A critical remark on the applicability of E-OBS European gridded temperature data set for validating control climate simulations

NASA Astrophysics Data System (ADS)

Kyselý, Jan; Plavcová, Eva

2010-12-01

The study compares daily maximum (Tmax) and minimum (Tmin) temperatures in two data sets interpolated from irregularly spaced meteorological stations to a regular grid: the European gridded data set (E-OBS), produced from a relatively sparse network of stations available in the European Climate Assessment and Dataset (ECA&D) project, and a data set gridded onto the same grid from a high-density network of stations in the Czech Republic (GriSt). We show that large differences exist between the two gridded data sets, particularly for Tmin. The errors tend to be larger in tails of the distributions. In winter, temperatures below the 10% quantile of Tmin, which is still far from the very tail of the distribution, are too warm by almost 2°C in E-OBS on average. A large bias is found also for the diurnal temperature range. Comparison with simple average series from stations in two regions reveals that differences between GriSt and the station averages are minor relative to differences between E-OBS and either of the two data sets. The large deviations between the two gridded data sets affect conclusions concerning validation of temperature characteristics in regional climate model (RCM) simulations. The bias of the E-OBS data set and limitations with respect to its applicability for evaluating RCMs stem primarily from (1) insufficient density of information from station observations used for the interpolation, including the fact that the stations available may not be representative for a wider area, and (2) inconsistency between the radii of the areal average values in high-resolution RCMs and E-OBS. Further increases in the amount and quality of station data available within ECA&D and used in the E-OBS data set are essentially needed for more reliable validation of climate models against recent climate on a continental scale.

Reconstitution de données climatiques pour l’Algérie du Nord : application des réseaux neuronaux

NASA Astrophysics Data System (ADS)

Bouaoune, Djahida; Dahmani-Megrerouche, Malika

2010-11-01

In the present context of climate change and preservation of biodiversity, the appreciation of the vulnerability of the natural ecosystems and their capacity of adaptation appears among the main preoccupations to the world level (GIEC, 2007). This assessment of the ecosystems requires the availability of climatic data, what is often made difficult by the weak density or even the absence of meteorological stations notably, to the level of the mountains zones. In order to study the climate-vegetation relationship in North Algeria, we use an automatic interpolation method, the neural network method, for the reconstitution of climatic data of the sampled sites, (1035 phytoecological samples), from the existing meteorological network (269 stations). This method is characterized by a great suppleness of non-linearity and by its capacity for reconstituting information from partial and not well-defined indications such as the case of data provided from meteorological networks. In order to reconstitution of climatic data, we use the explicate variables, longitude, latitude and altitude, the variables to explain being the rainfall and temperatures. To define the best approach, the network calibration has been activated on climatic parameters taken globally or solely, for the whole of study zone, and by geographical sector. The results of the interpolation are expressed through a climatic parameter cartography, released automatically by the MapInfo software. The reliability results obtained by this method can be appreciated by elaboration of errors maps comparing to reference data.

Representativeness of four precipitation observational networks of China

NASA Astrophysics Data System (ADS)

Ren, Yuyu; Ren, Guoyu

2012-08-01

Four precipitation observational networks with varied station densities are maintained in China. They are: the Global Climate Observation System (GCOS) Surface Network (GSN), the national Reference Climate Network (RCN), the national Basic Meteorological Network (BMN), and the national Ordinary Meteorological Network (OMN). The GSN, RCN, BMN, and the merged network of RCN and BMN (R&B) have been widely used in climatology and climate change studies. In this paper, the impact of the usage of different networks on the precipitation climatology of China is evaluated by using the merged dataset of All Station Network (ASN) as a benchmark. The results show that all networks can capture the main features of the country average precipitation and its changing trends. The differences of average annual precipitation of the various networks from that of the ASN are less than 50 mm (⩽ 10%). All networks can successfully detect the rising trend of the average annual precipitation during 1961-2009, with the R&B exhibiting the best representativeness (only 2.90% relative difference) and the GSN the poorest (39.77%). As to the change trends of country average monthly precipitation, the networks can be ranked in descending order as R&B (1.27%), RCN (2.35%), BMN (4.17%), and GSN (7.46%), and larger relative differences appear from August to November. The networks produce quite consistent spatial patterns of annual precipitation change trends, and all show an increasing trend of precipitation in Northwest and Southeast China, and a decreasing trend in North China, Northeast China, and parts of central China. However, the representativeness of the BMN and R&B are better in annual and seasonal precipitation trends, in spite of the fact that they are still far from satisfactory. The relative differences of trends in some months and regions even reach more than 50%. The results also show that the representativeness of the RCN for country average precipitation is higher than that of the BMN because the RCN has a more homogeneous distribution of stations.

ClimaDat: A long-term network to study at different scales climatic processes and interactions between climatic compartments

NASA Astrophysics Data System (ADS)

Morgui, Josep Anton; Agueda, Alba; Batet, Oscar; Curcoll, Roger; Ealo, Marina; Grossi, Claudia; Occhipinti, Paola; Sánchez-García, Laura; Arias, Rosa; Rodó, Xavi

2013-04-01

ClimaDat (www.climadat.es) is a pioneer project of the Institut Català de Ciències del Clima (IC3) in collaboration with and funded by "la Caixa" Foundation. This project aims at studying the interactions between climate and ecosystems at different spatial and temporal scales. The ClimaDat project consists of a network of eight long-term observatory stations distributed over Spain, installed at natural and remote areas, and covering different climatic domains (e.g. Mediterranean, Atlantic, subtropics) and natural systems (e.g. delta, karsts, high mountain areas). Data obtained in the ClimaDat network will help us to understand how ecosystems are influenced by and eventually might feedback different processes in the climate system. The point of focus of these studies will be taken into account regional-and-local conditions to understand climatic global scale eventsThe data gathered will be used to study the behavior of the global element cycles and associated greenhouse gas emissions. The network is expected to offer near real-time (NRT) data free for the scientific community. Instrumentation installed at these stations mainly consists of: CO2, CH4, H2O, CO, N2O, SF6 and 222Rn analyzers, isotopic CO2, CH4 and H2O analyzers, meteorological sensors, eddy covariance equipment, four-component radiometers, soil moisture and temperature sensors, and sap flow meters. Each station may have a more focused subset of all this equipment, depending on the specific characteristics of the site. Instrumentation selected for this network has been chosen to comply with standards established in international research infrastructure projects, such as ICOS (http://www.icos-infrastructure.eu/home) or InGOS (http://www.ingos-infrastructure.eu/). Preliminary data time-series of greenhouse gases concentrations and meteorological variables are presented in this study for three currently operational ClimaDat stations: the Natural Park of the Ebre Delta (lat 40.75° N - long 0.79° E), the Regional Park of the Sierra de Gredos (lat 40.22° N - long -5.14° E) and the Natural Park of Baixa Limia - Serra do Xurès (lat 41.99° N - long -8.01° E). The wind source influencing regions of the three stations are also presented in this work, according to the results obtained using the HYSPLIT trajectory model (http://ready.arl.noaa.gov/HYSPLIT.php).

Impacts of alternative climate information on hydrologic processes with SWAT: A comparison of NCDC, PRISM and NEXRAD datasets

USDA-ARS?s Scientific Manuscript database

Precipitation and temperature are two primary drivers that significantly affect hydrologic processes in a watershed. A network of land-based National Climatic Data Center (NCDC) weather stations has been typically used as a primary source of climate input for agro-ecosystem models. However, the ne...

New climatic classification of Nepal

NASA Astrophysics Data System (ADS)

Karki, Ramchandra; Talchabhadel, Rocky; Aalto, Juha; Baidya, Saraju Kumar

2016-08-01

Although it is evident that Nepal has an extremely wide range of climates within a short latitudinal distance, there is a lack of comprehensive research in this field. The climatic zoning in a topographically complex country like Nepal has important implications for the selection of scientific station network design and climate model verification, as well as for studies examining the effects of climate change in terms of shifting climatic boundaries and vegetation in highly sensitive environments. This study presents a new high-resolution climate map of Nepal on the basis of long-term (1981-2010) monthly precipitation data for 240 stations and mean air temperature data for 74 stations, using original and modified Köppen-Geiger climate classification systems. Climatic variables used in Köppen-Geiger system were calculated (i) at each station and (ii) interpolated to 1-km spatial resolution using kriging which accounted for latitude, longitude, and elevation. The original Köppen-Geiger scheme could not identify all five types of climate (including tropical) observed in Nepal. Hence, the original scheme was slightly modified by changing the boundary of coldest month mean air temperature value from 18 °C to 14.5 °C in order to delineate the realistic climatic condition of Nepal. With this modification, all five types of climate (including tropical) were identified. The most common dominant type of climate for Nepal is temperate with dry winter and hot summer (Cwa).

Similarity indices of meteo-climatic gauging stations: definition and comparison.

PubMed

Barca, Emanuele; Bruno, Delia Evelina; Passarella, Giuseppe

2016-07-01

Space-time dependencies among monitoring network stations have been investigated to detect and quantify similarity relationships among gauging stations. In this work, besides the well-known rank correlation index, two new similarity indices have been defined and applied to compute the similarity matrix related to the Apulian meteo-climatic monitoring network. The similarity matrices can be applied to address reliably the issue of missing data in space-time series. In order to establish the effectiveness of the similarity indices, a simulation test was then designed and performed with the aim of estimating missing monthly rainfall rates in a suitably selected gauging station. The results of the simulation allowed us to evaluate the effectiveness of the proposed similarity indices. Finally, the multiple imputation by chained equations method was used as a benchmark to have an absolute yardstick for comparing the outcomes of the test. In conclusion, the new proposed multiplicative similarity index resulted at least as reliable as the selected benchmark.

Updated population metadata for United States historical climatology network stations

USGS Publications Warehouse

Owen, T.W.; Gallo, K.P.

2000-01-01

The United States Historical Climatology Network (HCN) serial temperature dataset is comprised of 1221 high-quality, long-term climate observing stations. The HCN dataset is available in several versions, one of which includes population-based temperature modifications to adjust urban temperatures for the "heat-island" effect. Unfortunately, the decennial population metadata file is not complete as missing values are present for 17.6% of the 12 210 population values associated with the 1221 individual stations during the 1900-90 interval. Retrospective grid-based populations. Within a fixed distance of an HCN station, were estimated through the use of a gridded population density dataset and historically available U.S. Census county data. The grid-based populations for the HCN stations provide values derived from a consistent methodology compared to the current HCN populations that can vary as definitions of the area associated with a city change over time. The use of grid-based populations may minimally be appropriate to augment populations for HCN climate stations that lack any population data, and are recommended when consistent and complete population data are required. The recommended urban temperature adjustments based on the HCN and grid-based methods of estimating station population can be significantly different for individual stations within the HCN dataset.

The Ogallala Agro-Climate Tool (Technical Description)

USDA-ARS?s Scientific Manuscript database

A Visual Basic agro-climate application capable of estimating irrigation demand and crop water use over the Ogallala Aquifer region is described here. The application’s meteorological database consists of daily precipitation and temperature data from 141 U.S. Historical Climatology Network stations ...

Observing climate change trends in ocean biogeochemistry: when and where.

PubMed

Henson, Stephanie A; Beaulieu, Claudie; Lampitt, Richard

2016-04-01

Understanding the influence of anthropogenic forcing on the marine biosphere is a high priority. Climate change-driven trends need to be accurately assessed and detected in a timely manner. As part of the effort towards detection of long-term trends, a network of ocean observatories and time series stations provide high quality data for a number of key parameters, such as pH, oxygen concentration or primary production (PP). Here, we use an ensemble of global coupled climate models to assess the temporal and spatial scales over which observations of eight biogeochemically relevant variables must be made to robustly detect a long-term trend. We find that, as a global average, continuous time series are required for between 14 (pH) and 32 (PP) years to distinguish a climate change trend from natural variability. Regional differences are extensive, with low latitudes and the Arctic generally needing shorter time series (<~30 years) to detect trends than other areas. In addition, we quantify the 'footprint' of existing and planned time series stations, that is the area over which a station is representative of a broader region. Footprints are generally largest for pH and sea surface temperature, but nevertheless the existing network of observatories only represents 9-15% of the global ocean surface. Our results present a quantitative framework for assessing the adequacy of current and future ocean observing networks for detection and monitoring of climate change-driven responses in the marine ecosystem. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Pan-Eurasian experiment (PEEX) establishing a process towards high level Pan-Eurasian atmosphere-ecosystem observation networks

NASA Astrophysics Data System (ADS)

Lappalainen, Hanna K.; Petäjä, Tuukka; Zaytzeva, Nina; Viisanen, Yrjö; Kotlyakov, Vladimir; Kasimov, Nikolay; Bondur, Valery; Matvienko, Gennady; Zilitinkevich, Sergej; Kulmala, Markku

2014-05-01

Pan-Eurasian Experiment (PEEX) is a new multidisciplinary research approach aiming at resolving the major uncertainties in the Earth system science and global sustainability questions in the Arctic and boreal Pan-Eurasian regions (Kulmala et al. 2011). The main goal of PEEX Research agenda is to contribute to solving the scientific questions that are specifically important for the Pan-Eurasian region in the coming years, in particular the global climate change and its consequences to nature and human society. Pan Eurasian region represents one the Earth most extensive areas of boreal forest (taiga) and the largest natural wetlands, thus being a significant source area of trace gas emissions, biogenic aerosol particles, and source and sink area for the greenhouse gas (GHG) exchange in a global scale (Guenther et al. 1995, Timkovsky et al. 2010, Tunved et al. 2006, Glagolev et al. 2010). One of the first activities of the PEEX initiative is to establish a process towards high level Pan-Eurasian Observation Networks. Siberian region is currently lacking a coordinated, coherent ground based atmosphere-ecosystem measurement network, which would be crucial component for observing and predicting the effects of climate change in the Northern Pan- Eurasian region The vision of the Pan-Eurasion network will be based on a hierarchical SMEAR-type (Stations Measuring Atmosphere-Ecosystem Interactions) integrated land-atmosphere observation system (Hari et al. 2009). A suite of stations have been selected for the Preliminary Phase of PEEX Observation network. These Preliminary Phase stations includes the SMEAR-type stations in Finland (SMEAR-I-II-II-IV stations), in Estonia (SMEAR-Järviselja) and in China (SMEAR-Nanjing) and selected stations in Russia and ecosystem station network in China. PEEX observation network will fill in the current observational gap in the Siberian region and bring the Siberian observation setup into international context with the with standardized or comparable procedures. It will prove a basis for the long-term continuation of advanced measurements on aerosols, clouds, GHGs and trace gases in Northern Pan- Eurasian area to be operated by PEEX educated technical staff.

VEMAP Phase 2 bioclimatic database. I. Gridded historical (20th century) climate for modeling ecosystem dynamics across the conterminous USA

USGS Publications Warehouse

Kittel, T.G.F.; Rosenbloom, N.A.; Royle, J. Andrew; Daly, Christopher; Gibson, W.P.; Fisher, H.H.; Thornton, P.; Yates, D.N.; Aulenbach, S.; Kaufman, C.; McKeown, R.; Bachelet, D.; Schimel, D.S.; Neilson, R.; Lenihan, J.; Drapek, R.; Ojima, D.S.; Parton, W.J.; Melillo, J.M.; Kicklighter, D.W.; Tian, H.; McGuire, A.D.; Sykes, M.T.; Smith, B.; Cowling, S.; Hickler, T.; Prentice, I.C.; Running, S.; Hibbard, K.A.; Post, W.M.; King, A.W.; Smith, T.; Rizzo, B.; Woodward, F.I.

2004-01-01

Analysis and simulation of biospheric responses to historical forcing require surface climate data that capture those aspects of climate that control ecological processes, including key spatial gradients and modes of temporal variability. We developed a multivariate, gridded historical climate dataset for the conterminous USA as a common input database for the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP), a biogeochemical and dynamic vegetation model intercomparison. The dataset covers the period 1895-1993 on a 0.5?? latitude/longitude grid. Climate is represented at both monthly and daily timesteps. Variables are: precipitation, mininimum and maximum temperature, total incident solar radiation, daylight-period irradiance, vapor pressure, and daylight-period relative humidity. The dataset was derived from US Historical Climate Network (HCN), cooperative network, and snowpack telemetry (SNOTEL) monthly precipitation and mean minimum and maximum temperature station data. We employed techniques that rely on geostatistical and physical relationships to create the temporally and spatially complete dataset. We developed a local kriging prediction model to infill discontinuous and limited-length station records based on spatial autocorrelation structure of climate anomalies. A spatial interpolation model (PRISM) that accounts for physiographic controls was used to grid the infilled monthly station data. We implemented a stochastic weather generator (modified WGEN) to disaggregate the gridded monthly series to dailies. Radiation and humidity variables were estimated from the dailies using a physically-based empirical surface climate model (MTCLIM3). Derived datasets include a 100 yr model spin-up climate and a historical Palmer Drought Severity Index (PDSI) dataset. The VEMAP dataset exhibits statistically significant trends in temperature, precipitation, solar radiation, vapor pressure, and PDSI for US National Assessment regions. The historical climate and companion datasets are available online at data archive centers. ?? Inter-Research 2004.

Hydro-climatic data network (HCDN); a U.S. Geological Survey streamflow data set for the United States for the study of climate variations, 1874-1988

USGS Publications Warehouse

Slack, J.R.; Landwehr, Jurate Maciunas

1992-01-01

Records of streamflow can provide an account of climatic variation over a hydrologic basin. The ability to do so is conditioned on the absence of confounding factors that diminish the climate signal. A national data set of streamflow records that are relatively free of confounding anthropogenic influences has been developed for the purpose of studying the variation in surface-water conditions throughout the United States. Records in the U.S. Geological Survey (USGS) National Water Storage and Retrieval System (WATSTORE) data base for active and discontinued streamflow gaging stations through water year 1988 (that is, through September 30, 1988) were reviewed jointly with data specialists in each USGS District office. The resulting collection of stations, each with its respective period of record satisfying the qualifying criteria, is called the Hydro-Climatic Data Network, or HCDN. The HCDN consists of 1,659 sites throughout the United States and its territories, totaling 73,231 water years of daily mean discharge values. For each station in the HCDN, information necessary for its identification, along with any qualifying comments about the available record and a set of descriptive watershed characteristics are provided in tabular format in this report, both on paper and on computer disk (enclosed). For each station in the HCDN, the appropriate daily mean discharge values were compiled, and statistical characteristics, including monthly mean discharges and annual mean, minimum and maximum discharges, were derived. The discharge data values are provided in a companion report.

An aid to streamlining fire-weather station networks

Treesearch

R. William Furman

1975-01-01

For reasons of economy it may be necessary to close one or several fire-weather stations in a protection area. Since it is logical to close those stations that will have the least impact on the ability of the fire manager to assess overall fire danger, it is desirable to know if there is duplication in monitoring fire climate, and to what degree. A method is proposed...

Designing optimized multi-species monitoring networks to detect range shifts driven by climate change: a case study with bats in the North of Portugal.

PubMed

Amorim, Francisco; Carvalho, Sílvia B; Honrado, João; Rebelo, Hugo

2014-01-01

Here we develop a framework to design multi-species monitoring networks using species distribution models and conservation planning tools to optimize the location of monitoring stations to detect potential range shifts driven by climate change. For this study, we focused on seven bat species in Northern Portugal (Western Europe). Maximum entropy modelling was used to predict the likely occurrence of those species under present and future climatic conditions. By comparing present and future predicted distributions, we identified areas where each species is likely to gain, lose or maintain suitable climatic space. We then used a decision support tool (the Marxan software) to design three optimized monitoring networks considering: a) changes in species likely occurrence, b) species conservation status, and c) level of volunteer commitment. For present climatic conditions, species distribution models revealed that areas suitable for most species occur in the north-eastern part of the region. However, areas predicted to become climatically suitable in the future shifted towards west. The three simulated monitoring networks, adaptable for an unpredictable volunteer commitment, included 28, 54 and 110 sampling locations respectively, distributed across the study area and covering the potential full range of conditions where species range shifts may occur. Our results show that our framework outperforms the traditional approach that only considers current species ranges, in allocating monitoring stations distributed across different categories of predicted shifts in species distributions. This study presents a straightforward framework to design monitoring schemes aimed specifically at testing hypotheses about where and when species ranges may shift with climatic changes, while also ensuring surveillance of general population trends.

Analysis of surface-water data network in Kansas for effectiveness in providing regional streamflow information; with a section on theory and application of generalized least squares

USGS Publications Warehouse

Medina, K.D.; Tasker, Gary D.

1987-01-01

This report documents the results of an analysis of the surface-water data network in Kansas for its effectiveness in providing regional streamflow information. The network was analyzed using generalized least squares regression. The correlation and time-sampling error of the streamflow characteristic are considered in the generalized least squares method. Unregulated medium-, low-, and high-flow characteristics were selected to be representative of the regional information that can be obtained from streamflow-gaging-station records for use in evaluating the effectiveness of continuing the present network stations, discontinuing some stations, and (or) adding new stations. The analysis used streamflow records for all currently operated stations that were not affected by regulation and for discontinued stations for which unregulated flow characteristics, as well as physical and climatic characteristics, were available. The State was divided into three network areas, western, northeastern, and southeastern Kansas, and analysis was made for the three streamflow characteristics in each area, using three planning horizons. The analysis showed that the maximum reduction of sampling mean-square error for each cost level could be obtained by adding new stations and discontinuing some current network stations. Large reductions in sampling mean-square error for low-flow information could be achieved in all three network areas, the reduction in western Kansas being the most dramatic. The addition of new stations would be most beneficial for mean-flow information in western Kansas. The reduction of sampling mean-square error for high-flow information would benefit most from the addition of new stations in western Kansas. Southeastern Kansas showed the smallest error reduction in high-flow information. A comparison among all three network areas indicated that funding resources could be most effectively used by discontinuing more stations in northeastern and southeastern Kansas and establishing more new stations in western Kansas.

Two Long-Term Instrumental Climatic Data Bases of the People's Republic of China (1997)

DOE Data Explorer

Shiyan, T. [Chinese Academy of Sciences (CAS), Beijing (China); Congbin, Fu [Chinese Academy of Sciences (CAS), Beijing (China); Zhaomei, Zeng [Chinese Academy of Sciences (CAS), Beijing (China); Qingyun, Zhang [Chinese Academy of Sciences (CAS), Beijing (China); Kaiser, D. P.

1991-01-01

Two long-term instrumental data bases containing meteorological observations from the People's Republic of China (PRC) are presented in this NDP . The first version of this database was made available in 1991 by the Carbon Dioxide Information Analysis Center (CDIAC) as CDIAC NDP-039. This update of the database includes data through 1993. These data sets were compiled in accordance with a joint research agreement signed by the U.S. Department of Energy and the PRC Chinese Academy of Sciences (CAS) on August 19, 1987. CAS has provided records from 267 stations, partitioned into two networks of 65 and 205 stations, with three stations common to both data bases. The 65-station-network data contain monthly means, extremes, or totals of barometric pressure, air temperature, precipitation amount, relative humidity, sunshine duration, cloud amount, dominant wind direction and frequency, wind speed, and number of days with snow cover. Station histories are available from 59 of the 65 stations. The 205-station-network data contain monthly mean temperatures and monthly precipitation totals; however, station histories are not currently available. Sixteen stations from these data sets (13 from the 65-station, 3 from the 205-station) have temperature and/or precipitation records beginning before 1900, whereas the remaining stations began observing in the early to mid-1900s.

Impacts and societal benefits of research activities at Summit Station, Greenland

NASA Astrophysics Data System (ADS)

Hawley, R. L.; Burkhart, J. F.; Courville, Z.; Dibb, J. E.; Koenig, L.; Vaughn, B. H.

2017-12-01

Summit Station began as the site for the Greenland Ice Sheet Project 2 ice core in 1989. Since then, it has hosted both summer campaign science, and since 1997, year-round observations of atmospheric and cryospheric processes. The station has been continuously occupied since 2003. While most of the science activities at the station are supported by the US NSF Office of Polar Programs, the station also hosts many interagency and international investigations in physical glaciology, atmospheric chemistry, satellite validation, astrophysics and other disciplines. Summit is the only high elevation observatory north of the Arctic circle that can provide clean air or snow sites. The station is part of the INTER-ACT consortium of Arctic research stations with the main objective to identify, understand, predict and respond to diverse environmental changes, and part of the International Arctic Systems for Observing the Atmosphere (IASOA) that coordinates Arctic research activities and provides a networked, observations-based view of the Arctic. The Summit Station Science Summit, sponsored by NSF, assembled a multidisciplinary group of scientists to review Summit Station science, define the leading research questions for Summit, and make community-based recommendations for future science goals and governance for Summit. The impact of several on-going observation records was summarized in the report "Sustaining the Science Impact of Summit Station, Greenland," including the use of station data in weather forecasts and climate models. Observations made at the station as part of long-term, year-round research or during shorter summer-only campaign seasons contribute to several of the identified Social Benefit Areas (SBAs) outlined in the International Arctic Observations Assessment Framework published by the IDA Science and Technology Policy Institute and Sustaining Arctic Observing Networks as an outcome of the 2016 Arctic Science Ministerial. The SBAs supported by research conducted at Summit include Fundamental Understanding of Arctic Systems, Infrastructure and Operations, Terrestrial and Freshwater Ecosystems and Processes and Weather and Climate. Future efforts at maintaining the station's long-term climate record will focus on these areas, as identified in the Summit Station Science Summit report.

Analysis of surface-water data network in Kansas for effectiveness in providing regional streamflow information

USGS Publications Warehouse

Medina, K.D.; Tasker, Gary D.

1985-01-01

The surface water data network in Kansas was analyzed using generalized least squares regression for its effectiveness in providing regional streamflow information. The correlation and time-sampling error of the streamflow characteristic are considered in the generalized least squares method. Unregulated medium-flow, low-flow and high-flow characteristics were selected to be representative of the regional information that can be obtained from streamflow gaging station records for use in evaluating the effectiveness of continuing the present network stations, discontinuing some stations; and/or adding new stations. The analysis used streamflow records for all currently operated stations that were not affected by regulation and discontinued stations for which unregulated flow characteristics , as well as physical and climatic characteristics, were available. The state was divided into three network areas, western, northeastern, and southeastern Kansas, and analysis was made for three streamflow characteristics in each area, using three planning horizons. The analysis showed that the maximum reduction of sampling mean square error for each cost level could be obtained by adding new stations and discontinuing some of the present network stations. Large reductions in sampling mean square error for low-flow information could be accomplished in all three network areas, with western Kansas having the most dramatic reduction. The addition of new stations would be most beneficial for man- flow information in western Kansas, and to lesser degrees in the other two areas. The reduction of sampling mean square error for high-flow information would benefit most from the addition of new stations in western Kansas, and the effect diminishes to lesser degrees in the other two areas. Southeastern Kansas showed the smallest error reduction in high-flow information. A comparison among all three network areas indicated that funding resources could be most effectively used by discontinuing more stations in northeastern and southeastern Kansas and establishing more new stations in western Kansas. (Author 's abstract)

Daily Temperature and Precipitation Data for 518 Russian Meteorological Stations (1881 - 2010)

DOE Data Explorer

Bulygina, O. N. [All-Russian Research Institute of Hydrometeorological Information-World Data Centre; Razuvaev, V. N. [All-Russian Research Institute of Hydrometeorological Information-World Data Centre

2012-01-01

Over the past several decades, many climate datasets have been exchanged directly between the principal climate data centers of the United States (NOAA's National Climatic Data Center (NCDC)) and the former-USSR/Russia (All-Russian Research Institute for Hydrometeorological Information-World Data Center (RIHMI-WDC)). This data exchange has its roots in a bilateral initiative known as the Agreement on Protection of the Environment (Tatusko 1990). CDIAC has partnered with NCDC and RIHMI-WDC since the early 1990s to help make former-USSR climate datasets available to the public. The first former-USSR daily temperature and precipitation dataset released by CDIAC was initially created within the framework of the international cooperation between RIHMI-WDC and CDIAC and was published by CDIAC as NDP-040, consisting of data from 223 stations over the former USSR whose data were published in USSR Meteorological Monthly (Part 1: Daily Data). The database presented here consists of records from 518 Russian stations (excluding the former-USSR stations outside the Russian territory contained in NDP-040), for the most part extending through 2010. Records not extending through 2010 result from stations having closed or else their data were not published in Meteorological Monthly of CIS Stations (Part 1: Daily Data). The database was created from the digital media of the State Data Holding. The station inventory was arrived at using (a) the list of Roshydromet stations that are included in the Global Climate Observation Network (this list was approved by the Head of Roshydromet on 25 March 2004) and (b) the list of Roshydromet benchmark meteorological stations prepared by V.I. Kodratyuk, Head of the Department at Voeikov Main Geophysical Observatory.

Amplification or suppression: Social networks and the climate change-migration association in rural Mexico.

PubMed

Nawrotzki, Raphael J; Riosmena, Fernando; Hunter, Lori M; Runfola, Daniel M

2015-11-01

Increasing rates of climate migration may be of economic and national concern to sending and destination countries. It has been argued that social networks - the ties connecting an origin and destination - may operate as "migration corridors" with the potential to strongly facilitate climate change-related migration. This study investigates whether social networks at the household and community levels amplify or suppress the impact of climate change on international migration from rural Mexico. A novel set of 15 climate change indices was generated based on daily temperature and precipitation data for 214 weather stations across Mexico. Employing geostatistical interpolation techniques, the climate change values were linked to 68 rural municipalities for which sociodemographic data and detailed migration histories were available from the Mexican Migration Project. Multi-level discrete-time event-history models were used to investigate the effect of climate change on international migration between 1986 and 1999. At the household level, the effect of social networks was approximated by comparing the first to the last move, assuming that through the first move a household establishes internal social capital. At the community level, the impact of social capital was explored through interactions with a measure of the proportion of adults with migration experience. The results show that rather than amplifying , social capital may suppress the sensitivity of migration to climate triggers, suggesting that social networks could facilitate climate change adaptation in place.

GPS IPW as a Meteorological Parameter and Climate Global Change Indicator

NASA Astrophysics Data System (ADS)

Kruczyk, M.; Liwosz, T.

2011-12-01

Paper focuses on comprehensive investigation of the GPS derived IPW (Integrated Precipitable Water, also IWV) as a geophysical tool. GPS meteorology is now widely acknowledged indirect method of atmosphere sensing. First we demonstrate GPS IPW quality. Most thorough inter-technique comparisons of directly measured IPW are attainable only for some observatories (note modest percentage of GPS stations equipped with meteorological devices). Nonetheless we have managed to compare IPW series derived from GPS tropospheric solutions (ZTD mostly from IGS and EPN solutions) and some independent techniques. IPW values from meteorological sources we used are: radiosoundings, sun photometer and input fields of numerical weather prediction model. We can treat operational NWP models as meteorological database within which we can calculate IWV for all GPS stations independently from network of direct measurements (COSMO-LM model maintained by Polish Institute of Meteorology and Water Management was tried). Sunphotometer (CIMEL-318, Central Geophysical Observatory IGF PAS, Belsk, Poland) data seems the most genuine source - so we decided for direct collocation of GPS measurements and sunphotometer placing permanent GPS receiver on the roof of Belsk Observatory. Next we analyse IPW as geophysical parameter: IPW demonstrates some physical effects evoked by station location (height and series correlation coefficient as a function of distance) and weather patterns like dominant wind directions (in case of neighbouring stations). Deficiency of surface humidity data to model IPW is presented for different climates. This inadequacy and poor humidity data representation in NWP model extremely encourages investigating information exchange potential between Numerical Model and GPS network. The second and most important aspect of this study concerns long series of IPW (daily averaged) which can serve as climatological information indicator (water vapour role in climate system is hard to exaggerate). Especially intriguing are relatively unique shape of such series in different climates. Long lasting changes in weather conditions: 'dry' and 'wet' years are also visible. The longer and more uniform our series are the better chance to estimate the magnitude of climatological IWV changes. Homogenous ZTD solution during long period is great concern in this approach (problems with GPS strategy and reference system changes). In case of continental network (EUREF Permanent Network) reliable data we get only after reprocessing. Simple sinusoidal model has been adjusted to the IPW series (LS method) for selected stations (mainly Europe but also other continents - IGS stations), every year separately. Not only amplitudes but also phases of annual signal differ from year to year. Longer IPW series (up to 14 years) searched for some climatological signal sometimes reveal weak steady trend. Large number of GPS permanent stations, relative easiness of IPW derivation (only and surface meteo data needed apart from GPS solution) and water vapour significance in water cycle and global climate make this GPS IPW promising element of global environmental change monitoring.

Bus network redesign for inner southeast suburbs of Melbourne, Australia

NASA Astrophysics Data System (ADS)

Pandangwati, S. T.; Milyanab, N. A.

2017-06-01

Public transport is the most effective mode of transport in the era of climate change and oil depletion. It can address climate change issues by reducing urban greenhouse gas emission and oil consumption while at the same time improving mobility. However, many public transport networks are not effective and instead create high operating costs with low frequencies and occupancy. Melbourne is one example of a metropolitan area that faces this problem. Even though the city has well-integrated train and tram networks, Melbourne’s bus network still needs to be improved. This study used network planning approach to redesign the bus network in the City of Glen Eira, a Local Government Area (LGA) in the southeastern part of Metropolitan Melbourne. The study area is the area between Gardenvale North and Oakleigh Station, as well as between Caulfield and Patterson Stations. This area needs network improvement mainly because of the meandering bus routes that run within it. This study aims to provide recommendations for improving the performance of bus services by reducing meandering routes, improving transfer point design and implementing coordinated timetables. The recommendations were formulated based on a ‘ready-made’ concept to increase bus occupancy. This approach can be implemented in other cities with similar problems and characteristics including those in Indonesia.

Impact of automatization in temperature series in Spain and comparison with the POST-AWS dataset

NASA Astrophysics Data System (ADS)

Aguilar, Enric; López-Díaz, José Antonio; Prohom Duran, Marc; Gilabert, Alba; Luna Rico, Yolanda; Venema, Victor; Auchmann, Renate; Stepanek, Petr; Brandsma, Theo

2016-04-01

Climate data records are most of the times affected by inhomogeneities. Especially inhomogeneities introducing network-wide biases are sometimes related to changes happening almost simultaneously in an entire network. Relative homogenization is difficult in these cases, especially at the daily scale. A good example of this is the substitution of manual observations (MAN) by automatic weather stations (AWS). Parallel measurements (i.e. records taken at the same time with the old (MAN) and new (AWS) sensors can provide an idea of the bias introduced and help to evaluate the suitability of different correction approaches. We present here a quality controlled dataset compiled under the DAAMEC Project, comprising 46 stations across Spain and over 85,000 parallel measurements (AWS-MAN) of daily maximum and minimum temperature. We study the differences between both sensors and compare it with the available metadata to account for internal inhomogeneities. The differences between both systems vary much across stations, with patterns more related to their particular settings than to climatic/geographical reasons. The typical median biases (AWS-MAN) by station (comprised between the interquartile range) oscillate between -0.2°C and 0.4 in daily maximum temperature and between -0.4°C and 0.2°C in daily minimum temperature. These and other results are compared with a larger network, the Parallel Observations Scientific Team, a working group of the International Surface Temperatures Initiative (ISTI-POST) dataset, which comprises our stations, as well as others from different countries in America, Asia and Europe.

Amplification or suppression: Social networks and the climate change—migration association in rural Mexico

PubMed Central

Riosmena, Fernando; Hunter, Lori M.; Runfola, Daniel M.

2015-01-01

Increasing rates of climate migration may be of economic and national concern to sending and destination countries. It has been argued that social networks – the ties connecting an origin and destination – may operate as “migration corridors” with the potential to strongly facilitate climate change-related migration. This study investigates whether social networks at the household and community levels amplify or suppress the impact of climate change on international migration from rural Mexico. A novel set of 15 climate change indices was generated based on daily temperature and precipitation data for 214 weather stations across Mexico. Employing geostatistical interpolation techniques, the climate change values were linked to 68 rural municipalities for which sociodemographic data and detailed migration histories were available from the Mexican Migration Project. Multi-level discrete-time event-history models were used to investigate the effect of climate change on international migration between 1986 and 1999. At the household level, the effect of social networks was approximated by comparing the first to the last move, assuming that through the first move a household establishes internal social capital. At the community level, the impact of social capital was explored through interactions with a measure of the proportion of adults with migration experience. The results show that rather than amplifying, social capital may suppress the sensitivity of migration to climate triggers, suggesting that social networks could facilitate climate change adaptation in place. PMID:26692656

Small-scale variations of climate change in mountainous forested terrain - a regional study from H.J. Andrews Long Term Ecological Research site in Oregon, USA

NASA Astrophysics Data System (ADS)

Honzakova, Katerina; Hoffmann, Peter; Jones, Julia; Thomas, Christoph

2017-04-01

There has been conflicting evidence as to whether high elevations are experiencing more pronounced climate warming than lower elevations in mountainous regions. In this study we analyze temperature records from H.J. Andrews Long Term Ecological Research, Oregon, USA and several nearby areas, comprising together 28 stations located in Cascade Mountains. The data, starting in 1958, are first checked for quality and homogenized using the Standard Normal Homogeneity Test. As a reference, composite climate time series based on the Global Historic Climate Network is created and together with cross-referencing against station records used to correct breaks and shifts in the data. In the next step, we investigate temperature patterns of the study site from 1958 to 2016 and compare them for valley and hill stations. In particular, we explore seasonality and inter-annual variability of the records and trends of the last day of frost. Additionally, 'cold' sums (positive and negative) are calculated to obtain a link between temperature and ecosystems' responses (such as budbreaks). So far, valley stations seem to be more prone to climate change than ridge or summit stations, contrary to current thinking. Building on previous knowledge, we attempt to provide physical explanations for the temperature records, focusing on wind patterns and associated phenomena such as cold air drainage and pooling. To aid this we analyze wind speed and direction data available for some of the stations since 1996, including seasonality and inter-annual variability of the observed flows.

The Pascal Mars Scout Mission

NASA Technical Reports Server (NTRS)

Haberle, R. M.; Fonda, Mark (Technical Monitor)

2002-01-01

Except for Earth, Mars is the planet most amenable to surface-based climate studies. Its surface is accessible, and the kind of observations that are needed, such as meteorological measurements from a long-lived global network, are readily achievable. Weather controls the movement of dust, the exchange of water between the surface and atmosphere, and the cycling of CO2 between the poles. We know there is a weather signal, we know how to measure it, and we know how to interpret it. Pascal seeks to understand the long-term global behavior of near-surface weather systems on Mars, how they interact with its surface, and, therefore, how they control its climate system. To achieve this, Pascal delivers 18 Science Stations to the surface of the planet that operate for three Mars years (5.6 Earth years). The network has stations operating in the tropics, midlatitudes, and polar regions of both hemispheres. During entry, descent, and landing, each Pascal probe acquires deceleration measurements to determine thermal structure, and descent images to characterize local terrain. On the surface, each Science Station takes daily measurements of pressure, opacity, temperature, wind speed, and water vapor concentration and monthly panoramic images of the landing environment. These data will characterize the planet's climate system and how atmosphere-surface interactions control it. The Pascal mission is named after 17th century French Scientist, Blaise Pascal, who pioneered measurements of atmospheric pressure. Pressure is the most critical measurement because it records the "heartbeat" of the planet's general circulation and climate system.

A spatiotemporal analysis of U.S. station temperature trends over the last century

NASA Astrophysics Data System (ADS)

Capparelli, V.; Franzke, C.; Vecchio, A.; Freeman, M. P.; Watkins, N. W.; Carbone, V.

2013-07-01

This study presents a nonlinear spatiotemporal analysis of 1167 station temperature records from the United States Historical Climatology Network covering the period from 1898 through 2008. We use the empirical mode decomposition method to extract the generally nonlinear trends of each station. The statistical significance of each trend is assessed against three null models of the background climate variability, represented by stochastic processes of increasing temporal correlation length. We find strong evidence that more than 50% of all stations experienced a significant trend over the last century with respect to all three null models. A spatiotemporal analysis reveals a significant cooling trend in the South-East and significant warming trends in the rest of the contiguous U.S. It also shows that the warming trend appears to have migrated equatorward. This shows the complex spatiotemporal evolution of climate change at local scales.

Identifying a base network of federally funded streamgaging stations

USGS Publications Warehouse

Ries, Kernell G.; Kolva, J.R.; Stewart, D.W.

2004-01-01

The U.S. Geological Survey (USGS) has completed a preliminary analysis to identify streamgaging stations needed in a base network that would satisfy five primary Federal goals for collecting streamflow information. The five goals are (1) determining streamflow at interstate and international borders and at locations mandated by court decrees, (2) determining the streamflow component of water budgets for the major river basins of the Nation, (3) providing real-time streamflow information to the U.S. National Weather Service to support flood-forecasting activities, (4) providing streamflow information at locations of monitoring stations included in USGS national water-quality networks, and (5) providing streamflow information necessary for regionalization of streamflow characteristics and assessing potential long-term trends in streamflow associated with changes in climate. The analysis was done using a Geographic Information System. USGS headquarters staff made initial selections of stations that satisfied at least one of the five goals, and then staff in each of the 48 USGS district offices reviewed the selections, making suggestions for additions or changes based on detailed local knowledge of the streams in the area. The analysis indicated that 4,242 streamgaging stations are needed in the base network to meet the 5 Federal goals for streamflow information. Of these, 2,692 stations (63.5 percent) are currently operated by the USGS, 277 stations (6.5 percent) are currently operated by other agencies, 865 (20.4 percent) are discontinued USGS stations that need to be reactivated, and 408 (9.6 percent) are locations where new stations are needed. Copyright ASCE 2004.

Using crowdsourced data from citizen weather stations to analyse air temperature in 'local climate zones' in Berlin, Germany

NASA Astrophysics Data System (ADS)

Fenner, Daniel; Meier, Fred; Bechtel, Benjamin; Otto, Marco; Scherer, Dieter

2017-04-01

Provision of observational data with high spatial coverage over extended time periods still remains as one of the biggest challenges in urban climate research. Classical meteorological networks are seldomly designed to monitor atmospheric conditions in a broad variety of urban environments, though the heterogeneity of urban structures leads to distinct thermal characteristics on local scales, i.e., hundreds of metres to several kilometres. One approach to overcome the aforementioned challenges of observation networks is to use data from weather stations that are maintained by citizens. The private company 'netatmo' (www.netatmo.com) produces and distributes such citizen weather stations (CWS) around the world. The stations automatically send their data to the netatmo server, and the user decides if data are publicly shared. Shared data can freely be retrieved via an application programming interface. We collected air temperature (T) data for the year 2015 for the city of Berlin, Germany, and surroundings with more than 1500 'netatmo' CWS in the study area. The entire data set was thoroughly quality checked, and filter techniques, involving data from a reference network, were developed to address different types of errors associated with CWS data. Additionally, the accuracy of 'netatmo' CWS was checked in a climate chamber and in a long-term field experiment. Since the terms 'urban' and 'rural' are ambiguous in urban climate studies, Stewart and Oke (2012) developed the 'local climate zone' (LCZ) concept to enhance understanding and interpretation of air temperature differences in urban regions. LCZ classification for the study region was conducted using the 'WUDAPT' approach by Bechtel et al. (2015). The quality-checked CWS data were used to analyse T characteristics of LCZ classes in Berlin and surroundings. Specifically, we analysed how LCZ classes are represented by CWS in 2015, how T varies within each LCZ class ('intra-LCZ variability'), and if significant differences can be detected between LCZ classes ('inter-LCZ differences'). Results show that most 'built-up' LCZ classes in the study region are represented by CWS, while only few CWS are located in 'natural' LCZ classes (i.e. in inner-city parks or in rural areas). T as measured by CWS showed overall good agreement with data from a network of professional weather stations throughout the year, though for some LCZ classes mean monthly deviations were up to 1 K. Intra-LCZ variability of T was especially pronounced during night-time hours and during summer months. We found significant inter-LCZ differences in T mainly for dissimilar LCZ classes and during night-time. Our results indicate the suitability of CWS data for T monitoring of specific LCZ classes and the applicability of this data set for further scientific research. Bechtel, B., P. J. Alexander, J. Böhner, J. Ching, O. Conrad, J. Feddema, G. Mills, L. See, and I. D. Stewart (2015): Mapping Local Climate Zones for a Worldwide Database of the Form and Function of Cities. ISPRS Int. J. Geo-Inf. 4: 199-219 Stewart, I. D. and T. R. Oke (2012): Local climate zones for urban temperature studies. Bull. Amer. Meteor. Soc. 93 (12): 1879-1900

Optimizing Placement of Weather Stations: Exploring Objective Functions of Meaningful Combinations of Multiple Weather Variables

NASA Astrophysics Data System (ADS)

Snyder, A.; Dietterich, T.; Selker, J. S.

2017-12-01

Many regions of the world lack ground-based weather data due to inadequate or unreliable weather station networks. For example, most countries in Sub-Saharan Africa have unreliable, sparse networks of weather stations. The absence of these data can have consequences on weather forecasting, prediction of severe weather events, agricultural planning, and climate change monitoring. The Trans-African Hydro-Meteorological Observatory (TAHMO.org) project seeks to address these problems by deploying and operating a large network of weather stations throughout Sub-Saharan Africa. To design the TAHMO network, we must determine where to place weather stations within each country. We should consider how we can create accurate spatio-temporal maps of weather data and how to balance the desired accuracy of each weather variable of interest (precipitation, temperature, relative humidity, etc.). We can express this problem as a joint optimization of multiple weather variables, given a fixed number of weather stations. We use reanalysis data as the best representation of the "true" weather patterns that occur in the region of interest. For each possible combination of sites, we interpolate the reanalysis data between selected locations and calculate the mean average error between the reanalysis ("true") data and the interpolated data. In order to formulate our multi-variate optimization problem, we explore different methods of weighting each weather variable in our objective function. These methods include systematic variation of weights to determine which weather variables have the strongest influence on the network design, as well as combinations targeted for specific purposes. For example, we can use computed evapotranspiration as a metric that combines many weather variables in a way that is meaningful for agricultural and hydrological applications. We compare the errors of the weather station networks produced by each optimization problem formulation. We also compare these errors to those of manually designed weather station networks in West Africa, planned by the respective host-country's meteorological agency.

A stream-gaging network analysis for the 7-day, 10-year annual low flow in New Hampshire streams

USGS Publications Warehouse

Flynn, Robert H.

2003-01-01

The 7-day, 10-year (7Q10) low-flow-frequency statistic is a widely used measure of surface-water availability in New Hampshire. Regression equations and basin-characteristic digital data sets were developed to help water-resource managers determine surface-water resources during periods of low flow in New Hampshire streams. These regression equations and data sets were developed to estimate streamflow statistics for the annual and seasonal low-flow-frequency, and period-of-record and seasonal period-of-record flow durations. generalized-least-squares (GLS) regression methods were used to develop the annual 7Q10 low-flow-frequency regression equation from 60 continuous-record stream-gaging stations in New Hampshire and in neighboring States. In the regression equation, the dependent variables were the annual 7Q10 flows at the 60 stream-gaging stations. The independent (or predictor) variables were objectively selected characteristics of the drainage basins that contribute flow to those stations. In contrast to ordinary-least-squares (OLS) regression analysis, GLS-developed estimating equations account for differences in length of record and spatial correlations among the flow-frequency statistics at the various stations.A total of 93 measurable drainage-basin characteristics were candidate independent variables. On the basis of several statistical parameters that were used to evaluate which combination of basin characteristics contribute the most to the predictive power of the equations, three drainage-basin characteristics were determined to be statistically significant predictors of the annual 7Q10: (1) total drainage area, (2) mean summer stream-gaging station precipitation from 1961 to 90, and (3) average mean annual basinwide temperature from 1961 to 1990.To evaluate the effectiveness of the stream-gaging network in providing regional streamflow data for the annual 7Q10, the computer program GLSNET (generalized-least-squares NETwork) was used to analyze the network by application of GLS regression between streamflow and the climatic and basin characteristics of the drainage basin upstream from each stream-gaging station. Improvement to the predictive ability of the regression equations developed for the network analyses is measured by the reduction in the average sampling-error variance, and can be achieved by collecting additional streamflow data at existing stations. The predictive ability of the regression equations is enhanced even further with the addition of new stations to the network. Continued data collection at unregulated stream-gaging stations with less than 14 years of record resulted in the greatest cost-weighted reduction to the average sampling-error variance of the annual 7Q10 regional regression equation. The addition of new stations in basins with underrepresented values for the independent variables of the total drainage area, average mean annual basinwide temperature, or mean summer stream-gaging station precipitation in the annual 7Q10 regression equation yielded a much greater cost-weighted reduction to the average sampling-error variance than when more data were collected at existing unregulated stations. To maximize the regional information obtained from the stream-gaging network for the annual 7Q10, ranking of the streamflow data can be used to determine whether an active station should be continued or if a new or discontinued station should be activated for streamflow data collection. Thus, this network analysis can help determine the costs and benefits of continuing the operation of a particular station or activating a new station at another location to predict the 7Q10 at ungaged stream reaches. The decision to discontinue an existing station or activate a new station, however, must also consider its contribution to other water-resource analyses such as flood management, water quality, or trends in land use or climatic change.

