KRILLBASE: a circumpolar database of Antarctic krill and salp numerical densities, 1926–2016

Abstract. Antarctic krill (Euphausia superba) and salps are major macroplankton contributors to Southern Ocean food webs and krill are also fished commercially. Managing this fishery sustainably, against a backdrop of rapid regional climate change, requires information on distribution and time trends. Many data on the abundance of both taxa have been obtained from net sampling surveys since 1926, but much of this is stored in national archives, sometimes only in notebooks. In order to make these important data accessible we have collated available abundance data (numerical density, no. m−2) of postlarval E. superba and salps (combined aggregate and solitary stages and species) into a central database, KRILLBASE, together with environmental information, standardisation and metadata. The aim is to provide a temporal-spatial data resource to support a variety of research such as biogeochemistry, autecology, higher predator foraging and food web modelling in addition to fisheries management and conservation. Previous versions of KRILLBASE have led to a series of papers since 2004 which illustrate some of the potential uses of this database. With increasing numbers of requests for these data we here provide an updated version of KRILLBASE that contains data from 15,194 net hauls, including 12,758 with krill abundance data and 9,726 with salp abundance data. These data were collected by 10 nations and span 56 seasons in two epochs (1926–1939 and 1976–2016). Here, we illustrate the seasonal, inter-annual, regional and depth coverage of sampling, and provide both circumpolar- and regional-scale distribution maps. Krill abundance data have been standardised to accommodate variation in sampling methods, and we have presented these as well as the raw data. Information is provided on how to screen, interpret and use KRILLBASE to reduce artefacts in interpretation, with contact points for the main data providers.

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KRILLBASE: a circumpolar database of Antarctic krill and salp numerical densities, 1926–2016

Earth System Science Data ◽

10.5194/essd-9-193-2017 ◽

2017 ◽

Vol 9 (1) ◽

pp. 193-210 ◽

Cited By ~ 29

Author(s):

Angus Atkinson ◽

Simeon L. Hill ◽

Evgeny A. Pakhomov ◽

Volker Siegel ◽

Ricardo Anadon ◽

...

Keyword(s):

Spatial Data ◽

Antarctic Krill ◽

Regional Scale ◽

Published Data ◽

Numerical Density ◽

Data Set ◽

Data Resource ◽

Abundance Data ◽

Krill Abundance ◽

Contact Points

Abstract. Antarctic krill (Euphausia superba) and salps are major macroplankton contributors to Southern Ocean food webs and krill are also fished commercially. Managing this fishery sustainably, against a backdrop of rapid regional climate change, requires information on distribution and time trends. Many data on the abundance of both taxa have been obtained from net sampling surveys since 1926, but much of this is stored in national archives, sometimes only in notebooks. In order to make these important data accessible we have collated available abundance data (numerical density, no. m−2) of postlarval E. superba and salp individual (multiple species, and whether singly or in chains). These were combined into a central database, KRILLBASE, together with environmental information, standardisation and metadata. The aim is to provide a temporal-spatial data resource to support a variety of research such as biogeochemistry, autecology, higher predator foraging and food web modelling in addition to fisheries management and conservation. Previous versions of KRILLBASE have led to a series of papers since 2004 which illustrate some of the potential uses of this database. With increasing numbers of requests for these data we here provide an updated version of KRILLBASE that contains data from 15 194 net hauls, including 12 758 with krill abundance data and 9726 with salp abundance data. These data were collected by 10 nations and span 56 seasons in two epochs (1926–1939 and 1976–2016). Here, we illustrate the seasonal, inter-annual, regional and depth coverage of sampling, and provide both circumpolar- and regional-scale distribution maps. Krill abundance data have been standardised to accommodate variation in sampling methods, and we have presented these as well as the raw data. Information is provided on how to screen, interpret and use KRILLBASE to reduce artefacts in interpretation, with contact points for the main data providers. The DOI for the published data set is doi:10.5285/8b00a915-94e3-4a04-a903-dd4956346439.

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Overview of the Mount Tai Experiment (MTX2006) in central East China in June 2006: studies of significant regional air pollution

Atmospheric Chemistry and Physics ◽

10.5194/acp-13-8265-2013 ◽

2013 ◽

Vol 13 (16) ◽

pp. 8265-8283 ◽

Cited By ~ 28

Author(s):

Y. Kanaya ◽

H. Akimoto ◽

Z.-F. Wang ◽

P. Pochanart ◽

K. Kawamura ◽

...

