–10 m altitude range above the ground can reach values of ∼ 10–30 ∘C(100m)-1 (∼ 100–300 ∘Ckm-1). The results are in good agreement with the coincident surface air temperatures measured at 2, 6, and 10 m levels at the National Oceanic and Atmospheric Administration flux tower at the Polar Environment Atmospheric Research Laboratory. Above 10 m more gradual inversion with order-of-magnitude smaller lapse rates is recorded by the drone. This inversion lapse rate agrees well with the results obtained from the radiosonde temperature measurements. Above the sea ice drone temperature profiles are found to have an isothermal layer above a surface-based layer of instability, which is attributed to the heat flux through the sea ice. With the drones we were able to evaluate the influence of local topography on the surface-based inversion structure above the ground and to measure extremely cold temperatures of air that can pool in topographic depressions. The unique technical challenges of conducting drone campaigns in the winter High Arctic are highlighted in the paper.