Assessing measurement uncertainty in meteorology in urban environments

NASA Astrophysics Data System (ADS)

Curci, S.; Lavecchia, C.; Frustaci, G.; Paolini, R.; Pilati, S.; Paganelli, C.

2017-10-01

Measurement uncertainty in meteorology has been addressed in a number of recent projects. In urban environments, uncertainty is also affected by local effects which are more difficult to deal with than for synoptic stations. In Italy, beginning in 2010, an urban meteorological network (Climate Network®) was designed, set up and managed at national level according to high metrological standards and homogeneity criteria to support energy applications. The availability of such a high-quality operative automatic weather station network represents an opportunity to investigate the effects of station siting and sensor exposure and to estimate the related measurement uncertainty. An extended metadata set was established for the stations in Milan, including siting and exposure details. Statistical analysis on an almost 3-year-long operational period assessed network homogeneity, quality and reliability. Deviations from reference mean values were then evaluated in selected low-gradient local weather situations in order to investigate siting and exposure effects. In this paper the methodology is depicted and preliminary results of its application to air temperature discussed; this allowed the setting of an upper limit of 1 °C for the added measurement uncertainty at the top of the urban canopy layer.

Pan-Arctic river discharge: Prioritizing monitoring of future climate change hot spots

NASA Astrophysics Data System (ADS)

Bring, Arvid; Shiklomanov, Alexander; Lammers, Richard B.

2017-01-01

The Arctic freshwater cycle is changing rapidly, which will require adequate monitoring of river flows to detect, observe, and understand changes and provide adaptation information. There has, however, been little detail about where the greatest flow changes are projected, and where monitoring therefore may need to be strengthened. In this study, we used a set of recent climate model runs and an advanced macro-scale hydrological model to analyze how flows across the continental pan-Arctic are projected to change and where the climate models agree on significant changes. We also developed a method to identify where monitoring stations should be placed to observe these significant changes, and compared this set of suggested locations with the existing network of monitoring stations. Overall, our results reinforce earlier indications of large increases in flow over much of the Arctic, but we also identify some areas where projections agree on significant changes but disagree on the sign of change. For monitoring, central and eastern Siberia, Alaska, and central Canada are hot spots for the highest changes. To take advantage of existing networks, a number of stations across central Canada and western and central Siberia could form a prioritized set. Further development of model representation of high-latitude hydrology would improve confidence in the areas we identify here. Nevertheless, ongoing observation programs may consider these suggested locations in efforts to improve monitoring of the rapidly changing Arctic freshwater cycle.

Automated general temperature correction method for dielectric soil moisture sensors

NASA Astrophysics Data System (ADS)

Kapilaratne, R. G. C. Jeewantinie; Lu, Minjiao

2017-08-01

An effective temperature correction method for dielectric sensors is important to ensure the accuracy of soil water content (SWC) measurements of local to regional-scale soil moisture monitoring networks. These networks are extensively using highly temperature sensitive dielectric sensors due to their low cost, ease of use and less power consumption. Yet there is no general temperature correction method for dielectric sensors, instead sensor or site dependent correction algorithms are employed. Such methods become ineffective at soil moisture monitoring networks with different sensor setups and those that cover diverse climatic conditions and soil types. This study attempted to develop a general temperature correction method for dielectric sensors which can be commonly used regardless of the differences in sensor type, climatic conditions and soil type without rainfall data. In this work an automated general temperature correction method was developed by adopting previously developed temperature correction algorithms using time domain reflectometry (TDR) measurements to ThetaProbe ML2X, Stevens Hydra probe II and Decagon Devices EC-TM sensor measurements. The rainy day effects removal procedure from SWC data was automated by incorporating a statistical inference technique with temperature correction algorithms. The temperature correction method was evaluated using 34 stations from the International Soil Moisture Monitoring Network and another nine stations from a local soil moisture monitoring network in Mongolia. Soil moisture monitoring networks used in this study cover four major climates and six major soil types. Results indicated that the automated temperature correction algorithms developed in this study can eliminate temperature effects from dielectric sensor measurements successfully even without on-site rainfall data. Furthermore, it has been found that actual daily average of SWC has been changed due to temperature effects of dielectric sensors with a significant error factor comparable to ±1% manufacturer's accuracy.

The World Radiation Monitoring Center of the Baseline Surface Radiation Network: Status 2017

NASA Astrophysics Data System (ADS)

Driemel, Amelie; König-Langlo, Gert; Sieger, Rainer; Long, Charles N.

2017-04-01

The World Radiation Monitoring Center (WRMC) is the central archive of the Baseline Surface Radiation Network (BSRN). The BSRN was initiated by the World Climate Research Programme (WCRP) Working Group on Radiative Fluxes and began operations in 1992. One of its aims is to provide short and long-wave surface radiation fluxes of the best possible quality to support the research projects of the WCRP and other scientific projects. The high quality, uniform and consistent measurements of the BSRN network can be used to monitor the short- and long-wave radiative components and their changes with the best methods currently available, to validate and evaluate satellite-based estimates of the surface radiative fluxes, and to verify the results of global climate models. In 1992 the BSRN/WRMC started at ETH Zurich, Switzerland with 9 stations. Since 2007 the archive is hosted by the Alfred-Wegener-Institut (AWI) in Bremerhaven, Germany (http://www.bsrn.awi.de/) and comprises a network of currently 59 stations in contrasting climatic zones, covering a latitude range from 80°N to 90°S. Of the 59 stations, 23 offer the complete radiation budget (down- and upwelling short- and long-wave data). In addition to the ftp-service access instituted at ETH Zurich, the archive at AWI offers data access via PANGAEA - Data Publisher for Earth & Environmental Science (https://www.pangaea.de). PANGAEA guarantees the long-term availability of its content through a commitment of the operating institutions. Within PANGAEA, the metadata of the stations are freely available. To access the data itself an account is required. If the scientist accepts to follow the data release guidelines of the archive (http://bsrn.awi.de/data/conditions-of-data-release/) he or she can get an account from amelie.driemel@awi.de. Currently, more than 9,400 station months (>780 years) are available for interested scientists (see also https://dataportals.pangaea.de/bsrn/?q=LR0100 for an overview on available data). After long years of excellent service as the director of the WRMC, Gert-König Langlo retires in 2017. He is handing over the duties to the current WRMC data curator Amelie Driemel who will continue this important task in the years to come.

The GCOS Reference Upper-Air Network (GRUAN)

NASA Astrophysics Data System (ADS)

Vömel, H.; Berger, F. H.; Immler, F. J.; Seidel, D.; Thorne, P.

2009-04-01

While the global upper-air observing network has provided useful observations for operational weather forecasting for decades, its measurements lack the accuracy and long-term continuity needed for understanding climate change. Consequently, the scientific community faces uncertainty on such key issues as the trends of temperature in the upper troposphere and stratosphere or the variability and trends of stratospheric water vapour. To address these shortcomings, and to ensure that future climate records will be more useful than the records to date, the Global Climate Observing System (GCOS) program initiated the GCOS Reference Upper Air Network (GRUAN). GRUAN will be a network of about 30-40 observatories with a representative sampling of geographic regions and surface types. These stations will provide upper-air reference observations of the essential climate variables, i.e. temperature, geopotential, humidity, wind, radiation and cloud properties using specialized radiosondes and complementary remote sensing profiling instrumentation. Long-term stability, quality assurance / quality control, and a detailed assessment of measurement uncertainties will be the key aspects of GRUAN observations. The network will not be globally complete but will serve to constrain and adjust data from more spatially comprehensive global observing systems including satellites and the current radiosonde networks. This paper outlines the scientific rationale for GRUAN, its role in the Global Earth Observation System of Systems, network requirements and likely instrumentation, management structure, current status and future plans.

A Mars Micro-Meteorological Station Mission

NASA Technical Reports Server (NTRS)

Merrihew, Steven C.; Haberle, Robert; Lemke, Lawrence G.

1995-01-01

The Mars Micro-Meteorological Station (Micro-Met) Mission is designed to provide the global surface pressure measurements required to help characterize the martian general circulation and climate system. Measurements of surface pressure distributed both spatially and temporally, coupled with simultaneous measurements from orbit, will enable the determination of the general circulation, structure and driving factors of the martian atmosphere as well as the seasonal CO2 cycle. The influence of these atmospheric factors will in turn provide insight into the overall martian climate system. With the science objective defined as the long term (at least one Mars year) globally distributed measurement of surface atmospheric pressure, a straightforward, near term and low cost network mission has been designed. The Micro-Met mission utilizes a unique silicon micro-machined pressure sensor coupled with a robust and lightweight surface station to deliver to Mars 16 Micro-Met stations via a Med-Lite launch vehicle. The battery powered Micro-Met surface stations are designed to autonomously measure, record and transmit the science data via a UHF relay satellite. Entry, descent and landing is provided by an aeroshell with a new lightweight ceramic thermal protection system, a parachute and an impact absorbing structure. The robust lander is capable of surviving the landing loads imposed by the high altitude landing sites required in a global network. By trading the ability to make many measurements at a single site for the ability to make a single measurement at several sites, the Micro-Met mission design satisfies the requirement for truly global meteorological science.

Integrating Climate and Ecosystem-Response Sciences in Temperate Western North American Mountains: The CIRMOUNT Initiative

NASA Astrophysics Data System (ADS)

Millar, C. I.; Fagre, D. B.

2004-12-01

Mountain regions are uniquely sensitive to changes in climate, vulnerable to climate effects on biotic and physical factors of intense social concern, and serve as critical early-warning systems of climate impacts. Escalating demands on western North American (WNA) mountain ecosystems increasingly stress both natural resources and rural community capacities; changes in mountain systems cascade to issues of national concern. Although WNA has long been a focus for climate- and climate-related environmental research, these efforts remain disciplinary and poorly integrated, hindering interpretation into policy and management. Knowledge is further hampered by lack of standardized climate monitoring stations at high-elevations in WNA. An initiative is emerging as the Consortium for Integrated Climate Research in Western Mountains (CIRMOUNT) whose primary goal is to improve knowledge of high-elevation climate systems and to better integrate physical, ecological, and social sciences relevant to climate change, ecosystem response, and natural-resource policy in WNA. CIRMOUNT seeks to focus research on climate variability and ecosystem response (progress in understanding synoptic scale processes) that improves interpretation of linkages between ecosystem functions and human processing (progress in understanding human-environment integration), which in turn would yield applicable information and understanding on key societal issues such as mountains as water towers, biodiversity, carbon forest sinks, and wildland hazards such as fire and forest dieback (progress in understanding ecosystem services and key thresholds). Achieving such integration depends first on implementing a network of high-elevation climate-monitoring stations, and linking these with integrated ecosystem-response studies. Achievements since 2003 include convening the 2004 Mountain Climate Sciences Symposium (1, 2) and several special sessions at technical conferences; initiating a biennial mountain climate research symposium (MTNCLIM), the first to be held in spring 2005; developing a strategy for climate-monitoring in WNA; installing and networking high-elevation (>3000m) climate-monitoring stations; and completing three target regions (Glacier National Park, MT; Sierra Nevada and White Mountains, CA) of the international GLORIA (Global Observation Research Initiative in Alpine Environments) plant-monitoring project, the first in WNA. CIRMOUNT emphasizes integration at the regional scale in WNA, collaborating with and complementing projects such as the Western Mountain Initiative, whose mandate is more targeted than CIRMOUNT's, and global programs such as GLORIA and the international Mountain Research Initiative. Achievement of continuing success in WNA hinges on the capacity to secure long-term funding and institutional investment. (1) See associated URL for paper and poster pdfs (2) Discussing the future of western U.S. mountains, climate change, and ecosystems. EOS 31 August 2004, 85(35), p. 329

A climate trend analysis of Uganda

USGS Publications Warehouse

Funk, Christopher C.; Rowland, Jim; Eilerts, Gary; White, Libby

2012-01-01

This brief report, drawing from a multi-year effort by the U.S. Agency for International Development (USAID) Famine Early Warning Systems Network (FEWS NET), identifies observed changes in rainfall and temperature in Uganda, based on an analysis of a quality-controlled, long time series of station observations throughout Uganda. Extending recent trends forward, it also provides a current and near-future context for understanding the actual nature of climate change impacts in the country, and a basis for identifying climate adaptations that may protect and improve the country's food security.

Interact - Access to the Arctic

NASA Astrophysics Data System (ADS)

Johansson, M.; Callaghan, T. V.

2013-12-01

INTERACT is currently a network of 50 terrestrial research stations from all Arctic countries, but is still growing. The network was inaugurated in January 2011 when it received an EU 7th Framework award. INTERACT's main objective is to build capacity for identifying, understanding, predicting and responding to diverse environmental changes throughout the wide environmental and land-use envelopes of the Arctic. Implicit in this objective is the task to build capacity for monitoring, research, education and outreach. INTERACT is increasing access to the Arctic: 20 INTERACT research stations in Europe and Russia are offering Transnational Access and so far, 5600 person-days of access have been granted from the total of 10,000 offered. An INTERACT Station Managers' Forum facilitates a dialogue among station managers on subjects such as best practice in station management and standardised monitoring. The Station Managers' Forum has produced a unique 'one-stop-shop' for information from 45 research stations in an informative and attractive Station Catalogue that is available in hard copy and on the INTERACT web site (www.eu-interact.org). INTERACT also includes three joint research activities that are improving monitoring in remote, harsh environments and are making data capture and dissemination more efficient. Already, new equipment for measuring feedbacks from the land surface to the climate system has been installed at several locations, while best practices for sensor networking have been established. INTERACT networks with most of the high-level Arctic organisations: it includes AMAP and WWF as partners, is endorsed by IASC and CBMP, has signed MoUs with ISAC and the University of the Arctic, is a task within SAON, and contributes to the Cold Region community within GEO/GEOSS. INTERACT welcomes other interactions.

Predicting Thermal Regimes of Stream Networks Across New England: Natural and Anthropogenic Influences

EPA Science Inventory

Thermal regime is a critical factor in models predicting joint effects of watershed management activities and climate change on habitat suitability for fish. We used a database of lotic temperature time series across New England (> 7000 station-year combinations) from state a...

Global, Hemispheric, and Zonal Temperature Deviations Derived From a 63-Station Radiosonde Network

DOE Data Explorer

Angell, J. K. [NOAA, Air Resources Laboratory

2011-01-01

Surface temperatures and thickness-derived temperatures from a 63-station, globally distributed radiosonde network have been used to estimate global, hemispheric, and zonal annual and seasonal temperature deviations. Most of the temperature values used were column-mean temperatures, obtained from the differences in height (thickness) between constant-pressure surfaces at individual radiosonde stations. The pressure-height data before 1980 were obtained from published values in Monthly Climatic Data for the World. Between 1980 and 1990, Angell used data from both the Climatic Data for the World and the Global Telecommunications System (GTS) Network received at the National Meteorological Center. Between 1990 and 1995, the data were obtained only from GTS, and since 1995 the data have been obtained from National Center for Atmospheric Research files. The data are evaluated as deviations from the mean based on the interval 1958-1977. The station deviations have been averaged (with equal weighting) to obtain annual and seasonal temperature deviations for the globe, the Northern and Southern Hemispheres, and the following latitudinal zones: North (60° N-90° N) and South (60° S-90° S) Polar; North (30° N-60° N) and South (30° S-60° S) Temperate; North (10° N-30° N) and South (10° S-30° S) Subtropical; Tropical(30° S-30° N); and Equatorial (10° S-10° N). The seasonal calculations are for the standard meteorological seasons (i.e., winter is defined as December, January, and February; spring is March, April, and May, etc.) and the annual calculations are for December through the following November (i.e., for the four meteorological seasons). For greater details, see Angell and Korshover (1983) and Angell (1988, 1991)

Satellite-based detection of global urban heat-island temperature influence

USGS Publications Warehouse

Gallo, K.P.; Adegoke, Jimmy O.; Owen, T.W.; Elvidge, C.D.

2002-01-01

This study utilizes a satellite-based methodology to assess the urban heat-island influence during warm season months for over 4400 stations included in the Global Historical Climatology Network of climate stations. The methodology includes local and regional satellite retrievals of an indicator of the presence green photosynthetically active vegetation at and around the stations. The difference in local and regional samples of the normalized difference vegetation index (NDVI) is used to estimate differences in mean air temperature. Stations classified as urban averaged 0.90??C (N. Hemisphere) and 0.92??C (S. Hemisphere) warmer than the surrounding environment on the basis of the NDVI-derived temperature estimates. Additionally, stations classified as rural averaged 0.19??C (N. Hemisphere) and 0.16??C (S. Hemisphere) warmer than the surrounding environment. The NDVI-derived temperature estimates were found to be in reasonable agreement with temperature differences observed between climate stations. The results suggest that satellite-derived data sets can be used to estimate the urban heat-island temperature influence on a global basis and that a more detailed analysis of rural stations and their surrounding environment may be necessary to assure that temperature trends derived from assumed rural environments are not influenced by changes in land use/land cover. Copyright 2002 by the American Geophysical Union.

Predicting thermal regimes of stream networks across the Chesapeake Bay Watershed: Natural and anthropogenic influences

EPA Science Inventory

Thermal regimes are a critical factor in models predicting joint effects of watershed management activities and climate change on fish habitat suitability. We have compiled a database of lotic temperature time series across the Chesapeake Bay Watershed (725 station-year combinat...

Greenhouse gas network design using backward Lagrangian particle dispersion modelling - Part 1: Methodology and Australian test case

NASA Astrophysics Data System (ADS)

Ziehn, T.; Nickless, A.; Rayner, P. J.; Law, R. M.; Roff, G.; Fraser, P.

2014-03-01

This paper describes the generation of optimal atmospheric measurement networks for determining carbon dioxide fluxes over Australia using inverse methods. A Lagrangian particle dispersion model is used in reverse mode together with a Bayesian inverse modelling framework to calculate the relationship between weekly surface fluxes and hourly concentration observations for the Australian continent. Meteorological driving fields are provided by the regional version of the Australian Community Climate and Earth System Simulator (ACCESS) at 12 km resolution at an hourly time scale. Prior uncertainties are derived on a weekly time scale for biosphere fluxes and fossil fuel emissions from high resolution BIOS2 model runs and from the Fossil Fuel Data Assimilation System (FFDAS), respectively. The influence from outside the modelled domain is investigated, but proves to be negligible for the network design. Existing ground based measurement stations in Australia are assessed in terms of their ability to constrain local flux estimates from the land. We find that the six stations that are currently operational are already able to reduce the uncertainties on surface flux estimates by about 30%. A candidate list of 59 stations is generated based on logistic constraints and an incremental optimization scheme is used to extend the network of existing stations. In order to achieve an uncertainty reduction of about 50% we need to double the number of measurement stations in Australia. Assuming equal data uncertainties for all sites, new stations would be mainly located in the northern and eastern part of the continent.

Greenhouse gas network design using backward Lagrangian particle dispersion modelling - Part 1: Methodology and Australian test case

NASA Astrophysics Data System (ADS)

Ziehn, T.; Nickless, A.; Rayner, P. J.; Law, R. M.; Roff, G.; Fraser, P.

2014-09-01

This paper describes the generation of optimal atmospheric measurement networks for determining carbon dioxide fluxes over Australia using inverse methods. A Lagrangian particle dispersion model is used in reverse mode together with a Bayesian inverse modelling framework to calculate the relationship between weekly surface fluxes, comprising contributions from the biosphere and fossil fuel combustion, and hourly concentration observations for the Australian continent. Meteorological driving fields are provided by the regional version of the Australian Community Climate and Earth System Simulator (ACCESS) at 12 km resolution at an hourly timescale. Prior uncertainties are derived on a weekly timescale for biosphere fluxes and fossil fuel emissions from high-resolution model runs using the Community Atmosphere Biosphere Land Exchange (CABLE) model and the Fossil Fuel Data Assimilation System (FFDAS) respectively. The influence from outside the modelled domain is investigated, but proves to be negligible for the network design. Existing ground-based measurement stations in Australia are assessed in terms of their ability to constrain local flux estimates from the land. We find that the six stations that are currently operational are already able to reduce the uncertainties on surface flux estimates by about 30%. A candidate list of 59 stations is generated based on logistic constraints and an incremental optimisation scheme is used to extend the network of existing stations. In order to achieve an uncertainty reduction of about 50%, we need to double the number of measurement stations in Australia. Assuming equal data uncertainties for all sites, new stations would be mainly located in the northern and eastern part of the continent.

Geographic patterns and dynamics of Alaskan climate interpolated from a sparse station record

USGS Publications Warehouse

Fleming, Michael D.; Chapin, F. Stuart; Cramer, W.; Hufford, Gary L.; Serreze, Mark C.

2000-01-01

Data from a sparse network of climate stations in Alaska were interpolated to provide 1-km resolution maps of mean monthly temperature and precipitation-variables that are required at high spatial resolution for input into regional models of ecological processes and resource management. The interpolation model is based on thin-plate smoothing splines, which uses the spatial data along with a digital elevation model to incorporate local topography. The model provides maps that are consistent with regional climatology and with patterns recognized by experienced weather forecasters. The broad patterns of Alaskan climate are well represented and include latitudinal and altitudinal trends in temperature and precipitation and gradients in continentality. Variations within these broad patterns reflect both the weakening and reduction in frequency of low-pressure centres in their eastward movement across southern Alaska during the summer, and the shift of the storm tracks into central and northern Alaska in late summer. Not surprisingly, apparent artifacts of the interpolated climate occur primarily in regions with few or no stations. The interpolation model did not accurately represent low-level winter temperature inversions that occur within large valleys and basins. Along with well-recognized climate patterns, the model captures local topographic effects that would not be depicted using standard interpolation techniques. This suggests that similar procedures could be used to generate high-resolution maps for other high-latitude regions with a sparse density of data.

Hydro-Climatic Data Network (HCDN) Streamflow Data Set, 1874-1988

USGS Publications Warehouse

Slack, James Richard; Lumb, Alan M.; Landwehr, Jurate Maciunas

1993-01-01

The potential consequences of climate change to continental water resources are of great concern in the management of those resources. Critically important to society is what effect fluctuations in the prevailing climate may have on hydrologic conditions, such as the occurrence and magnitude of floods or droughts and the seasonal distribution of water supplies within a region. Records of streamflow that are unaffected by artificial diversions, storage, or other works of man in or on the natural stream channels or in the watershed can provide an account of hydrologic responses to fluctuations in climate. By examining such records given known past meteorologic conditions, we can better understand hydrologic responses to those conditions and anticipate the effects of postulated changes in current climate regimes. Furthermore, patterns in streamflow records can indicate when a change in the prevailing climate regime may have occurred in the past, even in the absence of concurrent meteorologic records. A streamflow data set, which is specifically suitable for the study of surface-water conditions throughout the United States under fluctuations in the prevailing climatic conditions, has been developed. This data set, called the Hydro-Climatic Data Network, or HCDN, consists of streamflow records for 1,659 sites throughout United States and its Territories. Records cumulatively span the period 1874 through 1988, inclusive, and represent a total of 73,231 water years of information. Development of the HCDN Data Set: Records for the HCDN were obtained through a comprehensive search of the extensive surface- water data holdings of the U.S. Geological Survey (USGS), which are contained in the USGS National Water Storage and Retrieval System (WATSTORE). All streamflow discharge records in WATSTORE through September 30, 1988, were examined for inclusion in the HCDN in accordance with strictly defined criteria of measurement accuracy and natural conditions. No reconstructed records of 'natural flow' were permitted, nor was any record extended or had missing values 'filled in' using computational algorithms. If the streamflow at a station was judged to be free of controls for only a part of the entire period of record that is available for the station, then only that part was included in the HCDN, but only if it was of sufficient length (generally 20 years) to warrant inclusion. In addition to the daily mean discharge values, complete station identification information and basin characteristics were retrieved from WATSTORE for inclusion in the HCDN. Statistical characteristics, including the monthly mean discharge, as well as the annual mean, minimum and maximum discharge values, were derived for the records in the HCDN data set. For a full description of the development and content of the Hydro-Climatic Data Network, please take a look at the HCDN Report.

The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements

NASA Astrophysics Data System (ADS)

Dorigo, W. A.; Wagner, W.; Hohensinn, R.; Hahn, S.; Paulik, C.; Drusch, M.; Mecklenburg, S.; van Oevelen, P.; Robock, A.; Jackson, T.

2011-02-01

In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol. To overcome many of these limitations, the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status January 2011), the ISMN contains data of 16 networks and more than 500 stations located in the North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that both the number of stations and the time period covered by the existing stations are still growing. Hence, it will become an increasingly important resource for validating and improving satellite-derived soil moisture products and studying climate related trends. As the ISMN is animated by the scientific community itself, we invite potential networks to enrich the collection by sharing their in situ soil moisture data.

The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements

NASA Astrophysics Data System (ADS)

Dorigo, W. A.; Wagner, W.; Hohensinn, R.; Hahn, S.; Paulik, C.; Xaver, A.; Gruber, A.; Drusch, M.; Mecklenburg, S.; van Oevelen, P.; Robock, A.; Jackson, T.

2011-05-01

In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol. To overcome many of these limitations, the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status May 2011), the ISMN contains data of 19 networks and more than 500 stations located in North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that both the number of stations and the time period covered by the existing stations are still growing. Hence, it will become an increasingly important resource for validating and improving satellite-derived soil moisture products and studying climate related trends. As the ISMN is animated by the scientific community itself, we invite potential networks to enrich the collection by sharing their in situ soil moisture data.

WegenerNet climate station network region Feldbach/Austria: From local measurements to weather and climate data products at 1 km-scale resolution

NASA Astrophysics Data System (ADS)

Kabas, T.; Leuprecht, A.; Bichler, C.; Kirchengast, G.

2010-12-01

South-eastern Austria is characteristic for experiencing a rich variety of weather and climate patterns. For this reason, the county of Feldbach was selected by the Wegener Center as a focus area for a pioneering observation experiment at very high resolution: The WegenerNet climate station network (in brief WegenerNet) comprises 151 meteorological stations within an area of about 20 km × 15 km (~ 1.4 km × 1.4 km station grid). All stations measure the main parameters temperature, humidity and precipitation with 5 minute sampling. Selected further stations include measurements of wind speed and direction completed by soil parameters as well as air pressure and net radiation. The collected data is integrated in an automatic processing system including data transfer, quality control, product generation, and visualization. Each station is equipped with an internet-attached data logger and the measurements are transferred as binary files via GPRS to the WegenerNet server in 1 hour intervals. The incoming raw data files of measured parameters as well as several operating values of the data logger are stored in a relational database (PostgreSQL). Next, the raw data pass the Quality Control System (QCS) in which the data are checked for its technical and physical plausibility (e.g., sensor specifications, temporal and spatial variability). In consideration of the data quality (quality flag), the Data Product Generator (DPG) results in weather and climate data products on various temporal scales (from 5 min to annual) for single stations and regular grids. Gridded data are derived by vertical scaling and squared inverse distance interpolation (1 km × 1 km and 0.01° × 0.01° grids). Both subsystems (QCS and DPG) are realized by the programming language Python. For application purposes the resulting data products are available via the bi-lingual (dt, en) WegenerNet data portal (www.wegenernet.org). At this time, the main interface is still online in a system in which MapServer is used to import spatial data by its database interface and to generate images of static geographic formats. However, a Java applet is additionally needed to display these images on the users local host. Furthermore, station data are visualized as time series by the scripting language PHP. Since February 2010, the visualization of gridded data products is a first step to a new data portal based on OpenLayers. In this GIS framework, all geographic information (e.g., OpenStreetMap) is displayed with MapServer. Furthermore, the visualization of all meteorological parameters are generated on the fly by a Python CGI script and transparently overlayed on the maps. Hence, station data and gridded data are visualized and further prepared for download in common data formats (csv, NetCDF). In conclusion, measured data and generated data products are provided with a data latency less than 1-2 hours in standard operation (near real time). Following an introduction of the processing system along the lines above, resulting data products are presented online at the WegenerNet data portal.

Does using different modern climate datasets impact pollen-based paleoclimate reconstructions in North America during the past 2,000 years

NASA Astrophysics Data System (ADS)

Ladd, Matthew; Viau, Andre

2013-04-01

Paleoclimate reconstructions rely on the accuracy of modern climate datasets for calibration of fossil records under the assumption of climate normality through time, which means that the modern climate operates in a similar manner as over the past 2,000 years. In this study, we show how using different modern climate datasets have an impact on a pollen-based reconstruction of mean temperature of the warmest month (MTWA) during the past 2,000 years for North America. The modern climate datasets used to explore this research question include the: Whitmore et al., (2005) modern climate dataset; North American Regional Reanalysis (NARR); National Center For Environmental Prediction (NCEP); European Center for Medium Range Weather Forecasting (ECMWF) ERA-40 reanalysis; WorldClim, Global Historical Climate Network (GHCN) and New et al., which is derived from the CRU dataset. Results show that some caution is advised in using the reanalysis data on large-scale reconstructions. Station data appears to dampen out the variability of the reconstruction produced using station based datasets. The reanalysis or model-based datasets are not recommended for paleoclimate large-scale North American reconstructions as they appear to lack some of the dynamics observed in station datasets (CRU) which resulted in warm-biased reconstructions as compared to the station-based reconstructions. The Whitmore et al. (2005) modern climate dataset appears to be a compromise between CRU-based datasets and model-based datasets except for the ERA-40. In addition, an ultra-high resolution gridded climate dataset such as WorldClim may only be useful if the pollen calibration sites in North America have at least the same spatial precision. We reconstruct the MTWA to within +/-0.01°C by using an average of all curves derived from the different modern climate datasets, demonstrating the robustness of the procedure used. It may be that the use of an average of different modern datasets may reduce the impact of uncertainty of paleoclimate reconstructions, however, this is yet to be determined with certainty. Future evaluation using for example the newly developed Berkeley earth surface temperature datasets should be tested against the paleoclimate record.

The Effects of Data Gaps on the Calculated Monthly Mean Maximum and Minimum Temperatures in the Continental United States: A Spatial and Temporal Study.

NASA Astrophysics Data System (ADS)

Stooksbury, David E.; Idso, Craig D.; Hubbard, Kenneth G.

1999-05-01

Gaps in otherwise regularly scheduled observations are often referred to as missing data. This paper explores the spatial and temporal impacts that data gaps in the recorded daily maximum and minimum temperatures have on the calculated monthly mean maximum and minimum temperatures. For this analysis 138 climate stations from the United States Historical Climatology Network Daily Temperature and Precipitation Data set were selected. The selected stations had no missing maximum or minimum temperature values during the period 1951-80. The monthly mean maximum and minimum temperatures were calculated for each station for each month. For each month 1-10 consecutive days of data from each station were randomly removed. This was performed 30 times for each simulated gap period. The spatial and temporal impact of the 1-10-day data gaps were compared. The influence of data gaps is most pronounced in the continental regions during the winter and least pronounced in the southeast during the summer. In the north central plains, 10-day data gaps during January produce a standard deviation value greater than 2°C about the `true' mean. In the southeast, 10-day data gaps in July produce a standard deviation value less than 0.5°C about the mean. The results of this study will be of value in climate variability and climate trend research as well as climate assessment and impact studies.

A global gridded dataset of daily precipitation going back to 1950, ideal for analysing precipitation extremes

NASA Astrophysics Data System (ADS)

Contractor, S.; Donat, M.; Alexander, L. V.

2017-12-01

Reliable observations of precipitation are necessary to determine past changes in precipitation and validate models, allowing for reliable future projections. Existing gauge based gridded datasets of daily precipitation and satellite based observations contain artefacts and have a short length of record, making them unsuitable to analyse precipitation extremes. The largest limiting factor for the gauge based datasets is a dense and reliable station network. Currently, there are two major data archives of global in situ daily rainfall data, first is Global Historical Station Network (GHCN-Daily) hosted by National Oceanic and Atmospheric Administration (NOAA) and the other by Global Precipitation Climatology Centre (GPCC) part of the Deutsche Wetterdienst (DWD). We combine the two data archives and use automated quality control techniques to create a reliable long term network of raw station data, which we then interpolate using block kriging to create a global gridded dataset of daily precipitation going back to 1950. We compare our interpolated dataset with existing global gridded data of daily precipitation: NOAA Climate Prediction Centre (CPC) Global V1.0 and GPCC Full Data Daily Version 1.0, as well as various regional datasets. We find that our raw station density is much higher than other datasets. To avoid artefacts due to station network variability, we provide multiple versions of our dataset based on various completeness criteria, as well as provide the standard deviation, kriging error and number of stations for each grid cell and timestep to encourage responsible use of our dataset. Despite our efforts to increase the raw data density, the in situ station network remains sparse in India after the 1960s and in Africa throughout the timespan of the dataset. Our dataset would allow for more reliable global analyses of rainfall including its extremes and pave the way for better global precipitation observations with lower and more transparent uncertainties.

A Case Study: Optimal Stage Gauge NetworkUsing Multi Objective Genetic Algorithm

NASA Astrophysics Data System (ADS)

Joo, H. J.; Han, D.; Jung, J.; Kim, H. S.

2017-12-01

Recently, the possibility of occurrence of localized strong heavy rainfall due to climate change is increasing and flood damage is also increasing trend in Korea. Therefore we need more precise hydrologic analysis for preparing alternatives or measures for flood reduction by considering climate conditions which we have difficulty in the prediction. To do this, obtaining reliable hydrologic data, for an example, stage data, is very important. However, the existing stage gauge stations are scattered around the country, making it difficult to maintain them in a stable manner, and subsequently hard to acquire the hydrologic data that could be used for reflecting the localized hydrologic characteristics. In order to overcome such restrictions, this paper not only aims to establish a plan to acquire the water stage data in a constant and proper manner by using limited manpower and costs, but also establishes the fundamental technology for acquiring the water level observation data or the stage data. For that, this paper identifies the current status of the stage gauge stations installed in the Chung-Ju dam in Han river, Korea and extract the factors related to the division and characteristics of basins. Then, the obtained factors are used to develop the representative unit hydrograph that shows the characteristics of flow. After that, the data are converted into the probability density function and the stations at individual basins are selected by using the entropy theory. In last step, we establish the optimized stage gauge network by the location of the stage station and grade using the Multi Objective Genetic Algorithm(MOGA) technique that takes into account for the combinations of the number of the stations. It is expected that this paper can help establish an optimal observational network of stage guages as it can be applied usefully not only for protecting against floods in a stable manner, but also for acquiring the hydrologic data in an efficient manner. Keywords : Unit Hydrograph, Entropy, Grade of Stage Gauge Station, Multi Objective Genetic Algorithm(MOGA), Optimal Stage Guage Network Acknowledgements This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT & Future Planning(2017R1A2B3005695)

The Austrian Network of Isotopes in Precipitation and Surface water: more than 50 years applications and interpretations of basic isotope-hydrological data for Central Europe

NASA Astrophysics Data System (ADS)

Wyhlidal, S.; Rank, D.; Kralik, M.

2017-12-01

Austria runs one of the longest-standing and most dense isotope precipitation collection networks worldwide, resulting in a unique isotope time series. Stable isotope variations in precipitation are a consequence of isotope effects accompanying each step of the water cycle. Therefore, stable isotope ratios of oxygen (18O/16O) and hydrogen (2H/1H) in precipitation provide important information about the origin and atmospheric transport of water vapour. The separation of a remote moisture source signals from local influences is thereby challenging. The amount of precipitation in Austria is highly influenced by the Alpine mountain range (400-3.000 mm/a). The amount of annual precipitation increases towards the mountain ranges. However, strong regional differences exist between the north and south of the Austrian Alps because the Alpine range functions as weather divide. The isotope time series of the stations of the Austrian precipitation network show significant but not uniform long-term trends. While the 10-year running mean of some mountain stations exhibit a highly significant increase in δ18O of about 1 ‰ since 1975, the change of δ18O at the valley stations is less pronounced. The increasing δ18O values can be correlated to an increase mean air temperature in the Alpine area and can be used as an additional indicator of climate change in this region. The differences in δ18O-values of sampling stations at similar altitudes can be explained by the origin of the air moisture. An Atlantic influence causes lower δ18O-values than sources from the Mediterranean. This can be explained by the different distances to the sea. Deuterium excess is a second-order isotopic parameter which is often interpreted as a tracer of the evaporation conditions of water vapor at the moisture source in terms of relative humidity, wind speed, and sea surface temperature, but can also be modified by local influences, such as below-cloud evaporation and equilibrium fractionation under very cold conditions. The long-term variations of d-excess in precipitation at selected stations show a significant difference in the behavior of the d-excess at mountain and valley stations. Deuterium excess and δ18O will be used to explore climate effects on precipitation signatures observed and elicit how they can be integrated in to global climate models.

Ground and surface temperature variability for remote sensing of soil moisture in a heterogeneous landscape

USDA-ARS?s Scientific Manuscript database

At the Little River Watershed (LRW) heterogeneous landscape near Tifton Georgia US an in situ network of stations operated by the US Department of Agriculture-Agriculture Research Service (USDA-ARS-SEWRL) was established in 2003 for the long term study of climatic and soil biophysical processes. To ...

Estimating the urban bias of surface shelter temperatures using upper-air and satellite data. Part 2: Estimation of the urban bias

NASA Technical Reports Server (NTRS)

Epperson, David L.; Davis, Jerry M.; Bloomfield, Peter; Karl, Thomas R.; Mcnab, Alan L.; Gallo, Kevin P.

1995-01-01

A methodology is presented for estimating the urban bias of surface shelter temperatures due to the effect of the urban heat island. Multiple regression techniques were used to predict surface shelter temperatures based on the time period 1986-89 using upper-air data from the European Centre for Medium-Range Weather Forecasts (ECMWF) to represent the background climate, site-specific data to represent the local landscape, and satellite-derived data -- the normalized difference vegetation index (NDVI) and the Defense Meteorological Satellite Program (DMSP) nighttime brightness data -- to represent the urban and rural landscape. Local NDVI and DMSP values were calculated for each station using the mean NDVI and DMSP values from a 3 km x 3 km area centered over the given station. Regional NDVI and DMSP values were calculated to represent a typical rural value for each station using the mean NDVI and DMSP values from a 1 deg x 1 deg latitude-longitude area in which the given station was located. Models for the United States were then developed for monthly maximum, mean, and minimum temperatures using data from over 1000 stations in the U.S. Cooperative (COOP) Network and for monthly mean temperatures with data from over 1150 stations in the Global Historical Climate Network (GHCN). Local biases, or the differences between the model predictions using the observed NDVI and DMSP values, and the predictions using the background regional values were calculated and compared with the results of other research. The local or urban bias of U.S. temperatures, as derived from all U.S. stations (urban and rural) used in the models, averaged near 0.40 C for monthly minimum temperatures, near 0.25 C for monthly mean temperatures, and near 0.10 C for monthly maximum temperatures. The biases of monthly minimum temperatures for individual stations ranged from near -1.1 C for rural stations to 2.4 C for stations from the largest urban areas. The results of this study indicate minimal problems for global application once global NDVI and DMSP data become available.

Mapping of the Land Cover Spatiotemporal Characteristics in Northern Russia Caused by Climate Change

NASA Astrophysics Data System (ADS)

Panidi, E.; Tsepelev, V.; Torlopova, N.; Bobkov, A.

2016-06-01

The study is devoted to the investigation of regional climate change in Northern Russia. Due to sparseness of the meteorological observation network in northern regions, we investigate the application capabilities of remotely sensed vegetation cover as indicator of climate change at the regional scale. In previous studies, we identified statistically significant relationship between the increase of surface air temperature and increase of the shrub vegetation productivity. We verified this relationship using ground observation data collected at the meteorological stations and Normalised Difference Vegetation Index (NDVI) data produced from Terra/MODIS satellite imagery. Additionally, we designed the technique of growing seasons separation for detailed investigation of the land cover (shrub cover) dynamics. Growing seasons are the periods when the temperature exceeds +5°C and +10°C. These periods determine the vegetation productivity conditions (i.e., conditions that allow growth of the phytomass). We have discovered that the trend signs for the surface air temperature and NDVI coincide on planes and river floodplains. On the current stage of the study, we are working on the automated mapping technique, which allows to estimate the direction and magnitude of the climate change in Northern Russia. This technique will make it possible to extrapolate identified relationship between land cover and climate onto territories with sparse network of meteorological stations. We have produced the gridded maps of NDVI and NDWI for the test area in European part of Northern Russia covered with the shrub vegetation. Basing on these maps, we may determine the frames of growing seasons for each grid cell. It will help us to obtain gridded maps of the NDVI linear trend for growing seasons on cell-by-cell basis. The trend maps can be used as indicative maps for estimation of the climate change on the studied areas.

The SASSCAL contribution to climate observation, climate data management and data rescue in Southern Africa

NASA Astrophysics Data System (ADS)

Kaspar, F.; Helmschrot, J.; Mhanda, A.; Butale, M.; de Clercq, W.; Kanyanga, J. K.; Neto, F. O. S.; Kruger, S.; Castro Matsheka, M.; Muche, G.; Hillmann, T.; Josenhans, K.; Posada, R.; Riede, J.; Seely, M.; Ribeiro, C.; Kenabatho, P.; Vogt, R.; Jürgens, N.

2015-07-01

A major task of the newly established "Southern African Science Service Centre for Climate Change and Adaptive Land Management" (SASSCAL; www.sasscal.org) and its partners is to provide science-based environmental information and knowledge which includes the provision of consistent and reliable climate data for Southern Africa. Hence, SASSCAL, in close cooperation with the national weather authorities of Angola, Botswana, Germany and Zambia as well as partner institutions in Namibia and South Africa, supports the extension of the regional meteorological observation network and the improvement of the climate archives at national level. With the ongoing rehabilitation of existing weather stations and the new installation of fully automated weather stations (AWS), altogether 105 AWS currently provide a set of climate variables at 15, 30 and 60 min intervals respectively. These records are made available through the SASSCAL WeatherNet, an online platform providing near-real time data as well as various statistics and graphics, all in open access. This effort is complemented by the harmonization and improvement of climate data management concepts at the national weather authorities, capacity building activities and an extension of the data bases with historical climate data which are still available from different sources. These activities are performed through cooperation between regional and German institutions and will provide important information for climate service related activities.

AI-based (ANN and SVM) statistical downscaling methods for precipitation estimation under climate change scenarios

NASA Astrophysics Data System (ADS)

Mehrvand, Masoud; Baghanam, Aida Hosseini; Razzaghzadeh, Zahra; Nourani, Vahid

2017-04-01

Since statistical downscaling methods are the most largely used models to study hydrologic impact studies under climate change scenarios, nonlinear regression models known as Artificial Intelligence (AI)-based models such as Artificial Neural Network (ANN) and Support Vector Machine (SVM) have been used to spatially downscale the precipitation outputs of Global Climate Models (GCMs). The study has been carried out using GCM and station data over GCM grid points located around the Peace-Tampa Bay watershed weather stations. Before downscaling with AI-based model, correlation coefficient values have been computed between a few selected large-scale predictor variables and local scale predictands to select the most effective predictors. The selected predictors are then assessed considering grid location for the site in question. In order to increase AI-based downscaling model accuracy pre-processing has been developed on precipitation time series. In this way, the precipitation data derived from various GCM data analyzed thoroughly to find the highest value of correlation coefficient between GCM-based historical data and station precipitation data. Both GCM and station precipitation time series have been assessed by comparing mean and variances over specific intervals. Results indicated that there is similar trend between GCM and station precipitation data; however station data has non-stationary time series while GCM data does not. Finally AI-based downscaling model have been applied to several GCMs with selected predictors by targeting local precipitation time series as predictand. The consequences of recent step have been used to produce multiple ensembles of downscaled AI-based models.

Seasonal variation of air temperature at the Mendel Station, James Ross Island in the period of 2006-2009

NASA Astrophysics Data System (ADS)

Laska, Kamil; Prošek, Pavel; Budík, Ladislav

2010-05-01

Key words: air temperature, seasonal variation, James Ross Island, Antarctic Peninsula Recently, significant role of the atmospheric and oceanic circulation variation on positive trend of near surface air temperature along the Antarctic Peninsula has been reported by many authors. However, small number of the permanent meteorological stations located on the Peninsula coast embarrasses a detail analysis. It comprises analysis of spatiotemporal variability of climatic conditions and validation of regional atmospheric climate models. However, geographical location of the Czech Johann Gregor Mendel Station (hereafter Mendel Station) newly established on the northern ice-free part of the James Ross Island provides an opportunity to fill the gap. There are recorded important meteorological characteristics which allow to evaluate specific climatic regime of the region and their impact on the ice-shelf disintegration and glacier retreat. Mendel Station (63°48'S, 57°53'W) is located on marine terrace at the altitude of 7 m. In 2006, a monitoring network of several automatic weather stations was installed at different altitudes ranging from the seashore level up to mesas and tops of glaciers (514 m a.s.l.). In this contribution, a seasonal variation of near surface air temperature at the Mendel Station in the period of 2006-2009 is presented. Annual mean air temperature was -7.2 °C. Seasonal mean temperature ranged from +1.4 °C (December-February) to -17.7 °C (June-August). Frequently, the highest temperature occurred in the second half of January. It reached maximum of +8.1 °C. Sudden changes of atmospheric circulation pattern during winter caused a large interdiurnal variability of air temperature with the amplitude of 30 °C.

Birmingham Urban Climate Laboratory (BUCL): Experiences, Challenges and Applications of an Urban Temperature Network

NASA Astrophysics Data System (ADS)

Muller, Catherine; Chapman, Lee; Young, Duick; Grimmond, Sue; Cai, Xiaoming

2013-04-01

The Birmingham Urban Climate Laboratory (BUCL) has recently been established by the University of Birmingham. BUCL is an in-situ, real-time urban network that will incorporate 3 nested networks - a wide-array of 25 weather stations, a dense array of 131 low-cost air temperature sensors and a fine-array of temperature sensor across the city-centre (50/km^2) - with the primary aim of monitoring air temperatures across a morphologically-heterogeneous urban conurbation for a variety of applications. During its installation there have been a number of challenges to overcome, including siting equipment in suitable urban locations, ensuring that the measurements were 'representative' of the local-scale climate, managing a large, near real-time data set and implementing QA/QC procedures. From these experiences, the establishment of a standardised urban meteorological network metadata protocol has been proposed in order to improve data quality, to ensure the end-user has access to all the supplementary information they would require for conducting valid analyses and to encourage the adequate recording and documentation of any changes to in-situ urban networks over time. This paper will provide an introduction to the BUCL in-situ network, give an overview of the challenges and experiences gained from its implementation, and finally discuss the proposed applications of the network, including its use in remote sensing observations of urban temperatures, as well as health and infrastructure applications.

New estimates of changes in snow cover over Russia in recent decades

NASA Astrophysics Data System (ADS)

Bulygina, O.; Korshunova, N.; Razuvaev, V.; Groisman, P. Y.