Keyword(s):

Air Pollution ◽

Regional Climate ◽

Regional Scale ◽

Photochemical Activity ◽

East China ◽

Strong Impact ◽

Source Attribution ◽

Annual Variations ◽

Photochemical Aging ◽

Regional Air Pollution

Abstract. We conducted an intensive field campaign at the summit of Mt. Tai (36.26° N, 117.11° E, 1534 m above sea level), Shandong Province, located at the center of central East China, during the period 28 May to 30 June 2006, to study seasonal maxima of regional air pollution with respect to ozone (O3) and aerosols. The specific objectives, campaign design, and major findings are summarized. High concentrations of O3 and its precursors, and aerosols, were detected and studied in the context of annual variations. Most importantly, we identified that emissions from regional-scale open crop residue burning after the harvesting of winter wheat, together with photochemical aging, strongly increased the concentrations of O3, aerosols, and primary pollutants in this month of year. Studies of in situ photochemical activity, regional source attribution of O3, O3–aerosol interactions, validation of satellite observations of tropospheric NO2, behaviors of volatile organic compounds and organic/inorganic aerosol species, loss rates of black carbon (BC), and instrument inter-comparisons are also summarized. The observed BC levels must have a strong impact on the regional climate.

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The Swiss joint information platform for natural hazards

Abstracts of the ICA ◽

10.5194/ica-abs-1-12-2019 ◽

2019 ◽

Vol 1 ◽

pp. 1-2

Author(s):

Philipp Angehrn ◽

Sabina Steiner ◽

Christophe Lienert

Keyword(s):

Natural Hazards ◽

Spatial Data ◽

Natural Hazard ◽

Regional Scale ◽

Measurement Data ◽

User Feedback ◽

Acceptance Testing ◽

Spatial Density ◽

Data Sets ◽

Information Platform

Abstract. The Swiss Joint Information Platform for Natural Hazards (GIN) has been realized from 2008 to 2010 as part of the Swiss federal government’s OWARNA project, which aimed at optimizing warning and alerting procedures against natural hazard. The first online-version of the platform went productive in 2011 with the primary goal of providing measured and forecast natural hazard data in form of processed cartographic, graphic and other multimedia products to professional users &ndash; before, during and after natural hazard events. In Switzerland water-, weather-, snow- and earthquake-related hazards are the most relevant ones.In 2013, an online survey showed that the platform does not fully meet user expectations, particularly as to user experience and usability of its cartographic, web-based user interface. Revaluation and redesign of the overall platform were necessary in order to improve map legibility, caused by the complexity of data, large data amounts, and high spatial density of online, real-time measurement data locations. A new web design and user interaction concept have been developed in 2014 and eventually put online in June 2017. User acceptance testing by means of surveys and direct user feedback sessions were key factors in this perennial redesign process. The GIN platform now features important novel technical and graphical elements: The starting page is based on a dashboard containing virtual dossiers (Fig. 1), with which users configure their desired information, data, and map bundles individually, or use predefined adaptable views on various existing data sets. In addition, there is a new overall spatial search function to query data parameters. A responsive approach further improves the usability of the platform. The focus of these new features is on multi-views involving maps, diagrams, tables, text products, as well as selected geographical areas on maps, and fast data queries (Fig. 2). Current user feedback suggests that the new GIN platform design is well received, and that it is moving closer to its very goal: online monitoring and management of natural hazard events by enhanced usability, more targeted and higher personalization.Several Swiss Cantons (i.e., the political entities in Switzerland below the federation) actively participated, and still participate, in the conceptual GIN platform development process through advisory board meetings and consultations. On the operational level, Cantons actively provide and contribute further natural hazard information and measurement data from their own natural hazard monitoring networks. These additional Cantonal regional-scale data sets help to fill spatial data gaps, where no Federal data is available. GIN thusly integrates natural hazard data from Federal and Cantonal levels (and partly even private level), which adds value to all stakeholders on various political levels involved in natural hazard management (Federal, Cantonal, Regional, Communal crisis committees). Stakeholders not only use GIN’s ample database and cartographic product portfolio to accomplish their early warning and crisis management tasks, but also benefit from seamless, secure and reliable IT-services, provided by the Swiss Federal Government. With the new GIN platform, Switzerland has a powerful, integrative, and comprehensive tool for monitoring and responding to natural hazard events.