2017-12-01

Snow covers plays critical roles in the energy and water balance of the Earth through its unique physical properties (high reflectivity and low thermal conductivity) and water storage. The main objective of this research is to monitoring snow cover change in Russia. The estimates of changes of major snow characteristics (snow cover duration, maximum winter snow depth, snow water equivalent) are described. Apart from the description of long-term averages of snow characteristics, the estimates of their change that are averaged over quasi-homogeneous climatic regions are derived and regional differences in the change of snow characteristics are studied. We used in our study daily snow observations for 820 Russian meteorological station from 1966 to 2017. All of these meteorological stations are of unprotected type. The water equivalent is analyzed from snow course survey data at 958 meteorological stations from 1966 to 2017. The time series are prepared by RIHMI-WDC. Regional analysis of snow cover data was carried out using quasi-homogeneous climatic regions. The area-averaging technique using station values converted to anomalies with respect to a common reference period (in this study, 1981-2010). Anomalies were arithmetically averaged first within 1°N x 2°E grid cells and thereafter by a weighted average value derived over the quasi-homogeneous climatic regions. This approach provides a more uniform spatial field for averaging. By using a denser network of meteorological stations, bringing into consideration snow course data and, we managed to specify changes in all observed major snow characteristics and to obtain estimates generalized for quasi-homogeneous climatic regions. The detected changes in the dates of the establishment and disappearance of the snow cover.

Reference hydrologic networks I. The status and potential future directions of national reference hydrologic networks for detecting trends

USGS Publications Warehouse

Whitfield, Paul H.; Burn, Donald H.; Hannaford, Jamie; Higgins, Hélène; Hodgkins, Glenn A.; Marsh, Terry; Looser, Ulrich

2012-01-01

Identifying climate-driven trends in river flows on a global basis is hampered by a lack of long, quality time series data for rivers with relatively undisturbed regimes. This is a global problem compounded by the lack of support for essential long-term monitoring. Experience demonstrates that, with clear strategic objectives, and the support of sponsoring organizations, reference hydrologic networks can constitute an exceptionally valuable data source to effectively identify, quantify and interpret hydrological change—the speed and magnitude of which is expected to a be a primary driver of water management and flood alleviation strategies through the future—and for additional applications. Reference hydrologic networks have been developed in many countries in the past few decades. These collections of streamflow gauging stations, that are maintained and operated with the intention of observing how the hydrology of watersheds responds to variations in climate, are described. The status of networks under development is summarized. We suggest a plan of actions to make more effective use of this collection of networks.

Providing the Larger Climate Context During Extreme Weather - Lessons from Local Television News

NASA Astrophysics Data System (ADS)

Woods, M.; Cullen, H. M.

2015-12-01

Local television weathercasters, in their role as Station Scientists, are often called upon to educate viewers about the science and impacts of climate change. Climate Central supports these efforts through its Climate Matters program. Launched in 2010 with support from the National Science Foundation, the program has grown into a network that includes more than 245 weathercasters from across the country and provides localized information on climate and ready-to-use, broadcast quality graphics and analyses in both English and Spanish. This presentation will focus on discussing best practices for integrating climate science into the local weather forecast as well as advances in the science of extreme event attribution. The Chief Meteorologist at News10 (Sacramento, CA) will discuss local news coverage of the ongoing California drought, extreme weather and climate literacy.

GuMNet - A high altitude monitoring network in the Sierra de Guadarrama (Madrid, Spain)

NASA Astrophysics Data System (ADS)

Santolaria-Canales, Edmundo

2016-04-01

The Guadarrama Monitoring Network (GuMNet) is an observational infrastructure focused on monitoring the state of the atmosphere and the ground in the Sierra de Guadarrama, 50 km NW of the city of Madrid. The network is composed of10 stations ranging from low altitude (900 m a.s.l.) to high mountain climate (2400 m a.s.l.). The atmospheric instrumentation includes sensors for air temperature, air humidity, 4-component net radiation, precipitation, snow height and wind speed and direction. The surface and subsurface infrastructure includes temperature and humidity sensors distributed in 9 trenches up to a maximum of 1 m depth and additionally temperature sensors in 15 PVC cased boreholes down to 20 m and 2 m with a higher vertical resolution close to the surface. All stations are located in exposed open areas except for one site that is in a forested area for measuring air-ground fluxes under forest conditions. High altitude sites are focused on periglacial areas and lower altitude sites have emphasis on pastures. One of the low altitude sites is equipped with a 10 m high tower with 3D sonic anemometers and a CO2/H2O analyzer that will allow the sampling of wind profiles and H2O and CO2 eddy covariance fluxes, important for estimation of CO2 and energy exchanges over complex vegetated surfaces. The network is connected via general packet radio service to the central lab in the Campus of Excellence of Moncloa and management software has been developed to handle the operation of the infrastructure. The data provided by GuMNet will help to improve the characterization of atmospheric variability from turbulent scales to meteorology and climate at high mountain areas, as well as land-atmosphere interactions. The network information aims at meeting the needs of accuracy to be used for biological, agricultural, hydrological, meteorological and climatic investigations in this area with relevance for ecosystem oriented studies. This setup will complement the broader network of meteorological stations of the Spanish National Meteorological Agency(AEMET), mostly distributed in the lower latitude range. This initiative is supported and developed by research groups integrating the GuMNet Consortium from the Complutense and Polytechnical Universities of Madrid (UCM and UPM), the Energetic Environmental and Technological Research Centre (CIEMAT), AEMET, and the National Park Sierra de Guadarrama (PNSG) which provided the initial foundations of this network. GuMNet will be operational in 2016. Web: http://www.ucm.es/gumnet/ Contact: edmundo.santolaria@ucm.es

Compilation of climate data from heterogeneous networks across the Hawaiian Islands

PubMed Central

Longman, Ryan J.; Giambelluca, Thomas W.; Nullet, Michael A.; Frazier, Abby G.; Kodama, Kevin; Crausbay, Shelley D.; Krushelnycky, Paul D.; Cordell, Susan; Clark, Martyn P.; Newman, Andy J.; Arnold, Jeffrey R.

2018-01-01

Long-term, accurate observations of atmospheric phenomena are essential for a myriad of applications, including historic and future climate assessments, resource management, and infrastructure planning. In Hawai‘i, climate data are available from individual researchers, local, State, and Federal agencies, and from large electronic repositories such as the National Centers for Environmental Information (NCEI). Researchers attempting to make use of available data are faced with a series of challenges that include: (1) identifying potential data sources; (2) acquiring data; (3) establishing data quality assurance and quality control (QA/QC) protocols; and (4) implementing robust gap filling techniques. This paper addresses these challenges by providing: (1) a summary of the available climate data in Hawai‘i including a detailed description of the various meteorological observation networks and data accessibility, and (2) a quality controlled meteorological dataset across the Hawaiian Islands for the 25-year period 1990-2014. The dataset draws on observations from 471 climate stations and includes rainfall, maximum and minimum surface air temperature, relative humidity, wind speed, downward shortwave and longwave radiation data. PMID:29437162

Compilation of climate data from heterogeneous networks across the Hawaiian Islands

NASA Astrophysics Data System (ADS)

Longman, Ryan J.; Giambelluca, Thomas W.; Nullet, Michael A.; Frazier, Abby G.; Kodama, Kevin; Crausbay, Shelley D.; Krushelnycky, Paul D.; Cordell, Susan; Clark, Martyn P.; Newman, Andy J.; Arnold, Jeffrey R.

2018-02-01

Long-term, accurate observations of atmospheric phenomena are essential for a myriad of applications, including historic and future climate assessments, resource management, and infrastructure planning. In Hawai'i, climate data are available from individual researchers, local, State, and Federal agencies, and from large electronic repositories such as the National Centers for Environmental Information (NCEI). Researchers attempting to make use of available data are faced with a series of challenges that include: (1) identifying potential data sources; (2) acquiring data; (3) establishing data quality assurance and quality control (QA/QC) protocols; and (4) implementing robust gap filling techniques. This paper addresses these challenges by providing: (1) a summary of the available climate data in Hawai'i including a detailed description of the various meteorological observation networks and data accessibility, and (2) a quality controlled meteorological dataset across the Hawaiian Islands for the 25-year period 1990-2014. The dataset draws on observations from 471 climate stations and includes rainfall, maximum and minimum surface air temperature, relative humidity, wind speed, downward shortwave and longwave radiation data.

High-resolution grids of hourly meteorological variables for Germany

NASA Astrophysics Data System (ADS)

Krähenmann, S.; Walter, A.; Brienen, S.; Imbery, F.; Matzarakis, A.

2018-02-01

We present a 1-km2 gridded German dataset of hourly surface climate variables covering the period 1995 to 2012. The dataset comprises 12 variables including temperature, dew point, cloud cover, wind speed and direction, global and direct shortwave radiation, down- and up-welling longwave radiation, sea level pressure, relative humidity and vapour pressure. This dataset was constructed statistically from station data, satellite observations and model data. It is outstanding in terms of spatial and temporal resolution and in the number of climate variables. For each variable, we employed the most suitable gridding method and combined the best of several information sources, including station records, satellite-derived data and data from a regional climate model. A module to estimate urban heat island intensity was integrated for air and dew point temperature. Owing to the low density of available synop stations, the gridded dataset does not capture all variations that may occur at a resolution of 1 km2. This applies to areas of complex terrain (all the variables), and in particular to wind speed and the radiation parameters. To achieve maximum precision, we used all observational information when it was available. This, however, leads to inhomogeneities in station network density and affects the long-term consistency of the dataset. A first climate analysis for Germany was conducted. The Rhine River Valley, for example, exhibited more than 100 summer days in 2003, whereas in 1996, the number was low everywhere in Germany. The dataset is useful for applications in various climate-related studies, hazard management and for solar or wind energy applications and it is available via doi: 10.5676/DWD_CDC/TRY_Basis_v001.

Capacity Development of Youth in Geospatial Tools for Addressing Climate Change in Kenya

NASA Astrophysics Data System (ADS)

Mubea, K.; Kasera, K.; Maina, C.

2017-12-01

SERVIR E&SA builds on the institutional partnerships and networks in Eastern and Southern Africa together with the network and partnerships associated with USAID country missions in the region. The RCMRD Space Challenge was meant to equip students from high/secondary schools and primary schools within Kenya and beyond with the necessary skills and awareness in relation to environmental degradation, climate change and its drivers. Furthermore, this contributes to the achievement of Sustainable Development Goals (SDGs), developing the youth in Science, Technology, Engineering and Math (STEM) and ultimately contributing to capacity building of the youth with the objective of promoting sustainable development. RCMRD partnered with GLOBE Program Kenya, 4-H Kenya and Esri Eastern Africa in this endeavor. The challenge involved students from seven schools analyzing data from automatic weather stations and plotting the results against other location of schools. The students were required to use TAHMO Automatic Weather Stations (AWS) normalized atmospheric data provided by GLOBE, TAHMO and RCMRD. The three parameters, humidity, precipitation and temperature were found to be very closely related. The students generated graphs that were obtained from the normalized data for the five climatic zones in Kenya. Nasokol Girls School located at Kishaunet in West Pokot County (Kenya) emerged the winners followed by St. Scholastica Catholic Primary School in Nairobi, and Moi Forces Academy Nairobi. The students were urged to utilize the knowledge acquired to address challenges related to climate change. RCMRD Space Challenge will be held annually in Kenya in collaboration with partners.

Dynamic hydro-climatic networks in pristine and regulated rivers

NASA Astrophysics Data System (ADS)

Botter, G.; Basso, S.; Lazzaro, G.; Doulatyari, B.; Biswal, B.; Schirmer, M.; Rinaldo, A.

2014-12-01

Flow patterns observed at-a-station are the dynamical byproduct of a cascade of processes involving different compartments of the hydro-climatic network (e.g., climate, rainfall, soil, vegetation) that regulates the transformation of rainfall into streamflows. In complex branching rivers, flow regimes result from the heterogeneous arrangement around the stream network of multiple hydrologic cascades that simultaneously occur within distinct contributing areas. As such, flow regimes are seen as the integrated output of a complex "network of networks", which can be properly characterized by its degree of temporal variability and spatial heterogeneity. Hydrologic networks that generate river flow regimes are dynamic in nature. In pristine rivers, the time-variance naturally emerges at multiple timescales from climate variability (namely, seasonality and inter-annual fluctuations), implying that the magnitude (and the features) of the water flow between two nodes may be highly variable across different seasons and years. Conversely, the spatial distribution of river flow regimes within pristine rivers involves scale-dependent transport features, as well as regional climatic and soil use gradients, which in small and meso-scale catchments (A < 103 km2) are usually mild enough to guarantee quite uniform flow regimes and high spatial correlations. Human-impacted rivers, instead, constitute hybrid networks where observed spatio-temporal patterns are dominated by anthropogenic shifts, such as landscape alterations and river regulation. In regulated rivers, the magnitude and the features of water flows from node to node may change significantly through time due to damming and withdrawals. However, regulation may impact river regimes in a spatially heterogeneous manner (e.g. in localized river reaches), with a significant decrease of spatial correlations and network connectivity. Provided that the spatial and temporal dynamics of flow regimes in complex rivers may strongly impact important biotic processes involved in the river food web (e.g. biofilm and riparian vegetation dynamics), the study of rivers as dynamic networks provides important clues to water management strategies and freshwater ecosystem studies.

Trans-African Hydro-Meteorological Observatory (TAHMO): A network to monitor weather, water, and climate in Africa

NASA Astrophysics Data System (ADS)

Van De Giesen, N.; Hut, R.; Andreini, M.; Selker, J. S.

2013-12-01

The Trans-African Hydro-Meteorological Observatory (TAHMO) has a goal to design, build, install and operate a dense network of hydro-meteorological monitoring stations in sub-Saharan Africa; one every 35 km. This corresponds to a total of 20,000 stations. By applying ICT and innovative sensors, each station should cost not more than $500. The stations would be placed at schools and integrated in the environmental curriculum. Data will be combined with models and satellite observations to obtain a very complete insight into the distribution of water and energy stocks and fluxes. Within this project, we have built a prototype of an acoustic disdrometer (rain gauge) that can be produced for much less than the cost of a commercial equivalent with the same specifications. The disdrometer was developed in The Netherlands and tested in Tanzania for a total project cost of Euro 5000. First tests have been run at junior high schools in Ghana to incorporate hydro-meteorological measurements in the science curriculum. The latest activity concerns the organization of a crowdsourcing competitions across Africa to address business development and the design and building of new robust sensors. This has resulted in a wide network throughout the continent to bring this program forward.

Development and nationwide scale-up of Climate Matters, a localized climate change education program delivered by TV weathercasters.

NASA Astrophysics Data System (ADS)

Cullen, H. M.; Maibach, E.

2016-12-01

Most Americans view climate change as a threat that is distant in space (i.e., not here), time (i.e., not now), and species (i.e., not us). TV weathercasters are ideally positioned to educate Americans about the current and projected impacts of climate change in their community: they have tremendous reach, are trusted sources of climate information, and are highly skilled science communicators. In 2009, we learned that many weathercasters were potentially interested in reporting on climate change, but few actually were, citing significant barriers including a lack of time to prepare and air stories, and lack of access to high quality content. To test the premise that TV weathercasters can be effective climate educators - if supported with high quality localized climate communication content - in 2010 George Mason University, Climate Central and WLTX-TV (Columbia, SC) developed and pilot-tested Climate Matters, a series of short on-air (and online) segments about the local impacts of climate change, delivered by the station's chief meteorologist. During the first year, more than a dozen stories aired. To formally evaluate Climate Matters, we conducted pre- and post-test surveys of local TV news viewers in Columbia. After one year, WLTX viewers had developed a more science-based understanding of climate change than viewers of other local news stations, confirming our premise that when TV weathercasters report on the local implications of climate change, their viewers learn. Through a series of expansions, including the addition of important new partners - AMS, NASA, NOAA & Yale University - Climate Matters has become a comprehensive nationwide climate communication resource program for American TV weathercasters. As of March 2016, a network of 313 local weathercasters nationwide (at 202 stations in 111 media markets) are participating in the program, receiving new content on a weekly basis. This presentation will review the theoretical basis of the program, detail its development and national scale-up, and conclude with insights for how to develop climate communication initiatives for other professional communities of practice in the U.S. and other countries.

Exploration of Objective Functions for Optimal Placement of Weather Stations

NASA Astrophysics Data System (ADS)

Snyder, A.; Dietterich, T.; Selker, J. S.

2016-12-01

Many regions of Earth lack ground-based sensing of weather variables. For example, most countries in Sub-Saharan Africa do not have reliable weather station networks. This absence of sensor data has many consequences ranging from public safety (poor prediction and detection of severe weather events), to agriculture (lack of crop insurance), to science (reduced quality of world-wide weather forecasts, climate change measurement, etc.). The Trans-African Hydro-Meteorological Observatory (TAHMO.org) project seeks to address these problems by deploying and operating a large network of weather stations throughout Sub-Saharan Africa. To design the TAHMO network, we must determine where to locate each weather station. We can formulate this as the following optimization problem: Determine a set of N sites that jointly optimize the value of an objective function. The purpose of this poster is to propose and assess several objective functions. In addition to standard objectives (e.g., minimizing the summed squared error of interpolated values over the entire region), we consider objectives that minimize the maximum error over the region and objectives that optimize the detection of extreme events. An additional issue is that each station measures more than 10 variables—how should we balance the accuracy of our interpolated maps for each variable? Weather sensors inevitably drift out of calibration or fail altogether. How can we incorporate robustness to failed sensors into our network design? Another important requirement is that the network should make it possible to detect failed sensors by comparing their readings with those of other stations. How can this requirement be met? Finally, we provide an initial assessment of the computational cost of optimizing these various objective functions. We invite everyone to join the discussion at our poster by proposing additional objectives, identifying additional issues to consider, and expanding our bibliography of relevant papers. A prize (derived from grapes grown in Oregon) will be awarded for the most insightful contribution to the discussion!

An application of HOMER and ACMANT for homogenising monthly precipitation records in Ireland

NASA Astrophysics Data System (ADS)

Coll, John; Curley, Mary; Domonkos, Peter; Aguilar, Enric; Walsh, Seamus; Sweeney, John

2015-04-01

Climate change studies based only on raw long-term data are potentially flawed due to the many breaks introduced from non-climatic sources. Consequently, accurate climate data is an essential prerequisite for basing climate related decision making on; and quality controlled, homogenised climate data are becoming integral to European Union Member State efforts to deliver climate services. Ireland has a good repository of monthly precipitation data at approximately 1900 locations stored in the Met Éireann database. The record length at individual precipitation stations varies greatly. However, an audit of the data established the continuous record length at each station and the number of missing months, and based on this two initial subsets of station series (n = 88 and n = 110) were identified for preliminary homogenisation efforts. The HOMER joint detection algorithm was applied to the combined network of these 198 longer station series on an Ireland-wide basis where contiguous intact monthly records ranged from ~40 to 71 years (1941 - 2010). HOMER detected 91 breaks in total in the country-wide series analysis distributed across 63 (~32%) of the 71 year series records analysed. In a separate approach, four sub-series clusters (n = 38 - 61) for the 1950 - 2010 period were used in a parallel analysis applying both ACMANT and HOMER to a regionalised split of the 198 series. By comparison ACMANT detected a considerably higher number of breaks across the four regional series clusters, 238 distributed across 123 (~62%) of the 61 year series records analysed. These preliminary results indicate a relatively high proportion of detected breaks in the series, a situation not generally reflected in observed later 20th century precipitation records across Europe (Domonkos, 2014). However, this elevated ratio of series with detected breaks (~32% in HOMER and ~62% in ACMANT) parallels the break detection rate in a recent analysis of series in the Netherlands (Buishand et al 2013). In the case of Ireland, the climate is even more markedly maritime than that of the Netherlands and the spatial correlations between the Irish series are high (>0.8). Therefore it is likely that both HOMER and ACMANT are detecting relatively small breaks in the series; e.g. the overall range of correction amplitudes derived by HOMER were small and only applied to sections of the corrected series. As Ireland has a relatively dense network of highly correlated station series, we anticipate continued high detection rates as the analysis is extended to incorporate a greater number of station series, and that the ongoing work will quantify the extent of any breaks in Ireland's monthly precipitation series. KEY WORDS: Ireland, precipitation, time series, homogenisation, HOMER, ACMANT. References Buishand, T.A., DeMartino, G., Spreeuw, J.N., Brandsma, T. (2013). Homogeneity of precipitation series in the Netherlands and their trends in the past century. International Journal of Climatology. 33:815-833 Domonkos, P. (2014). Homogenisation of precipitation time series with ACMANT. Theoretical and Applied Climatology. 118:1-2. DOI 10.1007/s00704-014-1298-5.

Pan-Arctic River Discharge: Where Can We Improve Monitoring of Future Change?

NASA Astrophysics Data System (ADS)

Bring, A.; Shiklomanov, A. I.; Lammers, R. B.

2016-12-01

The Arctic freshwater cycle is changing rapidly, which will require adequate monitoring of river flow to detect, observe and understand changes and provide adaptation information. There has however been little detail about where the greatest flow changes are projected, and where monitoring therefore may need to be strengthened. In this study, we used a set of recent climate model runs and an advanced macro-scale hydrological model to analyze how flows across the continental pan-Arctic are projected to change, and where the climate models agree on significant changes. We also developed a method to identify where monitoring stations should be placed to observe these significant changes, and compared this set of suggested locations with the existing network of monitoring stations. Overall, our results reinforce earlier indications of large increases in flow over much of the Arctic, but we also identify some areas where projections agree on significant changes but disagree on the sign of change. For monitoring, central and eastern Siberia, Alaska and central Canada are hot spots for the highest changes. To take advantage of existing networks, a number of stations across central Canada and western and central Siberia could form a prioritized set. Further development of model representation of high-latitude hydrology would improve confidence in the areas we identify here. Nevertheless, ongoing observation programs may consider these suggested locations in efforts to improve monitoring of the rapidly changing Arctic freshwater cycle.

Confronting weather and climate models with observational data from soil moisture networks over the United States

PubMed Central

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal D.; Balsamo, Gianpaolo; Lawrence, David M.

2018-01-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison. PMID:29645013

Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States

NASA Technical Reports Server (NTRS)

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A., Jr.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal Dean;

Confronting weather and climate models with observational data from soil moisture networks over the United States.

PubMed

Dirmeyer, Paul A; Wu, Jiexia; Norton, Holly E; Dorigo, Wouter A; Quiring, Steven M; Ford, Trenton W; Santanello, Joseph A; Bosilovich, Michael G; Ek, Michael B; Koster, Randal D; Balsamo, Gianpaolo; Lawrence, David M

2016-04-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison.

Drought-induced uplift in the western United States as observed by the EarthScope Plate Boundary Observatory GPS network

NASA Astrophysics Data System (ADS)

Borsa, A. A.; Agnew, D. C.; Cayan, D. R.

2014-12-01

The western United States (WUS) has been experiencing severe drought since 2013. The solid earth response to the accompanying loss of surface and near-surface water mass should be a broad region of uplift. We use seasonally-adjusted time series from continuously operating GPS stations in the EarthScope Plate Boundary Observatory and several smaller networks to measure this uplift, which reaches 15 mm in the California Coastal Ranges and Sierra Nevada and has a median value of 4 mm over the entire WUS. The pattern of mass loss due to the drought, which we recover from an inversion of uplift observations, ranges up to 50 cm of water equivalent and is consistent with observed decreases in precipitation and streamflow. We estimate the total deficit to be 240 Gt, equivalent to a uniform 10 cm layer of water over the entire region, or the magnitude of the current annual mass loss from the Greenland Ice Sheet. In the WUS, interannual changes in crustal loading are driven by changes in cool-season precipitation, which cause variations in surface water, snowpack, soil moisture, and groundwater. The results here demonstrate that the existing network of continuous GPS stations can be used to recover loading changes due to both wet and dry climate patterns. This suggests a new role for GPS networks such as that of the Plate Boundary Observatory. The exceptional stability of the GPS monumentation means that this network is also capable of monitoring the long-term effects of regional climate change. Surface displacement observations from GPS have the potential to expand the capabilities of the current hydrological observing network for monitoring current and future hydrological changes, with obvious social and economic benefits.

A global satellite assisted precipitation climatology

USGS Publications Warehouse

Funk, Christopher C.; Verdin, Andrew P.; Michaelsen, Joel C.; Pedreros, Diego; Husak, Gregory J.; Peterson, P.

2015-01-01

Accurate representations of mean climate conditions, especially in areas of complex terrain, are an important part of environmental monitoring systems. As high-resolution satellite monitoring information accumulates with the passage of time, it can be increasingly useful in efforts to better characterize the earth's mean climatology. Current state-of-the-science products rely on complex and sometimes unreliable relationships between elevation and station-based precipitation records, which can result in poor performance in food and water insecure regions with sparse observation networks. These vulnerable areas (like Ethiopia, Afghanistan, or Haiti) are often the critical regions for humanitarian drought monitoring. Here, we show that long period of record geo-synchronous and polar-orbiting satellite observations provide a unique new resource for producing high resolution (0.05°) global precipitation climatologies that perform reasonably well in data sparse regions. Traditionally, global climatologies have been produced by combining station observations and physiographic predictors like latitude, longitude, elevation, and slope. While such approaches can work well, especially in areas with reasonably dense observation networks, the fundamental relationship between physiographic variables and the target climate variables can often be indirect and spatially complex. Infrared and microwave satellite observations, on the other hand, directly monitor the earth's energy emissions. These emissions often correspond physically with the location and intensity of precipitation. We show that these relationships provide a good basis for building global climatologies. We also introduce a new geospatial modeling approach based on moving window regressions and inverse distance weighting interpolation. This approach combines satellite fields, gridded physiographic indicators, and in situ climate normals. The resulting global 0.05° monthly precipitation climatology, the Climate Hazards Group's Precipitation Climatology version 1 (CHPclim v.1.0,http://dx.doi.org/10.15780/G2159X), is shown to compare favorably with similar global climatology products, especially in areas with complex terrain and low station densities.

A global satellite-assisted precipitation climatology

NASA Astrophysics Data System (ADS)

Funk, C.; Verdin, A.; Michaelsen, J.; Peterson, P.; Pedreros, D.; Husak, G.

2015-10-01

Accurate representations of mean climate conditions, especially in areas of complex terrain, are an important part of environmental monitoring systems. As high-resolution satellite monitoring information accumulates with the passage of time, it can be increasingly useful in efforts to better characterize the earth's mean climatology. Current state-of-the-science products rely on complex and sometimes unreliable relationships between elevation and station-based precipitation records, which can result in poor performance in food and water insecure regions with sparse observation networks. These vulnerable areas (like Ethiopia, Afghanistan, or Haiti) are often the critical regions for humanitarian drought monitoring. Here, we show that long period of record geo-synchronous and polar-orbiting satellite observations provide a unique new resource for producing high-resolution (0.05°) global precipitation climatologies that perform reasonably well in data-sparse regions. Traditionally, global climatologies have been produced by combining station observations and physiographic predictors like latitude, longitude, elevation, and slope. While such approaches can work well, especially in areas with reasonably dense observation networks, the fundamental relationship between physiographic variables and the target climate variables can often be indirect and spatially complex. Infrared and microwave satellite observations, on the other hand, directly monitor the earth's energy emissions. These emissions often correspond physically with the location and intensity of precipitation. We show that these relationships provide a good basis for building global climatologies. We also introduce a new geospatial modeling approach based on moving window regressions and inverse distance weighting interpolation. This approach combines satellite fields, gridded physiographic indicators, and in situ climate normals. The resulting global 0.05° monthly precipitation climatology, the Climate Hazards Group's Precipitation Climatology version 1 (CHPclim v.1.0, doi:10.15780/G2159X), is shown to compare favorably with similar global climatology products, especially in areas with complex terrain and low station densities.

Famine Early Warning Systems Network (FEWS NET) Contributions to Strengthening Resilience and Sustainability for the East African Community

NASA Astrophysics Data System (ADS)

Budde, M. E.; Galu, G.; Funk, C. C.; Verdin, J. P.; Rowland, J.

2014-12-01

The Planning for Resilience in East Africa through Policy, Adaptation, Research, and Economic Development (PREPARED) is a multi-organizational project aimed at mainstreaming climate-resilient development planning and program implementation into the East African Community (EAC). The Famine Early Warning Systems Network (FEWS NET) has partnered with the PREPARED project to address three key development challenges for the EAC; 1) increasing resiliency to climate change, 2) managing trans-boundary freshwater biodiversity and conservation and 3) improving access to drinking water supply and sanitation services. USGS FEWS NET has been instrumental in the development of gridded climate data sets that are the fundamental building blocks for climate change adaptation studies in the region. Tools such as the Geospatial Climate Tool (GeoCLIM) have been developed to interpolate time-series grids of precipitation and temperature values from station observations and associated satellite imagery, elevation data, and other spatially continuous fields. The GeoCLIM tool also allows the identification of anomalies and assessments of both their frequency of occurrence and directional trends. A major effort has been put forth to build the capacities of local and regional institutions to use GeoCLIM to integrate their station data (which is not typically available to the public) into improved national and regional gridded climate data sets. In addition to the improvements and capacity building activities related to geospatial analysis tools, FEWS NET will assist in two other areas; 1) downscaling of climate change scenarios and 2) vulnerability impact assessments. FEWS NET will provide expertise in statistical downscaling of Global Climate Model output fields and work with regional institutions to assess results of other downscaling methods. Completion of a vulnerability impact assessment (VIA) involves the examination of sectoral consequences in identified climate "hot spots". FEWS NET will lead the VIA for the agriculture and food security sector, but will also provide key geospatial layers needed by multiple sectors in the areas of exposure, sensitivity, and adaptive capacity. Project implementation will strengthen regional coordination in policy-making, planning, and response to climate change issues.

Building Climate Service Capacities in Eastern Africa with CHIRP and GeoCLIM

NASA Astrophysics Data System (ADS)

Pedreros, D. H.; Magadzire, T.; Funk, C. C.; Verdin, J. P.; Peterson, P.; Landsfeld, M.; Husak, G. J.

2013-12-01

In developing countries there is a great need for capacity building within national and regional climate agencies to develop and analyze historical and real time gridded rainfall datasets. These datasets are of key importance for monitoring climate and agricultural food production at decadal and seasonal time scales, and for informing local decision makers. The Famine Early Warning Systems Network (FEWS NET), working together with the U.S. Geological Survey (USGS) and the Climate Hazards Group (CHG) of the University of California Santa Barbara, has developed an integrated set of data products and tools to support the development of African climate services. The core data product is the Climate Hazards Group Infrared Precipitation (CHIRP) dataset. The CHIRP is a new rainfall dataset resulting from the blending of satellite estimated precipitation with high resolution precipitation climatology. The CHIRP depicts rainfall on five day totals at 5km spatial resolution from 1981 to present. The CHG is developing and deploying a standalone tool - the GeoCLIM - which will allow national and regional meteorological agencies to blend the CHIRP with station observations, run simple crop water balance models, and conduct climatological, trend, and time series analysis. Blending satellite estimates and gauge data helps overcome limited in situ observing networks. Furthermore, the GeoCLIM combines rainfall, soil, and evapotranspiration data with crop hydrological requirements to calculate agricultural water balance, presented as the Water Requirement Satisfaction Index (WRSI). The WRSI is a measurement of the degree in which a crop's hydrological requirements have been satisfied by rainfall. We present the results of a training session for personnel of the East African Intergovernmental Authority on Development Climate Prediction and Applications Center. The two week training program included the use of the GeoCLIM to improve CHIRP using station data, and to calculate and analyze trends in rainfall, WRSI, and drought frequency in the region.

Climate driven variability and detectability of temporal trends in low flow indicators for Ireland

NASA Astrophysics Data System (ADS)

Hall, Julia; Murphy, Conor; Harrigan, Shaun

2013-04-01

Observational data from hydrological monitoring programs plays an important role in informing decision makers of changes in key hydrological variables. To analyse how changes in climate influence stream flow, undisturbed river basins with near-natural conditions limited from human influences are needed. This study analyses low flow indicators derived from observations from the Irish Reference Network. Within the trend analysis approach the influence of individual years or sub-periods on the detected trend are analysed using sequential trend tests on all possible periods (of at least 10 years in length) by varying the start and end dates of records for various indicators. Results from this study highlight that the current standard approach using fixed periods to determine long term trends is not appropriate as statistical significance and direction of trends from short term records do not persist continuously over entire record and can be heavily influenced by extremes within the record. The importance of longer records in contextualising short term trends derived from fixed-periods influenced by natural annual, inter-annual and multi-decadal variability is highlighted. Due to the low signal (trend) to noise (variability) ratio, the apparent trends derived from the low flow indicators cannot be used as confident guides to inform future water resources planning and decision making on climate change. Infact, some derived trends contradict expected climate change impacts and even small changes in study design can change the outcomes to a high degree. Therefore it is important not only to evaluate the magnitude of trends derived from monitoring data but also when a trend of a certain magnitude in a given indicator will be detectable to inform decision making or what changes might be required to detect trends for a certain significance level. In this study, the influence of observed variance in the monitoring records on the expected detection times for trends with a fixed magnitude are presented. Depending on the indicator selected, the sample variance and trend magnitude very different detection time estimates are obtained and in most cases not within the time required for anticipatory adaptation in the water resources sector. Additionally, the minimum changes in low flow indicators required to be detectable are large and changes are unlikely to be statistically detectable for many years. This means that water management and planning for anticipated future climatic changes will be required to take place without these changes being formally statistically detectable.Waiting for these trends to become formally detectable with the traditional statistical methods might not be an option for water resources management. Within the monitoring network, a considerable difference is apparent between stations in terms of detection times and changes required for detection. The existence of flow monitoring stations showing short detection times for specific indicators confirms the potential for identifying stations that may be first responders to climate induced changes. Identifying sentinel stations can increase the ability to more effectively optimise the deployment of resources for monitoring the influences of climatic change in a hydrometric reference network.

Benchmarking homogenization algorithms for monthly data

NASA Astrophysics Data System (ADS)

Venema, V. K. C.; Mestre, O.; Aguilar, E.; Auer, I.; Guijarro, J. A.; Domonkos, P.; Vertacnik, G.; Szentimrey, T.; Stepanek, P.; Zahradnicek, P.; Viarre, J.; Müller-Westermeier, G.; Lakatos, M.; Williams, C. N.; Menne, M. J.; Lindau, R.; Rasol, D.; Rustemeier, E.; Kolokythas, K.; Marinova, T.; Andresen, L.; Acquaotta, F.; Fratianni, S.; Cheval, S.; Klancar, M.; Brunetti, M.; Gruber, C.; Prohom Duran, M.; Likso, T.; Esteban, P.; Brandsma, T.

2012-01-01

The COST (European Cooperation in Science and Technology) Action ES0601: advances in homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies and because they represent two important types of statistics (additive and multiplicative). The algorithms were validated against a realistic benchmark dataset. The benchmark contains real inhomogeneous data as well as simulated data with inserted inhomogeneities. Random independent break-type inhomogeneities with normally distributed breakpoint sizes were added to the simulated datasets. To approximate real world conditions, breaks were introduced that occur simultaneously in multiple station series within a simulated network of station data. The simulated time series also contained outliers, missing data periods and local station trends. Further, a stochastic nonlinear global (network-wide) trend was added. Participants provided 25 separate homogenized contributions as part of the blind study. After the deadline at which details of the imposed inhomogeneities were revealed, 22 additional solutions were submitted. These homogenized datasets were assessed by a number of performance metrics including (i) the centered root mean square error relative to the true homogeneous value at various averaging scales, (ii) the error in linear trend estimates and (iii) traditional contingency skill scores. The metrics were computed both using the individual station series as well as the network average regional series. The performance of the contributions depends significantly on the error metric considered. Contingency scores by themselves are not very informative. Although relative homogenization algorithms typically improve the homogeneity of temperature data, only the best ones improve precipitation data. Training the users on homogenization software was found to be very important. Moreover, state-of-the-art relative homogenization algorithms developed to work with an inhomogeneous reference are shown to perform best. The study showed that automatic algorithms can perform as well as manual ones.

Benchmarking monthly homogenization algorithms

NASA Astrophysics Data System (ADS)

Venema, V. K. C.; Mestre, O.; Aguilar, E.; Auer, I.; Guijarro, J. A.; Domonkos, P.; Vertacnik, G.; Szentimrey, T.; Stepanek, P.; Zahradnicek, P.; Viarre, J.; Müller-Westermeier, G.; Lakatos, M.; Williams, C. N.; Menne, M.; Lindau, R.; Rasol, D.; Rustemeier, E.; Kolokythas, K.; Marinova, T.; Andresen, L.; Acquaotta, F.; Fratianni, S.; Cheval, S.; Klancar, M.; Brunetti, M.; Gruber, C.; Prohom Duran, M.; Likso, T.; Esteban, P.; Brandsma, T.

2011-08-01

The COST (European Cooperation in Science and Technology) Action ES0601: Advances in homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies and because they represent two important types of statistics (additive and multiplicative). The algorithms were validated against a realistic benchmark dataset. The benchmark contains real inhomogeneous data as well as simulated data with inserted inhomogeneities. Random break-type inhomogeneities were added to the simulated datasets modeled as a Poisson process with normally distributed breakpoint sizes. To approximate real world conditions, breaks were introduced that occur simultaneously in multiple station series within a simulated network of station data. The simulated time series also contained outliers, missing data periods and local station trends. Further, a stochastic nonlinear global (network-wide) trend was added. Participants provided 25 separate homogenized contributions as part of the blind study as well as 22 additional solutions submitted after the details of the imposed inhomogeneities were revealed. These homogenized datasets were assessed by a number of performance metrics including (i) the centered root mean square error relative to the true homogeneous value at various averaging scales, (ii) the error in linear trend estimates and (iii) traditional contingency skill scores. The metrics were computed both using the individual station series as well as the network average regional series. The performance of the contributions depends significantly on the error metric considered. Contingency scores by themselves are not very informative. Although relative homogenization algorithms typically improve the homogeneity of temperature data, only the best ones improve precipitation data. Training was found to be very important. Moreover, state-of-the-art relative homogenization algorithms developed to work with an inhomogeneous reference are shown to perform best. The study showed that currently automatic algorithms can perform as well as manual ones.

Raingauge-Based Rainfall Nowcasting with Artificial Neural Network

NASA Astrophysics Data System (ADS)

Liong, Shie-Yui; He, Shan

2010-05-01

Rainfall forecasting and nowcasting are of great importance, for instance, in real-time flood early warning systems. Long term rainfall forecasting demands global climate, land, and sea data, thus, large computing power and storage capacity are required. Rainfall nowcasting's computing requirement, on the other hand, is much less. Rainfall nowcasting may use data captured by radar and/or weather stations. This paper presents the application of Artificial Neural Network (ANN) on rainfall nowcasting using data observed at weather and/or rainfall stations. The study focuses on the North-East monsoon period (December, January and February) in Singapore. Rainfall and weather data from ten stations, between 2000 and 2006, were selected and divided into three groups for training, over-fitting test and validation of the ANN. Several neural network architectures were tried in the study. Two architectures, Backpropagation ANN and Group Method of Data Handling ANN, yielded better rainfall nowcasting, up to two hours, than the other architectures. The obtained rainfall nowcasts were then used by a catchment model to forecast catchment runoff. The results of runoff forecast are encouraging and promising.With ANN's high computational speed, the proposed approach may be deliverable for creating the real-time flood early warning system.

Six and Three-Hourly Meteorological Observations From 223 Former U.S.S.R. Stations (NPD-048)

DOE Data Explorer

Razuvaev, V. N. [All-Russian Research Institute of Hydrometeorological Information, World Data Center, Russia; Apasova, E. B. [All-Russian Research Institute of Hydrometeorological Information, World Data Center, Russia; Martuganov, R. A. [All-Russian Research Institute of Hydrometeorological Information, World Data Center, Russia; Kaiser, D. P. [CDIAC, Oak Ridge National Laboratory; Marino, G. P. [CDIAC, Oak Ridge National Laboratory

2007-11-01

This database contains 6- and 3-hourly meteorological observations from a 223-station network of the former Soviet Union. These data have been made available through cooperation between the two principal climate data centers of the United States and Russia: the National Climatic Data Center (NCDC), in Asheville, North Carolina, and the All-Russian Research Institute of Hydrometeorological Information-World Data Centre (RIHMI-WDC) in Obninsk, Russia. The first version of this database extended through the mid-1980s (ending year dependent upon station) and was made available in 1995 by the Carbon Dioxide Information Analysis Center (CDIAC) as NDP-048. A second version of the database extended the data records through 1990. This third, and current version of the database includes data through 2000 for over half of the stations (mainly for Russia), whereas the remainder of the stations have records extending through various years of the 1990s. Because of the break up of the Soviet Union in 1991, and since RIHMI-WDC is a Russian institution, only Russain stations are generally available through 2000. The non-Russian station records in this database typically extend through 1991. Station records consist of 6- and 3-hourly observations of some 24 meteorological variables including temperature, past and present weather type, precipitation amount, cloud amount and type, sea level pressure, relative humidity, and wind direction and speed. The 6-hourly observations extend from 1936 through 1965; the 3-hourly observations extend from 1966 through 2000 (or through the latest year available). These data have undergone extensive quality assurance checks by RIHMI-WDC, NCDC, and CDIAC. The database represents a wealth of meteorological information for a large and climatologically important portion of the earth's land area, and should prove extremely useful for a wide variety of regional climate change studies.

Homogenisation of minimum and maximum air temperature in northern Portugal

NASA Astrophysics Data System (ADS)

Freitas, L.; Pereira, M. G.; Caramelo, L.; Mendes, L.; Amorim, L.; Nunes, L.

2012-04-01

Homogenization of minimum and maximum air temperature has been carried out for northern Portugal for the period 1941-2010. The database corresponds to the values of the monthly arithmetic averages calculated from daily values observed at stations within the network of stations managed by the national Institute of Meteorology (IM). Some of the weather stations of IM's network are collecting data for more than a century; however, during the entire observing period, some factors have affected the climate series and have to be considered such as, changes in the station surroundings and changes related to replacement of manually operated instruments. Besides these typical changes, it is of particular interest the station relocation to rural areas or to the urban-rural interface and the installation of automatic weather stations in the vicinity of the principal or synoptic stations with the aim of replacing them. The information from these relocated and new stations was merged to produce just one but representative time series of that site. This process starts at the end 90's and the information of the time series fusion process constitutes the set of metadata used. Two basic procedures were performed: (i) preliminary statistical and quality control analysis; and, (ii) detection and correction of problems of homogeneity. In the first case, was developed and used software for quality control, specifically dedicated for the detection of outliers, based on the quartile values of the time series itself. The analysis of homogeneity was performed using the MASH (Multiple Analysis of Series for Homogenisation) and HOMER, which is a software application developed and recently made available within the COST Action ES0601 (COST-ES0601, 2012). Both methods provide a fast quality control of the original data and were developed for automatic processing, analyzing, homogeneity testing and adjusting of climatological data, but manual usage is also possible. Obtained results with both methods will be presented, compared and discussed along with the results of the sensitivity tests performed with both methods. COST-ES0601, 2012: "ACTION COST-ES0601 - Advances in homogenisation methods of climate series: an integrated approach HOME". Available at http://www.homogenisation.org/v_02_15/ [accessed 3 January 2012].

Framework for a U.S. Geological Survey Hydrologic Climate-Response Program in Maine

USGS Publications Warehouse

Hodgkins, Glenn A.; Lent, Robert M.; Dudley, Robert W.; Schalk, Charles W.

2009-01-01

This report presents a framework for a U.S. Geological Survey (USGS) hydrologic climate-response program designed to provide early warning of changes in the seasonal water cycle of Maine. Climate-related hydrologic changes on Maine's rivers and lakes in the winter and spring during the last century are well documented, and several river and lake variables have been shown to be sensitive to air-temperature changes. Monitoring of relevant hydrologic data would provide important baseline information against which future climate change can be measured. The framework of the hydrologic climate-response program presented here consists of four major parts: (1) identifying homogeneous climate-response regions; (2) identifying hydrologic components and key variables of those components that would be included in a hydrologic climate-response data network - as an example, streamflow has been identified as a primary component, with a key variable of streamflow being winter-spring streamflow timing; the data network would be created by maintaining existing USGS data-collection stations and establishing new ones to fill data gaps; (3) regularly updating historical trends of hydrologic data network variables; and (4) establishing basins for process-based studies. Components proposed for inclusion in the hydrologic climate-response data network have at least one key variable for which substantial historical data are available. The proposed components are streamflow, lake ice, river ice, snowpack, and groundwater. The proposed key variables of each component have extensive historical data at multiple sites and are expected to be responsive to climate change in the next few decades. These variables are also important for human water use and (or) ecosystem function. Maine would be divided into seven climate-response regions that follow major river-basin boundaries (basins subdivided to hydrologic units with 8-digit codes or larger) and have relatively homogeneous climates. Key hydrologic variables within each climate-response region would be analyzed regularly to maintain up-to-date analyses of year-to-year variability, decadal variability, and longer term trends. Finally, one basin in each climate-response region would be identified for process-based hydrologic and ecological studies.

How robust is the pre-1931 National Climatic Data Center—climate divisional dataset? Examples from Georgia and Louisiana

NASA Astrophysics Data System (ADS)

Allard, Jason; Thompson, Clint; Keim, Barry D.

2015-04-01

The National Climatic Data Center's climate divisional dataset (CDD) is commonly used in climate change analyses. This dataset is a spatially continuous dataset for the conterminous USA from 1895 to the present. The CDD since 1931 is computed by averaging all available representative cooperative weather station data into a single monthly value for each of the 344 climate divisions of the conterminous USA, while pre-1931 data for climate divisions are derived from statewide averages using regression equations. This study examines the veracity of these pre-1931 data. All available Cooperative Observer Program (COOP) stations within each climate division in Georgia and Louisiana were averaged into a single monthly value for each month and each climate division from 1897 to 1930 to generate a divisional dataset (COOP DD), using similar methods to those used by the National Climatic Data Center to generate the post-1931 CDD. The reliability of the official CDD—derived from statewide averages—to produce temperature and precipitation means and trends prior to 1931 are then evaluated by comparing that dataset with the COOP DD with difference-of-means tests, correlations, and linear regression techniques. The CDD and the COOP DD are also compared to a divisional dataset derived from the United States Historical Climatology Network (USHCN) data (USHCN DD), with difference of means and correlation techniques, to demonstrate potential impacts of inhomogeneities within the CDD and the COOP DD. The statistical results, taken as a whole, not only indicate broad similarities between the CDD and COOP DD but also show that the CDD does not adequately portray pre-1931 temperature and precipitation in certain climate divisions within Georgia and Louisiana. In comparison with the USHCN DD, both the CDD and the COOP DD appear to be subject to biases that probably result from changing stations within climate divisions. As such, the CDD should be used judiciously for long-term studies of climate change, and past studies using the CDD should be evaluated in the context of these new findings.

Monitoring of persistent organic pollutants in Africa. Part 2: design of a network to monitor the continental and intercontinental background.

PubMed

Lammel, G; Dobrovolný, P; Dvorská, A; Chromá, K; Brázdil, R; Holoubek, I; Hosek, J

2009-11-01

A network for the study of long-term trends of the continental background in Africa and the intercontinental background of persistent organic pollutants as resulting from long-range transport of contaminants from European, South Asian, and other potential source regions, as well as by watching supposedly pristine regions, i.e. the Southern Ocean and Antarctica is designed. The results of a pilot phase sampling programme in 2008 and meteorological and climatological information from the period 1961-2007 was used to apply objective criteria for the selection of stations for the monitoring network: out the original 26 stations six have been rejected because of suggested strong local sources of POPs and three others because of local meteorological effects, which may prevent part of the time long-range transported air to reach the sampling site. Representativeness of the meteorological patterns during the pilot phase with respect to climatology was assessed by comparison of the more local airflow situation as given by climatological vs. observed wind roses and by comparison of backward trajectories with the climatological wind (NCEP/NCAR re-analyses). With minor exceptions advection to nine inspected stations was typical for present-day climate during the pilot phase, 2008. Six to nine stations would cover satisfyingly large and densely populated regions of North-eastern, West and East Africa and its neighbouring seas, the Mediterranean, Northern and Equatorial Atlantic Ocean, the Western Indian Ocean and the Southern Ocean. Among the more densely populated areas Southern Cameroon, parts of the Abessinian plateau and most of the Great Lakes area would not be covered. The potential of the network is not hampered by on-going long-term changes of the advection to the selected stations, as these do hardly affect the coverage of target areas.

Diurnal centroid of ecosystem energy and carbon fluxes at FLUXNET sites

Treesearch

Kell B. Wilson; Dennis Baldocchi; Eva Falge; Marc Aubinet; Paul Berbigier; Christian Bernhofer; Han Dolman; Chris Field; Allen Goldstein; Andre Granier; Dave Hollinger; Gabriel Katul; B.E. Law; Tilden Meyers; John Moncrieff; Russ Monson; John Tenhunen; Riccardo Valentini; Shashi Verma; Steve Wofsy

2003-01-01

Data from a network of eddy covariance stations in Europe and North America (FLUXNET) were analyzed to examine the diurnal patterns of surface energy and carbon fluxes during the summer period across a range of ecosystems and climates. Diurnal trends were quantified by assessing the time of day surface fluxes and meteorological variable reached peak values, using the...

Analysis of Compound Water Hazard in Coastal Urbanized Areas under the Future Climate

NASA Astrophysics Data System (ADS)

Shibuo, Y.; Taniguchi, K.; Sanuki, H.; Yoshimura, K.; Lee, S.; Tajima, Y.; Koike, T.; Furumai, H.; Sato, S.

2017-12-01

Several studies indicate the increased frequency and magnitude of heavy rainfalls as well as the sea level rise under the future climate, which implies that coastal low-lying urbanized areas may experience increased risk against flooding. In such areas, where river discharge, tidal fluctuation, and city drainage networks altogether influence urban inundation, it is necessary to consider their potential interference to understand the effect of compound water hazard. For instance, pump stations cannot pump out storm water when the river water level is high, and in the meantime the river water level shall increase when it receives pumped water from cities. At the further downstream, as the tidal fluctuation regulates the water levels in the river, it will also affect the functionality of pump stations and possible inundation from rivers. In this study, we estimate compound water hazard in the coastal low-lying urbanized areas of the Tsurumi river basin under the future climate. We developed the seamlessly integrated river, sewerage, and coastal hydraulic model that can simulate river water levels, water flow in sewerage network, and inundation from the rivers and/or the coast to address the potential interference issue. As a forcing, the pseudo global warming method, which applies the changes in GCM anomaly to re-analysis data, is employed to produce ensemble typhoons to drive the seamlessly integrated model. The results show that heavy rainfalls caused by the observed typhoon generally become stronger under the pseudo global climate condition. It also suggests that the coastal low-lying areas become extensively inundated if the onset of river flooding and storm surge coincides.

Comparing interpolation techniques for annual temperature mapping across Xinjiang region

NASA Astrophysics Data System (ADS)

Ren-ping, Zhang; Jing, Guo; Tian-gang, Liang; Qi-sheng, Feng; Aimaiti, Yusupujiang

2016-11-01

Interpolating climatic variables such as temperature is challenging due to the highly variable nature of meteorological processes and the difficulty in establishing a representative network of stations. In this paper, based on the monthly temperature data which obtained from the 154 official meteorological stations in the Xinjiang region and surrounding areas, we compared five spatial interpolation techniques: Inverse distance weighting (IDW), Ordinary kriging, Cokriging, thin-plate smoothing splines (ANUSPLIN) and Empirical Bayesian kriging(EBK). Error metrics were used to validate interpolations against independent data. Results indicated that, the ANUSPLIN performed best than the other four interpolation methods.

An investigation on generalization ability of artificial neural networks and M5 model tree in modeling reference evapotranspiration

NASA Astrophysics Data System (ADS)

Kisi, Ozgur; Kilic, Yasin

2016-11-01

The generalization ability of artificial neural networks (ANNs) and M5 model tree (M5Tree) in modeling reference evapotranspiration ( ET 0 ) is investigated in this study. Daily climatic data, average temperature, solar radiation, wind speed, and relative humidity from six different stations operated by California Irrigation Management Information System (CIMIS) located in two different regions of the USA were used in the applications. King-City Oasis Rd., Arroyo Seco, and Salinas North stations are located in San Joaquin region, and San Luis Obispo, Santa Monica, and Santa Barbara stations are located in the Southern region. In the first part of the study, the ANN and M5Tree models were used for estimating ET 0 of six stations and results were compared with the empirical methods. The ANN and M5Tree models were found to be better than the empirical models. In the second part of the study, the ANN and M5Tree models obtained from one station were tested using the data from the other two stations for each region. ANN models performed better than the CIMIS Penman, Hargreaves, Ritchie, and Turc models in two stations while the M5Tree models generally showed better accuracy than the corresponding empirical models in all stations. In the third part of the study, the ANN and M5Tree models were calibrated using three stations located in San Joaquin region and tested using the data from the other three stations located in the Southern region. Four-input ANN and M5Tree models performed better than the CIMIS Penman in only one station while the two-input ANN models were found to be better than the Hargreaves, Ritchie, and Turc models in two stations.

Pan evaporation modeling using six different heuristic computing methods in different climates of China

NASA Astrophysics Data System (ADS)

Wang, Lunche; Kisi, Ozgur; Zounemat-Kermani, Mohammad; Li, Hui

2017-01-01

Pan evaporation (Ep) plays important roles in agricultural water resources management. One of the basic challenges is modeling Ep using limited climatic parameters because there are a number of factors affecting the evaporation rate. This study investigated the abilities of six different soft computing methods, multi-layer perceptron (MLP), generalized regression neural network (GRNN), fuzzy genetic (FG), least square support vector machine (LSSVM), multivariate adaptive regression spline (MARS), adaptive neuro-fuzzy inference systems with grid partition (ANFIS-GP), and two regression methods, multiple linear regression (MLR) and Stephens and Stewart model (SS) in predicting monthly Ep. Long-term climatic data at various sites crossing a wide range of climates during 1961-2000 are used for model development and validation. The results showed that the models have different accuracies in different climates and the MLP model performed superior to the other models in predicting monthly Ep at most stations using local input combinations (for example, the MAE (mean absolute errors), RMSE (root mean square errors), and determination coefficient (R2) are 0.314 mm/day, 0.405 mm/day and 0.988, respectively for HEB station), while GRNN model performed better in Tibetan Plateau (MAE, RMSE and R2 are 0.459 mm/day, 0.592 mm/day and 0.932, respectively). The accuracies of above models ranked as: MLP, GRNN, LSSVM, FG, ANFIS-GP, MARS and MLR. The overall results indicated that the soft computing techniques generally performed better than the regression methods, but MLR and SS models can be more preferred at some climatic zones instead of complex nonlinear models, for example, the BJ (Beijing), CQ (Chongqing) and HK (Haikou) stations. Therefore, it can be concluded that Ep could be successfully predicted using above models in hydrological modeling studies.

Data Acquisition System for Russian Arctic Magnetometer Network

NASA Astrophysics Data System (ADS)

Janzhura, A.; Troshichev, O. A.; Takahashi, K.

2010-12-01

Monitoring of magnetic activity in the auroral zone is very essential for space weather problem. The big part of northern auroral zone lies in the Russian sector of Arctica. The Russian auroral zone stations are located far from the proper infrastructure and communications, and getting the data from the stations is complicated and nontrivial task. To resolve this problem a new acquisition system for magnetometers was implemented and developed in last few years, with the magnetic data transmission in real time that is important for many forecasting purpose. The system, based on microprocessor modules, is very reliable in hush climatic conditions. The information from the magnetic sensors transmits to AARI data center by satellite communication system and is presented at AARI web pages. This equipment upgrading of Russian polar magnetometer network is supported by the international RapidMag program.

Daily Snow Depth Measurements from 195 Stations in the United States (1997) (NDP-059)

DOE Data Explorer

Easterling, D. R. [NOAA, National Climatic Data Center; Jamason, P. [NOAA, National Climatic Data Center; Bowman, D. P. [NOAA, National Climatic Data Center; Hughes, P. Y. [NOAA, National Climatic Data Center; Mason, E. H. [NOAA, National Climatic Data Center; Allison, L. J. [ORNL, Carbon Dioxide Information Analysis Center (CDIAC)

1997-02-01

This data package provides daily measurements of snow depth at 195 National Weather Service (NWS) first-order climatological stations in the United States. The data have been assembled and made available by the National Climatic Data Center (NCDC) in Asheville, North Carolina. The 195 stations encompass 388 unique sampling locations in 48 of the 50 states; no observations from Delaware or Hawaii are included in the database. Station selection criteria emphasized the quality and length of station records while seeking to provide a network with good geographic coverage. Snow depth at the 388 locations was measured once per day on ground open to the sky. The daily snow depth is the total depth of the snow on the ground at measurement time. The time period covered by the database is 1893-1992; however, not all station records encompass the complete period. While a station record ideally should contain daily data for at least the seven winter months (January through April and October through December), not all stations have complete records. Each logical record in the snow depth database contains one station's daily data values for a period of one month, including data source, measurement, and quality flags. The snow depth data have undergone extensive manual and automated quality assurance checks by NCDC and the Carbon Dioxide Information Analysis Center (CDIAC). These reviews involved examining the data for completeness, reasonableness, and accuracy, and included comparison of some data records with records in NCDC's Summary of the Day First Order online database. Since the snow depth measurements have been taken at NWS first-order stations that have long periods of record, they should prove useful in monitoring climate change.

Long-term Trends in Mean Annual Streamflow in the United States for the Period 1960 to 2012

NASA Astrophysics Data System (ADS)

Anderson, M. T.; Norton, P. A.

2013-12-01

Long-term trends in mean annual streamflow were examined in the United States for evidence of climate change. Streamflow serves as a useful integrator of many climate factors, such as precipitation, evapotranspiration, temperature and other hydrologic processes. The U.S. Geological Survey network of gaging stations with continuous record for the period 1960 through 2012 were considered and analyzed using the Kendall Tau statistical method looking for monotonic trends at a p-value greater than or equal to 0.1. Of the stations with 52 years of continuous record, 489 had upward trends while 260 stations had downward trends. Distinct geographic patterns of upward and downward trends emerged. Upward trends predominate in a band of stations extending from the eastern Dakotas through the Midwest to the New England states. Downward trends predominate in the southeastern United States and the Rocky Mountains of Wyoming, Montana and Idaho. Of those stations with upward trends, 56 stations had an increase in the annual mean that more than doubled from 1960 to 2012. The James River in South Dakota and the Red River of the North in North Dakota stand out for the magnitude of increase and the volume of water the increase represents. Of those stations with downward trends, 35 stations had a decrease that was more than half of the annual mean from 1960 to 2012. This presentation will provide details of these trends, the volumes of water represented, the associated precipitation trends and some evidence of land use change.

Climate Forcing Datasets for Agricultural Modeling: Merged Products for Gap-Filling and Historical Climate Series Estimation

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Goldberg, Richard; Chryssanthacopoulos, James

2014-01-01

The AgMERRA and AgCFSR climate forcing datasets provide daily, high-resolution, continuous, meteorological series over the 1980-2010 period designed for applications examining the agricultural impacts of climate variability and climate change. These datasets combine daily resolution data from retrospective analyses (the Modern-Era Retrospective Analysis for Research and Applications, MERRA, and the Climate Forecast System Reanalysis, CFSR) with in situ and remotely-sensed observational datasets for temperature, precipitation, and solar radiation, leading to substantial reductions in bias in comparison to a network of 2324 agricultural-region stations from the Hadley Integrated Surface Dataset (HadISD). Results compare favorably against the original reanalyses as well as the leading climate forcing datasets (Princeton, WFD, WFD-EI, and GRASP), and AgMERRA distinguishes itself with substantially improved representation of daily precipitation distributions and extreme events owing to its use of the MERRA-Land dataset. These datasets also peg relative humidity to the maximum temperature time of day, allowing for more accurate representation of the diurnal cycle of near-surface moisture in agricultural models. AgMERRA and AgCFSR enable a number of ongoing investigations in the Agricultural Model Intercomparison and Improvement Project (AgMIP) and related research networks, and may be used to fill gaps in historical observations as well as a basis for the generation of future climate scenarios.

Evaluation of Uncertainty in Precipitation Datasets for New Mexico, USA

NASA Astrophysics Data System (ADS)

Besha, A. A.; Steele, C. M.; Fernald, A.

2014-12-01

Climate change, population growth and other factors are endangering water availability and sustainability in semiarid/arid areas particularly in the southwestern United States. Wide coverage of spatial and temporal measurements of precipitation are key for regional water budget analysis and hydrological operations which themselves are valuable tool for water resource planning and management. Rain gauge measurements are usually reliable and accurate at a point. They measure rainfall continuously, but spatial sampling is limited. Ground based radar and satellite remotely sensed precipitation have wide spatial and temporal coverage. However, these measurements are indirect and subject to errors because of equipment, meteorological variability, the heterogeneity of the land surface itself and lack of regular recording. This study seeks to understand precipitation uncertainty and in doing so, lessen uncertainty propagation into hydrological applications and operations. We reviewed, compared and evaluated the TRMM (Tropical Rainfall Measuring Mission) precipitation products, NOAA's (National Oceanic and Atmospheric Administration) Global Precipitation Climatology Centre (GPCC) monthly precipitation dataset, PRISM (Parameter elevation Regression on Independent Slopes Model) data and data from individual climate stations including Cooperative Observer Program (COOP), Remote Automated Weather Stations (RAWS), Soil Climate Analysis Network (SCAN) and Snowpack Telemetry (SNOTEL) stations. Though not yet finalized, this study finds that the uncertainty within precipitation estimates datasets is influenced by regional topography, season, climate and precipitation rate. Ongoing work aims to further evaluate precipitation datasets based on the relative influence of these phenomena so that we can identify the optimum datasets for input to statewide water budget analysis.

Capacity Building with CHIRPS Amidst a Station-Recording Crisis

NASA Astrophysics Data System (ADS)

Peterson, P.

2016-12-01

Station data are essential for improving the accuracy of satellite-derived rainfall products. However we face a severe reporting crisis as the number of available stations observations has declined precipitously. For example there were 2400 monthly stations available in Africa (excluding South Africa) in the 1980's, while at present there are about 500 stations (Figure 1). In this talk we describe how partnerships with regional and national collaborators can improve our collective ability to monitor food production and inform decision making. A high quality, long-term, high-resolution precipitation dataset is key for supporting agricultural drought monitoring, food security and early warning. Here we present the Climate Hazards group InfraRed Precipitation with Stations (CHIRPS) v2.0, developed by scientists at the University of California, Santa Barbara and the U.S. Geological Survey Earth Resources Observation and Science Center under the direction of Famine Early Warning Systems Network (FEWS NET). This quasi-global precipitation product is available at daily to seasonal time scales with a spatial resolution of 0.05° and a 1981 to near real-time period of record. The Climate Hazards Group (CHG) has developed an extensive database of in situ daily, pentadal, and monthly precipitation totals with over a billion daily observations worldwide. Under support from the USAID FEWS NET, CHG/USGS has developed a two way strategy for incorporating contributed station data while providing web-based visualization tools to partners in developing nations. For example, we are currently working with partners in Mexico (Conagua), Southern Africa (SASSCAL), Colombia (IDEAM), Somalia (SWALIM) and Ethiopia (NMA). These institutions provide in situ observations which enhance the CHIRPS. The CHIRPS is then placed in a web accessible geospatial database. Partners in these countries can then access and display this information using web based mapping tools. This provides a win-win collaboration, leading to improved globally accessible precipitation estimates and improved climate services in developing nations.

The Climate Hazards group InfraRed Precipitation (CHIRP) with Stations (CHIRPS): Development and Validation

NASA Astrophysics Data System (ADS)

Peterson, P.; Funk, C. C.; Husak, G. J.; Pedreros, D. H.; Landsfeld, M.; Verdin, J. P.; Shukla, S.

2013-12-01

CHIRP and CHIRPS are new quasi-global precipitation products with daily to seasonal time scales, a 0.05° resolution, and a 1981 to near real-time period of record. Developed by the Climate Hazards Group at UCSB and scientists at the U.S. Geological Survey Earth Resources Observation and Science Center specifically for drought early warning and environmental monitoring, CHIRPS provides moderate latency precipitation estimates that place observed hydrologic extremes in their historic context. Three main types of information are used in the CHIRPS: (1) global 0.05° precipitation climatologies, (2) time-varying grids of satellite-based precipitation estimates, and (3) in situ precipitation observations. CHIRP: The global grids of long-term (1980-2009) average precipitation were estimated for each month based on station data, averaged satellite observations, and physiographic parameters. 1981-present time-varying grids of satellite precipitation were derived from spatially varying regression models based on pentadal cold cloud duration (CCD) values and TRMM V7 training data. The CCD time-series were derived from the CPC and NOAA B1 datasets. Pentadal CCD-percent anomaly values were multiplied by pentadal climatology fields to produce low bias pentadal precipitation estimates. CHIRPS: The CHG station blending procedure uses the satellite-observed spatial covariance structure to assign relative weights to neighboring stations and the CHIRP values. The CHIRPS blending procedure is based on the expected correlation between precipitation at a given target location and precipitation at the locations of the neighboring observation stations. These correlations are estimated using the CHIRP fields. The CHG has developed an extensive archive of in situ daily, pentadal and monthly precipitation totals. The CHG database has over half a billion daily rainfall observations since 1980 and another half billion before 1980. Most of these observations come from four sets of global climate observations: the monthly Global Historical Climate Network version 2 archive, the daily Global Historical Climate Network archive, the Global Summary of the Day dataset (GSOD), and the daily Global Telecommunication System (GTS) archive provided by NOAA's Climate Prediction Center (CPC). A screening procedure was developed to flag and remove potential false zeros from the daily data, since these potentially spurious data can artificially suppress rainfall totals. Validation: Our validation focused on precipitation products with global coverage, long periods of record and near real-time availability: CHIRP, CHIRPS, CPC-Unified, CFS Reanalysis and ECMWF datasets were compared to GPCC and high quality datasets from Uganda, Colombia and the Sahel. The CHIRP and CHIRPS are shown to have low systematic errors (bias) and low mean absolute errors. Analyses in Uganda, Colombia and the Sahel indicate that the ECMWF, CPC-Unified and CFS-Reanalysis have large inhomogeneities, making them unsuitable for drought monitoring. The CHIRPS performance appears quite similar to research quality products like the GPCC and GPCP, but with higher resolution and lower latency.

Predictability Analysis of PM10 Concentrations in Budapest

NASA Astrophysics Data System (ADS)

Ferenczi, Zita

2013-04-01

Climate, weather and air quality may have harmful effects on human health and environment. Over the past few hundred years we had to face the changes in climate in parallel with the changes in air quality. These observed changes in climate, weather and air quality continuously interact with each other: pollutants are changing the climate, thus changing the weather, but climate also has impacts on air quality. The increasing number of extreme weather situations may be a result of climate change, which could create favourable conditions for rising of pollutant concentrations. Air quality in Budapest is determined by domestic and traffic emissions combined with the meteorological conditions. In some cases, the effect of long-range transport could also be essential. While the time variability of the industrial and traffic emissions is not significant, the domestic emissions increase in winter season. In recent years, PM10 episodes have caused the most critical air quality problems in Budapest, especially in winter. In Budapest, an air quality network of 11 stations detects the concentration values of different pollutants hourly. The Hungarian Meteorological Service has developed an air quality prediction model system for the area of Budapest. The system forecasts the concentration of air pollutants (PM10, NO2, SO2 and O3) for two days in advance. In this work we used meteorological parameters and PM10 data detected by the stations of the air quality network, as well as the forecasted PM10 values of the air quality prediction model system. In this work we present the evaluation of PM10 predictions in the last two years and the most important meteorological parameters affecting PM10 concentration. The results of this analysis determine the effect of the meteorological parameters and the emission of aerosol particles on the PM10 concentration values as well as the limits of this prediction system.

The Future of the United States Antarctic Program

NASA Astrophysics Data System (ADS)

Thom, J. E.; Weidner, G. A.; Lazzara, M. A.; Knuth, S. L.; Cassano, J. J.

2009-04-01

The last three decades have seen Antarctic surface meteorological observations augmented by an increasing number of automated weather stations (AWS). Since 1980, the University of Wisconsin-Madison has managed an expanding array of AWS in Antarctica that are funded through the United States' National Science Foundation. The AWS network began with six stations and has grown to approximately 60 stations. The majority of the AWS use a custom electronics package designed in the 1970s and modified over approximately 20 years. However, dramatic changes in the electronics industry have led the UW-Madison to transition its AWS to commercial-off-the-shelf (COTS) components capable of integrating on-station storage, varied sensors, multiple data telemetry options, and a flexible operating system. Among the important technical issues arising from adopting a COTS-based AWS system are limited temperature certification for Antarctic conditions; non-standard integration of the varied telecommunications equipment; potentially inflexible data acquisition schemes; and frequent product upgrades, changes, and obsolescence. The UW-Madison presents the current status of its AWS system; its recent experience with new data loggers, sensors, and communication options; and its attempts to obtain a standardized AWS. The intent is to encourage the development of a forum where groups can document their experiences with varied AWS systems in the extreme polar climate. Recent events have added another challenge within the United States Antarctic Program, as it has become clear that budgetary and logistic limitations will drastically impact the AWS program. With logistical costs playing a bigger factor in funding AWS operations, international coordination and cooperation will be important in deploying and maintaining the AWS networks (such as GCOS) that are critical to monitoring the world's climate.

The Trans-African Hydro-Meteorlogical Observatory (TAHMO): Interactions with Schools, Students, and Citizens

NASA Astrophysics Data System (ADS)

Van De Giesen, N.; Selker, J. S.; Annor, F. O.

2016-12-01

The Trans-African Hydro-Meteorological Observatory (TAHMO) is an ambitious science initiative that aims to install and operate a dense network of measurement station throughout sub-Saharan Africa. The final density may be as high as one station every 30 km or a total of 20,000 stations. This network needs to be maintained both physically and financially. Financial sustainability must be guaranteed through a set of business cases that are relevant for people near the stations. For example, farmers need predictions to schedule irrigation or fertilizer application. It, at least from the point of view of academia, not trivial to become so directly relevant that a population with a very low average income is able and willing to pay for the upkeep of the research infrastructure. Still, when we scale the financial impact of a good weather prediction system with GDP, total value must be two to three billion dollars per years, a thousand time more than would be needed for network upkeep. TAHMO stations are placed at schools for two reasons. First, schools provide social and physical protection that would be difficult to provide otherwise, although cell towers do the same. More importantly, TAHMO engages teachers and students by offering curriculum items about the environment, sensing, and even business development. In this, we work closely with the GLOBE program that has a network in many countries in which TAHMO is active. We also team up schools in pairs to exchange ideas and information about weather and climate across continents. Finally, TAHMO works closely together with African universities in Ghana, Nigeria, Kenya, and Uganda. Engagement takes place through sensor competitions that really bring about a lot of creative energy. Many students who were involved in the competitions are still working to make TAHMO a reality. The projection for 2017 is to have 800 stations running and reporting.

Country-wide rainfall maps from cellular communication networks

PubMed Central

Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

2013-01-01

Accurate and timely surface precipitation measurements are crucial for water resources management, agriculture, weather prediction, climate research, as well as ground validation of satellite-based precipitation estimates. However, the majority of the land surface of the earth lacks such data, and in many parts of the world the density of surface precipitation gauging networks is even rapidly declining. This development can potentially be counteracted by using received signal level data from the enormous number of microwave links used worldwide in commercial cellular communication networks. Along such links, radio signals propagate from a transmitting antenna at one base station to a receiving antenna at another base station. Rain-induced attenuation and, subsequently, path-averaged rainfall intensity can be retrieved from the signal’s attenuation between transmitter and receiver. Here, we show how one such a network can be used to retrieve the space–time dynamics of rainfall for an entire country (The Netherlands, ∼35,500 km2), based on an unprecedented number of links (∼2,400) and a rainfall retrieval algorithm that can be applied in real time. This demonstrates the potential of such networks for real-time rainfall monitoring, in particular in those parts of the world where networks of dedicated ground-based rainfall sensors are often virtually absent. PMID:23382210

Cluster analysis of Southeastern U.S. climate stations

NASA Astrophysics Data System (ADS)

Stooksbury, D. E.; Michaels, P. J.

1991-09-01

A two-step cluster analysis of 449 Southeastern climate stations is used to objectively determine general climate clusters (groups of climate stations) for eight southeastern states. The purpose is objectively to define regions of climatic homogeneity that should perform more robustly in subsequent climatic impact models. This type of analysis has been successfully used in many related climate research problems including the determination of corn/climate districts in Iowa (Ortiz-Valdez, 1985) and the classification of synoptic climate types (Davis, 1988). These general climate clusters may be more appropriate for climate research than the standard climate divisions (CD) groupings of climate stations, which are modifications of the agro-economic United States Department of Agriculture crop reporting districts. Unlike the CD's, these objectively determined climate clusters are not restricted by state borders and thus have reduced multicollinearity which makes them more appropriate for the study of the impact of climate and climatic change.

Weather Stations as Educational and Hazard-Forecasting Tools

NASA Astrophysics Data System (ADS)

Bowman, L. J.; Gierke, J. S.; Gochis, E. E.; Dominguez, R.; Mayer, A. S.

2014-12-01

Small, relatively inexpensive (<$1000 USD) weather stations can be valuable tools for enhancing inquiry-based educational opportunities at all grade levels, while also facilitating compilation of climate data for longer term research. Weather stations and networks of stations have been installed both locally and abroad in mostly rural and resource-limited settings. The data are being used either in the classroom to engage students in place-based, scientific investigations and/or research to improve hydrometeorological hazard forecasting, including water scarcity. The San Vicente (El Salvador) Network of six stations monitors rainfall to aid warning and evacuations for landslide and flooding hazards. Other parameters are used in modeling the watershed hydrology. A station installed in Hermosillo, Mexico is used in both Geography and Ecology Classes. Trends in temperature and rainfall are graphed and compared to historic data gathered over the last 30 years by CONAGUA. These observations are linked to local water-related problems, including well salinization, diminished agriculture, depleted aquifers, and social conflict regarding access to water. Two weather stations were installed at the Hannahville Indian Community School (Nah Tah Wahsh) in Michigan for educational purposes of data collection, analysis, and presentation. Through inquiry-based explorations of local hydrological processes, students are introduced to how meteorological data are used in understanding watershed hydrology and the sustainable management of groundwater resources. Several Michigan Technological University Peace Corps Masters International students have deployed weather stations in and around the communities where they serve, and the data are used in research to help in understanding water resource availability and irrigation needs.

Climate and ET: Does Plant Water Requirements Increase during Droughts?

NASA Astrophysics Data System (ADS)

Fipps, G.; Bonaiti, G.; Swanson, C.

2012-04-01

With the expected rise in global warming and increased frequency of extreme climate variability in the coming decades, conservation and efficient use of water resources is essential and must make use of the most accurate and representative data available. Historically, governmental and private organizations have used estimates of plant water use estimated from a variety of methods for long-term water planning, for designing hydraulic structures, and for establishing regulatory guidance and conservation programs intended to reduce water waste. In recent years, there has been an expansion of agricultural weather station networks which report daily ETo (potential evapotranspiration) and commercial irrigation controllers with instrumentation which calculate real-time ETo from weather parameters. Efforts are underway to use this more precise information for regional water planning and ETo is routinely used for designing and implementing drought response programs. The year 2011 marked the driest year on record in the State of Texas. Compounding the lack of rainfall was record heat during the summer of 2011. In 2011, real-time ETo (reference evapotranspiration) data in Texas was 30 to 50% higher than historic averages. The implications are quite serious, as most current water planning and drought contingency plans do not take into consideration increases in ET during such periods, and irrigation planning and capacity sizing are based on historic averages of consumptive use. This paper examines the relationship between ET and climate during this extreme climatic event. While the solar radiation was near normal levels, temperature and wind was much higher and dew points much lower than norms. The variability and statistical difference between long term average ETo and ETo measurements (from 2006 to 2011) for selected weather stations of the Texas ET Network.

Development of the TLALOCNet GPS-Met Network in Northwestern Mexico: Supporting Continuous Water Vapor Observations of the North American Monsoon

NASA Astrophysics Data System (ADS)

Galetzka, J.; Feaux, K.; Cabral, E.; Salazar-Tlaczani, L.; Adams, D. K.; Serra, Y. L.; Mattioli, G. S.; Miller, M. M.

2014-12-01

TLALOCNet is a combined atmospheric and tectonic cGPS-Met network in Mexico designed for the investigation of climate, atmospheric processes, the earthquake cycle, and tectonics. While EarthScope-Plate Boundary Observatory (conterminous US, Alaska, Puerto Rico) is among the networks poised to become a nucleus for hemisphere-scale GPS observations, the completion of TLALOCNet at the end of 2015 will close a gap between PBO and other Latin American GPS networks that include COCONet (Central America, Caribbean, and Northern South America), CAnTO, CAP, and IGS extending from Alaska to Patagonia. The National Science Foundation funded the construction and operation of TLALOCNet, with significant matching funds and resources provided by the Universidad Nacional Autónoma de México (UNAM). The project will involve the construction or refurbishment of 38 cGPS-Met stations in Mexico built to PBO standards. The first three TLALOCNet stations were installed in the northern Mexican states of Sonora and Chihuahua in July 2014, following the North American Monsoon GPS Transect Experiment 2013. Together these observations better characterize critical components of water transport in the region. Data from these stations are now available through the UNAVCO data archive and can be downloaded from http://facility.unavco.org/data/dai2/app/dai2.html#. By the end of 2014, TLALOCNet data, together with complementary data from other regional cGPS networks in Mexico, will also be openly available through a Mexico-based data center. We will present the status of the project to date, including an overview of the station hardware, data communications, data flow, construction schedule, and science objectives. We will also present some of the challenges encountered, including regional logistics, shipping and importation, site security, and other issues associated with the construction and operation of a large continuous GPS network.

Atmospheric Carbon Monoxide Mixing Ratios NOAA Climate Monitoring and Diagnostics Laboratory Cooperative Air Sampling Network (1988-1993) (DB1011)

DOE Data Explorer

Novelli, P. C.; Masarie, K. A.

1994-01-01

Individual site files provide CO mixing ratios in parts per billion (ppb) (ppb = parts in 109 by mole fraction) based on measurements from the NOAA/CMDL Cooperative Air Sampling Network beginning 1988. Data are provided through June 1993 for stations at which the first sample was collected before July 1991. All samples were analyzed for CO at the NOAA/CMDL laboratory in Boulder by gas chromatography with mercuric oxide reduction detection, and all measurements are referenced to the CMDL CO scale (Novelli et al., 1991, Novelli et al., 1994).

Uncertainty of future projections of species distributions in mountainous regions.

PubMed

Tang, Ying; Winkler, Julie A; Viña, Andrés; Liu, Jianguo; Zhang, Yuanbin; Zhang, Xiaofeng; Li, Xiaohong; Wang, Fang; Zhang, Jindong; Zhao, Zhiqiang

2018-01-01

Multiple factors introduce uncertainty into projections of species distributions under climate change. The uncertainty introduced by the choice of baseline climate information used to calibrate a species distribution model and to downscale global climate model (GCM) simulations to a finer spatial resolution is a particular concern for mountainous regions, as the spatial resolution of climate observing networks is often insufficient to detect the steep climatic gradients in these areas. Using the maximum entropy (MaxEnt) modeling framework together with occurrence data on 21 understory bamboo species distributed across the mountainous geographic range of the Giant Panda, we examined the differences in projected species distributions obtained from two contrasting sources of baseline climate information, one derived from spatial interpolation of coarse-scale station observations and the other derived from fine-spatial resolution satellite measurements. For each bamboo species, the MaxEnt model was calibrated separately for the two datasets and applied to 17 GCM simulations downscaled using the delta method. Greater differences in the projected spatial distributions of the bamboo species were observed for the models calibrated using the different baseline datasets than between the different downscaled GCM simulations for the same calibration. In terms of the projected future climatically-suitable area by species, quantification using a multi-factor analysis of variance suggested that the sum of the variance explained by the baseline climate dataset used for model calibration and the interaction between the baseline climate data and the GCM simulation via downscaling accounted for, on average, 40% of the total variation among the future projections. Our analyses illustrate that the combined use of gridded datasets developed from station observations and satellite measurements can help estimate the uncertainty introduced by the choice of baseline climate information to the projected changes in species distribution.

Uncertainty of future projections of species distributions in mountainous regions

PubMed Central

Tang, Ying; Viña, Andrés; Liu, Jianguo; Zhang, Yuanbin; Zhang, Xiaofeng; Li, Xiaohong; Wang, Fang; Zhang, Jindong; Zhao, Zhiqiang

2018-01-01

Multiple factors introduce uncertainty into projections of species distributions under climate change. The uncertainty introduced by the choice of baseline climate information used to calibrate a species distribution model and to downscale global climate model (GCM) simulations to a finer spatial resolution is a particular concern for mountainous regions, as the spatial resolution of climate observing networks is often insufficient to detect the steep climatic gradients in these areas. Using the maximum entropy (MaxEnt) modeling framework together with occurrence data on 21 understory bamboo species distributed across the mountainous geographic range of the Giant Panda, we examined the differences in projected species distributions obtained from two contrasting sources of baseline climate information, one derived from spatial interpolation of coarse-scale station observations and the other derived from fine-spatial resolution satellite measurements. For each bamboo species, the MaxEnt model was calibrated separately for the two datasets and applied to 17 GCM simulations downscaled using the delta method. Greater differences in the projected spatial distributions of the bamboo species were observed for the models calibrated using the different baseline datasets than between the different downscaled GCM simulations for the same calibration. In terms of the projected future climatically-suitable area by species, quantification using a multi-factor analysis of variance suggested that the sum of the variance explained by the baseline climate dataset used for model calibration and the interaction between the baseline climate data and the GCM simulation via downscaling accounted for, on average, 40% of the total variation among the future projections. Our analyses illustrate that the combined use of gridded datasets developed from station observations and satellite measurements can help estimate the uncertainty introduced by the choice of baseline climate information to the projected changes in species distribution. PMID:29320501

Mountainous Ecosystem Sensor Array (MESA): a mesh sensor network for climate change research in remote mountainous environments

NASA Astrophysics Data System (ADS)

Robinson, P. W.; Neal, D.; Frome, D.; Kavanagh, K.; Davis, A.; Gessler, P. E.; Hess, H.; Holden, Z. A.; Link, T. E.; Newingham, B. A.; Smith, A. M.

2013-12-01

Developing sensor networks robust enough to perform unattended in the world's remote regions is critical since these regions serve as important benchmarks that lack anthropogenic influence. Paradoxically, the factors that make these remote, natural sites challenging for sensor networking are often what make them indispensable for climate change research. The MESA (Mountainous Ecosystem Sensor Array) project has faced these challenges and developed a wireless mesh sensor network across a 660 m topoclimatic gradient in a wilderness area in central Idaho. This sensor array uses advances in sensing, networking, and power supply technologies to provide near real-time synchronized data covering a suite of biophysical parameters used in ecosystem process models. The 76 sensors in the network monitor atmospheric carbon dioxide concentration, humidity, air and soil temperature, soil water content, precipitation, incoming and outgoing shortwave and longwave radiation, snow depth, wind speed and direction, and leaf wetness at synchronized time intervals ranging from two minutes to two hours and spatial scales from a few meters to two kilometers. We present our novel methods of placing sensors and network nodes above, below, and throughout the forest canopy without using meteorological towers. In addition, we explain our decision to use different forms of power (wind and solar) and the equipment we use to control and integrate power harvesting. Further, we describe our use of the network to sense and quantify its own power use. Using examples of environmental data from the project, we discuss how these data may be used to increase our understanding of the effects of climate change on ecosystem processes in mountainous environments. MESA sensor locations across a 700 m topoclimatic gradient at the University of Idaho Taylor Wilderness Research Station.

What will be the weather like tomorrow?

NASA Astrophysics Data System (ADS)

Christelle, Guilloux

2014-05-01

Since June 2010, our school is part of the network '"météo à l'école'": it hosts an autonomous weather station, approved by Météo France , which measures continuously the temperature and precipitation. The data is transmitted by a GSM module to a computer server. After its validation by Météo France, it is send online every day on a public accessible website : http://www.edumeteo.org/ The MPS Education ( Scientific Methods and Practices) in junior high school classes (one hour and half per week throughout the school year ) makes full use of data from the networks '"météo à l'école'" data and Météo France. Three scientific disciplines :; Mathematics, Life and Earth Sciences, Physical Sciences and Chemistry are part of a schedule defined after consultation and educational coherence to enable students to: - Discovering and understanding the operation of the sensors station, weather satellites ... - Operating satellite images, studying of the atmosphere and weather phenomena (formation of a storm, for example) - Operating collected data (networks 'météo à l'école' and Météo France) to identify climatic differences between regions, seasons, and their effects on living beings (study of the greenhouse effect and climate warming among others). The ultimate goal is to discover used tools and data to produce a weather forecast. We work for these purposes with the Cité de l'Espace in Toulouse (weather Pole) and the head forecaster Meteo France Merignac.

Climatic driving forces in inter-annual variation of global FPAR

NASA Astrophysics Data System (ADS)

Peng, Dailiang; Liu, Liangyun; Yang, Xiaohua; Zhou, Bin

2012-09-01

Fraction of Absorbed Photosynthetically Active Radiation (FPAR) characterizes vegetation canopy functioning and its energy absorption capacity. In this paper, we focus on climatic driving forces in inter-annual variation of global FPAR from 1982 to 2006 by Global Historical Climatology Network (GHCN-Monthly) data. Using FPAR-Simple Ratio Vegetation Index (SR) relationship, Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) was used to estimate FPAR at the global scale. The correlation between inter-annual variation of FPAR and temperature, precipitation derived from GHCN-Monthly was examined, during the periods of March-May (MAM), June-August (JJA), September-November (SON), and December-February (DJF) over from 1982 to 2006. The analysis of climatic influence on global FPAR revealed the significant correlation with temperature and precipitation in some meteorological stations area, and a more significant correlation with precipitation was found than which with temperature. Some stations in the regions between 30° N and 60° N and around 30° S in South America, where the annual FPAR variation showed a significant positive correlation with temperature (P < 0.01 or P < 0.05) during MAM, SON, and DJF, as well as in Europe during MAM and SON period. A negative correlation for more stations was observed during JJA. For precipitation, there were many stations showed a significant positive correlation with inter-annual variation of global FPAR (P < 0.01 or P < 0.05), especially for the tropical rainfall forest of Africa and Amazon during the dry season of JJA and SON.

Isoscapes of tree-ring carbon-13 perform like meteorological networks in predicting regional precipitation patterns

NASA Astrophysics Data System (ADS)

del Castillo, Jorge; Aguilera, Mònica; Voltas, Jordi; Ferrio, Juan Pedro

2013-03-01

isotopes in tree rings provide climatic information with annual resolution dating back for centuries or even millennia. However, deriving spatially explicit climate models from isotope networks remains challenging. Here we propose a methodology to model regional precipitation from carbon isotope discrimination (Δ13C) in tree rings by (1) building regional spatial models of Δ13C (isoscapes) and (2) deriving precipitation maps from Δ13C-isoscapes, taking advantage of the response of Δ13C to precipitation in seasonally dry climates. As a case study, we modeled the spatial distribution of mean annual precipitation (MAP) in the northeastern Iberian Peninsula, a region with complex topography and climate (MAP = 303-1086 mm). We compiled wood Δ13C data for two Mediterranean species that exhibit complementary responses to seasonal precipitation (Pinus halepensis Mill., N = 38; Quercus ilex L.; N = 44; pooling period: 1975-2008). By combining multiple regression and geostatistical interpolation, we generated one Δ13 C-isoscape for each species. A spatial model of MAP was then built as the sum of two complementary maps of seasonal precipitation, each one derived from the corresponding Δ13C-isoscape (September-November from Q. ilex; December-August from P. halepensis). Our approach showed a predictive power for MAP (RMSE = 84 mm) nearly identical to that obtained by interpolating data directly from a similarly dense network of meteorological stations (RMSE = 80-83 mm, N = 65), being only outperformed when using a much denser meteorological network (RMSE = 56-57 mm, N = 340). This method offers new avenues for modeling spatial variability of past precipitation, exploiting the large amount of information currently available from tree-ring networks.

Deploying temporary networks for upscaling of sparse network stations

NASA Astrophysics Data System (ADS)

Coopersmith, Evan J.; Cosh, Michael H.; Bell, Jesse E.; Kelly, Victoria; Hall, Mark; Palecki, Michael A.; Temimi, Marouane

2016-10-01

Soil observations networks at the national scale play an integral role in hydrologic modeling, drought assessment, agricultural decision support, and our ability to understand climate change. Understanding soil moisture variability is necessary to apply these measurements to model calibration, business and consumer applications, or even human health issues. The installation of soil moisture sensors as sparse, national networks is necessitated by limited financial resources. However, this results in the incomplete sampling of the local heterogeneity of soil type, vegetation cover, topography, and the fine spatial distribution of precipitation events. To this end, temporary networks can be installed in the areas surrounding a permanent installation within a sparse network. The temporary networks deployed in this study provide a more representative average at the 3 km and 9 km scales, localized about the permanent gauge. The value of such temporary networks is demonstrated at test sites in Millbrook, New York and Crossville, Tennessee. The capacity of a single U.S. Climate Reference Network (USCRN) sensor set to approximate the average of a temporary network at the 3 km and 9 km scales using a simple linear scaling function is tested. The capacity of a temporary network to provide reliable estimates with diminishing numbers of sensors, the temporal stability of those networks, and ultimately, the relationship of the variability of those networks to soil moisture conditions at the permanent sensor are investigated. In this manner, this work demonstrates the single-season installation of a temporary network as a mechanism to characterize the soil moisture variability at a permanent gauge within a sparse network.

Development of a global historic monthly mean precipitation dataset

NASA Astrophysics Data System (ADS)

Yang, Su; Xu, Wenhui; Xu, Yan; Li, Qingxiang

2016-04-01

Global historic precipitation dataset is the base for climate and water cycle research. There have been several global historic land surface precipitation datasets developed by international data centers such as the US National Climatic Data Center (NCDC), European Climate Assessment & Dataset project team, Met Office, etc., but so far there are no such datasets developed by any research institute in China. In addition, each dataset has its own focus of study region, and the existing global precipitation datasets only contain sparse observational stations over China, which may result in uncertainties in East Asian precipitation studies. In order to take into account comprehensive historic information, users might need to employ two or more datasets. However, the non-uniform data formats, data units, station IDs, and so on add extra difficulties for users to exploit these datasets. For this reason, a complete historic precipitation dataset that takes advantages of various datasets has been developed and produced in the National Meteorological Information Center of China. Precipitation observations from 12 sources are aggregated, and the data formats, data units, and station IDs are unified. Duplicated stations with the same ID are identified, with duplicated observations removed. Consistency test, correlation coefficient test, significance t-test at the 95% confidence level, and significance F-test at the 95% confidence level are conducted first to ensure the data reliability. Only those datasets that satisfy all the above four criteria are integrated to produce the China Meteorological Administration global precipitation (CGP) historic precipitation dataset version 1.0. It contains observations at 31 thousand stations with 1.87 × 107 data records, among which 4152 time series of precipitation are longer than 100 yr. This dataset plays a critical role in climate research due to its advantages in large data volume and high density of station network, compared to other datasets. Using the Penalized Maximal t-test method, significant inhomogeneity has been detected in historic precipitation datasets at 340 stations. The ratio method is then employed to effectively remove these remarkable change points. Global precipitation analysis based on CGP v1.0 shows that rainfall has been increasing during 1901-2013 with an increasing rate of 3.52 ± 0.5 mm (10 yr)-1, slightly higher than that in the NCDC data. Analysis also reveals distinguished long-term changing trends at different latitude zones.

Assessing uncertainty in high-resolution spatial climate data across the US Northeast.

PubMed

Bishop, Daniel A; Beier, Colin M

2013-01-01

Local and regional-scale knowledge of climate change is needed to model ecosystem responses, assess vulnerabilities and devise effective adaptation strategies. High-resolution gridded historical climate (GHC) products address this need, but come with multiple sources of uncertainty that are typically not well understood by data users. To better understand this uncertainty in a region with a complex climatology, we conducted a ground-truthing analysis of two 4 km GHC temperature products (PRISM and NRCC) for the US Northeast using 51 Cooperative Network (COOP) weather stations utilized by both GHC products. We estimated GHC prediction error for monthly temperature means and trends (1980-2009) across the US Northeast and evaluated any landscape effects (e.g., elevation, distance from coast) on those prediction errors. Results indicated that station-based prediction errors for the two GHC products were similar in magnitude, but on average, the NRCC product predicted cooler than observed temperature means and trends, while PRISM was cooler for means and warmer for trends. We found no evidence for systematic sources of uncertainty across the US Northeast, although errors were largest at high elevations. Errors in the coarse-scale (4 km) digital elevation models used by each product were correlated with temperature prediction errors, more so for NRCC than PRISM. In summary, uncertainty in spatial climate data has many sources and we recommend that data users develop an understanding of uncertainty at the appropriate scales for their purposes. To this end, we demonstrate a simple method for utilizing weather stations to assess local GHC uncertainty and inform decisions among alternative GHC products.

Ka-Band Site Characterization of the NASA Near Earth Network in Svalbard, Norway

NASA Technical Reports Server (NTRS)

Acosta, R.; Morse, J.; Nessel, J.; Zemba, M.; Tuttle, K.; Caroglanian, A.; Younes, B.; Pedersen, Sten-Chirstian

2011-01-01

Critical to NASA s rapid migration toward Ka-Band is the comprehensive characterization of the communication channels at NASA's ground sites to determine the effects of the atmosphere on signal propagation and the network's ability to support various classes of users in different orbits. Accordingly, NASA has initiated a number of studies involving the ground sites of its Near Earth and Deep Space Networks. Recently, NASA concluded a memorandum of agreement (MOA) with the Norwegian Space Centre of the Kingdom of Norway and began a joint site characterization study to determine the atmospheric effects on Ka-Band links at the Svalbard Satellite Station in Norway, which remains a critical component of NASA s Near Earth Communication Network (NEN). System planning and design for Ka-band links at the Svalbard site cannot be optimally achieved unless measured attenuation statistics (e.g. cumulative distribution functions (CDF)) are obtained. In general, the CDF will determine the necessary system margin and overall system availability due to the atmospheric effects. To statistically characterize the attenuation statistics at the Svalbard site, NASA has constructed a ground-based monitoring station consisting of a multi-channel total power radiometer (25.5 - 26.5 GHz) and a weather monitoring station to continuously measure (at 1 second intervals) attenuation and excess noise (brightness temperature). These instruments have been tested in a laboratory environment as well as in an analogous outdoor climate (i.e. winter in Northeast Ohio), and the station was deployed in Svalbard, Norway in May 2011. The measurement campaign is planned to last a minimum of 3 years but not exceeding a maximum of 5 years.

The CzeCOS Network

NASA Astrophysics Data System (ADS)

Havránková, Kateřina; Taufarová, Klára; Šigut, Ladislav; McGloin, Ryan; Acosta, Manuel; Dušek, Jiří; Krupková, Lenka; Macálková-Mžourková, Lenka; Pavelka, Marian; Dařenová, Eva; Yadav, Shilpi; Nguyen, Vinh; Guerra, Carlos; Janous, Dalibor; Marek, Michal V.

2017-04-01

The Global Change Research Institute of the Czech Academy of Sciences (CzechGlobe) have established a well-equipped network of ecosystem stations, with modern instrumentation for eco-physiological, plant physiological and micrometeorological studies, and estimation of GHG emissions. The network of stations (CzeCOS) covers the main terrestrial ecosystems of the Czech Republic (young and old coniferous forest, deciduous forest, mixed floodplain forest, grassland, wetland and cropland). The ecosystem stations are equipped with eddy covariance systems, soil and stem chamber systems for CO2 efflux and instruments for making micrometeorological measurements. The network enables detailed research to be conducted on topics such as: the carbon balance of different ecosystems, energy balance closure, the impact of current climate conditions on production and ecosystem disturbances during extreme weather conditions (drought, floods, winter storms, etc.) at regional, national and international scales. As a part of global networks (Fluxnet, ANAEe, ICOS), CzeCOS participates in evaluating and predicting environmental change and helps in the proposal of mitigation measures. Another important issue studied at some of the CzeCOS sites is the use of the eddy covariance method in sloping terrain in order to improve eddy covariance data processing for sites in this kind of terrain. Here we show specific results from the sites and outline the importance of the regional/national network for improving our knowledge about the exchange of matter and energy fluxes at different ecosystems. This study was supported by the Ministry of Education, Youth and Sports of CR within the National Sustainability Program I (NPU I), grant number LO1415 and LD 15040. Computational resources were provided by the CESNET LM2015042 and the CERIT Scientific Cloud LM2015085, provided under the programme "Projects of Large Research, Development, and Innovations Infrastructures".