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The climate penalty for clean fossil fuel combustion

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-11-24567-2011 ◽

2011 ◽

Vol 11 (9) ◽

pp. 24567-24589 ◽

Cited By ~ 1

Author(s):

W. Junkermann ◽

B. Vogel ◽

M. A. Sutton

Keyword(s):

Ultrafine Particles ◽

Power Plants ◽

Cloud Condensation Nuclei ◽

Regional Climate ◽

Fine Particulate Matter ◽

Regional Scale ◽

Cloud Microphysics ◽

Environmental Damage ◽

Particulate Emissions ◽

Gas Cleaning

Abstract. To cope with the world's growing demand for energy, a large number of coal-fired power plants are currently in operation or under construction. To prevent environmental damage from acidic sulphur and particulate emissions, many such installations are equipped with flue gas cleaning technology that reduces the emitted amounts of sulphur dioxide (SO2) and nitrogen dioxide (NO2). However, the consequences of this technology for aerosol emissions, and in particular the regional scale impact on cloud microphysics, have not been studied until now. We performed airborne investigations to measure aerosol size distributions in the air masses downwind of coal-fired power installations. We show how the current generation of clean technology reduces the emission of sulphur and fine particulate matter, but leads to an unanticipated increase in the direct emission of ultrafine particles (1–10 nm median diameter) which are highly effective precursors of cloud condensation nuclei (CCN). Our analysis shows how these additional ultrafine particles modify cloud microphysics, as well as precipitation intensity and distribution on a regional scale downwind of emission sources. Effectively, the number of small water droplets is increased, thus reducing the water available for large droplets and rain formation. The corresponding changes in the precipitation budget with a shift from more frequent steady rain to occasionally more vigorous rain events, or even a significant regional reduction of annual precipitation, introduce an unanticipated risk for regional climate and agricultural production, especially in semi-arid climate zones.

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Study of Potential Climate for Sugarcane Production in the State of Rio Grande Do Sul, Brazil, By Means of Geoprocessing

Computational Methods for Agricultural Research ◽

10.4018/978-1-61692-871-1.ch006 ◽

2011 ◽

pp. 96-106

Author(s):

Fernando Soares ◽

José Alba ◽

Elódio Sebem ◽

Marcos Wrege

Keyword(s):

Spatial Analysis ◽

Spatial Data ◽

Regional Scale ◽

Rio Grande ◽

Local Scale ◽

The State ◽

Rio Grande Do Sul ◽

Gis Technology ◽

Physiological Maturity ◽

Climate Study

A potential climate study for sugarcane of a sector of Rio Grande do Sul State, Brazil is presented here. GIS technology was applied for evaluation of the risk of frost and for integration of spatial data. The problem was focused in regional scale and in local scale (Municipality of Jaguari). Results showed that cultivation can be programmed in order to obtain physiological maturity before the period of risk of frost, thus avoiding low production. Spatial analysis of the information allows rapid perspective for productivity of sugarcane in a specific territory. The Municipality of Jaguari has large potential for cultivation of sugarcane because of the absence of the risk of frost. Its productivity allows for expansion into suitable neighboring areas. Also, geoprocessing combined with the study of climate and soil appears as a significant tool for interpreting the areas with aptitude for production of sugarcane or for the industry of sugar and alcohol.

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CORDEX-WRF v1.3: development of a module for the Weather Research and Forecasting (WRF) model to support the CORDEX community

Geoscientific Model Development ◽

10.5194/gmd-12-1029-2019 ◽

2019 ◽

Vol 12 (3) ◽

pp. 1029-1066 ◽

Cited By ~ 2

Author(s):

Lluís Fita ◽

Jan Polcher ◽

Theodore M. Giannaros ◽

Torge Lorenz ◽

Josipa Milovac ◽

...