Micro weather stations for in situ measurements in the Martian planetary boundary layer

NASA Technical Reports Server (NTRS)

Crisp, D.; Kaiser, W. J.; Kenny, T. W.; Vanzandt, T. R.; Tillman, J. E.

1992-01-01

Viking Lander meteorology measurements show that the Martian planetary boundary layer (PBL) has large diurnal and seasonal variations in pressure, wind velocity, relative humidity, and airborne dust loading. An even larger range of conditions was inferred from remote sensing observations acquired by the Mariner 9 and Viking orbiters. Numerical models indicate that these changes may be accompanied by dramatic vertical and horizontal wind shears (100 m/s/km) and rapid changes in the static stability. In-situ measurements from a relatively small number surface stations could yield global constraints on the Martian climate and atmospheric general circulation by providing ground truth for remote sensing instruments on orbiters. A more complete understanding of the meteorology of the PBL is an essential precursor to manned missions to Mars because this will be their working environment. In-situ measurements are needed for these studies because the spatial and temporal scales that characterize the important meteorological processes near the surface cannot be resolved from orbit. The Mars Environmental Survey (MESUR) Program will provide the first opportunity to deploy a network of surface weather stations for a comprehensive investigation of the Martian PBL. The feasibility and utility of a network of micro-weather stations for making in-situ meteorological measurements in the Martian PBL are assessed.

Long-term analysis and appropriate metrics of climate change in Mongolia

NASA Astrophysics Data System (ADS)

Jamiyansharav, Khishigbayar

This study addresses three important issues related to long-term climate change study in Mongolia. Mongolia is one of the biggest land-locked countries in Asia and 75--80 percent of the land is rangeland, which is highly vulnerable to climate change. Climate will affect many sectors critical to the country's economic, social, and ecological welfare. Therefore, it is regionally and globally important to evaluate climate change in Mongolia. Chapter 1 discusses the qualitative and descriptive study on exposure characteristics of the 17 Mongolian meteorological stations, which are part of the Global Climate Observing Network (GCON). The global average temperature anomalies are based in part on the GCON stations' meteorological data. To document the possible exposures surrounding the weather stations, the Mongolian meteorological stations were surveyed during July--August 2005. From the total 17 stations, 47 percent were determined strongly influenced by urban character landscape, 41 percent received some anthropogenic influences, and 12 percent had very little to no anthropogenic influences. Even though the Mongolian meteorological stations' exposure characteristics are better than the European and North American stations' the strict adherence in following WMO guidelines is important and urgently needed. Chapter 2 evaluates the long-term (1961--2005) trends in seasonal and annual surface mean, maximum, minimum temperatures and precipitation. Furthermore, this study compares the long-term mean temperature trends with decadal (1998--2007) trends. This chapter also discusses the extreme climate indices on spatial and temporal scales. According to the results, the long-term linear temperature trends show a clear increasing trend whereas the decadal trends show the decreasing trend mostly in winter and spring. The analysis of extreme indices (1961--2001) indicate that most of the stations frost and icing days are decreased and summer days, tropical nights, monthly maximum value of daily minimum, maximum temperatures and growing season length are increased. Precipitation indices varied substantially and there were no unified temporal and spatial pattern. In addition to that, I am suggesting effective temperature as an appropriate metric to evaluate surface heat change because it counts not only air temperature but also surface humidity. Chapter 3 discusses a case study of grazing intensity on surface energy budgets. To evaluate the land atmospheric interactions over the grassland area depending on the different grazing intensity I conducted the case study over the Shortgrass Steppe Long-Term Ecological Research site on Northern Great Plains of US to imply the findings in semiarid shortgrass steppe of Mongolia. The study site has much of similarities with Mongolian shortgrass steppe and has more frequent, high quality data. This study evaluates the impact of grazing on microclimate and energy budgets in a dry (163 mm) and two near-normal (262 and 260 mm) precipitation years based on continuously measured 20 minute interval data. This study helps to describe surface energy partitioning in semi-arid grasslands that has long history of grazing. The main finding of the study is grazing has a potential impact on the energy partitioning under conditions of higher water availability, but not during dry conditions.

Assessment of climate change impacts on climate variables using probabilistic ensemble modeling and trend analysis

NASA Astrophysics Data System (ADS)

Safavi, Hamid R.; Sajjadi, Sayed Mahdi; Raghibi, Vahid

2017-10-01

Water resources in snow-dependent regions have undergone significant changes due to climate change. Snow measurements in these regions have revealed alarming declines in snowfall over the past few years. The Zayandeh-Rud River in central Iran chiefly depends on winter falls as snow for supplying water from wet regions in high Zagrous Mountains to the downstream, (semi-)arid, low-lying lands. In this study, the historical records (baseline: 1971-2000) of climate variables (temperature and precipitation) in the wet region were chosen to construct a probabilistic ensemble model using 15 GCMs in order to forecast future trends and changes while the Long Ashton Research Station Weather Generator (LARS-WG) was utilized to project climate variables under two A2 and B1 scenarios to a future period (2015-2044). Since future snow water equivalent (SWE) forecasts by GCMs were not available for the study area, an artificial neural network (ANN) was implemented to build a relationship between climate variables and snow water equivalent for the baseline period to estimate future snowfall amounts. As a last step, homogeneity and trend tests were performed to evaluate the robustness of the data series and changes were examined to detect past and future variations. Results indicate different characteristics of the climate variables at upstream stations. A shift is observed in the type of precipitation from snow to rain as well as in its quantities across the subregions. The key role in these shifts and the subsequent side effects such as water losses is played by temperature.

Evaporation over a Heterogeneous Mixed Savanna-Agricultural Catchment using a Distributed Wireless Sensor Network

NASA Astrophysics Data System (ADS)

Ceperley, N. C.; Mande, T.; Barrenetxea, G.; Vetterli, M.; Yacouba, H.; Repetti, A.; Parlange, M. B.

2010-12-01

Small scale rain fed agriculture is the primary livelihood for a large part of the population of Burkina Faso. Regional climate change means that this population is becoming increasingly vulnerable. Additionally, as natural savanna is converted for agriculture, hydrological systems are observed to become less stable as infiltration is decreased and rapid runoff is increased to the detriment of crop productivity, downstream populations and local water sources. The majority of the Singou River Basin, located in South East Burkina Faso is managed by hunting reserves, geared to maintaining high populations of wild game; however, residents surrounding the protected areas have been forced to intensify agriculture that has resulted in soil degradation as well as increases in the frequency and severity of flooding and droughts. Agroforestry, or planting trees in cultivated fields, has been proposed as a solution to help buffer these negative consequences, however the specific hydrologic behavior of the watershed land cover is unknown. We have installed a distributed sensor network of 17 Sensorscope wireless meteorological stations. These stations are dispersed across cultivated rice and millet fields, natural savanna, fallow fields, and around agroforestry fields. Sensorscope routes data through the network of stations to be delivered by a GPRS connection to a main server. This multi hop network allows data to be gathered over a large area and quickly adapts to changes in station performance. Data are available in real time via a website that can be accessed by a mobile phone. The stations are powered autonomously by small photovoltaic panels. This deployment is the first time that these meteorological stations have been used on the African continent. Initial calibration with measures from 2 eddy covariance stations allows us to calculate the energy balance at each of the Sensorscope stations. Thus, we can observe variation in evaporation over the various land cover in the watershed. This research will both contribute to scientific understanding of West African vegetation and inform local reforestation and agricultural management. Concurrent to this scientific research, the community is improving natural resource management efforts including reforestation, a botanical garden and environmental education. Our hope is that the results of our evaporation modeling will inform local farmers and thus help improve their adaption to changing weather patterns and land cover.

Engendering Climate Information Networks in Africa: Case Studies of Digital and FM Radio for Disseminating Disaster Early Warnings to Women and Youth

NASA Astrophysics Data System (ADS)

Stewart, M. M.; Pratt, M.

2002-05-01

This paper examines the effectiveness of FM and digital radio in disseminating weather and climate information to remote rural populations in Niger and Uganda. In Niger, poor communications infrastructure necessitated the establishment of a basic radio system as a first step towards disseminating climate information. Dissemination via digital radio is limited, in this context, by lack of technical support and the difficulty of maintaining computer equipment in the hot and dusty climate. Community FM stations have supported a range of mitigation activities that reduced vulnerability in all sites studied. Digital radio proved a more effective tool for disseminating climate information in Uganda, where technical knowledge is more prevalent and infrastructure networks are stronger. The primary challenge in Uganda lies in maintaining equipment in remote locations and disseminating information to a wider audience by linking with FM radio. Climate and weather information is already demonstrating positive impacts on agricultural production in Uganda, health and civil society in Niger, and on vulnerability reduction in both countries. Radio,particularly FM, was an excellent medium for disseminating information to women, youth, and other hard to reach populations. Discussion will focus on recommendations for improving the effectiveness of both systems and for practically linking FM and digital dissemination systems for better communication of climate information. Implications of the case studies will also be discussed in the context of digital and FM radio as media for disseminating other types of scientific information.

Data from selected U.S. Geological Survey national stream water-quality monitoring networks (WQN) on CD-ROM

USGS Publications Warehouse

Alexander, R.B.; Ludtke, A.S.; Fitzgerald, K.K.; Schertz, T.L.

1996-01-01

Data from two U.S. Geological Survey (USGS) national stream water-quality monitoring networks, the National Stream Quality Accounting Network (NASQAN) and the Hydrologic Benchmark Network (HBN), are now available in a two CD-ROM set. These data on CD-ROM are collectively referred to as WQN, water-quality networks. Data from these networks have been used at the national, regional, and local levels to estimate the rates of chemical flux from watersheds, quantify changes in stream water quality for periods during the past 30 years, and investigate relations between water quality and streamflow as well as the relations of water quality to pollution sources and various physical characteristics of watersheds. The networks include 679 monitoring stations in watersheds that represent diverse climatic, physiographic, and cultural characteristics. The HBN includes 63 stations in relatively small, minimally disturbed basins ranging in size from 2 to 2,000 square miles with a median drainage basin size of 57 square miles. NASQAN includes 618 stations in larger, more culturally-influenced drainage basins ranging in size from one square mile to 1.2 million square miles with a median drainage basin size of about 4,000 square miles. The CD-ROMs contain data for 63 physical, chemical, and biological properties of water (122 total constituents including analyses of dissolved and water suspended-sediment samples) collected during more than 60,000 site visits. These data approximately span the periods 1962-95 for HBN and 1973-95 for NASQAN. The data reflect sampling over a wide range of streamflow conditions and the use of relatively consistent sampling and analytical methods. The CD-ROMs provide ancillary information and data-retrieval tools to allow the national network data to be properly and efficiently used. Ancillary information includes the following: descriptions of the network objectives and history, characteristics of the network stations and water-quality data, historical records of important changes in network sample collection and laboratory analytical methods, water reference sample data for estimating laboratory measurement bias and variability for 34 dissolved constituents for the period 1985-95, discussions of statistical methods for using water reference sample data to evaluate the accuracy of network stream water-quality data, and a bibliography of scientific investigations using national network data and other publications relevant to the networks. The data structure of the CD-ROMs is designed to allow users to efficiently enter the water-quality data to user-supplied software packages including statistical analysis, modeling, or geographic information systems. On one disc, all data are stored in ASCII form accessible from any computer system with a CD-ROM driver. The data also can be accessed using DOS-based retrieval software supplied on a second disc. This software supports logical queries of the water-quality data based on constituent concentrations, sample- collection date, river name, station name, county, state, hydrologic unit number, and 1990 population and 1987 land-cover characteristics for station watersheds. User-selected data may be output in a variety of formats including dBASE, flat ASCII, delimited ASCII, or fixed-field for subsequent use in other software packages.

ARC3.2 Summary for City Leaders Climate Change and Cities: Second Assessment Report of the Urban Climate Change Research Network

NASA Technical Reports Server (NTRS)

Rosenzweig, C.; Solecki, W.; Romero-Lankao, P.; Mehrotra, S.; Dhakal, S.; Bowman, T.; Ibrahim, S. Ali

2015-01-01

ARC3.2 presents a broad synthesis of the latest scientific research on climate change and cities. Mitigation and adaptation climate actions of 100 cities are documented throughout the 16 chapters, as well as online through the ARC3.2 Case Study Docking Station. Pathways to Urban Transformation, Major Findings, and Key Messages are highlighted here in the ARC3.2 Summary for City Leaders. These sections lay out what cities need to do achieve their potential as leaders of climate change solutions. UCCRN Regional Hubs in Europe, Latin America, Africa, Australia and Asia will share ARC3.2 findings with local city leaders and researchers. The ARC3.2 Summary for City Leaders synthesizes Major Findings and Key Messages on urban climate science, disasters and risks, urban planning and design, mitigation and adaptation, equity and environmental justice, economics and finance, the private sector, urban ecosystems, urban coastal zones, public health, housing and informal settlements, energy, water, transportation, solid waste, and governance. These were based on climate trends and future projections for 100 cities around the world.

The Network for the Detection of Atmospheric Composition Change (NDACC): history, status and perspectives

NASA Astrophysics Data System (ADS)

De Mazière, Martine; Thompson, Anne M.; Kurylo, Michael J.; Wild, Jeannette D.; Bernhard, Germar; Blumenstock, Thomas; Braathen, Geir O.; Hannigan, James W.; Lambert, Jean-Christopher; Leblanc, Thierry; McGee, Thomas J.; Nedoluha, Gerald; Petropavlovskikh, Irina; Seckmeyer, Gunther; Simon, Paul C.; Steinbrecht, Wolfgang; Strahan, Susan E.

2018-04-01

The Network for the Detection of Atmospheric Composition Change (NDACC) is an international global network of more than 90 stations making high-quality measurements of atmospheric composition that began official operations in 1991 after 5 years of planning. Apart from sonde measurements, all measurements in the network are performed by ground-based remote-sensing techniques. Originally named the Network for the Detection of Stratospheric Change (NDSC), the name of the network was changed to NDACC in 2005 to better reflect the expanded scope of its measurements. The primary goal of NDACC is to establish long-term databases for detecting changes and trends in the chemical and physical state of the atmosphere (mesosphere, stratosphere, and troposphere) and to assess the coupling of such changes with climate and air quality. NDACC's origins, station locations, organizational structure, and data archiving are described. NDACC is structured around categories of ground-based observational techniques (sonde, lidar, microwave radiometers, Fourier-transform infrared, UV-visible DOAS (differential optical absorption spectroscopy)-type, and Dobson-Brewer spectrometers, as well as spectral UV radiometers), timely cross-cutting themes (ozone, water vapour, measurement strategies, cross-network data integration), satellite measurement systems, and theory and analyses. Participation in NDACC requires compliance with strict measurement and data protocols to ensure that the network data are of high and consistent quality. To widen its scope, NDACC has established formal collaborative agreements with eight other cooperating networks and Global Atmosphere Watch (GAW). A brief history is provided, major accomplishments of NDACC during its first 25 years of operation are reviewed, and a forward-looking perspective is presented.

The Network for the Detection of Atmospheric Composition Change (NDACC): History, Status and Perspectives

NASA Technical Reports Server (NTRS)

Simon, Paul C.; De Maziere, Martine; Bernhard, Germar; Blumenstock, Thomas; McGee, Thomas J.; Petropavlovskikh, Irina; Steinbrecht, Wolfgang; Wild, Jeannette D.; Lambert, Jean-Christopher; Seckmeyer, Gunther;

GLACIOCLIM-SAMBA: A Terre Adelie / Wilkes Land Antarctic surface mass balance observatory

NASA Astrophysics Data System (ADS)

Genthon, C.; Frezzotti, M.; Le Meur, E.; Magand, O.; Six, D.; Wagnon, P.

2005-12-01

While local measurements at hundreds of sites are now available (although sometimes questionable, e.g. Magand et al., this volume) to verify how large-scale models reproduce the spatial distribution of the surface mass balance (SMB) of Antarctica, few field observations yet make it possible to verify current intra- and inter-annual variability and trends of the SMB in the models, and to evaluate the processes that relate this variability with that of climate. It is a major aim of the GLACIOCLIM-SAMBA observatory (http://lgge.obs.ujf-grenoble.fr/~christo/glacioclim/samba/), initiated in 2004, to provide such observations in the Terre Adelie and Wilkes Land area. Recognizing that the largest absolute changes (and thus contribution to sea-level) of Antarctic SMB are expected where the current mean SMB is largest, that is in the coastal regions, SAMBA is largely focused on ice sheet margin. To sample spatial scales compatible with the scales resolved by models used to predict climate and SMB changes, a 150 km accumulation stakes line is being set up from the coast near the French Dumont d'Urville station, towards to Antarctic plateau in the general direction of the Italy/France Concordia station. Ground penetrating radar survey will provide snap-shot SMB interpolation along the stakes line. A blue ice stretch at the coast is being monitored by a 50-stake ablation network. Three 50-stakes networks are being set up near Concordia station to relate coastal and plateau SMB variability and change. An automatic weather station (AWS, including radiation) deployed at the coast, and the D-10, D-47 and DCII Antarctic Meteorological Research Center (http://amrc.ssec.wisc.edu/) AWSs, provide meteorological information to relate observed SMB and climate. Italian meteorology and radiation programs at Concordia, planned micrometeorology special campaigns at the margin, and precipitation monitoring at both sites, should help decipher the processes that relate SMB and climate variability. As a summary of results on the existing observatory as of Jan; 2005: i) The first year mean SMB along a 50 km stakes line was ~60 cm water equivalent (we), which qualifies 2004 as a very high accumulation year in the Terre Adelie area; ii) Spatial variability along the stakes line is high, ranging from 16 to 125 cm (we), confirming the need for spatial sampling consistent with the scales resolved by climate models; iii) At the coastal blue ice, ablation occurs in summer only while the winter SMB is close to 0. The SAMBA observatory is scheduled to operate for at least 10 years, hopefully more if successful, with main support by the French (IPEV) and Italian (PNRA) Polar Institutes. The French ministry of research and Institut National des Sciences de l'univers (Climate Change and Cryosphere and ORE-GLACIOCLIM programs) also contribute support. All SAMBA observations will be distributed and freely available on the internet as soon as the observatory is fully operational and validated.

GUMNET - A new long-term monitoring initiative in the Guadarrama Mountains, Madrid, Spain

NASA Astrophysics Data System (ADS)

Rath, Volker; Fidel González Rouco, J.; Yagüe Anguis, Carlos

2014-05-01

We are announcing a new monitoring network in the Guadarrama Mountains north of Madrid, which is planned to be operational in early 2015. This network integrates atmospheric measurements as well as subsurface observations. It aims at improving the characterization of atmosphere-ground interactions in mountainous terrain, the hydrometeorology of the region, climatic change, and related research lines. It will also provide the meteorological and climate data which form the necessary background information for biological, agricultural and hydrological investigations in this area. Currently, the initiative is supported by research groups from the Complutense and Polytechnical Universities of Madrid (UCM and UPM), the Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), the Spanish National Meteorological Agency (AEMET), and finally the Parque Nacional de la Sierra de Guadarrama (PNSG). This infrastructure forms part of the Campus of Excellence Moncloa, and is supposed to become a focus of local as well as of international research. However, it is not associated with a particular project: data will in principle be available to the scientific and public communities. Also, the integration of new instruments (long or short term) will be welcome. The starting setup is as following: A group of WMO-compatible meteorological station in the central area of the massif will be installed, which include also a subsurface component of boreholes (≡20 m depth), where temperature and moisture will be measured. This core group is complemented by a reference site near El Escorial (including a fixed and a mobile tower for micrometeorological investigations). This setup is embedded in a network of meteorological stations run partly by AEMET and partly by the PNSG, which will provide the information necessary for the characterization of regional meteorology and climate. Finally, part of the data will be made available quasi-online on a central web server in Madrid. (temporary web page: http://tifon.fis.ucm.es/~gumnet/)

Quantifying the quality of precipitation data from different sources

NASA Astrophysics Data System (ADS)

Leijnse, Hidde; Wauben, Wiel; Overeem, Aart; de Haij, Marijn

2015-04-01

There is an increasing demand for high-resolution rainfall data. The current manual and automatic networks of climate and meteorological stations provide high quality rainfall data, but they cannot provide the high spatial and temporal resolution required for many applications. This can only partly be solved by using remotely sensed data. It is therefore necessary to consider third-party data, such as rain gauges operated by amateurs and rainfall intensities from commercial cellular communication links. The quality of such third-party data is highly variable and generally lower than that of dedicated networks. Often, such data quality information is missing for third party data. In order to be able to use data from various sources it is vital that quantitative knowledge of the data quality is available. This holds for all data sources, including the rain gauges in the reference networks of climate and meteorological stations. Data quality information is generally either not available or very limited for third-party data sources. For most dedicated climate meteorological networks, this information is only available for the sensor in laboratory conditions. In many cases, however, a significant part of the measurement errors and uncertainties is determined by the siting and maintenance of the sensor, for which generally only qualitative information is available. Furthermore sensors may have limitations under specific conditions. We aim to quantify data quality for different data sources by performing analyses on collocated data sets. Here we present an intercomparison of two years of precipitation data from six different sources (manual rain gauge, automatic rain gauge, present weather sensor, weather radar, commercial cellular communication links, and Meteosat) at three different locations in the Netherlands. We use auxiliary meteorological data to determine if the quality is influenced by other variables (e.g. the temperature influencing the evaporation from the rain gauge). We use three techniques to compare the data sets: 1) direct comparison; 2) triple collocation (see Stoffelen, 1998); and 3) comparison of statistics. Stoffelen, A. (1998). Toward the true near-surface wind speed: Error modeling and calibration using triple collocation. Journal of Geophysical Research: Oceans (1978-2012), 103(C4), 7755-7766.

Generating daily weather data for ecosystem modelling in the Congo River Basin

NASA Astrophysics Data System (ADS)

Petritsch, Richard; Pietsch, Stephan A.

2010-05-01

Daily weather data are an important constraint for diverse applications in ecosystem research. In particular, temperature and precipitation are the main drivers for forest ecosystem productivity. Mechanistic modelling theory heavily relies on daily values for minimum and maximum temperatures, precipitation, incident solar radiation and vapour pressure deficit. Although the number of climate measurement stations increased during the last centuries, there are still regions with limited climate data. For example, in the WMO database there are only 16 stations located in Gabon with daily weather measurements. Additionally, the available time series are heavily affected by measurement errors or missing values. In the WMO record for Gabon, on average every second day is missing. Monthly means are more robust and may be estimated over larger areas. Therefore, a good alternative is to interpolate monthly mean values using a sparse network of measurement stations, and based on these monthly data generate daily weather data with defined characteristics. The weather generator MarkSim was developed to produce climatological time series for crop modelling in the tropics. It provides daily values for maximum and minimum temperature, precipitation and solar radiation. The monthly means can either be derived from the internal climate surfaces or prescribed as additional inputs. We compared the generated outputs observations from three climate stations in Gabon (Lastourville, Moanda and Mouilla) and found that maximum temperature and solar radiation were heavily overestimated during the long dry season. This is due to the internal dependency of the solar radiation estimates to precipitation. With no precipitation a cloudless sky is assumed and thus high incident solar radiation and a large diurnal temperature range. However, in reality it is cloudy in the Congo River Basin during the long dry season. Therefore, we applied a correction factor to solar radiation and temperature range based on the ratio of values on rainy days and days without rain, respectively. For assessing the impact of our correction, we simulated the ecosystem behaviour using the climate data from Lastourville, Moanda and Mouilla with the mechanistic ecosystem model Biome-BGC. Differences in terms of the carbon, nitrogen and water cycle were subsequently analysed and discussed.

Utility of High Temporal Resolution Observations for Heat Health Event Characterization

NASA Astrophysics Data System (ADS)

Palecki, M. A.

2017-12-01

Many heat health watch systems produce a binary on/off warning when conditions are predicted to exceed a given threshold during a day. Days with warnings and their mortality/morbidity statistics are analyzed relative to days not warned to determine the impacts of the event on human health, the effectiveness of warnings, and other statistics. The climate analyses of the heat waves or extreme temperature events are often performed with hourly or daily observations of air temperature, humidity, and other measured or derived variables, especially the maxima and minima of these data. However, since the beginning of the century, 5-minute observations are readily available for many weather and climate stations in the United States. NOAA National Centers for Environmental Information (NCEI) has been collecting 5-minute observations from the NOAA Automated Surface Observing System (ASOS) stations since 2000, and from the U.S. Climate Reference Network (USCRN) stations since 2005. This presentation will demonstrate the efficacy of utilizing 5-minute environmental observations to characterize heat waves by counting the length of time conditions exceed extreme thresholds based on individual and multiple variables and on derived variables such as the heat index. The length and depth of recovery periods between daytime heating periods will also be examined. The length of time under extreme conditions will influence health outcomes for those directly exposed. Longer periods of dangerous conditions also could increase the chances for poor health outcomes for those only exposed intermittently through cumulative impacts.

Which homogenisation method is appropriate for daily time series of relative humidity?

NASA Astrophysics Data System (ADS)

Chimani, Barbara; Nemec, Johanna; Auer, Ingeborg; Venema, Victor

2014-05-01

Data homogenisation is an essential part of reliable climate data analyses. Different tools for detecting and adjusting breaks in daily extreme temperatures (Tmin, Tmax) and daily precipitation sums were developed in the last years. Due to its influence on health, plants and construction relative humidity is another parameter of great importance. On the basis of 6 networks of measured (and homogenized with respect to the monthly means) relative humidity data, which cover different climatic areas in Austria, a synthetic data set for testing and validating homogenisation methods was built. Each network consists of 4 to 6 station time series with a minimum length of 5 years. The so-called surrogate networks resemble the statistical properties (e.g. distribution of parameter, auto- and cross correlation within the network) of the measured time series, but are extended to 100 year long time series, which are in a first step assumed to be homogeneous. For creating the best possible surrogate dataset of relative humidity detailed statistical information on potential inhomogeneities is decisive. Information on the potential breaks was taken from parallel measurements available for some Austrian locations, mostly representing changes in instrumentation and/or station relocation. Beside changes in the distribution of the parameter the analyses includes an estimation of changes in the number of missing data, global and local biases, both on a seasonal and annual basis. An additional break is to be expected in the Austrian time series due to a change in observation time in 1970/1971. Since this change occurred simultaneously at all Austrian climate stations, standard homogenisation methods, which rely on a comparison with reference stations, are not able to detect or correct this shift. Therefore an independent correction method for this type of break, to be applied before homogenisation was developed. This type of change point was not included in the surrogate network. Artificial inhomogenities were introduced to the dataset in three steps: (1) deterministic change points: within one homogeneous sub-period (HSP) a constant perturbation is added to each relative humidity values, (2) deterministic + random changes: random changes do not change the mean of the HSP but can affect the distribution of the parameter, (3) in addition realistic changes in break frequency and missing data. In order to tests the efficiency of homogenisation methods, the procedure was separated in break detection and adjustment of inhomogenities. The methods MASH (Szentimrey, 1999), ACMANT (Domonkos, 2011), PRODIGE (Caussinus and Mestre, 2004), SNHT (Alexandersson, 1986), Vincent (Vincent, 1998), E-P method (Easterling and Peterson, 1995) and Bivariate test (Maronna and Yohai, 1978) were selected for break detection. Break detection is in all methods restricted to monthly, seasonal or annual data. Since we are dealing with daily data, the amount of methods for break correction is reduced and we concentrate on the following methods: MASH, Vincent, SPLIDHOM (Mestre et al., 2011) and the percentile method (Stepanek, 2009). Information on the statistical characteristics of breaks in relative humidity series, the correction method concerning the changed observation times and first results concerning break detection will be presented.

MODIS Interactive Subsetting Tool (MIST)

NASA Astrophysics Data System (ADS)

McAllister, M.; Duerr, R.; Haran, T.; Khalsa, S. S.; Miller, D.

2008-12-01

In response to requests from the user community, NSIDC has teamed with the Oak Ridge National Laboratory Distributive Active Archive Center (ORNL DAAC) and the Moderate Resolution Data Center (MrDC) to provide time series subsets of satellite data covering stations in the Greenland Climate Network (GC-NET) and the International Arctic Systems for Observing the Atmosphere (IASOA) network. To serve these data NSIDC created the MODIS Interactive Subsetting Tool (MIST). MIST works with 7 km by 7 km subset time series of certain Version 5 (V005) MODIS products over GC-Net and IASOA stations. User- selected data are delivered in a text Comma Separated Value (CSV) file format. MIST also provides online analysis capabilities that include generating time series and scatter plots. Currently, MIST is a Beta prototype and NSIDC intends that user requests will drive future development of the tool. The intent of this poster is to introduce MIST to the MODIS data user audience and illustrate some of the online analysis capabilities.

Validation of the CHIRPS Satellite Rainfall Estimates over Eastern of Africa

NASA Astrophysics Data System (ADS)

Dinku, T.; Funk, C. C.; Tadesse, T.; Ceccato, P.

2017-12-01

Long and temporally consistent rainfall time series are essential in climate analyses and applications. Rainfall data from station observations are inadequate over many parts of the world due to sparse or non-existent observation networks, or limited reporting of gauge observations. As a result, satellite rainfall estimates have been used as an alternative or as a supplement to station observations. However, many satellite-based rainfall products with long time series suffer from coarse spatial and temporal resolutions and inhomogeneities caused by variations in satellite inputs. There are some satellite rainfall products with reasonably consistent time series, but they are often limited to specific geographic areas. The Climate Hazards Group Infrared Precipitation (CHIRP) and CHIRP combined with station observations (CHIRPS) are recently produced satellite-based rainfall products with relatively high spatial and temporal resolutions and quasi-global coverage. In this study, CHIRP and CHIRPS were evaluated over East Africa at daily, dekadal (10-day) and monthly time scales. The evaluation was done by comparing the satellite products with rain gauge data from about 1200 stations. The is unprecedented number of validation stations for this region covering. The results provide a unique region-wide understanding of how satellite products perform over different climatic/geographic (low lands, mountainous regions, and coastal) regions. The CHIRP and CHIRPS products were also compared with two similar satellite rainfall products: the African Rainfall Climatology version 2 (ARC2) and the latest release of the Tropical Applications of Meteorology using Satellite data (TAMSAT). The results show that both CHIRP and CHIRPS products are significantly better than ARC2 with higher skill and low or no bias. These products were also found to be slightly better than the latest version of the TAMSAT product. A comparison was also done between the latest release of the TAMSAT product (TAMSAT3) and the earlier version(TAMSAT2), which has shown that the latest version is a substantial improvement over the previous one, particularly with regards to the bias statistics.

Update on Plans to Establish a National Phenology Network in the U.S.A.

NASA Astrophysics Data System (ADS)

Betancourt, J.; Schwartz, M.; Breshears, D.; Cayan, D.; Dettinger, M.; Inouye, D.; Post, E.; Reed, B.; Gray, S.

2005-12-01

The passing of the seasons is the most pervasive source of climatic and biological variability on Earth, yet phenological monitoring has been spotty worldwide. Formal phenological networks were recently established in Europe and Canada, and we are now following their lead in organizing a National Phenology Network (NPN) for the U.S.A. With support from federal agencies (NSF, USGS, NPS, USDA-FS, EPA, NOAA, NASA), on Aug. 22-26 we organized a workshop in Tucson, Arizona to begin planning a national-scale, multi-tiered phenological network. A prototype for a web-based NPN and preliminary workshop results are available at http://www.npn.uwm.edu. The main goals of NPN will be to: (1) facilitate thorough understanding of phenological phenomena, including causes and effects; (2) provide ground truthing to make the most of heavy public investment in remote sensing data; (3) allow detection and prediction of environmental change for a wide of variety of applications; (4) harness the power of mass participation and engage tens of thousands of "citizen scientists" in meeting national needs in Education, Health, Commerce, Natural Resources and Agriculture; (5) develop a model system for substantive collaboration across different levels of government, academia and the private sector. Just as the national networks of weather stations and stream gauges are critical for providing weather, climate and water-related information, NPN will help safeguard and procure goods and services that ecosystems provide. We expect that NPN will consist of a four-tiered, expandable structure: 1) a backbone network linked to existing weather stations, run by recruited public observers; 2) A smaller, second tier of intensive observations, run by scientists at established research sites; 3) a much larger network of observations made by citizen scientists; and 4) remote sensing observations that can be validated with surface observations, thereby providing wall-to-wall coverage for the U.S.A. Key to the success of NPN will be formal linkages with other ecological networks (e.g., LTER, AmeriFlux, NEON, USDA-FS Inventory and Analysis, NPS Inventory and Monitoring) and strategic co-location of phenological measurements with weather stations (e.g., NOAA's Real-Time Observation Network and state mesonets). Establishment and operation of NPN will require partnerships among multiple federal and state agencies, universities, and NGO's. Interagency agreements will facilitate data sharing, staff commitments, and the transfer of funds, while demonstrating policy-level support for NPN and smoothing the path for use of phenological data in decision-making. A formal implementation report will be completed and circulated for review by Dec. 1, 2005. As soon as the network can start assimilating observations from the public at large (tier 3), NPN will start recruiting observers through NGO's, as well as regional and national media. Every effort will be made to start making observations and expanding the monitoring network by Spring 2006.

Long-Term INP Measurements within the BACCHUS project

NASA Astrophysics Data System (ADS)

Schrod, Jann; Bingemer, Heinz; Curtius, Joachim

2016-04-01

The European research project BACCHUS (Impact of Biogenic versus Anthropogenic emissions on Clouds and Climate: towards a Holistic UnderStanding) studies the interactions between aerosols, clouds and the climate system, and tries to reconstruct pre-industrial aerosol and cloud conditions from data collected in pristine environments. The number concentration of Ice Nucleating Particles (INP) is an important, yet scarcely known parameter. As a partner of Work package 1 of BACCHUS we began in September 2014 to operate a globally spanned network of four INP sampling stations, which is the first of its kind. The stations are located at the ATTO observatory in the Brazilian Rainforest, the Caribbean Sea (Martinique), the Zeppelin Observatory at Svalbard in the Arctic, and in central Europe (Germany). Samples are collected routinely every day or every few days by electrostatic precipitation of aerosol particles onto Si substrates. The samples are stored in petri-slides, and shipped to our laboratory in Frankfurt, Germany. The number of ice nucleating particles on the substrate is analyzed in the isothermal static diffusion chamber FRIDGE by growing ice on the INP and photographing and counting the crystals. The measurements in the temperature range from -20°C to -30°C and relative humidities of 100-135% (with respect to ice) address primarily the deposition/condensation nucleation modes. Here we present INP and supporting aerosol data from this novel INP network for the first time.

Implications of Climate Change on the Heat Budget of Lentic Systems Used for Power Station Cooling: Case Study Clinton Lake, Illinois.

PubMed

Quijano, Juan C; Jackson, P Ryan; Santacruz, Santiago; Morales, Viviana M; García, Marcelo H

2016-01-05

We use a numerical model to analyze the impact of climate change-in particular higher air temperatures-on a nuclear power station that recirculates the water from a reservoir for cooling. The model solves the hydrodynamics, the transfer of heat in the reservoir, and the energy balance at the surface. We use the numerical model to (i) quantify the heat budget in the reservoir and determine how this budget is affected by the combined effect of the power station and climate change and (ii) quantify the impact of climate change on both the downstream thermal pollution and the power station capacity. We consider four different scenarios of climate change. Results of simulations show that climate change will reduce the ability to dissipate heat to the atmosphere and therefore the cooling capacity of the reservoir. We observed an increase of 25% in the thermal load downstream of the reservoir, and a reduction in the capacity of the power station of 18% during the summer months for the worst-case climate change scenario tested. These results suggest that climate change is an important threat for both the downstream thermal pollution and the generation of electricity by power stations that use lentic systems for cooling.

Implications of climate change on the heat budget of lentic systems used for power station cooling: Case study Clinton Lake, Illinois

USGS Publications Warehouse

Quijano, Juan C; Jackson, P. Ryan; Santacruz, Santiago; Morales, Viviana M; Garcia, Marcelo H.

2016-01-01

We use a numerical model to analyze the impact of climate change--in particular higher air temperatures--on a nuclear power station that recirculates the water from a reservoir for cooling. The model solves the hydrodynamics, the transfer of heat in the reservoir, and the energy balance at the surface. We use the numerical model to (i) quantify the heat budget in the reservoir and determine how this budget is affected by the combined effect of the power station and climate change and (ii) quantify the impact of climate change on both the downstream thermal pollution and the power station capacity. We consider four different scenarios of climate change. Results of simulations show that climate change will reduce the ability to dissipate heat to the atmosphere and therefore the cooling capacity of the reservoir. We observed an increase of 25% in the thermal load downstream of the reservoir, and a reduction in the capacity of the power station of 18% during the summer months for the worst-case climate change scenario tested. These results suggest that climate change is an important threat for both the downstream thermal pollution and the generation of electricity by power stations that use lentic systems for cooling.

Spatial analysis of sunshine duration by combination of satellite and station data

NASA Astrophysics Data System (ADS)

Frei, C.; Stöckli, R.; Dürr, B.

2009-09-01

Sunshine duration can exhibit rich fine scale patterns associated with special meteorological phenomena, such as fog layers and topographically triggered clouds. Networks of climate stations are mostly too coarse and poorly representative to resolve these patterns explicitly. We present a method which combines station observations with satellite-derived cloud-cover data to produce km-scale fields of sunshine duration. The method is not relying on contemporous satellite information, hence it can be applied over climatological time scales. We apply and evaluate the combination method over the territory of Switzerland. The combination method is based on Universal Kriging. First, the satellite data (a Heliosat clear sky index from MSG, extending over a 5 year preiod) is subjected to a S-mode Principal Component (PC) Analysis. Second, a set of leading PC loadings (seasonally stratified) is introduced as external drift covariates and their optimal linear combination is estimated from the station data (70 stations). Finally, the stochastic component is an autocorrelated field with an exponential variogram, estimated climatologically for each calendar month. For Switzerland the leading PCs of the clear sky index depict familiar patterns of cloud variability which are inhereted in the combination process. The resulting sunshine duration fields exhibit fine-scale structures that are physically plausible, linked to the topography and characteristic of the regional climate. These patterns could not be inferred from station data and/or topographic predictors alone. A cross-validation reveals that the combination method explains between 80-90% of the spatial variance in winter and autumn months. In spring and summer the relative performance is lower (60-75% explained spatial variance) but absolute errors are smaller. Our presentation will also discuss some results from a climatology of the derived sunshine duration fields.

An Algorithm for the Retrieval of 30-m Snow-Free Albedo from Landsat Surface Reflectance and MODIS BRDF

NASA Technical Reports Server (NTRS)

Shuai, Yanmin; Masek, Jeffrey G.; Gao, Feng; Schaaf, Crystal B.

2011-01-01

We present a new methodology to generate 30-m resolution land surface albedo using Landsat surface reflectance and anisotropy information from concurrent MODIS 500-m observations. Albedo information at fine spatial resolution is particularly useful for quantifying climate impacts associated with land use change and ecosystem disturbance. The derived white-sky and black-sky spectral albedos maybe used to estimate actual spectral albedos by taking into account the proportion of direct and diffuse solar radiation arriving at the ground. A further spectral-to-broadband conversion based on extensive radiative transfer simulations is applied to produce the broadband albedos at visible, near infrared, and shortwave regimes. The accuracy of this approach has been evaluated using 270 Landsat scenes covering six field stations supported by the SURFace RADiation Budget Network (SURFRAD) and Atmospheric Radiation Measurement Southern Great Plains (ARM/SGP) network. Comparison with field measurements shows that Landsat 30-m snow-free shortwave albedos from all seasons generally achieve an absolute accuracy of +/-0.02 - 0.05 for these validation sites during available clear days in 2003-2005,with a root mean square error less than 0.03 and a bias less than 0.02. This level of accuracy has been regarded as sufficient for driving global and regional climate models. The Landsat-based retrievals have also been compared to the operational 16-day MODIS albedo produced every 8-days from MODIS on Terra and Aqua (MCD43A). The Landsat albedo provides more detailed landscape texture, and achieves better agreement (correlation and dynamic range) with in-situ data at the validation stations, particularly when the stations include a heterogeneous mix of surface covers.

Trends in Extreme Rainfall Frequency in the Contiguous United States: Attribution to Climate Change and Climate Variability Modes

NASA Astrophysics Data System (ADS)

Armal, S.; Devineni, N.; Khanbilvardi, R.

2017-12-01

This study presents a systematic analysis for identifying and attributing trends in the annual frequency of extreme rainfall events across the contiguous United States to climate change and climate variability modes. A Bayesian multilevel model is developed for 1,244 stations simultaneously to test the null hypothesis of no trend and verify two alternate hypotheses: Trend can be attributed to changes in global surface temperature anomalies, or to a combination of cyclical climate modes with varying quasi-periodicities and global surface temperature anomalies. The Bayesian multilevel model provides the opportunity to pool information across stations and reduce the parameter estimation uncertainty, hence identifying the trends better. The choice of the best alternate hypotheses is made based on Watanabe-Akaike Information Criterion, a Bayesian pointwise predictive accuracy measure. Statistically significant time trends are observed in 742 of the 1,244 stations. Trends in 409 of these stations can be attributed to changes in global surface temperature anomalies. These stations are predominantly found in the Southeast and Northeast climate regions. The trends in 274 of these stations can be attributed to the El Nino Southern Oscillations, North Atlantic Oscillation, Pacific Decadal Oscillation and Atlantic Multi-Decadal Oscillation along with changes in global surface temperature anomalies. These stations are mainly found in the Northwest, West and Southwest climate regions.

Statistical downscaling rainfall using artificial neural network: significantly wetter Bangkok?

NASA Astrophysics Data System (ADS)

Vu, Minh Tue; Aribarg, Thannob; Supratid, Siriporn; Raghavan, Srivatsan V.; Liong, Shie-Yui

2016-11-01

Artificial neural network (ANN) is an established technique with a flexible mathematical structure that is capable of identifying complex nonlinear relationships between input and output data. The present study utilizes ANN as a method of statistically downscaling global climate models (GCMs) during the rainy season at meteorological site locations in Bangkok, Thailand. The study illustrates the applications of the feed forward back propagation using large-scale predictor variables derived from both the ERA-Interim reanalyses data and present day/future GCM data. The predictors are first selected over different grid boxes surrounding Bangkok region and then screened by using principal component analysis (PCA) to filter the best correlated predictors for ANN training. The reanalyses downscaled results of the present day climate show good agreement against station precipitation with a correlation coefficient of 0.8 and a Nash-Sutcliffe efficiency of 0.65. The final downscaled results for four GCMs show an increasing trend of precipitation for rainy season over Bangkok by the end of the twenty-first century. The extreme values of precipitation determined using statistical indices show strong increases of wetness. These findings will be useful for policy makers in pondering adaptation measures due to flooding such as whether the current drainage network system is sufficient to meet the changing climate and to plan for a range of related adaptation/mitigation measures.

Bedrock displacements in Greenland manifest ice mass variations, climate cycles and climate change

PubMed Central

Bevis, Michael; Wahr, John; Khan, Shfaqat A.; Madsen, Finn Bo; Brown, Abel; Willis, Michael; Kendrick, Eric; Knudsen, Per; Box, Jason E.; van Dam, Tonie; Caccamise, Dana J.; Johns, Bjorn; Nylen, Thomas; Abbott, Robin; White, Seth; Miner, Jeremy; Forsberg, Rene; Zhou, Hao; Wang, Jian; Wilson, Terry; Bromwich, David; Francis, Olivier

2012-01-01

The Greenland GPS Network (GNET) uses the Global Positioning System (GPS) to measure the displacement of bedrock exposed near the margins of the Greenland ice sheet. The entire network is uplifting in response to past and present-day changes in ice mass. Crustal displacement is largely accounted for by an annual oscillation superimposed on a sustained trend. The oscillation is driven by earth’s elastic response to seasonal variations in ice mass and air mass (i.e., atmospheric pressure). Observed vertical velocities are higher and often much higher than predicted rates of postglacial rebound (PGR), implying that uplift is usually dominated by the solid earth’s instantaneous elastic response to contemporary losses in ice mass rather than PGR. Superimposed on longer-term trends, an anomalous ‘pulse’ of uplift accumulated at many GNET stations during an approximate six-month period in 2010. This anomalous uplift is spatially correlated with the 2010 melting day anomaly. PMID:22786931

Isoscapes of tree-ring carbon-13 perform like meteorological networks in predicting regional precipitation patterns

NASA Astrophysics Data System (ADS)

del Castillo, Jorge; Aguilera, Mònica; Voltas, Jordi; Ferrio, Juan Pedro

2013-04-01

Stable isotopes in tree rings provide climatic information with annual resolution dating back for centuries or even millennia. However, deriving spatially explicit climate models from isotope networks remains challenging. Here we propose a methodology to model regional precipitation from carbon isotope discrimination (Δ13C) in tree rings by (1) building regional spatial models of Δ13C (isoscapes), and (2) deriving precipitation maps from 13C-isoscapes, taking advantage of the response of Δ13C to precipitation in seasonally-dry climates. As a case study, we modeled the spatial distribution of mean annual precipitation (MAP) in the northeastern Iberian Peninsula, a region with complex orography and climate (MAP=303-1086 mm). We compiled wood Δ13C data for two Mediterranean species that exhibit complementary responses to seasonal precipitation (Pinus halepensis Mill., N=38; Quercus ilex L.; N=44; pooling period: 1975-2008). By combining multiple regression and geostatistical interpolation, we generated one 13C-isoscape for each species. A spatial model of MAP was then built as the sum of two complementary maps of seasonal precipitation, each one derived from the corresponding 13C-isoscape (September-November from Q. ilex; December-August from P. halepensis). Our approach showed a predictive power for MAP (RMSE=84 mm) nearly identical to that obtained by interpolating data directly from a similarly dense network of meteorological stations (RMSE=80-83 mm, N=65), being only outperformed when using a much denser meteorological network (RMSE=56-57 mm, N=340). This method offers new avenues for modeling spatial variability of past precipitation, exploiting the large amount of information currently available from tree-ring networks. Acknowledgements: This work was funded by MC-ERG-246725 (FP7, EU) and AGL 2012-40039-C02-02 (MINECO, Spain). JdC and JPF are supported by FPI fellowship (MCINN) and Ramón y Cajal programme (RYC-2008-02050, MINECO), respectively.

Climate change in safety assessment of a surface disposal facility

NASA Astrophysics Data System (ADS)

Leterme, B.

2012-04-01

The Belgian Agency for Radioactive Waste and Enriched Fissile Materials (ONDRAF/NIRAS) aims to develop a surface disposal facility for LILW-SL in Dessel (North-East of Belgium). Given the time scale of interest for the safety assessment (several millennia), a number of parameters in the modelling chain near field - geosphere - biosphere may be influenced by climate change. The present study discusses how potential climate change impact was accounted for the following quantities: (i) near field infiltration through the repository earth cover, (ii) partial pressure of CO2 in the water infiltrating the cover and draining the concrete, and (iii) groundwater recharge in the vicinity of the site. For these three parameters, the impact of climate change is assessed using climatic analogue stations, i.e. stations presently under climatic conditions corresponding to a given climate state. Results indicate that : (i) Using Gijon (Spain) as representative analogue station for the next millennia, infiltration at the bottom of the soil layer towards the modules of the facility is expected to increase (from 346 to 413 mm/y) under a subtropical climate. Although no colder climate is foreseen in the next 10 000 years, the approach was also tested with analogue stations for a colder climate state. Using Sisimiut (Greenland) as representative analogue station, infiltration is expected to decrease (109 mm/y). (ii) Due to changes of the partial pressure of CO2 in the soil water, cement degradation is estimated to occur more rapidly under a warmer climate. (iii) A decrease of long-term annual average groundwater recharge by 12% was simulated using Gijon representative analogue (from 314 to 276 mm), although total rainfall was higher (947 mm) in the warmer climate compared to the current temperate climate (899 mm). For a colder climate state, groundwater recharge simulated for the representative analogue Sisimiut showed a decrease by 69% compared to current climate conditions. The advantages and weaknesses of using analogue stations are also discussed.

First results from comparison of rainfall estimations by GPM IMERG with rainfall measurements from the WegenerNet high density network

NASA Astrophysics Data System (ADS)

Oo, Sungmin; Foelsche, Ulrich; Kirchengast, Gottfried; Fuchsberger, Jürgen

2016-04-01

The research level products of the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG "Final" run datasets) were compared with rainfall measurements from the WegenerNet high density network as part of ground validation (GV) projects of GPM missions. The WegenerNet network comprises 151 ground level weather stations in an area of 15 km × 20 km in south-eastern Austria (Feldbach region, ˜46.93° N, ˜15.90° E) designed to serve as a long-term monitoring and validation facility for weather and climate research and applications. While the IMERG provides rainfall estimations every half hour at 0.1° resolution, the WegenerNet network measures rainfall every 5 minutes at around 2 km2 resolution and produces 200 m × 200 m gridded datasets. The study was conducted on the domain of the WegenerNet network; eight IMERG grids are overlapped with the network, two of which are entirely covered by the WegenerNet (40 and 39 stations in each grid). We investigated data from April to September of the years 2014 to 2015; the date of first two years after the launch of the GPM Core Observatory. Since the network has a flexibility to work with various spatial and temporal scales, the comparison could be conducted on average-points to pixel basis at both sub-daily and daily timescales. This presentation will summarize the first results of the comparison and future plans to explore the characteristics of errors in the IMERG datasets.

Regional and seasonal estimates of fractional storm coverage based on station precipitation observations

NASA Technical Reports Server (NTRS)

Gong, Gavin; Entekhabi, Dara; Salvucci, Guido D.

1994-01-01

Simulated climates using numerical atmospheric general circulation models (GCMs) have been shown to be highly sensitive to the fraction of GCM grid area assumed to be wetted during rain events. The model hydrologic cycle and land-surface water and energy balance are influenced by the parameter bar-kappa, which is the dimensionless fractional wetted area for GCM grids. Hourly precipitation records for over 1700 precipitation stations within the contiguous United States are used to obtain observation-based estimates of fractional wetting that exhibit regional and seasonal variations. The spatial parameter bar-kappa is estimated from the temporal raingauge data using conditional probability relations. Monthly bar-kappa values are estimated for rectangular grid areas over the contiguous United States as defined by the Goddard Institute for Space Studies 4 deg x 5 deg GCM. A bias in the estimates is evident due to the unavoidably sparse raingauge network density, which causes some storms to go undetected by the network. This bias is corrected by deriving the probability of a storm escaping detection by the network. A Monte Carlo simulation study is also conducted that consists of synthetically generated storm arrivals over an artificial grid area. It is used to confirm the bar-kappa estimation procedure and to test the nature of the bias and its correction. These monthly fractional wetting estimates, based on the analysis of station precipitation data, provide an observational basis for assigning the influential parameter bar-kappa in GCM land-surface hydrology parameterizations.

Dynamics of the middle atmosphere as observed by the ARISE project

NASA Astrophysics Data System (ADS)

Blanc, E.

2015-12-01

It has been strongly demonstrated that variations in the circulation of the middle atmosphere influence weather and climate all the way to the Earth's surface. A key part of this coupling occurs through the propagation and breaking of planetary and gravity waves. However, limited observations prevent to faithfully reproduce the dynamics of the middle atmosphere in numerical weather prediction and climate models. The main challenge of the ARISE (Atmospheric dynamics InfraStructure in Europe) project is to combine existing national and international observation networks including: the International infrasound monitoring system developed for the CTBT (Comprehensive nuclear-Test-Ban Treaty) verification, the NDACC (Network for the Detection of Atmospheric Composition Changes) lidar network, European observation infrastructures at mid latitudes (OHP observatory), tropics (Maïdo observatory), high latitudes (ALOMAR and EISCAT), infrasound stations which form a dense European network and satellites. The ARISE network is unique by its coverage (polar to equatorial regions in the European longitude sector), its altitude range (from troposphere to mesosphere and ionosphere) and the involved scales both in time (from seconds to tens of years) and space (from tens of meters to thousands of kilometers). Advanced data products are produced with the scope to assimilate data in the Weather Prediction models to improve future forecasts over weeks and seasonal time scales. ARISE observations are especially relevant for the monitoring of extreme events such as thunderstorms, volcanoes, meteors and at larger scales, deep convection and stratospheric warming events for physical processes description and study of long term evolution with climate change. Among the applications, ARISE fosters integration of innovative methods for remote detection of non-instrumented volcanoes including distant eruption characterization to provide notifications with reliable confidence indices to the civil aviation.

The Austrian radiation monitoring network ARAD - best practice and added value

NASA Astrophysics Data System (ADS)

Olefs, Marc; Baumgartner, Dietmar; Obleitner, Friedrich; Bichler, Christoph; Foelsche, Ulrich; Pietsch, Helga; Rieder, Harald; Weihs, Philipp; Geyer, Florian; Haiden, Thomas; Schöner, Wolfgang

2016-04-01

The Austrian RADiation monitoring network (ARAD) has been established to advance the national climate monitoring and to support satellite retrieval, atmospheric modelling and solar energy techniques development. Measurements cover the downwelling solar and thermal infrared radiation using instruments according to Baseline Surface Radiation Network (BSRN) standards. A unique feature of ARAD is its vertical dimension of five stations, covering an air column between about 200 m a.s.l. (Vienna) and 3100 m a.s.l. (BSRN site Sonnblick). The contribution outlines the aims and scopes of ARAD, its measurement and calibration standards, methods, strategies and station locations. ARAD network operation uses innovative data processing for quality assurance and quality control, applying manual and automated control algorithms. A combined uncertainty estimate for the broadband shortwave radiation fluxes at all five ARAD stations indicates that accuracies range from 1.5 to 23 %. If a directional response error of the pyranometers and the temperature response of the instruments and the data acquisition system (DAQ) is corrected, this expanded uncertainty reduces to 1.4 to 5.2 %. Thus, for large signals (global: 1000 W m-2, diffuse: 500 W m-2) BSRN target accuracies are met or closely met for 70 % of valid measurements at the ARAD stations after this correction. For small signals (50 W m-2), the targets are not achieved as a result of uncertainties associated with the DAQ or the instrument sensitivities. Additional accuracy gains can be achieved in future by additional measurements and corrections. However, for the measurement of direct solar radiation improved instrument accuracy is needed. ARAD could serve as a powerful example for establishing state-of-the-art radiation monitoring at the national level with a multiple-purpose approach. Instrumentation, guidelines and tools (such as the data quality control) developed within ARAD are best practices which could be adopted in other regions, thus saving high development costs.

The Austrian radiation monitoring network ARAD - best practice and added value

NASA Astrophysics Data System (ADS)

Olefs, M.; Baumgartner, D. J.; Obleitner, F.; Bichler, C.; Foelsche, U.; Pietsch, H.; Rieder, H. E.; Weihs, P.; Geyer, F.; Haiden, T.; Schöner, W.

2015-10-01

The Austrian RADiation monitoring network (ARAD) has been established to advance the national climate monitoring and to support satellite retrieval, atmospheric modelling and solar energy techniques development. Measurements cover the downwelling solar and thermal infrared radiation using instruments according to Baseline Surface Radiation Network (BSRN) standards. A unique feature of ARAD is its vertical dimension of five stations, covering an air column between about 200 m a.s.l. (Vienna) and 3100 m a.s.l. (BSRN site Sonnblick). The paper outlines the aims and scopes of ARAD, its measurement and calibration standards, methods, strategies and station locations. ARAD network operation uses innovative data processing for quality assurance and quality control, applying manual and automated control algorithms. A combined uncertainty estimate for the broadband shortwave radiation fluxes at all five ARAD stations indicates that accuracies range from 1.5 to 23 %. If a directional response error of the pyranometers and the temperature response of the instruments and the data acquisition system (DAQ) is corrected, this expanded uncertainty reduces to 1.4 to 5.2 %. Thus, for large signals (global: 1000 W m-2, diffuse: 500 W m-2) BSRN target accuracies are met or closely met for 70 % of valid measurements at the ARAD stations after this correction. For small signals (50 W m-2), the targets are not achieved as a result of uncertainties associated with the DAQ or the instrument sensitivities. Additional accuracy gains can be achieved in future by additional measurements and corrections. However, for the measurement of direct solar radiation improved instrument accuracy is needed. ARAD could serve as a powerful example for establishing state-of-the-art radiation monitoring at the national level with a multiple-purpose approach. Instrumentation, guidelines and tools (such as the data quality control) developed within ARAD are best practices which could be adopted in other regions, thus saving high development costs.

Evaluation of selected methods for determining streamflow during periods of ice effect

USGS Publications Warehouse

Melcher, Norwood B.; Walker, J.F.

1992-01-01

Seventeen methods for estimating ice-affected streamflow are evaluated for potential use with the U.S. Geological Survey streamflow-gaging station network. The methods evaluated were identified by written responses from U.S. Geological Survey field offices and by a comprehensive literature search. The methods selected and techniques used for applying the methods are described in this report. The methods are evaluated by comparing estimated results with data collected at three streamflow-gaging stations in Iowa during the winter of 1987-88. Discharge measurements were obtained at 1- to 5-day intervals during the ice-affected periods at the three stations to define an accurate baseline record. Discharge records were compiled for each method based on data available, assuming a 6-week field schedule. The methods are classified into two general categories-subjective and analytical--depending on whether individual judgment is necessary for method application. On the basis of results of the evaluation for the three Iowa stations, two of the subjective methods (discharge ratio and hydrographic-and-climatic comparison) were more accurate than the other subjective methods and approximately as accurate as the best analytical method. Three of the analytical methods (index velocity, adjusted rating curve, and uniform flow) could potentially be used at streamflow-gaging stations, where the need for accurate ice-affected discharge estimates justifies the expense of collecting additional field data. One analytical method (ice-adjustment factor) may be appropriate for use at stations with extremely stable stage-discharge ratings and measuring sections. Further research is needed to refine the analytical methods. The discharge-ratio and multiple-regression methods produce estimates of streamflow for varying ice conditions using information obtained from the existing U.S. Geological Survey streamflow-gaging network.

Survey of the seasonal snow cover in Alaska

NASA Technical Reports Server (NTRS)

Weller, G. E. (Principal Investigator)

1973-01-01

The author has identified the following significant results. ERTS-1 data are used together with synoptic-climatological data to describe the buildup of the seasonal snow and ice covers in a north-south transect of a total length of about 1250 km across Alaska. It has been demonstrated that the ERTS-1 data may, under favorable conditions, be used for accurate mapping of snow lines in high mountain regions. The analysis shows that especially in the Brooks Range and on the Arctic Slope where snow covers generally are relatively thin, the ERTS-1 scenes can be useful for qualitative descriptions of the snow and ice covers over wide expanses. The onset and retreat of the seasonal snow cover are sensitive indicators of climatic fluctuations and the ERTS-1 data offers a possibility to record variations of the snow and ice buildup from year to year in a practical and informative way, which should be especially useful for studies of climatic trends. This is particularly true in Alaska where the density of the station network is too low to permit interpolations between the stations.

Mesoscale surface equivalent temperature (T E) for East Central USA

NASA Astrophysics Data System (ADS)

Younger, Keri; Mahmood, Rezaul; Goodrich, Gregory; Pielke, Roger A.; Durkee, Joshua

2018-04-01

The purpose of this research is to investigate near surface mesoscale equivalent temperatures (T E) in Kentucky (located in east central USA) and potential land cover influences. T E is a measure of the moist enthalpy composed of the dry bulb temperature, T, and absolute humidity. Kentucky presents a unique opportunity to perform a study of this kind because of the observational infrastructure provided by the Kentucky Mesonet (www.kymesonet.org). This network maintains 69 research-grade, in-situ weather and climate observing stations across the Commonwealth. Equivalent temperatures were calculated utilizing high-quality observations from 33 of these stations. In addition, the Kentucky Mesonet offers higher spatial and temporal resolution than previous research on this topic. As expected, the differences (T E - T) were greatest in the summer (smallest in the winter), with an average of 35 °C (5 °C). In general, the differences were found to be the largest in the western climate division. This is attributed to agricultural land use and poorly drained land. These differences are smaller during periods of drought, signifying less influence of moisture.

Hydrologic Observatory Data Telemetry Network in an Extreme Environment

NASA Astrophysics Data System (ADS)

Irving, K.; Kane, D.

2007-12-01

A network of hydrological research data stations on the North Slope of Alaska using radio telemetry to gather data in "near real time" will be described. The network consists of approximately 25 research stations, 10 repeater stations, and 3 Internet-connected base stations (though data is also collected at repeater stations and research stations may also function as repeaters). With this operational network, radio link redundancy is sufficient to reach any research station from any base station. The data network is driven in "pull" mode using software running on computers in Fairbanks, and emphasis is placed on reliably collecting and storing data as found on the remote data loggers. Work is underway to deploy dynamic routing software on the controlling computers, at which point the network will be capable of automatically working around problems which may include icing on antennas, satellite sun outages, animal damage, and many others.

Quality of rivers of the United States, 1975 water year; based on the National Stream Quality Accounting Network (NASQAN)

USGS Publications Warehouse

Briggs, John C.; Ficke, John F.

1977-01-01

The National Stream Quality Accounting Network (NASQAN) was established by the U.S. Geological Survey to provide a nationally uniform basis for continuously assessing the quality of U.S. rivers. Stations generally are at the downstream end of hydrologic accounting units in order to measure the quantity and quality of water flowing from the units. The 1975 water year was the first year of operation of the network that represents essentially all of the accounting units and thereby describes the water- quality of the entire country. Data are available on a large number of water-quality constituents measured at 345 stations during the 1975 water year. Temperature data (usually continuous or daily measurements) from NASQAN stations were fitted to a first order harmonic equation and the parameters for the harmonic function are reported for each station. Mean temperatures generally range from 5°-10°C in the North to more than 20°C along the southern border of the continental United States and in Hawaii and Puerto Rico; means were less than 10°C at 63 stations and greater than 25°C at only 7 stations. Amplitudes of the temperature curves are greatest (greater than 12°C) for the streams at midlatitudes and in the Great and Central Plains, and they are smallest for the subtropical and cold-climate streams. Considering chemical and biological characteristics of U.S. streams as described by NASQAN data, water quality is best (by many standards) in the Northeast, Southeast, and Northwest. Waters there generally are low in dissolved solids and major and minor chemical constituents, generally are soft (except in Florida), and carry relatively small amounts of sediment. These conditions mainly reflect the geology of the regions and the relatively large amounts of precipitation. However, many of these waters show the effects of pollution and carry moderate or high levels of major nutrients and have correspondingly high populations of attached and floating plants. High counts of indicator bacteria also show signs of local pollution, particularly in regions of the country with large human and animal populations. In the Northeast, some heavy metals are at moderate levels, but not above most water-quality criteria.Rivers of most of the Mid-Continent and Southwest reflect the arid or semi-arid climate, erodible soils, and agricultural activities. They are characterized by moderate to high levels of dissolved major and minor constituents, sediment, major nutrients, and biota (floating and attached aquatic plants and indicator bacteria). In addition, the most incidences of pesticides in stream and bottom sediments were found in these regions. A special analysis was made to study the patterns of dissolved solids, major nutrients, phytoplankton, and zinc in the Mississippi River above Memphis, Tennessee. It was found that flow volume is an important factor in influencing river quality, and that stations with low concentration of major nutrients generally had low phytoplankton populations as well.

A climate trend analysis of Chad

USGS Publications Warehouse

Funk, Christopher C.; Rowland, Jim; Adoum, Alkhalil; Eilerts, Gary; White, Libby

2012-01-01

This brief report, drawing from a multi-year effort by the U.S. Agency for International Development (USAID) Famine Early Warning Systems Network (FEWS NET), identifies significant decreases in rainfall and increases in air temperature across Chad, especially in the eastern part of the country. These analyses are based on quality-controlled station observations. Conclusions:* Summer rains have decreased in eastern Chad during the past 20 years. * Temperatures have increased by 0.8 °Celsius since 1975, amplifying the effect of droughts. * Crop yields are very low and stagnant. * The amount of farmland per person is low, and decliningrapidly.* Population growth combined with stagnating yieldscould lead to a 30 percent reduction in per capita cereal production by 2025.* In many cases, areas with changing climate are coincident with zones of substantial conflict, indicating some degree of association; however, the contribution of climate change to these conflicts is not currently understood.

The Need and Opportunity for an Integrated Research, Development and Testing Station in the Alaskan High Arctic

NASA Astrophysics Data System (ADS)

Hardesty, J. O.; Ivey, M.; Helsel, F.; Dexheimer, D.; Cahill, C. F.; Bendure, A.; Lucero, D. A.; Roesler, E. L.

2016-12-01

This presentation will make the case for development of a permanent integrated research and testing station at Oliktok Point, Alaska; taking advantage of existing assets and infrastructure, controlled airspace, an active UAS program and local partnerships. Arctic research stations provide critical monitoring and research on climate change for conditions and trends in the Arctic. The US Chair of the Arctic Council has increased awareness of gaps in our understanding of Artic systems, scarce monitoring, lack of infrastructure and readiness for emergency response. Less sea ice brings competition for commercial shipping and resource extraction. Search and rescue, pollution mitigation and safe navigation need real-time, wide-area monitoring to respond to events. Multi-national responses for international traffic will drive a greater security presence to protect citizens and sovereign interests. To address research and technology gaps, there is a national need for a High Arctic Station with an approach that partners stakeholders from science, safety and security to develop comprehensive solutions. The Station should offer year-round use, logistic support and access to varied ecological settings; phased adaptation to changing needs; and support testing of technologies such as multiple autonomous platforms, renewable energies and microgrids, and sensors in Arctic settings. We propose an Arctic Station at Oliktok Point, Alaska. Combined with the Toolik Field Station and Barrow Environmental Observatory, they form a US network of Arctic Stations. An Oliktok Point Station can provide complementary and unique assets that include: ocean access, and coastal and terrestrial systems; road access; controlled airspaces on land and ocean; nearby air facilities, medical and logistic support; atmospheric observations from an adjacent ARM facility; connections to Barrow and Toolik; fiber-optic communications; University of Alaska Fairbanks UAS Test Facility partnership; and an airstrip and hangar for UAS. World-class Arctic research requires year-round access and facilities. The US currently conducts most Arctic research at stations outside the US. A US Arctic Station network enables monitoring that is specific to the US Arctic, to predict and understand impacts that affect people, communities and the planet.

Monitoring the Earth's Atmosphere with the Global IMS Infrasound Network

NASA Astrophysics Data System (ADS)

Brachet, Nicolas; Brown, David; Mialle, Pierrick; Le Bras, Ronan; Coyne, John; Given, Jeffrey

2010-05-01

The Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) is tasked with monitoring compliance with the Comprehensive Nuclear-Test-Ban Treaty (CTBT) which bans nuclear weapon explosions underground, in the oceans, and in the atmosphere. The verification regime includes a globally distributed network of seismic, hydroacoustic, infrasound and radionuclide stations which collect and transmit data to the International Data Centre (IDC) in Vienna, Austria shortly after the data are recorded at each station. The infrasound network defined in the Protocol of the CTBT comprises 60 infrasound array stations. Each array is built according to the same technical specifications, it is typically composed of 4 to 9 sensors, with 1 to 3 km aperture geometry. At the end of 2000 only one infrasound station was transmitting data to the IDC. Since then, 41 additional stations have been installed and 70% of the infrasound network is currently certified and contributing data to the IDC. This constitutes the first global infrasound network ever built with such a large and uniform distribution of stations. Infrasound data at the IDC are processed at the station level using the Progressive Multi-Channel Correlation (PMCC) method for the detection and measurement of infrasound signals. The algorithm calculates the signal correlation between sensors at an infrasound array. If the signal is sufficiently correlated and consistent over an extended period of time and frequency range a detection is created. Groups of detections are then categorized according to their propagation and waveform features, and a phase name is assigned for infrasound, seismic or noise detections. The categorization complements the PMCC algorithm to avoid overwhelming the IDC automatic association algorithm with false alarm infrasound events. Currently, 80 to 90% of the detections are identified as noise by the system. Although the noise detections are not used to build events in the context of CTBT monitoring, they represent valuable data for other civil applications like monitoring of natural hazards (volcanic activity, storm tracking) and climate change. Non-noise detections are used in network processing at the IDC along with seismic and hydroacoustic technologies. The arrival phases detected on the three waveform technologies may be combined and used for locating events in an automatically generated bulletin of events. This automatic event bulletin is routinely reviewed by analysts during the interactive review process. However, the fusion of infrasound data with the other waveform technologies has only recently (in early 2010) become part of the IDC operational system, after a software development and testing period that began in 2004. The build-up of the IMS infrasound network, the recent developments of the IDC infrasound software, and the progress accomplished during the last decade in the domain of real-time atmospheric modelling have allowed better understanding of infrasound signals and identification of a growing data set of ground-truth sources. These infragenic sources originate from natural or man-made sources. Some of the detected signals are emitted by local or regional phenomena recorded by a single IMS infrasound station: man-made cultural activity, wind farms, aircraft, artillery exercises, ocean surf, thunderstorms, rumbling volcanoes, iceberg calving, aurora, avalanches. Other signals may be recorded by several IMS infrasound stations at larger distances: ocean swell, sonic booms, and mountain associated waves. Only a small fraction of events meet the event definition criteria considering the Treaty verification mission of the Organization. Candidate event types for the IDC Reviewed Event Bulletin include atmospheric or surface explosions, meteor explosions, rocket launches, signals from large earthquakes and explosive volcanic eruptions.

Data mining on long-term barometric data within the ARISE2 project

NASA Astrophysics Data System (ADS)

Hupe, Patrick; Ceranna, Lars; Pilger, Christoph

2016-04-01

The Comprehensive nuclear-Test-Ban Treaty (CTBT) led to the implementation of an international infrasound array network. The International Monitoring System (IMS) network includes 48 certified stations, each providing data for up to 15 years. As part of work package 3 of the ARISE2 project (Atmospheric dynamics Research InfraStructure in Europe, phase 2) the data sets will be statistically evaluated with regard on atmospheric dynamics. The current study focusses on fluctuations of absolute air pressure. Time series have been analysed for 17 monitoring stations which are located all over the world between Greenland and Antarctica along the latitudes to represent different climate zones and characteristic atmospheric conditions. Hence this enables quantitative comparisons between those regions. Analyses are shown including wavelet power spectra, multi-annual time series of average variances with regard to long-wave scales, and spectral densities to derive characteristics and special events. Evaluations reveal periodicities in average variances on 2 to 20 day scale with a maximum in the winter months and a minimum in summer of the respective hemisphere. This basically applies to time series of IMS stations beyond the tropics where the dominance of cyclones and anticyclones changes with seasons. Furthermore, spectral density analyses illustrate striking signals for several dynamic activities within one day, e.g., the semidiurnal tide.

Network capability estimation. Vela network evaluation and automatic processing research. Technical report. [NETWORTH

DOE Office of Scientific and Technical Information (OSTI.GOV)

Snell, N.S.

1976-09-24

NETWORTH is a computer program which calculates the detection and location capability of seismic networks. A modified version of NETWORTH has been developed. This program has been used to evaluate the effect of station 'downtime', the signal amplitude variance, and the station detection threshold upon network detection capability. In this version all parameters may be changed separately for individual stations. The capability of using signal amplitude corrections has been added. The function of amplitude corrections is to remove possible bias in the magnitude estimate due to inhomogeneous signal attenuation. These corrections may be applied to individual stations, individual epicenters, ormore » individual station/epicenter combinations. An option has been added to calculate the effect of station 'downtime' upon network capability. This study indicates that, if capability loss due to detection errors can be minimized, then station detection threshold and station reliability will be the fundamental limits to network performance. A baseline network of thirteen stations has been performed. These stations are as follows: Alaskan Long Period Array, (ALPA); Ankara, (ANK); Chiang Mai, (CHG); Korean Seismic Research Station, (KSRS); Large Aperture Seismic Array, (LASA); Mashhad, (MSH); Mundaring, (MUN); Norwegian Seismic Array, (NORSAR); New Delhi, (NWDEL); Red Knife, Ontario, (RK-ON); Shillong, (SHL); Taipei, (TAP); and White Horse, Yukon, (WH-YK).« less

Estimating National-scale Emissions using Dense Monitoring Networks

NASA Astrophysics Data System (ADS)

Ganesan, A.; Manning, A.; Grant, A.; Young, D.; Oram, D.; Sturges, W. T.; Moncrieff, J. B.; O'Doherty, S.

2014-12-01

The UK's DECC (Deriving Emissions linked to Climate Change) network consists of four greenhouse gas measurement stations that are situated to constrain emissions from the UK and Northwest Europe. These four stations are located in Mace Head (West Coast of Ireland), and on telecommunication towers at Ridge Hill (Western England), Tacolneston (Eastern England) and Angus (Eastern Scotland). With the exception of Angus, which currently only measures carbon dioxide (CO2) and methane (CH4), the remaining sites are additionally equipped to monitor nitrous oxide (N2O). We present an analysis of the network's CH4 and N2O observations from 2011-2013 and compare derived top-down regional emissions with bottom-up inventories, including a recently produced high-resolution inventory (UK National Atmospheric Emissions Inventory). As countries are moving toward national-level emissions estimation, we also address some of the considerations that need to be made when designing these national networks. One of the novel aspects of this work is that we use a hierarchical Bayesian inversion framework. This methodology, which has newly been applied to greenhouse gas emissions estimation, is designed to estimate temporally and spatially varying model-measurement uncertainties and correlation scales, in addition to fluxes. Through this analysis, we demonstrate the importance of characterizing these covariance parameters in order to properly use data from high-density monitoring networks. This UK case study highlights the ways in which this new inverse framework can be used to address some of the limitations of traditional Bayesian inverse methods.

Identifying hub stations and important lines of bus networks: A case study in Xiamen, China

NASA Astrophysics Data System (ADS)

Zhang, Hui; Zhuge, Chengxiang; Yu, Xiaohua

2018-07-01

Hub stations and important lines play key roles in transfers between stations. In this paper, a node failure model is proposed to identify hub stations. In the model, we introduce two new indicators called neighborhood degree ratio and transfer index to evaluate the importance of stations, which consider neighborhood stations' degree of station and the initial transfer times between stations. Moreover, line accessibility is developed to measure the importance of lines in the bus network. Xiamen bus network in 2016 is utilized to test the model. The results show that the two introduced indicators are more effective to identify hub stations compared with traditional complex network indicators such as degree, clustering coefficient and betweenness.

Developing User-Driven Climate Information Services to Build Resilience Amongst Groups at Risk of Drought and Flood in Arid and Semi-Arid Land Counties in Kenya

NASA Astrophysics Data System (ADS)

Githungo, W. N.; Shaka, A.; Kniveton, D.; Muithya, L.; Powell, R.; Visman, E. L.

2014-12-01

The Arid and Semi-Arid Land (ASAL) counties of Kitui and Makueni in Kenya are experiencing increasing climate variability in seasonal rainfall, including changes in the onset, cessation and distribution of the two principal rains upon which the majority of the population's small-holder farmers and livestock keepers depend. Food insecurity is prevalent with significant numbers also affected by flooding during periods of intense rainfall. As part of a multi-partner Adaptation Consortium, Kenya Meteorological Services (KMS) are developing Climate Information Services (CIS) which can better support decision making amongst the counties' principal livelihoods groups and across County Government ministries. Building on earlier pilots and stakeholder discussion, the system combines the production of climate information tailored for transmission via regional and local radio stations with the establishment of a new SMS service. SMS are provided through a network of CIS intermediaries drawn from across key government ministries, religious networks, non-governmental and community groups, aiming to achieve one SMS recipient per 3-500 people. It also introduces a demand-led, premium-rate SMS weather information service which is designed to be self-financing in the long term. Supporting the ongoing process of devolution, KMS is downscaling national forecasts for each county, and providing seasonal, monthly, weekly and daily forecasts, as well as warnings of weather-related hazards. Through collaboration with relevant ministries, government bodies and research institutions, including livestock, agriculture, drought management and health, technical advisories are developed to provide guidance on application of the climate information. The system seeks to provide timely, relevant information which can enable people to use weather and climate information to support decisions which protect life and property and build resilience to ongoing climate variability and future change.

CentNet—A deployable 100-station network for surface exchange research

NASA Astrophysics Data System (ADS)

Oncley, S.; Horst, T. W.; Semmer, S.; Militzer, J.; Maclean, G.; Knudson, K.

2014-12-01

Climate, air quality, atmospheric composition, surface hydrology, and ecological processes are directly affected by the Earth's surface. Complexity of this surface exists at multiple spatial scales, which complicates the understanding of these processes. NCAR/EOL currently provides a facility to the research community to make direct eddy-covariance flux observations to quantify surface-atmosphere interactions. However, just as model resolution has continued to increase, there is a need to increase the spatial density of flux measurements to capture the wide variety of scales that contribute to exchange processes close to the surface. NCAR/EOL now has developed the CentNet facility, that is envisioned to have on the order of 100 surface flux stations deployable for periods of months to years. Each station would measure standard meteorological variables, all components of the surface energy balance (including turbulence fluxes and radiation), atmospheric composition, and other quantities to characterize the surface. Thus, CentNet can support observational research in the biogeosciences, hydrology, urban meteorology, basic meteorology, and turbulence. CentNet has been designed to be adaptable to a wide variety of research problems while keeping operations manageable. Tower infrastructure has been designed to be lightweight, easily deployed, and with a minimal set-up footprint. CentNet uses sensor networks to increase spatial sampling at each station. The data system saves every sample on site to retain flexibility in data analysis. We welcome guidance on development and funding priorities as we build CentNet.

Long-term trends in tourism climate index scores for 40 stations across Iran: the role of climate change and influence on tourism sustainability

NASA Astrophysics Data System (ADS)

Roshan, Gholamreza; Yousefi, Robabe; Fitchett, Jennifer M.

2016-01-01

Tourism is a rapidly growing international sector and relies intrinsically on an amenable climate to attract visitors. Climate change is likely to influence the locations preferred by tourists and the time of year of peak travel. This study investigates the effect of climate change on the Tourism Climate Index (TCI) for Iran. The paper first calculates the monthly TCI for 40 cities across Iran for each year from 1961 to 2010. Changes in the TCI over the study period for each of the cities are then explored. Increases in TCI are observed for at least one station in each month, whilst for some months no decreases occurred. For October, the maximum of 45 % of stations demonstrated significant changes in TCI, whilst for December only 10 % of stations demonstrated change. The stations Kashan, Orumiyeh, Shahrekord, Tabriz, Torbat-e-Heidarieh and Zahedan experienced significant increases in TCI for over 6 months. The beginning of the change in TCI is calculated to have occurred from 1970 to 1980 for all stations. Given the economic dependence on oil exports, the development of sustainable tourism in Iran is of importance. This critically requires the identification of locations most suitable for tourism, now and in the future, to guide strategic investment.

Long-term trends in tourism climate index scores for 40 stations across Iran: the role of climate change and influence on tourism sustainability.

PubMed

Roshan, Gholamreza; Yousefi, Robabe; Fitchett, Jennifer M

2016-01-01

Tourism is a rapidly growing international sector and relies intrinsically on an amenable climate to attract visitors. Climate change is likely to influence the locations preferred by tourists and the time of year of peak travel. This study investigates the effect of climate change on the Tourism Climate Index (TCI) for Iran. The paper first calculates the monthly TCI for 40 cities across Iran for each year from 1961 to 2010. Changes in the TCI over the study period for each of the cities are then explored. Increases in TCI are observed for at least one station in each month, whilst for some months no decreases occurred. For October, the maximum of 45% of stations demonstrated significant changes in TCI, whilst for December only 10% of stations demonstrated change. The stations Kashan, Orumiyeh, Shahrekord, Tabriz, Torbat-e-Heidarieh and Zahedan experienced significant increases in TCI for over 6 months. The beginning of the change in TCI is calculated to have occurred from 1970 to 1980 for all stations. Given the economic dependence on oil exports, the development of sustainable tourism in Iran is of importance. This critically requires the identification of locations most suitable for tourism, now and in the future, to guide strategic investment.

Ground-based measurement of column-averaged mixing ratios of methane and carbon dioxide in the Sichuan Basin of China by a desktop optical spectrum analyzer

NASA Astrophysics Data System (ADS)

Qin, Xiu-Chun; Nakayama, Tomoki; Matsumi, Yutaka; Kawasaki, Masahiro; Ono, Akiko; Hayashida, Sachiko; Imasu, Ryoichi; Lei, Li-Ping; Murata, Isao; Kuroki, Takahiro; Ohashi, Masafumi

2018-01-01

Remote sensing of the atmospheric greenhouse gases, methane (CH4) and carbon dioxide (CO2), contributes to the understanding of global warming and climate change. A portable ground-based instrument consisting of a commercially available desktop optical spectrum analyzer and a small sun tracker has been applied to measure the column densities of atmospheric CH4 and CO2 at Yanting observation station in a mountainous paddy field of the Sichuan Basin from September to November 2013. The column-averaged dry-air molar mixing ratios, XCH4/XCO2, are compared with those retrieved by satellite observations in the Sichuan Basin and by ground-based network observations in the same latitude zone as the Yanting observation station.

Streamflow measurements, basin characteristics, and streamflow statistics for low-flow partial-record stations operated in Massachusetts from 1989 through 1996

USGS Publications Warehouse

Ries, Kernell G.

1999-01-01

A network of 148 low-flow partial-record stations was operated on streams in Massachusetts during the summers of 1989 through 1996. Streamflow measurements (including historical measurements), measured basin characteristics, and estimated streamflow statistics are provided in the report for each low-flow partial-record station. Also included for each station are location information, streamflow-gaging stations for which flows were correlated to those at the low-flowpartial-record station, years of operation, and remarks indicating human influences of stream-flowsat the station. Three or four streamflow measurements were made each year for three years during times of low flow to obtain nine or ten measurements for each station. Measured flows at the low-flow partial-record stations were correlated with same-day mean flows at a nearby gaging station to estimate streamflow statistics for the low-flow partial-record stations. The estimated streamflow statistics include the 99-, 98-, 97-, 95-, 93-, 90-, 85-, 80-, 75-, 70-, 65-, 60-, 55-, and 50-percent duration flows; the 7-day, 10- and 2-year low flows; and the August median flow. Characteristics of the drainage basins for the stations that theoretically relate to the response of the station to climatic variations were measured from digital map data by use of an automated geographic information system procedure. Basin characteristics measured include drainage area; total stream length; mean basin slope; area of surficial stratified drift; area of wetlands; area of water bodies; and mean, maximum, and minimum basin elevation.Station descriptions and calculated streamflow statistics are also included in the report for the 50 continuous gaging stations used in correlations with the low-flow partial-record stations.

Toward Continental-scale Rainfall Monitoring Using Commercial Microwave Links From Cellular Communication Networks

NASA Astrophysics Data System (ADS)

Uijlenhoet, R.; Leijnse, H.; Overeem, A.

2017-12-01

Accurate and timely surface precipitation measurements are crucial for water resources management, agriculture, weather prediction, climate research, as well as ground validation of satellite-based precipitation estimates. However, the majority of the land surface of the earth lacks such data, and in many parts of the world the density of surface precipitation gauging networks is even rapidly declining. This development can potentially be counteracted by using received signal level data from the enormous number of microwave links used worldwide in commercial cellular communication networks. Along such links, radio signals propagate from a transmitting antenna at one base station to a receiving antenna at another base station. Rain-induced attenuation and, subsequently, path-averaged rainfall intensity can be retrieved from the signal's attenuation between transmitter and receiver. We have previously shown how one such a network can be used to retrieve the space-time dynamics of rainfall for an entire country (The Netherlands, ˜35,500 km2), based on an unprecedented number of links (˜2,400) and a rainfall retrieval algorithm that can be applied in real time. This demonstrated the potential of such networks for real-time rainfall monitoring, in particular in those parts of the world where networks of dedicated ground-based rainfall sensors are often virtually absent. The presentation will focus on the potential for upscaling this technique to continental-scale rainfall monitoring in Europe. In addition, several examples of recent applications of this technique on other continents (South America, Africa, Asia and Australia) will be given.

What would dense atmospheric observation networks bring to the quantification of city CO2 emissions?

NASA Astrophysics Data System (ADS)

Wu, Lin; Broquet, Grégoire; Ciais, Philippe; Bellassen, Valentin; Vogel, Felix; Chevallier, Frédéric; Xueref-Remy, Irène; Wang, Yilong

2016-06-01

Cities currently covering only a very small portion ( < 3 %) of the world's land surface directly release to the atmosphere about 44 % of global energy-related CO2, but they are associated with 71-76 % of CO2 emissions from global final energy use. Although many cities have set voluntary climate plans, their CO2 emissions are not evaluated by the monitoring, reporting, and verification (MRV) procedures that play a key role for market- or policy-based mitigation actions. Here we analyze the potential of a monitoring tool that could support the development of such procedures at the city scale. It is based on an atmospheric inversion method that exploits inventory data and continuous atmospheric CO2 concentration measurements from a network of stations within and around cities to estimate city CO2 emissions. This monitoring tool is configured for the quantification of the total and sectoral CO2 emissions in the Paris metropolitan area (˜ 12 million inhabitants and 11.4 TgC emitted in 2010) during the month of January 2011. Its performances are evaluated in terms of uncertainty reduction based on observing system simulation experiments (OSSEs). They are analyzed as a function of the number of sampling sites (measuring at 25 m a.g.l.) and as a function of the network design. The instruments presently used to measure CO2 concentrations at research stations are expensive (typically ˜ EUR 50 k per sensor), which has limited the few current pilot city networks to around 10 sites. Larger theoretical networks are studied here to assess the potential benefit of hypothetical operational lower-cost sensors. The setup of our inversion system is based on a number of diagnostics and assumptions from previous city-scale inversion experiences with real data. We find that, given our assumptions underlying the configuration of the OSSEs, with 10 stations only the uncertainty for the total city CO2 emission during 1 month is significantly reduced by the inversion by ˜ 42 %. It can be further reduced by extending the network, e.g., from 10 to 70 stations, which is promising for MRV applications in the Paris metropolitan area. With 70 stations, the uncertainties in the inverted emissions are reduced significantly over those obtained using 10 stations: by 32 % for commercial and residential buildings, by 33 % for road transport, by 18 % for the production of energy by power plants, and by 31 % for total emissions. These results indicate that such a high number of stations would be likely required for the monitoring of sectoral emissions in Paris using this observation-model framework. They demonstrate some high potential that atmospheric inversions can contribute to the monitoring and/or the verification of city CO2 emissions (baseline) and CO2 emission reductions (commitments) and the advantage that could be brought by the current developments of lower-cost medium precision (LCMP) sensors.

Ground Monitoring Neotropical Dry Forests: A Sensor Network for Forest and Microclimate Dynamics in Semi-Arid Environments (Enviro-Net°)

NASA Astrophysics Data System (ADS)

Rankine, C. J.; Sánchez-Azofeifa, G.

2011-12-01

In the face of unprecedented global change driven by anthropogenic pressure on natural systems it has become imperative to monitor and better understand potential shifts in ecosystem functioning and services from local to global scales. The utilization of automated sensors technologies offers numerous advantages over traditional on-site ecosystem surveying techniques and, as a result, sensor networks are becoming a powerful tool in environmental monitoring programs. Tropical forests, renowned for their biodiversity, are important regulators of land-atmosphere fluxes yet the seasonally dry tropical forests, which account for 40% of forested ecosystems in the American tropics, have been severely degraded over the past several decades and not much is known of their capacity to recover. With less than 1% of these forests protected, our ability to monitor the dynamics and quantify changes in the remaining primary and recovering secondary tropical dry forests is vital to understanding mechanisms of ecosystem stress responses and climate feedback with respect to annual productivity and desertification processes in the tropics. The remote sensing component of the Tropi-Dry: Human and Biophysical Dimensions of Tropical Dry Forests in the Americas research network supports a network of long-term tropical ecosystem monitoring platforms which focus on the dynamics of seasonally dry tropical forests in the Americas. With over 25 sensor station deployments operating across a latitudinal gradient in Mexico, Costa Rica, Brazil, and Argentina continuously collecting hyper-temporal sensory input based on standardized deployment parameters, this monitoring system is unique among tropical environments. Technologies used in the network include optical canopy phenology towers, understory wireless sensing networks, above and below ground microclimate stations, and digital cameras. Sensory data streams are uploaded to a cyber-infrastructure initiative, denominated Enviro-Net°, for data storage, management, visualization, and retrieval for further analysis. The use of tower and ground-based optical sensor networks and meteorological monitoring instrumentation has proven effective in capturing seasonal growth patterns in primary and secondary forest stands. Furthermore, the observed trends in above and below ground microclimate variables are shown to closely correlate with in-situ vegetative indices (NDVI and EVI) across study sites. These long-term environmental sensory data streams provide valuable insights as to how these threatened semi-arid ecosystems regenerate after disturbances and how they respond to environmental stress such as climate change in the tropical and sub-tropical latitudes.

Meteorological stations as a tool to teach on climate system sciences

NASA Astrophysics Data System (ADS)

Cerdà, Artemi; Bodí, Merche B.; Damián Ruiz-Sinoga, José

2010-05-01

Higher education has been focussed on teaching climate system theory. Meteorology and climatology student rarely visited a meteorological station. However, meteorological stations are the source of information for the climate system studies and they supply the key information for modelling. This paper shows how meteorological station is a key tool to introduce student to the study of climate and meteorology. The research stations of Montesa and El Teularet-Sierra de Enguera are being used for seven years to supply data to the students of Climatology, 1st year of the Degree in Geography at the University of Valencia. The results show that the students that used the raw data set were proud to use original data. Those students got higher qualifications and they choose also in the following year courses on climatology or Physical Geography. Then, the conclusions are that the use of meteorological stations is a positive contribution to the improvement of the knowledge of the students, and his compromise with the science and the environment.

Evaluation of Integration Degree of the ASG-EUPOS Polish Reference Networks With Ukrainian GeoTerrace Network Stations in the Border Area

NASA Astrophysics Data System (ADS)

Siejka, Zbigniew

2017-09-01

GNSS systems are currently the basic tools for determination of the highest precision station coordinates (e.g. basic control network stations or stations used in the networks for geodynamic studies) as well as for land, maritime and air navigation. All of these tasks are carried out using active, large scale, satellite geodetic networks which are complex, intelligent teleinformatic systems offering post processing services along with corrections delivered in real-time for kinematic measurements. Many countries in the world, also in Europe, have built their own multifunctional networks and enhance them with their own GNSS augmentation systems. Nowadays however, in the era of international integration, there is a necessity to consider collective actions in order to build a unified system, covering e.g. the whole Europe or at least some of its regions. Such actions have already been undertaken in many regions of the world. In Europe such an example is the development for EUPOS which consists of active national networks built in central eastern European countries. So far experience and research show, that the critical areas for connecting these networks are border areas, in which the positioning accuracy decreases (Krzeszowski and Bosy, 2011). This study attempts to evaluate the border area compatibility of Polish ASG-EUPOS (European Position Determination System) reference stations and Ukrainian GeoTerrace system reference stations in the context of their future incorporation into the EUPOS. The two networks analyzed in work feature similar hardware parameters. In the ASG-EUPOS reference stations network, during the analyzed period, 2 stations (WLDW and CHEL) used only one system (GPS), while, in the GeoTerrace network, all the stations were equipped with both GPS and GLONASS receivers. The ASG EUPOS reference station network (95.6%) has its average completeness greater by about 6% when compared to the GeoTerrace network (89.8%).

Multivariate analysis of climate along the southern coast of Alaska—some forestry implications.

Treesearch

Wilbur A. Farr; John S. Hard

1987-01-01

A multivariate analysis of climate was used to delineate 10 significantly different groups of climatic stations along the southern coast of Alaska based on latitude, longitude, seasonal temperatures and precipitation, frost-free periods, and total number of growing degree days. The climatic stations were too few to delineate this rugged, mountainous region into...

Statistical downscaling of sub-daily (6-hour) temperature in Romania, by means of artificial neural networks

NASA Astrophysics Data System (ADS)

Birsan, Marius-Victor; Dumitrescu, Alexandru; Cǎrbunaru, Felicia

2016-04-01

The role of statistical downscaling is to model the relationship between large-scale atmospheric circulation and climatic variables on a regional and sub-regional scale, making use of the predictions of future circulation generated by General Circulation Models (GCMs) in order to capture the effects of climate change on smaller areas. The study presents a statistical downscaling model based on a neural network-based approach, by means of multi-layer perceptron networks. Sub-daily temperature data series from 81 meteorological stations over Romania, with full data records are used as predictands. As large-scale predictor, the NCEP/NCAD air temperature data at 850 hPa over the domain 20-30E / 40-50N was used, at a spatial resolution of 2.5×2.5 degrees. The period 1961-1990 was used for calibration, while the validation was realized over the 1991-2010 interval. Further, in order to estimate future changes in air temperature for 2021-2050 and 2071-2100, air temperature data at 850 hPa corresponding to the IPCC A1B scenario was extracted from the CNCM33 model (Meteo-France) and used as predictor. This work has been realized within the research project "Changes in climate extremes and associated impact in hydrological events in Romania" (CLIMHYDEX), code PN II-ID-2011-2-0073, financed by the Romanian Executive Agency for Higher Education Research, Development and Innovation Funding (UEFISCDI).

A 280-Year Long Series of Phenological Observations of Cherry Tree Blossoming Dates for Switzerland

NASA Astrophysics Data System (ADS)

Rutishauser, T.; Luterbacher, J.; Wanner, H.

2003-04-01

Phenology is generally described as the timing of life cycle phases or activities of plants and animals in their temporal occurrence throughout the year (Lieth 1974). Recent studies have shown that meteorological and climatological impacts leave their 'fingerprints' across natural systems in general and strongly influence the seasonal activities of single animal and plant species. During the 20th century, phenological observation networks have been established around the world to document and analyze the influence of the globally changing climate to plants and wildlife. This work presents a first attempt of a unique 280-year long series of phenological observations of cherry tree blossoming dates for the Swiss plateau region. In Switzerland, a nation-wide phenological observation network has been established in 1951 currently documenting 69 phenophases of 26 different plant species. A guidebook seeks to increase objectiveness in the network observations. The observations of the blooming of the cherry tree (prunus avium) were chosen to calculate a mean series for the Swiss plateau region with observations from altitudes ranging between 370 and 860 asl. A total number of 737 observations from 21 stations were used. A linear regression was established between the mean blooming date and altitude in order to correct the data to a reference altitude level. Other ecological parameters were unaccounted for. The selected network data series from 1951 to 2000 was combined and prolonged with observations from various sources back to 1721. These include several historical observation series by farmers, clergymen and teachers, data from various stations collected at the newly established Swiss meteorological network from 1864 to 1873 and the single long series of observations from Liestal starting in 1894. The homogenized time series of observations will be compared with reconstructions of late winter temperatures as well as statistical estimations of blooming time based on long instrumental data from Europe. In addition, the series is one of the few historical phenological records to assess past climate and ecological changes. Lieth, H. (1974). Phenology and Seasonality Modeling. Berlin, Heidelberg, New York, Springer.

Effect of densifying the GNSS GBAS network on monitoring the troposphere zenith total delay and precipitable water vapour content during severe weather events

NASA Astrophysics Data System (ADS)

Kapłon, Jan; Stankunavicius, Gintautas

2016-04-01

The dense ground based augmentation networks can provide the important information for monitoring the state of neutral atmosphere. The GNSS&METEO research group at Wroclaw University of Environmental and Life Sciences (WUELS) is operating the self-developed near real-time service estimating the troposphere parameters from GNSS data for the area of Poland. The service is operational since December 2012 and it's results calculated from ASG-EUPOS GBAS network (120 stations) data are supporting the EGVAP (http://egvap.dmi.dk) project. At first the zenith troposphere delays (ZTD) were calculated in hourly intervals, but since September 2015 the service was upgraded to include SmartNet GBAS network (Leica Geosystems Polska - 150 stations). The upgrade included as well: increasing the result interval to 30 minutes, upgrade from Bernese GPS Software v. 5.0 to Bernese GNSS Software v. 5.2 and estimation of the ZTD and it's horizontal gradients. Processing includes nowadays 270 stations. The densification of network from 70 km of mean distance between stations to 40 km created the opportunity to investigate on it's impact on resolution of estimated ZTD and integrated water vapour content (IWV) fields during the weather events of high intensity. Increase in density of ZTD measurements allows to define better the meso-scale features within different synoptic systems (e.g. frontal waves, meso-scale convective systems, squall lines etc). These meso-scale structures, as a rule are short living but fast developing and hardly predictable by numerical models. Even so, such limited size systems can produce very hazardous phenomena - like widespread squalls and thunderstorms, tornadoes, heavy rains, snowfalls, hail etc. because of prevalence of Cb clouds with high concentration of IWV. Study deals with two meteorological events: 2015-09-01 with the devastating squalls and rainfall bringing 2M Euro loss of property in northern Poland and 2015-10-12 with the very active front bringing snowfall in southern part of the country. There are presented as well: the evaluation of differences in 2D fields of ZTD and IWV obtained from ASG-EUPOS network only and from ASG-EUPOS and SmartNet networks, their validation using IWV from numerical weather model and CM-SAF (Satellite Application Facility on Climate Monitoring) data. The results are interpreted towards the increase of possibility to detect the meso-scale weather features with densification of GNSS sensors network.