Keyword(s):

Regional Climate ◽

Regional Scale ◽

Wrf Model ◽

Data Access ◽

Quality Data ◽

Weather Research And Forecasting ◽

Time Step ◽

Mitigation And Adaptation ◽

Data Requirements ◽

Weather Research

Abstract. The Coordinated Regional Climate Downscaling Experiment (CORDEX) is a scientific effort of the World Climate Research Program (WRCP) for the coordination of regional climate initiatives. In order to accept an experiment, CORDEX provides experiment guidelines, specifications of regional domains, and data access and archiving. CORDEX experiments are important to study climate at the regional scale, and at the same time, they also have a very prominent role in providing regional climate data of high quality. Data requirements are intended to cover all the possible needs of stakeholders and scientists working on climate change mitigation and adaptation policies in various scientific communities. The required data and diagnostics are grouped into different levels of frequency and priority, and some of them even have to be provided as statistics (minimum, maximum, mean) over different time periods. Most commonly, scientists need to post-process the raw output of regional climate models, since the latter was not originally designed to meet the specific CORDEX data requirements. This post-processing procedure includes the computation of diagnostics, statistics, and final homogenization of the data, which is often computationally costly and time-consuming. Therefore, the development of specialized software and/or code is required. The current paper presents the development of a specialized module (version 1.3) for the Weather Research and Forecasting (WRF) model capable of outputting the required CORDEX variables. Additional diagnostic variables not required by CORDEX, but of potential interest to the regional climate modeling community, are also included in the module. “Generic” definitions of variables are adopted in order to overcome the model and/or physics parameterization dependence of certain diagnostics and variables, thus facilitating a robust comparison among simulations. The module is computationally optimized, and the output is divided into different priority levels following CORDEX specifications (Core, Tier 1, and additional) by selecting pre-compilation flags. This implementation of the module does not add a significant extra cost when running the model; for example, the addition of the Core variables slows the model time step by less than a 5 %. The use of the module reduces the requirements of disk storage by about a 50 %. The module performs neither additional statistics over different periods of time nor homogenization of the output data.

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Fifty-Seven-Year California Reanalysis Downscaling at 10 km (CaRD10). Part I: System Detail and Validation with Observations

Journal of Climate ◽

10.1175/2007jcli1482.1 ◽

2007 ◽

Vol 20 (22) ◽

pp. 5553-5571 ◽

Cited By ~ 79

Author(s):

Masao Kanamitsu ◽

Hideki Kanamaru

Keyword(s):

Time Scales ◽

Large Scale ◽

Global Analysis ◽

Regional Climate ◽

Regional Scale ◽

Surface Wind ◽

Lateral Boundary ◽

Climate Change Research ◽

Near Surface ◽

Precipitation Analysis

Abstract For the purpose of producing datasets for regional-scale climate change research and application, the NCEP–NCAR reanalysis for the period 1948–2005 was dynamically downscaled to hourly, 10-km resolution over California using the Regional Spectral Model. This is Part I of a two-part paper, describing the details of the downscaling system and comparing the downscaled analysis [California Reanalysis Downscaling at 10 km (CaRD10)] against observation and global analysis. An extensive validation of the downscaled analysis was performed using station observations, Higgins gridded precipitation analysis, and Precipitation-Elevation Regression on Independent Slopes Model (PRISM) precipitation analysis. In general, the CaRD10 near-surface wind and temperature fit better to regional-scale station observations than the NCEP–NCAR reanalysis used to force the regional model, supporting the premise that the regional downscaling is a viable method to attain regional detail from large-scale analysis. This advantage of CaRD10 was found on all time scales, ranging from hourly to decadal scales (i.e., from diurnal variation to multidecadal trend). Dynamically downscaled analysis provides ways to study various regional climate phenomena of different time scales because all produced variables are dynamically, physically, and hydrologically consistent. However, the CaRD10 is not free from problems. It suffers from positive bias in precipitation for heavy precipitation events. The CaRD10 is inaccurate near the lateral boundary where regional detail is damped by the lateral boundary relaxation. It is important to understand these limitations before the downscaled analysis is used for research.

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Study of Monsoonal Features Using Regional Climate Model over Heterogeneous Monsoon Dominated Region

E3S Web of Conferences ◽

10.1051/e3sconf/201910103004 ◽

2019 ◽

Vol 101 ◽

pp. 03004

Author(s):

Rohit Srivastava ◽

Ruchita Shah

Keyword(s):