New York Urban Hydro-Meteorological Testbed (NY-uHMT)

NASA Astrophysics Data System (ADS)

Norouzi, H.; Bah, A.

2017-12-01

It is well known that heat waves kill more persons, on average, than any other extreme weather event in the United States. New York City experiences much adversity due to inclement weather. Exploring climate variation in New Yorker City will help scientists and local government to detect and forecast extreme weather hazards and gather more localized temperature data within the five boroughs. Ground based weather stations are widely used to provide real time data to the public to prevent disasters. The New York urban Hydro-meteorological Testbed (NY-uHMT) is a hydro meteorological network that is used to investigate climate change in the New York City area. It is composed of twenty autonomous weather stations that will gather information on air temperature, relative humidity, rainfall and soil moisture properties around the densely populated NYC area. For each station, the data is stored on a Campbell Scientific CR200x data logger and can be accessed remotely using the LoggerNet software, or by direct connection using an RS-232 cable. Real-time weather data is acquired every fifteen minutes. The data is then periodically sampled and graphed through MATLAB code to be broadcasted on the uHMT website and is available at no charge to the public. We anticipate the results will show that the temperature, humidity, precipitation and soil moisture will vary from location to location depending on the magnitude of urbanization to the area.

A global assessment of NASA AIRS v6 and EUMETSAT IASI v6 precipitable water vapor using ground-based GPS SuomiNet stations

NASA Astrophysics Data System (ADS)

Roman, Jacola; Knuteson, Robert; August, Thomas; Hultberg, Tim; Ackerman, Steve; Revercomb, Hank

2016-08-01

Satellite remote sensing of precipitable water vapor (PWV) is essential for monitoring moisture in real time for weather applications, as well as tracking the long-term changes in PWV for climate change trend detection. This study assesses the accuracies of the current satellite observing system, specifically the National Aeronautics and Space Administration (NASA) Atmospheric Infrared Sounder (AIRS) v6 PWV product and the European Organization for the Exploitation of Meteorological Satellite Studies (EUMETSAT) Infrared Atmospheric Sounding Interferometer (IASI) v6 PWV product, using ground-based SuomiNet Global Positioning System (GPS) network as truth. Elevation-corrected collocated matchups to each SuomiNet GPS station in North America and around the world were created, and results were broken down by station, ARM region, climate zone, and latitude zone. The greatest difference, exceeding 5%, between IASI and AIRS retrievals occurred in the tropics. Generally, IASI and AIRS fall within a 5% error in the PWV range of 20-40 mm (a mean bias less than 2 mm), with a wet bias for extremely low PWV values (less than 5 mm) and a dry bias for extremely high PWV values (greater than 50 mm). The operational IR satellite products are able to capture the mean PWV but degrade in the extreme dry and wet regimes.

Evaluation of selected methods for determining streamflow during periods of ice effect

USGS Publications Warehouse

Melcher, N.B.; Walker, J.F.

1990-01-01

The methods are classified into two general categories, subjective and analytical, depending on whether individual judgement is necessary for method application. On the basis of results of the evaluation for the three Iowa stations, two of the subjective methods (discharge ratio and hydrographic-and-climatic comparison) were more accurate than the other subjective methods, and approximately as accurate as the best analytical method. Three of the analytical methods (index velocity, adjusted rating curve, and uniform flow) could potentially be used for streamflow-gaging stations where the need for accurate ice-affected discharge estimates justifies the expense of collecting additional field data. One analytical method (ice adjustment factor) may be appropriate for use for stations with extremely stable stage-discharge ratings and measuring sections. Further research is needed to refine the analytical methods. The discharge ratio and multiple regression methods produce estimates of streamflow for varying ice conditions using information obtained from the existing U.S. Geological Survey streamflow-gaging network.

Estimating extreme river discharges in Europe through a Bayesian network

NASA Astrophysics Data System (ADS)

Paprotny, Dominik; Morales-Nápoles, Oswaldo

2017-06-01

Large-scale hydrological modelling of flood hazards requires adequate extreme discharge data. In practise, models based on physics are applied alongside those utilizing only statistical analysis. The former require enormous computational power, while the latter are mostly limited in accuracy and spatial coverage. In this paper we introduce an alternate, statistical approach based on Bayesian networks (BNs), a graphical model for dependent random variables. We use a non-parametric BN to describe the joint distribution of extreme discharges in European rivers and variables representing the geographical characteristics of their catchments. Annual maxima of daily discharges from more than 1800 river gauges (stations with catchment areas ranging from 1.4 to 807 000 km2) were collected, together with information on terrain, land use and local climate. The (conditional) correlations between the variables are modelled through copulas, with the dependency structure defined in the network. The results show that using this method, mean annual maxima and return periods of discharges could be estimated with an accuracy similar to existing studies using physical models for Europe and better than a comparable global statistical model. Performance of the model varies slightly between regions of Europe, but is consistent between different time periods, and remains the same in a split-sample validation. Though discharge prediction under climate change is not the main scope of this paper, the BN was applied to a large domain covering all sizes of rivers in the continent both for present and future climate, as an example. Results show substantial variation in the influence of climate change on river discharges. The model can be used to provide quick estimates of extreme discharges at any location for the purpose of obtaining input information for hydraulic modelling.

Reconstruction of Flooding Events for the Central Valley, California from Instrumental and Documentary Weather Records

NASA Astrophysics Data System (ADS)

Dodds, S. F.; Mock, C. J.

2009-12-01

All available instrumental winter precipitation data for the Central Valley of California back to 1850 were digitized and analyzed to construct continuous time series. Many of these data, in paper or microfilm format, extend prior to modern National Weather Service Cooperative Data Program and Historical Climate Network data, and were recorded by volunteer observers from networks such as the US Army Surgeon General, Smithsonian Institution, and US Army Signal Service. Given incomplete individual records temporally, detailed documentary data from newspapers, personal diaries and journals, ship logbooks, and weather enthusiasts’ instrumental data, were used in conjunction with instrumental data to reconstruct precipitation frequency per month and season, continuous days of precipitation, and to identify anomalous precipitation events. Multilinear regression techniques, using surrounding stations and the relationships between modern and historical records, bridge timeframes lacking data and provided homogeneous nature of time series. The metadata for each station was carefully screened, and notes were made about any possible changes to the instrumentation, location of instruments, or an untrained observer to verify that anomalous events were not recorded incorrectly. Precipitation in the Central Valley varies throughout the entire region, but waterways link the differing elevations and latitudes. This study integrates the individual station data with additional accounts of flood descriptions through unique newspaper and journal data. River heights and flood extent inundating cities, agricultural lands, and individual homes are often recorded within unique documentary sources, which add to the understanding of flood occurrence within this area. Comparisons were also made between dam and levee construction through time and how waters are diverted through cities in natural and anthropogenically changed environments. Some precipitation that lead to flooding events that occur in the Central Valley in the mid-19th century through the early 20th century are more outstanding at some particular stations than the modern records include. Several years that are included in the study are 1850, 1862, 1868, 1878, 1881, 1890, and 1907. These flood years were compared to the modern record and reconstructed through time series and maps. Incorporating the extent and effects these anomalous events in future climate studies could improve models and preparedness for the future floods.

Statistical Downscaling Of Local Climate In The Alpine Region

NASA Astrophysics Data System (ADS)

Kaspar, Severin; Philipp, Andreas; Jacobeit, Jucundus

2016-04-01

The impact of climate change on the alpine region was disproportional strong in the past decades compared to the surrounding areas, which becomes manifest in a higher increase in surface air temperature. Beside the thermal changes also implications for the hydrological cycle may be expected, acting as a very important factor not only for the ecosystem but also for mankind, in the form of water security or considering economical aspects like winter tourism etc. Therefore, in climate impact studies, it is necessary to focus on variables with high influence on the hydrological cycle, for example temperature, precipitation, wind, humidity and radiation. The aim of this study is to build statistical downscaling models which are able to reproduce temperature and precipitation at the mountainous alpine weather stations Zugspitze and Sonnblick and to further project these models into the future to identify possible changes in the behavior of these climate variables and with that in the hydrological cycle. Beside facing a in general very complex terrain in this high elevated regions, we have the advantage of a more direct atmospheric influence on the meteorology of the exposed weather stations from the large scale circulation. Two nonlinear statistical methods are developed to model the station-data series on a daily basis: On the one hand a conditional classification approach was used and on the other hand a model based on artificial neural networks (ANNs) was built. The latter is in focus of this presentation. One of the important steps of developing a new model approach is to find a reliable predictor setup with e.g. informative predictor variables or adequate location and size of the spatial domain. The question is: Can we include synoptic background knowledge to identify an optimal domain for an ANN approach? The yet developed ANN setups and configurations show promising results in downscaling both, temperature (up to 80 % of explained variance) and precipitation (up to 60 % of explained variance).

The Swedish Research Infrastructure for Ecosystem Science - SITES

NASA Astrophysics Data System (ADS)

Lindroth, A.; Ahlström, M.; Augner, M.; Erefur, C.; Jansson, G.; Steen Jensen, E.; Klemedtsson, L.; Langenheder, S.; Rosqvist, G. N.; Viklund, J.

2017-12-01

The vision of SITES is to promote long-term field-based ecosystem research at a world class level by offering an infrastructure with excellent technical and scientific support and services attracting both national and international researchers. In addition, SITES will make data freely and easily available through an advanced data portal which will add value to the research. During the first funding period, three innovative joint integrating facilities were established through a researcher-driven procedure: SITES Water, SITES Spectral, and SITES AquaNet. These new facilities make it possible to study terrestrial and limnic ecosystem processes across a range of ecosystem types and climatic gradients, with common protocols and similar equipment. In addition, user-driven development at the nine individual stations has resulted in e.g. design of a long-term agricultural systems experiment, and installation of weather stations, flux systems, etc. at various stations. SITES, with its integrative approach and broad coverage of climate and ecosystem types across Sweden, constitutes an excellent platform for state-of-the-art research projects. SITES' support the development of: A better understanding of the way in which key ecosystems function and interact with each other at the landscape level and with the climate system in terms of mass and energy exchanges. A better understanding of the role of different organisms in controlling different processes and ultimately the functioning of ecosystems. New strategies for forest management to better meet the many and varied requirements from nature conservation, climate and wood, fibre, and energy supply points of view. Agricultural systems that better utilize resources and minimize adverse impacts on the environment. Collaboration with other similar infrastructures and networks is a high priority for SITES. This will enable us to make use of each others' experiences, harmonize metadata for easier exchange of data, and support each other to widen the user community.

Development of climate data input files for the Mechanistic-Empirical Pavement Design Guide (MEPDG).

DOT National Transportation Integrated Search

2011-06-30

Prior to this effort, Mississippi's MEPDG climate files were limited to 12 weather stations in only 10 countries and only seven weather stations had over 8 years (100 months)of data. Hence, building MEPDG climate input datasets improves modeling accu...

Los Alamos Climatology 2016 Update

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bruggeman, David Alan

The Los Alamos National Laboratory (LANL or the Laboratory) operates a meteorology monitoring network to support LANL emergency response, engineering designs, environmental compliance, environmental assessments, safety evaluations, weather forecasting, environmental monitoring, research programs, and environmental restoration. Weather data has been collected in Los Alamos since 1910. Bowen (1990) provided climate statistics (temperature and precipitation) for the 1961– 1990 averaging period, and included other analyses (e.g., wind and relative humidity) based on the available station locations and time periods. This report provides an update to the 1990 publication Los Alamos Climatology (Bowen 1990).

Investigation of land subsidence due to climate changes in surrounding areas of Urmia Lake (located in northwest of Iran) using wavelet coherence analysis of geodetic measurements and methodological data

NASA Astrophysics Data System (ADS)

Moghtased-Azar, K.; Mirzaei, A.; Nankali, H. R.; Tavakoli, F.

2012-04-01

Urmia Lake (salt lake in northwest of Iran) plays a valuable role in environment, wildlife and economy of Iran and the region, and now faces great challenges for survival. The Lake is in immediate and great danger and rapidly going to become salty desert. During the recent years and new heat wave, Iran, like many other countries are experiencing, is faced with relativity reduced rain fall. From a few years ago environment activists warned about potential dangers. Geodetic measurements, e.g., repeated leveling measurements of first order leveling network of Iran and continuous GPS measurements of Iranian Permanent GPS network of Iran (IPGN) showed that there is subsidence in surrounding areas of the lake. This paper investigates the relation between subsidence and climate changing in the area, using the wavelet coherence of the data of permanent GPS stations and daily methodological data. The results show that there is strong coherence between the subsidence phenomena induced by GPS data and climate warming from January 2009 up to end of August 2009. However, relative lake height variations computed from altimetry observations (TOPEX/POSEIDON (T/P), Jason-1 and Jason-2/OSTM) confirms maximum evaporation rates of the lake in this period.

Multi-decadal analysis of root-zone soil moisture applying the exponential filter across CONUS

NASA Astrophysics Data System (ADS)

Tobin, Kenneth J.; Torres, Roberto; Crow, Wade T.; Bennett, Marvin E.

2017-09-01

This study applied the exponential filter to produce an estimate of root-zone soil moisture (RZSM). Four types of microwave-based, surface satellite soil moisture were used. The core remotely sensed data for this study came from NASA's long-lasting AMSR-E mission. Additionally, three other products were obtained from the European Space Agency Climate Change Initiative (CCI). These datasets were blended based on all available satellite observations (CCI-active, CCI-passive, and CCI-combined). All of these products were 0.25° and taken daily. We applied the filter to produce a soil moisture index (SWI) that others have successfully used to estimate RZSM. The only unknown in this approach was the characteristic time of soil moisture variation (T). We examined five different eras (1997-2002; 2002-2005; 2005-2008; 2008-2011; 2011-2014) that represented periods with different satellite data sensors. SWI values were compared with in situ soil moisture data from the International Soil Moisture Network at a depth ranging from 20 to 25 cm. Selected networks included the US Department of Energy Atmospheric Radiation Measurement (ARM) program (25 cm), Soil Climate Analysis Network (SCAN; 20.32 cm), SNOwpack TELemetry (SNOTEL; 20.32 cm), and the US Climate Reference Network (USCRN; 20 cm). We selected in situ stations that had reasonable completeness. These datasets were used to filter out periods with freezing temperatures and rainfall using data from the Parameter elevation Regression on Independent Slopes Model (PRISM). Additionally, we only examined sites where surface and root-zone soil moisture had a reasonably high lagged r value (r > 0. 5). The unknown T value was constrained based on two approaches: optimization of root mean square error (RMSE) and calculation based on the normalized difference vegetation index (NDVI) value. Both approaches yielded comparable results; although, as to be expected, the optimization approach generally outperformed NDVI-based estimates. The best results were noted at stations that had an absolute bias within 10 %. SWI estimates were more impacted by the in situ network than the surface satellite product used to drive the exponential filter. The average Nash-Sutcliffe coefficients (NSs) for ARM ranged from -0. 1 to 0.3 and were similar to the results obtained from the USCRN network (0.2-0.3). NS values from the SCAN and SNOTEL networks were slightly higher (0.1-0.5). These results indicated that this approach had some skill in providing an estimate of RZSM. In terms of RMSE (in volumetric soil moisture), ARM values actually outperformed those from other networks (0.02-0.04). SCAN and USCRN RMSE average values ranged from 0.04 to 0.06 and SNOTEL average RMSE values were higher (0.05-0.07). These values were close to 0.04, which is the baseline value for accuracy designated for many satellite soil moisture missions.

Testing alternative models of climate-mediated extirpations.

PubMed

Beever, Erik A; Ray, Chris; Mote, Philip W; Wilkening, Jennifer L

2010-01-01

Biotic responses to climate change will vary among taxa and across latitudes, elevational gradients, and degrees of insularity. However, due to factors such as phenotypic plasticity, ecotypic variation, and evolved tolerance to thermal stress, it remains poorly understood whether losses should be greatest in populations experiencing the greatest climatic change or living in places where the prevailing climate is closest to the edge of the species' bioclimatic envelope (e.g., at the hottest, driest sites). Research on American pikas (Ochotona princeps) in montane areas of the Great Basin during 1994-1999 suggested that 20th-century population extirpations were predicted by a combination of biogeographic, anthropogenic, and especially climatic factors. Surveys during 2005-2007 documented additional extirpations and within-site shifts of pika distributions at remaining sites. To evaluate the evidence in support of alternative hypotheses involving effects of thermal stress on pikas, we placed temperature sensors at 156 locations within pika habitats in the vicinity of 25 sites with historical records of pikas in the Basin. We related these time series of sensor data to data on ambient temperature from weather stations within the Historical Climate Network. We then used these highly correlated relationships, combined with long-term data from the same weather stations, to hindcast temperatures within pika habitats from 1945 through 2006. To explain patterns of loss, we posited three alternative classes of direct thermal stress: (1) acute cold stress (number of days below a threshold temperature); (2) acute heat stress (number of days above a threshold temperature); and (3) chronic heat stress (average summer temperature). Climate change was defined as change in our thermal metrics between two 31-yr periods: 1945-1975 and 1976-2006. We found that patterns of persistence were well predicted by metrics of climate. Our best models suggest some effects of climate change; however, recent and long-term metrics of chronic heat stress and acute cold stress, neither previously recognized as sources of stress for pikas, were some of the best predictors of pika persistence. Results illustrate that extremely rapid distributional shifts can be explained by climatic influences and have implications for conservation topics such as reintroductions and early-warning indicators.

Testing alternative models of climate-mediated extirpations

USGS Publications Warehouse

Beever, E.A.; Chris, R.A.Y.; Mote, P.W.; Wilkening, J.L.

2010-01-01

Biotic responses to climate change will vary among taxa and across latitudes, elevational gradients, and degrees of insularity. However, due to factors such as phenotypic plasticity, ecotypic variation, and evolved tolerance to thermal stress, it remains poorly understood whether losses should be greatest in populations experiencing the greatest climatic change or living in places where the prevailing climate is closest to the edge of the species' bioclimatic envelope (e.g., at the hottest, driest sites). Research on American pikas (Ochotona princeps) in montane areas of the Great Basin during 1994-1999 suggested that 20th-century population extirpations were predicted by a combination of biogeographic, anthropogenic, and especially climatic factors. Surveys during 2005-2007 documented additional extirpations and within-site shifts of pika distributions at remaining sites. To evaluate the evidence in support of alternative hypotheses involving effects of thermal stress on pikas, we placed temperature sensors at 156 locations within pika habitats in the vicinity of 25 sites with historical records of pikas in the Basin. We related these time series of sensor data to data on ambient temperature from weather stations within the Historical Climate Network. We then used these highly correlated relationships, combined with long-term data from the same weather stations, to hindcast temperatures within pika habitats from 1945 through 2006. To explain patterns of loss, we posited three alternative classes of direct thermal stress: (1) acute cold stress (number of days below a threshold temperature); (2) acute heat stress (number of days above a threshold, temperature); and. (3) chronic heat stress (average summer temperature). Climate change was defined as change in our thermal metrics between two 31-y.r periods: 1945-1975 and 1976-2006. We found that patterns of persistence were well predicted by metrics of climate. Our best models suggest some effects of climate change; however, recent and long-term metrics of chronic heat stress and acute cold stress, neither previously recognized as sources of stress for pikas, were some of the best predictors of pika persistence. Results illustrate that extremely rapid distributional shifts can be explained by climatic influences and have implications for conservation topics such as reintroductions and early-warning indicators. ?? 2010 by the Ecological society of America.

Wavelength dependent light absorption as a cost effective, real-time surrogate for ambient concentrations of polycyclic aromatic hydrocarbons

NASA Astrophysics Data System (ADS)

Brown, Richard J. C.; Butterfield, David M.; Goddard, Sharon L.; Hussain, Delwar; Quincey, Paul G.; Fuller, Gary W.

2016-02-01

Many monitoring stations used to assess ambient air concentrations of pollutants regulated by European air quality directives suffer from being expensive to establish and operate, and from their location being based on the results of macro-scale modelling exercises rather than measurement assessments in candidate locations. To address these issues for the monitoring of polycyclic aromatic hydrocarbons (PAHs), this study has used data from a combination of the ultraviolet and infrared channels of aethalometers (referred to as UV BC), operated as part of the UK Black Carbon Network, as a surrogate measurement. This has established a relationship between concentrations of the PAH regulated in Europe, benzo[a]pyrene (B[a]P), and the UV BC signal at locations where these measurements have been made together from 2008 to 2014. This relationship was observed to be non-linear. Relationships for individual site types were used to predict measured concentrations with, on average, 1.5% accuracy across all annual averages, and with only 1 in 36 of the predicted annual averages deviating from the measured annual average by more than the B[a]P data quality objective for uncertainty of 50% (at -65%, with the range excluding this value between + 38% and -37%). These relationships were then used to predict B[a]P concentrations at stations where UV BC measurement are made, but PAH measurements are not. This process produced results which reflected expectations based on knowledge of the pollution climate at these stations gained from the measurements of other air quality networks, or from nearby stations. The influence of domestic solid fuel heating was clear using this approach which highlighted Strabane in Northern Ireland as a station likely to be in excess of the air quality directive target value for B[a]P.

ECOLES: a Citizen Observers network engaging communities to map climate change at the local level

NASA Astrophysics Data System (ADS)

Thejll, Peter; Walker, Nicholas; Sandholt, Inge; Brown, Ian; Solberg, Rune; Suwala, Jason; Kelly, Richard; Tangen, Helge; Berglund, Robin; Dean, Andy; Engset, Rune; Siewertsen, Bjarne

2016-04-01

Engaging people in environmental studies is an important way to bring across awareness of expected future climate changes, and also a way to measure environmental change in ways that are better or complementary to remote sensing methods. With a hands-on approach, people are more likely to embrace the idea that climate change is occurring, and with modern technologies it is possible to collect quite stunning amounts of relevant data. We suggest several national activities tailored to conditions in each of the participating countries and also to existing national CO-projects. The project focuses on gathering data on biological changes, on weather, and on snow-pack information in Nordic countries as well as Greenland and Canada. Data will be gathered with existing equipment (mobile phones and internet-connected weather stations) and the project provides the means for collation of data into a database for dissemination and quality control. Numerical data collected by small non-professional weather stations or mobile phones with sensors are not directly useful quantitatively for e.g. numerical weather prediction without validation of data quality, but with validation there is a huge untapped potential due to the number of observers. Students are a central part of the project, which also seeks to engage people out and about in nature, and people with their own weather stations or other environmental data-collection activities, as well as passive data collection from mobile phone data sensors in people's bags and pockets. Appropriate software, educational and training materials will be designed with end-users in mind; school-age materials will be produced in the appropriate languages (e.g. Kalaallisut for COs of school age in Greenland).

Newly Digitized Historical Climate Data of the German Bight and the Southern Baltic Sea Coasts

NASA Astrophysics Data System (ADS)

Röhrbein, Dörte; Tinz, Birger; von Storch, Hans

2015-04-01

The detection of historical climate information plays an important role with regard to the discussion on climate change, particularly on storminess. The German Meteorological Service houses huge archives of historical handwritten journals of weather observations. A considerable number of original observation sheets from stations along the coast of the German Bight and the southern Baltic Sea exists which has been until recently almost unnoticed. These stations are called signal stations and are positioned close to the shore. However, for this region meteorological observation data of 128 stations exist from 1877 to 1999 and are partly digitized. In this study we show an analysis of firstly newly digitized wind and surface air pressure data of 15 stations from 1877 to 1939 and we also present a case study of the storm surge at the coast of the southern Baltic Sea in December 1913. The data are quality controlled by formal, climatological, temporal and consistency checks. It is shown that these historical climate data are usable in consistency and quality for further investigations on climate change, e.g. as input for regional and global reanalysis.

An approach to the rationalization of streamflow data collection networks

NASA Astrophysics Data System (ADS)

Burn, Donald H.; Goulter, Ian C.

1991-01-01

A new procedure for rationalizing a streamflow data collection network is developed. The procedure is a two-phase approach in which in the first phase, a hierarchical clustering technique is used to identify groups of similar gauging stations. In the second phase, a single station from each identified group of gauging stations is selected to be retained in the rationalized network. The station selection phase is an inherently heuristic process that incorporates information about the characteristics of the individual stations in the network. The methodology allows the direct inclusion of user judgement into the station selection process in that it is possible to select more than one station from a group, if conditions warrant. The technique is demonstrated using streamflow gauging stations in and near the Pembina River basin, southern Manitoba, Canada.

Exploring Agro-Climatic Trends in Ethiopia Using CHIRPS

NASA Astrophysics Data System (ADS)

Pedreros, D. H.; Funk, C. C.; Brown, M. E.; Korecha, D.; Seid, Y. M.

2015-12-01

The Famine Early Warning Systems Network (FEWS NET) uses the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) to monitor agricultural food production in different regions of the world. CHIRPS is a 1981-present, 5 day, approximately 5km resolution, rainfall product based on a combination of geostationary satellite observations, a high resolution climatology and in situ station observations. Furthermore, FEWS NET has developed a gridded implementation of the Water Requirement Satisfaction Index (WRSI), a water balance measurement indicator of crop performance. This study takes advantage of the CHIRPS' long term period of record and high spatial and temporal resolution to examine agro-climatic trends in Ethiopia. We use the CHIRPS rainfall dataset to calculate the WRSI for the boreal spring and summer crop seasons, as well as for spring-summer rangelands conditions. We find substantial long term rainfall declines in the spring and summer seasons across southeastern and northeastern Ethiopia. Crop Model results indicate that rainfall declines in the cropped regions have been associated with water deficits during the critical grain filling periods in well populated and/or highly vulnerable parts of eastern Ethiopia. WRSI results in the pastoral areas indicate substantial reductions in rangeland health during the later part of the growing seasons. These health declines correspond to the regions of Somaliland and Afar that have experienced chronic severe food insecurity since 2010. Key words: CHIRPS, satellite estimated rainfall, agricultural production

Agriculturally Relevant Climate Extremes and Their Trends in the World's Major Growing Regions

NASA Astrophysics Data System (ADS)

Zhu, Xiao; Troy, Tara J.

2018-04-01

Climate extremes can negatively impact crop production, and climate change is expected to affect the frequency and severity of extremes. Using a combination of in situ station measurements (Global Historical Climatology Network's Daily data set) and multiple other gridded data products, a derived 1° data set of growing season climate indices and extremes is compiled over the major growing regions for maize, wheat, soybean, and rice for 1951-2006. This data set contains growing season climate indices that are agriculturally relevant, such as the number of hot days, duration of dry spells, and rainfall intensity. Before 1980, temperature-related indices had few trends; after 1980, statistically significant warming trends exist for each crop in the majority of growing regions. In particular, crops have increasingly been exposed to extreme hot temperatures, above which yields have been shown to decline. Rainfall trends are less consistent compared to temperature, with some regions receiving more rainfall and others less. Anomalous temperature and precipitation conditions are shown to often occur concurrently, with dry growing seasons more likely to be hotter, have larger drought indices, and have larger vapor pressure deficits. This leads to the confluence of a variety of climate conditions that negatively impact crop yields. These results show a consistent increase in global agricultural exposure to negative climate conditions since 1980.

FluxSuite: a New Scientific Tool for Advanced Network Management and Cross-Sharing of Next-Generation Flux Stations

NASA Astrophysics Data System (ADS)

Burba, G. G.; Johnson, D.; Velgersdyk, M.; Beaty, K.; Forgione, A.; Begashaw, I.; Allyn, D.

2015-12-01

Significant increases in data generation and computing power in recent years have greatly improved spatial and temporal flux data coverage on multiple scales, from a single station to continental flux networks. At the same time, operating budgets for flux teams and stations infrastructure are getting ever more difficult to acquire and sustain. With more stations and networks, larger data flows from each station, and smaller operating budgets, modern tools are needed to effectively and efficiently handle the entire process. This would help maximize time dedicated to answering research questions, and minimize time and expenses spent on data processing, quality control and station management. Cross-sharing the stations with external institutions may also help leverage available funding, increase scientific collaboration, and promote data analyses and publications. FluxSuite, a new advanced tool combining hardware, software and web-service, was developed to address these specific demands. It automates key stages of flux workflow, minimizes day-to-day site management, and modernizes the handling of data flows: Each next-generation station measures all parameters needed for flux computations Field microcomputer calculates final fully-corrected flux rates in real time, including computation-intensive Fourier transforms, spectra, co-spectra, multiple rotations, stationarity, footprint, etc. Final fluxes, radiation, weather and soil data are merged into a single quality-controlled file Multiple flux stations are linked into an automated time-synchronized network Flux network manager, or PI, can see all stations in real time, including fluxes, supporting data, automated reports, and email alerts PI can assign rights, allow or restrict access to stations and data: selected stations can be shared via rights-managed access internally or with external institutions Researchers without stations could form "virtual networks" for specific projects by collaborating with PIs from different actual networks This presentation provides detailed examples of FluxSuite currently utilized by two large flux networks in China (National Academy of Sciences & Agricultural Academy of Sciences), and smaller networks with stations in the USA, Germany, Ireland, Malaysia and other locations around the globe.

Challenges and Opportunities to Developing Synergies Among Diverse Environmental Observatories: FSML, NEON, and GLEON

NASA Astrophysics Data System (ADS)

Williamson, C. E.; Weathers, K. C.; Knoll, L. B.; Brentrup, J.

2012-12-01

Recent rapid advances in sensor technology and cyberinfrastructure have enabled the development of numerous environmental observatories ranging from local networks at field stations and marine laboratories (FSML) to continental scale observatories such as the National Ecological Observatory Network (NEON) to global scale observatories such as the Global Lake Ecological Observatory Network (GLEON). While divergent goals underlie the initial development of these observatories, and they are often designed to serve different communities, many opportunities for synergies exist. In addition, the use of existing infrastructure may enhance the cost-effectiveness of building and maintaining large scale observatories. For example, FSMLs are established facilities with the staff and infrastructure to host sensor nodes of larger networks. Many field stations have existing staff and long-term databases as well as smaller sensor networks that are the product of a single or small group of investigators with a unique data management system embedded in a local or regional community. These field station based facilities and data are a potentially untapped gold mine for larger continental and global scale observatories; common ecological and environmental challenges centered on understanding the impacts of changing climate, land use, and invasive species often underlie these efforts. The purpose of this talk is to stimulate a dialog on the challenges of merging efforts across these different spatial and temporal scales, as well as addressing how to develop synergies among observatory networks with divergent roots and philosophical approaches. For example, FSMLs have existing long-term databases and facilities, while NEON has sparse past data but a well-developed template and closely coordinated team working in a coherent format across a continental scale. GLEON on the other hand is a grass-roots network of experts in science, information technology, and engineering with a common goal of building a scalable network around the world to understand and predict how lakes respond to global change. Creating synergies among networks at these divergent scales requires open discussions ranging from data collection and management to data serving and sharing. Coordination of these efforts can provide an additional opportunity to educate both students and the public in innovative new ways about the broader continental to global scale of ecological and environmental challenges that they have observed in their more local ecosystems.

The collocated station Košetice - Kešín u Pacova, Czech Republic: an important research infrastructure in central Europe

NASA Astrophysics Data System (ADS)

Dvorska, Alice; Milan, Váňa; Vlastimil, Hanuš; Marian, Pavelka

2013-04-01

The collocated station Košetice - Křešín u Pacova, central Czech Republic, is a major research and monitoring infrastructure in the Czech Republic and central Europe. It consists of two basic components: the observatory Košetice run since 1988 by the Czech Hydrometeorological Institute and the atmospheric station (AS) Křešín u Pacova starting operation in 2013. The AS is built and run by CzechGlobe - Global Change Research Centre, Academy of Sciences of the Czech Republic and is situated 100 m far from the observatory. There are three research and monitoring activities at the collocated station providing data necessary for the research on climate and related changes. The AS Křešín u Pacova consists of a 250 m tall tower serving for ground-based and vertical gradient measurements of (i) concentrations of CO2, CO, CH4, total gaseous mercury and tropospheric ozone (continuously), (ii) elemental and organic carbon (semicontinuously), (iii) carbon and oxygen isotopes, radon, N2O, SF6 and other species (episodically), (iv) optical properties of atmospheric aerosols and (v) meteorological parameters and the boundary layer height. Further, eddy covariance measurements in the nearby agroecosystem provide data on CO2 and H2O fluxes between the atmosphere and the ecosystem. Finally, monitoring activities at the nearby small hydrological catchment Anenské povodí run under the GEOMON network enables studying local hydrological and biogeochemical cycles. These measurements are supported by the long-term monitoring of meteorological and air quality parameters at the observatory Košetice, that are representative for the central European background. The collocated station provides a big research opportunity and challenge due to (i) a broad spectra of monitored chemical species, meteorological, hydrological and other parameters, (ii) measurements in various environmental compartments and especially the atmosphere, (iii) provision of data suitable for conducting multidisciplinar research activities and (iv) participation in a number of international programmes and projects, i.e. ICOS (AS Křešín u Pacova), ACTRIS, ACCENT, CLRTAP/EMEP, GAW and ICP-IM (Košetice) and others. Finally, the collocated station has potential for a successful participation in the planned network of European superstations covering both climate and air quality issues, one of the key areas in the European Strategy Forum on Research Infrastructures (ESFRI) process. Acknowledgement: This work is supported by the CzechGlobe (CZ.1.05/1.1.00/02.0073) and CZ.1.07/2.4.00/31.0056 projects.

Climatic variation and runoff from partially-glacierised Himalayan tributary basins of the Ganges.

PubMed

Collins, David N; Davenport, Joshua L; Stoffel, Markus

2013-12-01

Climate records for locations across the southern slope of the Himalaya between 77°E and 91°E were selected together with discharge measurements from gauging stations on rivers draining partially-glacierised basins tributary to the Ganges, with a view to assessing impacts of climatic fluctuations on year-to-year variations of runoff during a sustained period of glacier decline. The aims were to describe temporal patterns of variation of glaciologically- and hydrologically-relevant climatic variables and of river flows from basins with differing percentages of ice-cover. Monthly precipitation and air temperature records, starting in the mid-nineteenth century at high elevation sites and minimising data gaps, were selected from stations in the Global Historical Climatology Network and CRUTEM3. Discharge data availability was limited to post 1960 for stations in Nepal and at Khab in the adjacent Sutlej basin. Strengths of climate-runoff relationships were assessed by correlation between overlapping portions of annual data records. Summer monsoon precipitation dominates runoff across the central Himalaya. Flow in tributaries of the Ganges in Nepal fluctuated from year to year but the general background level of flow was usually maintained from the 1960s to 2000s. Flow in the Sutlej, however, declined by 32% between the 1970s and 1990s, reflecting substantially reduced summer precipitation. Over the north-west Ganges-upper Sutlej area, monsoon precipitation declined by 30-40% from the 1960s to 2000s. Mean May-September air temperatures along the southern slope of the central Himalayas dipped from the 1960s, after a long period of slow warming or sustained temperatures, before rising rapidly from the mid-1970s so that in the 2000s summer air temperatures reached those achieved in earlier warmer periods. There are few measurements of runoff from highly-glacierised Himalayan headwater basins; runoff from one of which, Langtang Khola, was less than that of the monsoon-dominated Narayani river, in which basin Langtang is nested. Copyright © 2013 Elsevier B.V. All rights reserved.

Evaluation of the streamflow-gaging network of Texas and a proposed core network

USGS Publications Warehouse

Slade, Raymond M.; Howard, Teresa; Anaya, Roberto

2001-01-01

The U.S. Geological Survey streamflowgaging network in Texas is operated as part of the National Streamgaging Program and is jointly funded by the Geological Survey and Federal, State, and local agencies. This report documents an evaluation of the existing (as of October 1, 1999) network with regard to four major objectives of streamflow data; and on the basis of that evaluation, proposes a core network of streamflowgaging stations that best meets those objectives. The objectives are (1) regionalization (estimate flows or flow characteristics at ungaged sites in 11 hydrologically similar regions), (2) major flow (obtain flow rates and volumes in large streams), (3) outflow from the State (account for streamflow leaving the State), and (4) streamflow conditions assessment (assess current conditions with regard to long-term data, and define temporal trends in flow). The network analysis resulted in a proposed core network of 263 stations. Of those 263 stations, 43 were discontinued as of October 1, 1999, and 15 were partial-record stations. Fifty-five of the proposed core-network stations meet two of the four major objectives, 16 stations meet three objectives, and 1 station meets all four. One-hundred eighty-five stations with a median record length of 33 years were selected to meet the regionalization objective. Ninety-two stations with a median record length of about 62 years were selected to meet the major-flow objective. Twenty-six stations with a median record length of 59 years were selected to meet the outflow from the State objective. Fifty stations with a median record length of 53 years were selected to meet the streamflow conditions assessment objective.

Establishment of Karadeniz Technical University Permanent GNSS Station as Reactivated of TRAB IGS Station

NASA Astrophysics Data System (ADS)

Kazancı, Selma Zengin; Kayıkçı, Emine Tanır

2017-12-01

In recent years, Global Navigation Satellite Systems (GNSS) have gained great importance in terms of the benefi ts it provides such as precise geodetic point positioning, determining crustal deformations, navigation, vehicle monitoring systems and meteorological applications etc. As in Turkey, for this purpose, each country has set up its own GNSS station networks like Turkish National Permanent RTK Network analyzed precise station coordinates and velocities together with the International GNSS Service, Turkish National Fundamental GPS Network and Turkish National Permanent GNSS Network (TNPGN) stations not only are utilized as precise positioning but also GNSS meteorology studies so total number of stations are increased. This work is related to the reactivated of the TRAB IGS station which was established in Karadeniz Technical University, Department of Geomatics Engineering. Within the COST ES1206 Action (GNSS4SWEC) KTU analysis center was established and Trop-NET system developed by Geodetic Observatory Pecny (GOP, RIGTC) in order to troposphere monitoring. The project titled "Using Regional GNSS Networks to Strengthen Severe Weather Prediction" was accepted to the scientifi c and technological research council of Turkey (TUBITAK). With this project, we will design 2 new constructed GNSS reference station network. Using observation data of network, we will compare water vapor distribution derived by GNSS Meteorology and GNSS Tomography. At this time, KTU AC was accepted as E-GVAP Analysis Centre in December 2016. KTU reference station is aimed to be a member of the EUREF network with these studies.

47 CFR 25.135 - Licensing provisions for earth station networks in the non-voice, non-geostationary Mobile...

Code of Federal Regulations, 2014 CFR

2014-10-01

... Applications and Licenses Earth Stations § 25.135 Licensing provisions for earth station networks in the non... 47 Telecommunication 2 2014-10-01 2014-10-01 false Licensing provisions for earth station networks in the non-voice, non-geostationary Mobile-Satellite Service. 25.135 Section 25.135 Telecommunication...

Is the global mean temperature trend too low?

NASA Astrophysics Data System (ADS)

Venema, Victor; Lindau, Ralf

2015-04-01

The global mean temperature trend may be biased due to similar technological and economic developments worldwide. In this study we want to present a number of recent results that suggest that the global mean temperature trend might be steeper as generally thought. In the Global Historical Climate Network version 3 (GHCNv3) the global land surface temperature is estimated to have increased by about 0.8°C between 1880 and 2012. In the raw temperature record, the increase is 0.6°C; the 0.2°C difference is due to homogenization adjustments. Given that homogenization can only reduce biases, this 0.2°C stems from a partial correction of bias errors and it seems likely that the real non-climatic trend bias will be larger. Especially in regions with sparser networks, homogenization will not be able to improve the trend much. Thus if the trend bias in these regions is similar to the bias for more dense networks (industrialized countries), one would expect the real bias to be larger. Stations in sparse networks are representative for a larger region and are given more weight in the computation of the global mean temperature. If all stations are given equal weight, the homogenization adjustments of the GHCNv3 dataset are about 0.4°C per century. In the subdaily HadISH dataset one break with mean size 0.12°C is found every 15 years for the period 1973-2013. That would be a trend bias of 0.78°C per century on a station by station basis. Unfortunately, these estimates strongly focus on Western countries having more stations. It is known from the literature that rich countries have a (statistically insignificant) stronger trend in the global datasets. Regional datasets can be better homogenized than global ones, the main reason being that global datasets do not contain all stations known to the weather services. Furthermore, global datasets use automatic homogenization methods and have less or no metadata. Thus while regional data can be biased themselves, comparing them with global datasets can provide some indication on biases. Compared to the global BEST dataset for the same countries, the national datasets of Austria, Italy and Switzerland have a 0.36°C per century stronger trend since 1901. For the trend since 1960 we can also take Australia, France and Slovenia into account and find a trend bias of 0.40°C per century. Relative to CRUCY the trend biases are smaller and only statistically significant for the period since 1980. The most direct way to study biases in the temperature records is by making parallel measurements with historical measurement set-ups. Several recent parallel data studies for the transition to Stevenson screens suggest larger biases: Austria 0.2°C, Spain 0.5 & 0.6°C. As well as older tropical ones: India 0.42°C and Sri Lanka 0.37°C. The smaller values from the Parker (1994) review mainly stem from parallel measurements from North-West Europe, which may have less problems with exposure. Furthermore, the influence of many historical transitions, especially the ones that could cause an artificial smaller trend, have not been studied in detail yet. We urgently need to study improvements of exposure (especially in the (sub-)tropics), increases in watering and irrigation, mechanical ventilation, better paints, relocations to airports, and relocations to suburbs of stations that started in the cities and from village centers to pasture, for example. Our current understanding surprisingly suggests that the more recent period may have the largest biases, but it could also be that even the best datasets are unable to improve earlier data sufficiently. If the temperature trend were actually larger it would reduce discrepancies between studies for a number of problems in climatology. For example, the estimates of transient climate sensitivity using instrumental data are lower as the one using climate models, volcanic eruptions or paleo data. Furthermore, several changes observed in the climate system are larger than expected. On the other hand, a large trend in the land surface temperature would make the discrepancy with the tropospheric temperature even larger (radiosondes and satellites) and it would introduce a larger difference between land and sea temperature trends. Concluding, at the moment there is no strong evidence yet that the temperature trend is underestimated. However, we do have a considerable amount of evidence that suggests that there is a moderate, but climatologically important bias that we should study with urgency. As far as we know there are no estimates for the remaining uncertainty in the global mean trend after homogenization. Also studies into the causes of cooling biases are a pressing need. (Many have contributed to this study, but it is not clear at this moment who would be official collaborators; they will be added later.)

A Databank of Antarctic Surface Temperature and Pressure Data (NDP-032)

DOE Data Explorer

Jones, P. D. [University of East Anglia; Reid, P. A. [University of East Anglia; Kaiser, D. P.

2001-10-01

This database contains monthly mean surface temperature and mean sea level pressure data from twenty-nine meteorological stations within the Antarctic region. The first version of this database was compiled at the Climatic Research Unit (CRU) of University of East Anglia, Norwich, United Kingdom. The database extended through 1988 and was made available in 1989 by the Carbon Dioxide Information Analysis Center (CDIAC) as a Numeric Data Package (NDP), NDP-032. This update of the database includes data through early 1999 for most stations (through 2000 for a few), and also includes all available mean monthly maximum and minimum temperature data. For many stations this means that over 40 years of data are now available, enough for many of the trends associated with recent warming to be more thoroughly examined. Much of the original version of this dataset was obtained from the World Weather Records (WWR) volumes (1951-1970), Monthly Climatic Data for the World (since 1961), and several other sources. Updating the station surface data involved requesting data from countries who have weather stations on Antarctica. Of particular importance within this study are the additional data obtained from Australia, Britain and New Zealand. Recording Antarctic station data is particularly prone to errors. This is mostly due to climatic extremes, the nature of Antarctic science, and the variability of meteorological staff at Antarctic stations (high turnover and sometimes untrained meteorological staff). For this compilation, as many sources as possible were contacted in order to obtain as close to official `source' data as possible. Some error checking has been undertaken and hopefully the final result is as close to a definitive database as possible. This NDP consists of this html documentation file, an ASCII text version of this file, six temperature files (three original CRU files for monthly maximum, monthly minimum, and monthly mean temperature and three equivalent files slightly reformatted at CDIAC), two monthly mean pressure data files (one original CRU file and one slightly reformatted CDIAC version of the file), four graphics files that describe the station network and the nature of temperature and pressure trends, a file summarizing annual and mean-monthly trends in surface temperatures over Antarctica, a file summarizing monthly Antarctic surface temperature anomalies with respect to the period 1961-90, a station inventory file, and 3 FORTRAN and 3 SAS routines for reading the data that may be incorporated into analysis programs that users may devise. These 23 files have a total size of approximately 2 megabytes and are available via the Internet through CDIAC's Web site or anonymous FTP (File Transfer Protocol) server, and, upon request, various magnetic media.

Evaluation of outdoor human thermal sensation of local climate zones based on long-term database

NASA Astrophysics Data System (ADS)

Unger, János; Skarbit, Nóra; Gál, Tamás

2018-02-01

This study gives a comprehensive picture on the diurnal and seasonal general outdoor human thermal sensation levels in different urban quarters based on long-term (almost 3 years) data series from urban and rural areas of Szeged, Hungary. It is supplemented with a case study dealing with an extreme heat wave period which is more and more frequent in the last decades in the study area. The intra-urban comparison is based on a thermal aspect classification of the surface, namely, the local climate zone (LCZ) system, on an urban meteorological station network and on the utilization of the physiologically equivalent temperature (PET) comfort index with categories calibrated to the local population. The selected stations represent sunlit areas well inside the LCZ areas. The results show that the seasonal and annual average magnitudes of the thermal load exerted by LCZs in the afternoon and evening follow their LCZ numbers. It is perfectly in line with the LCZ concept originally concentrating only on air temperature ( T air) differences between the zones. Our results justified the subdivision of urban areas into LCZs and give significant support to the application possibilities of the LCZ concept as a broader term covering different thermal phenomena.

Urbanization effects on climatic changes in 24 particular timings of the seasonal cycle in the middle and lower reaches of the Yellow River

NASA Astrophysics Data System (ADS)

Qian, Cheng; Ren, Guoyu; Zhou, Yaqing

2016-05-01

Changes in the timing of the seasonal cycle are important to natural ecosystems and human society, particularly agronomic activity. Urbanization effects (UEs) on surface air temperature changes at the local scale can be strong. Quantifying the observed changes in the timing of the seasonal cycle associated with UEs or large-scale background climatic warming is beneficial for the detection and attribution of regional climate change and for effective human adaptation, particularly in China, where rapid urbanization and industrialization are occurring. In this study, long-term changes in 24 particular timings of seasonal cycle, known as the Twenty-four Solar Terms (24STs), in the middle and lower reaches of the Yellow River in China are analyzed on the basis of homogenized daily temperature data over 1961-2010. UEs on these changes are further assessed by using a rural-station network selected from 2419 meteorological stations. In terms of area mean, half of the 24STs have significantly warmed, and UEs have contributed to 0.07-0.14 °C/decade or 25.7-64.0 % of the overall warming. The climatic solar terms from mid-February to early May (September and early October) have significantly advanced (delayed) by 5-17 days (approximately 5 days) over the last 50 years; 2-4 (2-3) of these days are attributed to UEs. The contribution of urbanization to the advancing or delaying trends is 21.7-69.5 %. The implications of these quantitative results differ for farmers, urban residents, and migrant workers in cities.

DOI/GTN-P climate and active-layer data acquired in the National Petroleum Reserve-Alaska and the Arctic National Wildlife Refuge

USGS Publications Warehouse

Urban, Frank E.; Clow, Gary D.