High Resolution ◽

Regional Climate Model ◽

Climate Model ◽

Regional Climate ◽

Regional Scale ◽

Actual Performance ◽

The Earth ◽

Wide Range ◽

Resolution Model ◽

High Resolution Model

Global warming is an increase in average global temperature of the earth which lead to climate change. Heterogeneity in the earth-atmosphere system becomes difficult to capture at low resolution (1°x1°) by satellite. Such features may be captured by using high resolution model such as regional climate model (0.5°x 0.5°). This type of study is quite important for a monsoon dominated country like India where Indo-Gangetic Plains (IGP) faces highest heterogeneity due to its geographic location. Present study compares high resolution model features with satellite data over IGP for monsoon season during a normal rainfall year 2010 to understand the actual performance of model. Almost whole IGP simulates relative humidity (RH) with wide range (~50-100%), whereas satellite shows it with narrow range (~60-80%) during September, 2010. Thus model is able to pick the features which were missed by satellite. Hence further model simulation extends over India and adjoining oceanic regions which simulates data of southwest monsoon with high (~70-100%) RH, high (~0.4-0.7) cloud fraction (CF) and low (~80-200 W/m2) outgoing longwave radiation (OLR) over Arabian Sea during June, 2010. Such type of study can be useful to understand heterogeneity at regional scale with the help of high resolution model generated data.

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Accumulation rates (2009–2017) in Southeast Greenland derived from airborne snow radar and comparison with regional climate models

Annals of Glaciology ◽

10.1017/aog.2020.8 ◽

2020 ◽

Vol 61 (81) ◽

pp. 225-233 ◽

Cited By ~ 4

Author(s):

Lynn Montgomery ◽

Lora Koenig ◽

Jan T. M. Lenaerts ◽

Peter Kuipers Munneke

Keyword(s):

Spatial Data ◽

Climate Models ◽

Layer Structure ◽

Accumulation Rate ◽

Regional Climate ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Regional Climate Models ◽

Internal Layers ◽

Accumulation Rates

AbstractSince the year 2000, Greenland ice sheet mass loss has been dominated by a decrease in surface mass balance rather than an increase in solid ice discharge. Southeast Greenland is an important region to understand how high accumulation rates can offset increasing Greenland ice sheet meltwater runoff. To that end, we derive a new 9-year long dataset (2009–17) of accumulation rates in Southeast Greenland using NASA Operation IceBridge snow radar. Our accumulation dataset derived from internal layers focuses on high elevations (1500–3000 m) because at lower elevations meltwater percolation obscured internal layer structure. The uncertainty of the radar-derived accumulation rates is 11% [using Firn Densification Model (FDM) density profiles] and the average accumulation rate ranges from 0.5 to 1.2 m w.e. With our observations spanning almost a decade, we find large inter-annual variability, but no significant trend. Accumulation rates are compared with output from two regional climate models (RCMs), MAR and RACMO2. This comparison shows that the models are underestimating accumulation in Southeast Greenland and the models misrepresent spatial heterogeneity due to an orographically forced bias in snowfall near the coast. Our dataset is useful to fill in temporal and spatial data gaps, and to evaluate RCMs where few in situ measurements are available.

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Climate changes along the Labrador coasts during the Holocene based from pollen assemblages

10.5194/egusphere-egu2020-908 ◽

2020 ◽

Author(s):

Natasha Roy ◽

Bianca Fréchette ◽

Anne de Vernal

Keyword(s):

Regional Climate ◽

Regional Scale ◽

Climatic Conditions ◽

Modes Of Variability ◽

Natural Modes ◽

Climate Reconstructions ◽

Short Period ◽

Modern Analogue ◽

Northern Regions ◽

Natural Climate

The rapid ongoing warming recorded across northern regions is unprecedented. This warming is however not uniform across the territory and large regional discrepancies exist. It is therefore relevant to document the variations of climate in the past in both time and space in order to understand the regional climate dynamics. However, in Labrador, instrumental and historical data are rare and only cover a short period of time. Our knowledge of the natural evolution of the climate is therefore limited, which hampers our capacity to evaluate the natural modes of variability and simulate changes at regional scales. From this viewpoint, quantitative climate reconstructions from pollen assemblages are useful because they allow the development of time series covering long periods of time. Here, we report on pollen data from peat and lake sediments collected in the area of Okak, Nain and Dog Island along the Labrador coast. &#160;These data are used for climate reconstruction over the last millennia, thus allowing to document natural climate variability at regional scale. The climate parameters we reconstruct by the means of the modern analogue technique include the summer temperature, sunshine and precipitation. The results provide new insights about the climate of Labrador at local to regional scale, illustrating notably the importance of the Labrador Current on climatic conditions at nearshore locations. In fact, our climate reconstructions demonstrate a disparity with the regional climate curve which may testify of the east-west climatic gradient between islands and the land.

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