2014-01-01

This report provides data collected by the climate monitoring array of the U.S. Department of the Interior on Federal lands in Arctic Alaska over the period August 1998 to July 2013; this array is part of the Global Terrestrial Network for Permafrost, (DOI/GTN-P). In addition to presenting data, this report also describes monitoring, data collection, and quality-control methods. This array of 16 monitoring stations spans lat 68.5°N. to 70.5°N. and long 142.5°W. to 161°W., an area of approximately 150,000 square kilometers. Climate summaries are presented along with quality-controlled data. Data collection is ongoing and includes the following climate- and permafrost-related variables: air temperature, wind speed and direction, ground temperature, soil moisture, snow depth, rainfall totals, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.

DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2014

USGS Publications Warehouse

Urban, Frank E.; Clow, Gary D.

2016-03-04

This report provides data collected by the climate monitoring array of the U.S. Department of the Interior on Federal lands in Arctic Alaska over the period August 1998 to July 2014; this array is part of the Global Terrestrial Network for Permafrost (DOI/GTN-P). In addition to presenting data, this report also describes monitoring, data collection, and quality-control methods. The array of 16 monitoring stations spans lat 68.5°N. to 70.5°N. and long 142.5°W. to 161°W., an area of approximately 150,000 square kilometers. Climate summaries are presented along with quality-controlled data. Data collection is ongoing and includes the following climate- and permafrost-related variables: air temperature, wind speed and direction, ground temperature, soil moisture, snow depth, rainfall totals, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.

DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2015

USGS Publications Warehouse

Urban, Frank E.; Clow, Gary D.

2017-02-06

This report provides data collected by the climate monitoring array of the U.S. Department of the Interior on Federal lands in Arctic Alaska over the period August 1998 to July 2015; this array is part of the Global Terrestrial Network for Permafrost (DOI/GTN-P). In addition to presenting data, this report also describes monitoring, data collection, and quality-control methods. The array of 16 monitoring stations spans lat 68.5°N. to 70.5°N. and long 142.5°W. to 161°W., an area of approximately 150,000 square kilometers. Climate summaries are presented along with quality-controlled data. Data collection is ongoing and includes the following climate- and permafrost-related variables: air temperature, wind speed and direction, ground temperature, soil moisture, snow depth, rainfall totals, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.

DOI/GTN-P climate and active-layer data acquired in the National Petroleum Reserve: Alaska and the Arctic National Wildlife Refuge, 1998-2011

USGS Publications Warehouse

Urban, Frank E.; Clow, Gary D.

2014-01-01

This report provides data collected by the climate monitoring array of the U.S. Department of the Interior on Federal lands in Arctic Alaska over the period August 1998 to July 2011; this array is part of the Global Terrestrial Network for Permafrost, (DOI/GTN-P). In addition to presenting data, this report also describes monitoring, data collection, and quality-control methodology. This array of 16 monitoring stations spans lat 68.5°N. to 70.5°N. and long 142.5°W. to 161°W., an area of approximately 150,000 square kilometers. Climate summaries are presented along with quality-controlled data. Data collection is ongoing and includes the following climate- and permafrost-related variables: air temperature, wind speed and direction, ground temperature and soil moisture, snow depth, rainfall, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.

Evaluation of the streamflow-gaging network of Alaska in providing regional streamflow information

USGS Publications Warehouse

Brabets, Timothy P.

1996-01-01

In 1906, the U.S. Geological Survey (USGS) began operating a network of streamflow-gaging stations in Alaska. The primary purpose of the streamflow- gaging network has been to provide peak flow, average flow, and low-flow characteristics to a variety of users. In 1993, the USGS began a study to evaluate the current network of 78 stations. The objectives of this study were to determine the adequacy of the existing network in predicting selected regional flow characteristics and to determine if providing additional streamflow-gaging stations could improve the network's ability to predict these characteristics. Alaska was divided into six distinct hydrologic regions: Arctic, Northwest, Southcentral, Southeast, Southwest, and Yukon. For each region, historical and current streamflow data were compiled. In Arctic, Northwest, and Southwest Alaska, insufficient data were available to develop regional regression equations. In these areas, proposed locations of streamflow-gaging stations were selected by using clustering techniques to define similar areas within a region and by spatial visual analysis using the precipitation, physiographic, and hydrologic unit maps of Alaska. Sufficient data existed in Southcentral and Southeast Alaska to use generalized least squares (GLS) procedures to develop regional regression equations to estimate the 50-year peak flow, annual average flow, and a low-flow statistic. GLS procedures were also used for Yukon Alaska but the results should be used with caution because the data do not have an adequate spatial distribution. Network analysis procedures were used for the Southcentral, Southeast, and Yukon regions. Network analysis indicates the reduction in the sampling error of the regional regression equation that can be obtained given different scenarios. For Alaska, a 10-year planning period was used. One scenario showed the results of continuing the current network with no additional gaging stations and another scenario showed the results of adding gaging stations to the network. With the exception of the annual average discharge equation for Southeast Alaska, by adding gaging stations in all three regions, the sampling error was reduced to a greater extent than by not adding gaging stations. The proposed streamflow-gaging network for Alaska consists of 308 gaging stations, of which 32 are designated as index stations. If the proposed network can not be implemented in its entirety, then a lesser cost alternative would be to establish the index stations and to implement the network for a particular region.

Modelling hydrological extremes under non-stationary conditions using climate covariates

NASA Astrophysics Data System (ADS)

Vasiliades, Lampros; Galiatsatou, Panagiota; Loukas, Athanasios

2013-04-01

Extreme value theory is a probabilistic theory that can interpret the future probabilities of occurrence of extreme events (e.g. extreme precipitation and streamflow) using past observed records. Traditionally, extreme value theory requires the assumption of temporal stationarity. This assumption implies that the historical patterns of recurrence of extreme events are static over time. However, the hydroclimatic system is nonstationary on time scales that are relevant to extreme value analysis, due to human-mediated and natural environmental change. In this study the generalized extreme value (GEV) distribution is used to assess nonstationarity in annual maximum daily rainfall and streamflow timeseries at selected meteorological and hydrometric stations in Greece and Cyprus. The GEV distribution parameters (location, scale, and shape) are specified as functions of time-varying covariates and estimated using the conditional density network (CDN) as proposed by Cannon (2010). The CDN is a probabilistic extension of the multilayer perceptron neural network. Model parameters are estimated via the generalized maximum likelihood (GML) approach using the quasi-Newton BFGS optimization algorithm, and the appropriate GEV-CDN model architecture for the selected meteorological and hydrometric stations is selected by fitting increasingly complicated models and choosing the one that minimizes the Akaike information criterion with small sample size correction. For all case studies in Greece and Cyprus different formulations are tested with combinational cases of stationary and nonstationary parameters of the GEV distribution, linear and non-linear architecture of the CDN and combinations of the input climatic covariates. Climatic indices such as the Southern Oscillation Index (SOI), which describes atmospheric circulation in the eastern tropical pacific related to El Niño Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO) index that varies on an interdecadal rather than interannual time scale and the atmospheric circulation patterns as expressed by the North Atlantic Oscillation (NAO) index are used to express the GEV parameters as functions of the covariates. Results show that the nonstationary GEV model can be an efficient tool to take into account the dependencies between extreme value random variables and the temporal evolution of the climate.

Simulation-based coefficients for adjusting climate impact on energy consumption of commercial buildings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Na; Makhmalbaf, Atefe; Srivastava, Viraj

This paper presents a new technique for and the results of normalizing building energy consumption to enable a fair comparison among various types of buildings located near different weather stations across the U.S. The method was developed for the U.S. Building Energy Asset Score, a whole-building energy efficiency rating system focusing on building envelope, mechanical systems, and lighting systems. The Asset Score is calculated based on simulated energy use under standard operating conditions. Existing weather normalization methods such as those based on heating and cooling degrees days are not robust enough to adjust all climatic factors such as humidity andmore » solar radiation. In this work, over 1000 sets of climate coefficients were developed to separately adjust building heating, cooling, and fan energy use at each weather station in the United States. This paper also presents a robust, standardized weather station mapping based on climate similarity rather than choosing the closest weather station. This proposed simulated-based climate adjustment was validated through testing on several hundreds of thousands of modeled buildings. Results indicated the developed climate coefficients can isolate and adjust for the impacts of local climate for asset rating.« less

40 CFR 58.10 - Annual monitoring network plan and periodic network assessment.

Code of Federal Regulations, 2012 CFR

2012-07-01

... part of SLAMS, NCore stations, STN stations, State speciation stations, SPM stations, and/or, in... analysis method(s) for each measured parameter. (4) The operating schedules for each monitor. (5) Any...

40 CFR 58.10 - Annual monitoring network plan and periodic network assessment.

Code of Federal Regulations, 2013 CFR

2013-07-01

... part of SLAMS, NCore stations, STN stations, State speciation stations, SPM stations, and/or, in... and analysis method(s) for each measured parameter. (4) The operating schedules for each monitor. (5...

40 CFR 58.10 - Annual monitoring network plan and periodic network assessment.

Code of Federal Regulations, 2014 CFR

2014-07-01

... part of SLAMS, NCore stations, STN stations, State speciation stations, SPM stations, and/or, in... and analysis method(s) for each measured parameter. (4) The operating schedules for each monitor. (5...

Operation of International Monitoring System Network

NASA Astrophysics Data System (ADS)

Nikolova, Svetlana; Araujo, Fernando; Aktas, Kadircan; Malakhova, Marina; Otsuka, Riyo; Han, Dongmei; Assef, Thierry; Nava, Elisabetta; Mickevicius, Sigitas; Agrebi, Abdelouaheb

2015-04-01

The IMS is a globally distributed network of monitoring facilities using sensors from four technologies: seismic, hydroacoustic, infrasound and radionuclide. It is designed to detect the seismic and acoustic waves produced by nuclear test explosions and the subsequently released radioactive isotopes. Monitoring stations transmit their data to the IDC in Vienna, Austria, over a global private network known as the GCI. Since 2013, the data availability (DA) requirements for IMS stations account for quality of the data, meaning that in calculation of data availability data should be exclude if: - there is no input from sensor (SHI technology); - the signal consists of constant values (SHI technology); Even more strict are requirements for the DA of the radionuclide (particulate and noble gas) stations - received data have to be analyzed, reviewed and categorized by IDC analysts. In order to satisfy the strict data and network availability requirements of the IMS Network, the operation of the facilities and the GCI are managed by IDC Operations. Operations has following main functions: - to ensure proper operation and functioning of the stations; - to ensure proper operation and functioning of the GCI; - to ensure efficient management of the stations in IDC; - to provide network oversight and incident management. At the core of the IMS Network operations are a series of tools for: monitoring the stations' state of health and data quality, troubleshooting incidents, communicating with internal and external stakeholders, and reporting. The new requirements for data availability increased the importance of the raw data quality monitoring. This task is addressed by development of additional tools for easy and fast identifying problems in data acquisition, regular activities to check compliance of the station parameters with acquired data by scheduled calibration of the seismic network, review of the samples by certified radionuclide laboratories. The DA for the networks of different technologies in 2014 is: Primary seismic (PS) network - 95.70%, Infrasound network (IS) - 97.68%, Hydroacoustic network (HA) - 88.78%, Auxiliary Seismic - 86.07%; Radionuclide Particulate - 83.01% and Radionuclide Noble Gas -75.06%. IDC's strategy for further improving operations and management of the stations and meeting DA requirements is: - further development of tools and procedures to effectively identify and support troubleshooting of problems by the Station Operators; - effective support to the station operators to develop tailored Operation and Maintenance plans for their stations; - focus on early identification of the raw data quality problems at the station in order to support timely resolution; - extensive training programme for station operators (joined effort of IDC and IMS).

Intercomparison study of atmospheric methane and carbon dioxide concentrations measured at the Ebre River Delta Station

NASA Astrophysics Data System (ADS)

Occhipinti, Paola; Morguí, Josep Anton; Àgueda, Alba; Batet, Oscar; Borràs, Sílvia; Cañas, Lídia; Curcoll, Roger; Grossi, Claudia; Nofuentes, Manel; Vazquez, Eusebi; Rodó, Xavier

2015-04-01

In the framework of the ClimaDat project, IC3 has established a network of eight monitoring stations across the Iberian Peninsula and the Canarian Archipelago with the aim of studying climate processes. The monitoring station at the Ebre River Delta (DEC3) is located in the Ebre River Delta Natural Park (40° 44' N; 0° 47' E) and it is characterized by the typical North-Western Mediterranean climate. Since 2013, atmospheric greenhouse gases (GHG) and 222Rn tracer gas together with the meteorological parameters are continuously measured from a 10 m a.g.l. height tower. Atmospheric GHG (CO2, CH4, CO and N2O) concentrations are determined using a Picarro analyzer G2301 (CO2 and CH4) and a modified gas chromatograph (GC) Agilent 6890N (CO2, CH4, CO and N2O). Open data access is available from the www.climadat.es website. Data collected at the DEC3 station are also submitted to the InGOS platform since this station is part of the InGOS European infrastructure project. Researchers from the Laboratory of the Atmosphere and the Oceans (LAO) at IC3 have performed an intercomparison study at the DEC3 site between three different Picarro analyzers (two Picarro G2301 and one Picarro G2301M), a Los Gatos Research (LGR) analyzer and the GC system already installed at the station. The aim of this study is to compare and assess the measuring agreement between the four optical gas analyzers and the GC. In the first part of the experiment, all instruments have been calibrated using NOAA gases as primary standards analyzing five Praxair provided targets to evaluate the precision of the measuring instruments. Max Plank Institute (MPI) gases have been used as secondary standards for the GC whereas Praxair provided tanks are used as secondary standards for the Picarro and the LGR analyzers. In the second part of the experiment, atmospheric GHG were measured from natural atmospheric air taken from a 10 m a.g.l. inlet. Daily cycles of GHG measurements were carried out using different instruments simultaneously over a period of 24 hours, coupling the GC with a combination of two optical analyzers per time. Precision results together with the evaluation of the advantages and drawbacks of the use of these different GHG measuring instruments will be discussed. The intercomparison study here presented will be implemented by carrying it out at each of the eight ClimaDat monitoring stations in Spain, representing a quality control system for the analysis of GHG in the ClimaDat network.

Automatic data processing and analysis system for monitoring region around a planned nuclear power plant

NASA Astrophysics Data System (ADS)

Kortström, Jari; Tiira, Timo; Kaisko, Outi

2016-03-01

The Institute of Seismology of University of Helsinki is building a new local seismic network, called OBF network, around planned nuclear power plant in Northern Ostrobothnia, Finland. The network will consist of nine new stations and one existing station. The network should be dense enough to provide azimuthal coverage better than 180° and automatic detection capability down to ML -0.1 within a radius of 25 km from the site.The network construction work began in 2012 and the first four stations started operation at the end of May 2013. We applied an automatic seismic signal detection and event location system to a network of 13 stations consisting of the four new stations and the nearest stations of Finnish and Swedish national seismic networks. Between the end of May and December 2013 the network detected 214 events inside the predefined area of 50 km radius surrounding the planned nuclear power plant site. Of those detections, 120 were identified as spurious events. A total of 74 events were associated with known quarries and mining areas. The average location error, calculated as a difference between the announced location from environment authorities and companies and the automatic location, was 2.9 km. During the same time period eight earthquakes between magnitude range 0.1-1.0 occurred within the area. Of these seven could be automatically detected. The results from the phase 1 stations of the OBF network indicates that the planned network can achieve its goals.

47 CFR 73.4154 - Network/AM, FM station affiliation agreements.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 4 2011-10-01 2011-10-01 false Network/AM, FM station affiliation agreements. 73.4154 Section 73.4154 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) BROADCAST RADIO SERVICES RADIO BROADCAST SERVICES Rules Applicable to All Broadcast Stations § 73.4154 Network/AM...

47 CFR 73.4154 - Network/AM, FM station affiliation agreements.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 4 2010-10-01 2010-10-01 false Network/AM, FM station affiliation agreements. 73.4154 Section 73.4154 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) BROADCAST RADIO SERVICES RADIO BROADCAST SERVICES Rules Applicable to All Broadcast Stations § 73.4154 Network/AM...

Wireless Sensor Networks Approach

NASA Technical Reports Server (NTRS)

Perotti, Jose M.

2003-01-01

This viewgraph presentation provides information on hardware and software configurations for a network architecture for sensors. The hardware configuration uses a central station and remote stations. The software configuration uses the 'lost station' software algorithm. The presentation profiles a couple current examples of this network architecture in use.

Station Climatic Summaries, North America.

DTIC Science & Technology

1988-08-01

8603 (CB) ..................................... 371 MI IIGA ALPENA (PHELPS-COLLINS FIELD) 726390 8710 (Ce) ..................................... 372...direction APPROVED FOR PUBLIC RELEASE; DISTRIBUTION IS UNLIMITED 372 A W S Station Name: PHELPS-MOLLINS/ ALPENA KI Field Klev: 689 ft CLIMATIC BRIEF

Zoning vulnerability of climate change in variation of amount and trend of precipitation - Case Study: Great Khorasan province

NASA Astrophysics Data System (ADS)

Modiri, Ehsan; Modiri, Sadegh

2015-04-01

Climatic hazards have complex nature that many of them are beyond human control. Earth's climate is constantly fluctuating and trying to balance itself. More than 75% of Iran has arid and semi-arid climate thus assessment of climate change induced threats and vulnerabilities is essential. In order to investigate the reason for the changes in amount and trend of precipitation parameter, 17 synoptic stations have been selected in the interval of the establishment time of the station until 2013. These stations are located in three regions: Northern, Razavi and Southern Khorasan. For quality control of data in Monthly, quarterly and annual total precipitation of data were tested and checked by run test. Then probable trends in each of the areas was assessed by Kendall-tau test. Total annual precipitation of each station is the important factor that increase the sensitivity of vulnerability in the area with low rainfall. Annual amount of precipitation moving from north to south has been declining, though in different fields that they have different geomorphologic characteristics controversies occur. But clearly can be observed average of precipitation decline with decreasing latitude. There were positive trends in the annual precipitation in 6 stations, negative trends in 10 stations, as well as one station, has no trend. The remarkable notice is that all stations have a positive trend were in the northern region in the case study. These stations had been in ranging from none to Moderate classification of threats and vulnerability. After the initialization parameters to classify levels of risks and vulnerability, the two measures of mean annual precipitation and the trends of this fluctuation were combined together. This classification was created in five level for stations. Accordingly Golmakan, Ghochan, Torbate heydarieh, Bojnord and Mashhad were in none threat level. Khoor of Birjand and Boshruyeh have had complete stage of the threat level and had the greatest meteorological perspective risk. Finally, after determining the degree of threats, meteorological vulnerability zoning map was produced by kriging interpolation method and utilizing geographic information systems (GIS). It showed most studied areas were in complete level of investigation. Keywords: Vulnerability, Climate threats, GIS, Zoning, Precipitation, Crisis management.

37 CFR 201.17 - Statements of Account covering compulsory licenses for secondary transmissions by cable systems.

Code of Federal Regulations, 2014 CFR

2014-07-01

... distinct entity under the rules, regulations, and practices of the Federal Communications Commission in... signal equivalent, network station, independent station, noncommercial educational station, primary... purposes of this section. A translator station which retransmits the programs of a network station will be...

37 CFR 201.17 - Statements of Account covering compulsory licenses for secondary transmissions by cable systems.

Code of Federal Regulations, 2013 CFR

2013-07-01

... distinct entity under the rules, regulations, and practices of the Federal Communications Commission in... signal equivalent, network station, independent station, noncommercial educational station, primary... purposes of this section. A translator station which retransmits the programs of a network station will be...

37 CFR 201.17 - Statements of Account covering compulsory licenses for secondary transmissions by cable systems.

Code of Federal Regulations, 2012 CFR

2012-07-01

... distinct entity under the rules, regulations, and practices of the Federal Communications Commission in... signal equivalent, network station, independent station, noncommercial educational station, primary... purposes of this section. A translator station which retransmits the programs of a network station will be...

Cloud Compute for Global Climate Station Summaries

NASA Astrophysics Data System (ADS)

Baldwin, R.; May, B.; Cogbill, P.

2017-12-01

Global Climate Station Summaries are simple indicators of observational normals which include climatic data summarizations and frequency distributions. These typically are statistical analyses of station data over 5-, 10-, 20-, 30-year or longer time periods. The summaries are computed from the global surface hourly dataset. This dataset totaling over 500 gigabytes is comprised of 40 different types of weather observations with 20,000 stations worldwide. NCEI and the U.S. Navy developed these value added products in the form of hourly summaries from many of these observations. Enabling this compute functionality in the cloud is the focus of the project. An overview of approach and challenges associated with application transition to the cloud will be presented.

The local impact of climate change on the alpine mountains Zugspitze and Sonnblick

NASA Astrophysics Data System (ADS)

Kaspar, Severin; Philipp, Andreas; Jacobeit, Jucundus

2017-04-01

In the past decades, the alpine region indicates a high sensitivity to the impact of climate change, as one can see in a higher increase in surface air temperature in the alps compared to the surrounding area. Beside the effect on temperature, a change on the components of the hydrological cycle may be expected, which can be critical for mankind in many areas, where the alpine region provides water security or ensures economical income due to, for example, winter tourism. Changes in certain meteorological variables will also have effects on the alpine ecosystem itself. In this study, some of these quantities and their development under changing climate boundary conditions are examined for the meteorological stations Zugspitze and Sonnblick. Temperature, precipitation, wind and humidity were evaluated at the Zugspitze station, which is located in the northern part of the alps, temperature and precipitation at the Sonnblick Observatory, which is located in the center of the Alps. For the impact analysis, a statistical downscaling (SD) approach was developed to find a link between the large scale atmosphere and the respective local effect. The SD framework is based on the artificial neural network (ANN) method. Models are calibrated for each season on a daily time scale using the 20th century reanalysis dataset as a substitute for atmospheric observational data. The developed ANN setups and configurations show promising results, e.g. up to 90% of explained variance (R2) for temperature and up to 60 % R2 for precipitation and relative humidity, while wind strength reaches with about 30% the lowest performance values. The identified ANN setups are afterwards driven with scenario data from five general circulation models (GCMs) from CMIP5 and additionally with two further realizations of one of the GCMs. As representative concentration pathways, two radiative forcings, 4.5 and 8.5 Watts, are selected. All future projections show a continuing increase in temperature throughout the 21st century for both stations and all seasons. The impact on precipitation is more differentiated: While for all seasons of the Zugspitze station, increased precipitation is simulated (highest in winter), the Sonnblick station shows a decrease in summer. Relative humidity at the Zugspitze is expected to decrease slightly throughout the year and wind strength at the Zugspitze station is projected with a slight increase in winter and spring and a slight decrease in summer and autumn. Further analyses will consider the synoptic interpretation of the interdependency between large scale circulation and the respective local impact, to figure out the cause of the local climatic behavior in the 21st century. Therefore, classification algorithms will be applied as reference class forecast models for a quantitative evaluation.

Service offerings and interfaces for the ACTS network of earth stations

NASA Technical Reports Server (NTRS)

Coney, T. A.; Dobyns, T. R.; Chitre, D. M.; Lindstrom, R.

1988-01-01

The NASA Advanced Communications Technology Satellite (ACTS) will use a network of about 20 earth stations to operate as a Mode 1 network. This network will support two ACTS program objectives: to verify the technical performance of ACTS Mode 1 operation in GEO and to demonstrate the types and quality of services that can be provided by an ACTS Mode 1 communications system. The terrestrial interface design is a critical element in assuring that these network earth stations will meet the objectives. In this paper, the applicable terrestrial interface design requirements, the resulting interface specifications, and the associated terrestrial input/output hardware are discussed. A functional block diagram of a network earth station is shown.

Solar radiation observation stations with complete listing of data archived by the National Climatic Center, Asheville, North Carolina and initial listing of data not currently archived

NASA Technical Reports Server (NTRS)

Carter, E. A.; Wells, R. E.; Williams, B. B.; Christensen, D. L.

1976-01-01

A listing is provided of organizations taking solar radiation data, the 166 stations where observations are made, the type of equipment used, the form of the recorded data, and the period of operation of each station. Included is a listing of the data from 150 solar radiation stations collected over the past 25 years and stored by the National Climatic Center.

Disentangling Climate and Land-use Impacts on Grassland Carbon and Water Fluxes

NASA Astrophysics Data System (ADS)

Brunsell, N. A.; Nippert, J. B.

2014-12-01

Regional climate and land cover interact in a complex, non-linear manner to alter the local cycling of mass and energy. It is often difficult to isolate the role of either mechanism on the resultant fluxes. Here, we attempt to isolate these mechanisms through the use of network of 4 Ameriflux eddy covariance towers installed over different land cover and land use classes along a pronounced rainfall gradient. The land cover types include: annually burned C4 grassland, a 4 year burn site experiencing woody encroachment, an abandoned agricultural field and a new perennial agricultural site. We investigated the impact of rainfall variability, drought, and heat waves on the water and carbon budgets using data analysis, remote sensing, and modeling approaches. In addition, we have established a network of mini-meteorological stations at the annually and 4-year burn sites to assess micro-scale variability within the footprints of the towers as a function of topographic position, soil depth and soil water availability. Through the use of a wavelet multiscale decomposition and information theory metrics, we have isolated the role of environmental factors (temperature, humidity, soil moisture, etc.) on the fluxes across the different sites. By applying a similar analysis to model output, we can assess the ability of land-surface models to recreate the observed sensitity. Results indicate the utility of a network of measurement systems used in conjunction with land surface modeling and time series analysis to assess differential impacts to similar regional scale climate forcings. Implications for the role of land cover class in regional and global scale modeling systems will also be discussed.

The Sensitivity of Soil Moisture in Western U.S. Mountains to Changes in Snowmelt

NASA Astrophysics Data System (ADS)

Harpold, A. A.

2014-12-01

Snowmelt is the primary water source for human needs and ecosystems services in much of the Western U.S. Regional warming is expected to hasten snow disappearance and reduce snowpacks. The soil water budget strongly mediates the effects of changing snowmelt patterns by storing water and altering is partitioning to evaporation, transpiration, and runoff. This study therefore asked the research question, "Under what conditions was soil water availability coupled to snowmelt magnitudes and timing across Western U.S. mountains?" We posed three potential hypotheses to explain decoupling between soil water availability and snowmelt: 1. Contributions from post-snowmelt rainfall, 2. Longer growing season length and/or greater water demand, and/or 3. Insufficient soil water storage. Using 259 Snow Telemetry (SNOTEL) stations, we showed that the timing of Peak Soil Moisture (PSM) was strongly explained by snow disappearance (Pearson r-value of 0.62). However, differences in the coupling of PSM with DSD were dependent on soil and bedrock type, with well-drained areas having earlier PSM relative to DSD. A second analysis focused on 48 SNOTEL and Soil Climate Analysis Network (SCAN) stations in the Northwest and Intermountain Western U.S. where detailed soil hydraulic properties existed. We found the timing of snow disappearance was a strong influence (p<0.01) on the number of days per year that soil moisture was below wilting point at individual stations, whereas summer precipitation was a weaker predictor. We develop a framework to classify stations into three classes: 1. stations that were not subject to water stress from changing snowmelt patterns over the historical records, 2. stations subject to water stress during poor snowmelt years, and 3. stations that relied on rainfall to avoid water stress across historical records. Our combined results demonstrate that snow disappearance timing is a first-order control on soil water availability across many Western U.S. mountain ecosystems. However, soils properties could make areas more/less sensitive to changing snowpacks depending on seasonal precipitation patterns. This type of simple framework could be used to identify areas at risk of changing snowpacks and help constrain vegetation distributions as a consequence of climate change.

Has climate change shifted US maize planting times?

NASA Astrophysics Data System (ADS)

Butler, E.; Stine, A.; Huybers, P.

2012-12-01

Global warming has been accompanied by an earlier onset of spring phenological events across a range of ecosystems. However, the degree to which humans have adapted planting schedules to a changing climate remains an open question; the leading hypotheses for earlier planting are improved hardiness of cultivars and farming equipment. Here we examine the relationship between historical temperature and precipitation from 549 weather stations from the United States Historical Climatology Network (USHCN) with planting schedules from 20 states in the United States Department of Agriculture/National Agriculture Statistics Service (USDA/NASS) database. We construct an empirical model to relate yearly weather conditions to predict planting dates and compare this to the spatial distribution of climate conditions and mean planting times. Evidence for a relationship between climate and planting schedules indicates that planting schedules for US maize have been adapted to yearly variations and overall changes in climatology. As one might expect, hotter temperatures lead to earlier plantings while greater precipitation leads to later planting. These findings serve to indicate extant adaptation between US farmers and climate change, and will aid in forecasting future shifts to planting schedules as climate continues to change. Furthermore, the statistical model should also be useful for estimating planting times for states and years for which records do not otherwise exist.

Applicability of AgMERRA Forcing Dataset to Fill Gaps in Historical in-situ Meteorological Data

NASA Astrophysics Data System (ADS)

Bannayan, M.; Lashkari, A.; Zare, H.; Asadi, S.; Salehnia, N.

2015-12-01

Integrated assessment studies of food production systems use crop models to simulate the effects of climate and socio-economic changes on food security. Climate forcing data is one of those key inputs of crop models. This study evaluated the performance of AgMERRA climate forcing dataset to fill gaps in historical in-situ meteorological data for different climatic regions of Iran. AgMERRA dataset intercompared with in- situ observational dataset for daily maximum and minimum temperature and precipitation during 1980-2010 periods via Root Mean Square error (RMSE), Mean Absolute Error (MAE) and Mean Bias Error (MBE) for 17 stations in four climatic regions included humid and moderate, cold, dry and arid, hot and humid. Moreover, probability distribution function and cumulative distribution function compared between model and observed data. The results of measures of agreement between AgMERRA data and observed data demonstrated that there are small errors in model data for all stations. Except for stations which are located in cold regions, model data in the other stations illustrated under-prediction for daily maximum temperature and precipitation. However, it was not significant. In addition, probability distribution function and cumulative distribution function showed the same trend for all stations between model and observed data. Therefore, the reliability of AgMERRA dataset is high to fill gaps in historical observations in different climatic regions of Iran as well as it could be applied as a basis for future climate scenarios.

50 years of Global Seismic Observations

NASA Astrophysics Data System (ADS)

Anderson, K. R.; Butler, R.; Berger, J.; Davis, P.; Derr, J.; Gee, L.; Hutt, C. R.; Leith, W. S.; Park, J. J.

2007-12-01

Seismological recordings have been made on Earth for hundreds of years in some form or another, however, global monitoring of earthquakes only began in the 1890's when John Milne created 40 seismic observatories to measure the waves from these events. Shortly after the International Geophysical Year (IGY), a concerted effort was made to establish and maintain a more modern standardized seismic network on the global scale. In the early 1960's, the World-Wide Standardized Seismograph Network (WWSSN) was established through funding from the Advanced Research Projects Agency (ARPA) and was installed and maintained by the USGS's Albuquerque Seismological Laboratory (then a part of the US Coast and Geodetic Survey). This network of identical seismic instruments consisted of 120 stations in 60 countries. Although the network was motivated by nuclear test monitoring, the WWSSN facilitated numerous advances in observational seismology. From the IGY to the present, the network has been upgraded (High-Gain Long-Period Seismograph Network, Seismic Research Observatories, Digital WWSSN, Global Telemetered Seismograph Network, etc.) and expanded (International Deployment of Accelerometers, US National Seismic Network, China Digital Seismograph Network, Joint Seismic Project, etc.), bringing the modern day Global Seismographic Network (GSN) to a current state of approximately 150 stations. The GSN consists of state-of-the-art very broadband seismic transducers, continuous power and communications, and ancillary sensors including geodetic, geomagnetic, microbarographic, meteorological and other related instrumentation. Beyond the GSN, the system of global network observatories includes contributions from other international partners (e.g., GEOSCOPE, GEOFON, MEDNET, F-Net, CTBTO), forming an even larger backbone of permanent seismological observatories as a part of the International Federation of Digital Seismograph Networks. 50 years of seismic network operations have provided valuable data for earth science research. Developments in communications and other technological advances have expanded the role of the GSN in rapid earthquake analysis, tsunami warning, and nuclear test monitoring. With such long-term observations, scientists are now getting a glimpse of Earth structure changes on human time scales, such as the rotation of the inner core, as well as views into climate processes. Continued observations for the next 50 years will enhance our image of the Earth and its processes.

The new Mediterranean background monitoring station of Ersa, Cape Corsica: A long term Observatory component of the Chemistry-Aerosol Mediterranean Experiment (ChArMEx)

NASA Astrophysics Data System (ADS)

Dulac, Francois

2013-04-01

The Chemistry-Aerosol Mediterranean Experiment (ChArMEx, http://charmex.lsce.ipsl.fr/) is a French initiative supported by the MISTRALS program (Mediterranean Integrated Studies at Regional And Locals Scales, http://www.mistrals-home.org). It aims at a scientific assessment of the present and future state of the atmospheric environment in the Mediterranean Basin, and of its impacts on the regional climate, air quality, and marine biogeochemistry. The major stake is an understanding of the future of the Mediterranean region in a context of strong regional anthropogenic and climatic pressures. The target of ChArMEx is short-lived particulate and gaseous tropospheric trace species which are the cause of poor air quality events, have two-way interactions with climate, or impact the marine biogeochemistry. In order to fulfill these objectives, important efforts have been put in 2012 in order to implement the infrastructure and instrumentation for a fully equipped background monitoring station at Ersa, Cape Corsica, a key location at the crossroads of dusty southerly air masses and polluted outflows from the European continent. The observations at this station began in June 2012 (in the context of the EMEP / ACTRIS / PEGASOS / ChArMEx campaigns). A broad spectrum of aerosol properties is also measured at the station, from the chemical composition (off-line daily filter sampling in PM2.5/PM10, on-line Aerosol Chemical Speciation Monitor), ground optical properties (extinction/absorption/light scattering coeff. with 1-? CAPS PMex monitor, 7-? Aethalometer, 3-? Nephelometer), integrated and vertically resolved optical properties (4-? Cimel sunphotometer and LIDAR, respective), size distribution properties (N-AIS, SMPS, APS, and OPS instruments), mass (PM1/PM10 by TEOM/TEOM-FDMS), hygroscopicity (CCN), as well as total insoluble deposition. So far, real-time measurement of reactive gases (O3, CO, NO, NO2), and off-line VOC measurements (cylinders, cartridges) are also performed. A Kipp and Zonen system for monitoring direct and diffuse broadband radiative fluxes will also be in operation soon, as well as an ICOS/RAMCES CO2 and CH4 monitoring instrument. Through this unprecedented effort and with the support from ChArMEx, ADEME, and CORSiCA programs (http://www.obs-mip.fr/corsica), this observatory represents so far the most achieved French atmospheric station having the best set of instruments for measuring in-situ reactive gases and aerosols. It stands out as the station of not one laboratory but of a large number (see list of co-authors). It provides "real time" information useful to the local air quality network (Qualitair Corse, http://www.qualitaircorse.org/) concerning EU regulated parameters (O3, PMx). This station aims providing quality controlled climatically relevant gas/aerosol database following the recommendations of the EU-FP7 ACTRIS infrastructure, EMEP and WMO-GAW programs. Atmospheric datasets are currently available at the MISTRALS database (http://mistrals.sedoo.fr/ChArMEx/) and soon at the ACTRIS & GAW databases. After a brief presentation of the Cape Corsica Station (location, climatology, instrumental settings ...), we present here the first months of aerosols properties (optical / chemical / particle size) obtained at this station. Acknowledgements: the station is mainly supported by ADEME, CNRS-INSU, CEA, CTC, EMD, FEDER, and Météo-France.

Accuracy of tretyakov precipitation gauge: Result of wmo intercomparison

USGS Publications Warehouse

Yang, Daqing; Goodison, Barry E.; Metcalfe, John R.; Golubev, Valentin S.; Elomaa, Esko; Gunther, Thilo; Bates, Roy; Pangburn, Timothy; Hanson, Clayton L.; Emerson, Douglas G.; Copaciu, Voilete; Milkovic, Janja

1995-01-01

The Tretyakov non-recording precipitation gauge has been used historically as the official precipitation measurement instrument in the Russian (formerly the USSR) climatic and hydrological station network and in a number of other European countries. From 1986 to 1993, the accuracy and performance of this gauge were evaluated during the WMO Solid Precipitation Measurement Intercomparison at 11 stations in Canada, the USA, Russia, Germany, Finland, Romania and Croatia. The double fence intercomparison reference (DFIR) was the reference standard used at all the Intercomparison stations in the Intercomparison. The Intercomparison data collected at the different sites are compatible with respect to the catch ratio (measured/DFIR) for the same gauge, when compared using mean wind speed at the height of the gauge orifice during the observation period.The Intercomparison data for the Tretyakov gauge were compiled from measurements made at these WMO intercomparison sites. These data represent a variety of climates, terrains and exposures. The effects of environmental factors, such as wind speed, wind direction, type of precipitation and temperature, on gauge catch ratios were investigated. Wind speed was found to be the most important factor determining the gauge catch and air temperature had a secondary effect when precipitation was classified into snow, mixed and rain. The results of the analysis of gauge catch ratio versus wind speed and temperature on a daily time step are presented for various types of precipitation. Independent checks of the correction equations against the DFIR have been conducted at those Intercomparison stations and a good agreement (difference less than 10%) has been obtained. The use of such adjustment procedures should significantly improve the accuracy and homogeneity of gauge-measured precipitation data over large regions of the former USSR and central Europe.

Communicating Ocean Acidification and Climate Change to Public Audiences Using Scientific Data, Interactive Exploration Tools, and Visual Narratives

NASA Astrophysics Data System (ADS)

Miller, M. K.; Rossiter, A.; Spitzer, W.

2016-12-01

The Exploratorium, a hands-on science museum, explores local environmental conditions of San Francisco Bay to connect audiences to the larger global implications of ocean acidification and climate change. The work is centered in the Fisher Bay Observatory at Pier 15, a glass-walled gallery sited for explorations of urban San Francisco and the Bay. Interactive exhibits, high-resolution data visualizations, and mediated activities and conversations communicate to public audiences the impacts of excess carbon dioxide in the atmosphere and ocean. Through a 10-year education partnership with NOAA and two environmental literacy grants funded by its Office of Education, the Exploratorium has been part of two distinct but complementary strategies to increase climate literacy beyond traditional classroom settings. We will discuss two projects that address the ways complex scientific information can be transformed into learning opportunities for the public, providing information citizens can use for decision-making in their personal lives and their communities. The Visualizing Change project developed "visual narratives" that combine scientific visualizations and other images with story telling about the science and potential solutions of climate impacts on the ocean. The narratives were designed to engage curiosity and provide the public with hopeful and useful information to stimulate solutions-oriented behavior rather than to communicate despair about climate change. Training workshops for aquarium and museum docents prepare informal educators to use the narratives and help them frame productive conversations with the pubic. The Carbon Networks project, led by the Exploratorium, uses local and Pacific Rim data to explore the current state of climate change and ocean acidification. The Exploratorium collects and displays local ocean and atmosphere data as a member of the Central and Northern California Ocean Observing System and as an observing station for NOAA's Pacific Marine Environment Lab's carbon buoy network. Other Carbon Network partners, the Pacific Science Center and Waikiki Aquarium, also have access to local carbon data from NOAA. The project collectively explores the development of hands-on activities, teaching resources, and workshops for museum educators and classroom teachers.

Ice nucleating particles from a large-scale sampling network: insight into geographic and temporal variability

NASA Astrophysics Data System (ADS)

Schrod, Jann; Weber, Daniel; Thomson, Erik S.; Pöhlker, Christopher; Saturno, Jorge; Artaxo, Paulo; Curtius, Joachim; Bingemer, Heinz

2017-04-01

The number concentration of ice nucleating particles (INP) is an important, yet under quantified atmospheric parameter. The temporal and geographic extent of observations worldwide remains relatively small, with many regions of the world (even whole continents and oceans), almost completely unrepresented by observational data. Measurements at pristine sites are particularly rare, but all the more valuable because such observations are necessary to estimate the pre-industrial baseline of aerosol and cloud related parameters that are needed to better understand the climate system and forecast future scenarios. As a partner of BACCHUS we began in September 2014 to operate an INP measurement network of four sampling stations, with a global geographic distribution. The stations are located at unique sites reaching from the Arctic to the equator: the Amazonian Tall Tower Observatory ATTO in Brazil, the Observatoire Volcanologique et Sismologique on the island of Martinique in the Caribbean Sea, the Zeppelin Observatory at Svalbard in the Norwegian Arctic and the Taunus Observatory near Frankfurt, Germany. Since 2014 samples were collected regularly by electrostatic precipitation of aerosol particles onto silicon substrates. The INP on the substrate are activated and analyzed in the isothermal static diffusion chamber FRIDGE at temperatures between -20°C and -30°C and relative humidity with respect to ice from 115 to 135%. Here we present data from the years 2015 and 2016 from this novel INP network and from selected campaign-based measurements from remote sites, including the Mt. Kenya GAW station. Acknowledgements The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) project BACCHUS under grant agreement No 603445 and the Deutsche Forschungsgemeinschaft (DFG) under the Research Unit FOR 1525 (INUIT).

The impact of using different modern climate data sets in pollen-based paleoclimate reconstructions of North America

NASA Astrophysics Data System (ADS)

Ladd, M.; Way, R. G.; Viau, A. E.

2015-03-01

The use of different modern climate data sets is shown to impact a continental-scale pollen-based reconstruction of mean July temperature (TJUL) over the last 2000 years for North America. Data from climate stations, physically modeled from climate stations and reanalysis products are used to calibrate the reconstructions. Results show that the use of reanalysis products produces warmer and/or smoother reconstructions as compared to the use of station based data sets. The reconstructions during the period of 1050-1550 CE are shown to be more variable because of a high latitude cold-bias in the modern TJUL data. The ultra-high resolution WorldClim gridded data may only useful if the modern pollen sites have at least the same spatial precision as the gridded dataset. Hence we justify the use of the lapse-rate corrected University of East Anglia Climate Research Unit (CRU) based Whitmore modern climate data set for North American pollen-based climate reconstructions.

Problems in evaluating regional and local trends in temperature: An example from eastern Colorado, USA

USGS Publications Warehouse

Pielke, R.A.; Stohlgren, T.; Schell, L.; Parton, W.; Doesken, N.; Redmond, K.; Moeny, J.; McKee, T.; Kittel, T.G.F.

2002-01-01

We evaluated long-term trends in average maximum and minimum temperatures, threshold temperatures, and growing season in eastern Colorado, USA, to explore the potential shortcomings of many climate-change studies that either: (1) generalize regional patterns from single stations, single seasons, or a few parameters over short duration from averaging dissimilar stations: or (2) generalize an average regional pattern from coarse-scale general circulation models. Based on 11 weather stations, some trends were weakly regionally consistent with previous studies of night-time temperature warming. Long-term (80 + years) mean minimum temperatures increased significantly (P < 0.2) in about half the stations in winter, spring, and autumn and six stations had significant decreases in the number of days per year with temperatures ??? - 17.8 ??C (???0??F). However, spatial and temporal variation in the direction of change was enormous for all the other weather parameters tested, and, in the majority of tests, few stations showed significant trends (even at P < 0.2). In summer, four stations had significant increases and three stations had significant decreases in minimum temperatures, producing a strongly mixed regional signal. Trends in maximum temperature varied seasonally and geographically, as did trends in threshold temperature days ???32.2??C (???90??F) or days ???37.8??C (???100??F). There was evidence of a subregional cooling in autumn's maximum temperatures, with five stations showing significant decreasing trends. There were many geographic anomalies where neighbouring weather stations differed greatly in the magnitude of change or where they had significant and opposite trends. We conclude that sub-regional spatial and seasonal variation cannot be ignored when evaluating the direction and magnitude of climate change. It is unlikely that one or a few weather stations are representative of regional climate trends, and equally unlikely that regionally projected climate change from coarse-scale general circulation models will accurately portray trends at sub-regional scales. However, the assessment of a group of stations for consistent more qualitative trends (such as the number of days less than - 17.8??C, such as we found) provides a reasonably robust procedure to evaluate climate trends and variability. Copyright ?? 2002 Royal Meteorological Society.

The Central and Eastern U.S. Seismic Network: Legacy of USArray

NASA Astrophysics Data System (ADS)

Eakins, J. A.; Astiz, L.; Benz, H.; Busby, R. W.; Hafner, K.; Reyes, J. C.; Sharer, G.; Vernon, F.; Woodward, R.

2014-12-01

As the USArray Transportable Array entered the central and eastern United States, several Federal agencies (National Science Foundation, U.S. Geological Survey, U.S. Nuclear Regulatory Commission, and Department of Energy) recognized the unique opportunity to retain TA stations beyond the original timeline. The mission of the CEUSN is to produce data that enables researchers and Federal agencies alike to better understand the basic geologic questions, background earthquake rates and distribution, seismic hazard potential, and associated societal risks of this region. The selected long-term sub-array from Transportable Array (TA) stations includes nearly 200 sites, complemented by 100 broadband stations from the existing regional seismic networks to form the Central and Eastern United States Network (CEUSN). Multiple criteria for site selection were weighed by an inter-agency TA Station Selection (TASS) Working Group: seismic noise characteristics, data availability in real time, proximity to nuclear power plants, and homogeneous distribution throughout the region. The Array Network Facility (ANF) started collecting data for CEUSN network stations since late 2013, with all stations collected since May 2014. Regional seismic data streams are collected in real-time from the IRIS Data Management Center (DMC). TA stations selected to be part of CEUSN, retain the broadband sensor to which a 100 sps channel is added, the infrasound and environmental channels, and, at some stations, accelerometers are deployed. The upgraded sites become part of the N4 network for which ANF provides metadata and can issue remote commands to the station equipment. Stations still operated by TA, but planned for CEUSN, are included in the virtual network so all stations are currently available now. By the end of 2015, the remaining TA stations will be upgraded. Data quality control procedures developed for TA stations at ANF and at the DMC are currently performed on N4 data. However, teleseismic and regional events are only picked a few times a month to fulfill data quality checks on the data. The assembled CEUSN data sets can be requested from the DMC with the _CEUSN virtual network code. Acknowledgments to Seismic Regional Network Operators: C. Ammon, J. Ebel, D. Doser, R. Hermann, A. Holland, W-Y. Kim, C. Langston, T. Owens, and M. Withers.

NetMOD Version 2.0 Mathematical Framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Merchant, Bion J.; Young, Christopher J.; Chael, Eric P.

2015-08-01

NetMOD ( Net work M onitoring for O ptimal D etection) is a Java-based software package for conducting simulation of seismic, hydroacoustic and infrasonic networks. Network simulations have long been used to study network resilience to station outages and to determine where additional stations are needed to reduce monitoring thresholds. NetMOD makes use of geophysical models to determine the source characteristics, signal attenuation along the path between the source and station, and the performance and noise properties of the station. These geophysical models are combined to simulate the relative amplitudes of signal and noise that are observed at each ofmore » the stations. From these signal-to-noise ratios (SNR), the probabilities of signal detection at each station and event detection across the network of stations can be computed given a detection threshold. The purpose of this document is to clearly and comprehensively present the mathematical framework used by NetMOD, the software package developed by Sandia National Laboratories to assess the monitoring capability of ground-based sensor networks. Many of the NetMOD equations used for simulations are inherited from the NetSim network capability assessment package developed in the late 1980s by SAIC (Sereno et al., 1990).« less

Implementation of CGPS at Estartit, Ibiza and Barcelona harbours for sea level monitoring

NASA Astrophysics Data System (ADS)

Martinez-Benjamin, J. J.; Ortiz Castellon, M.; Martinez-Garcia, M.; Perez, B.; Bosch, E.; Termens, A.; Martinez de Oses, X.

2009-12-01

The determination of global and regional mean sea level variations with accura-cies better than 1 mm/yr is a critical problem, the resolution of which is central to the current debate on climate change and its impact on the environment. Highly accurate time series from both satellite altimetry and tide gauges are needed. Measuring the sea surface height with in-situ tide gauges and GPS receivers pro-vides an efficient way to control the long term stability of the radar altimeters and other applications as the vertical land motion and studies of sea level change. L’Estartit tide gauge is a classical floating tide gauge set up in l’Estartit harbour (NE Spain) in 1990. Data are taken in graphics registers from which each two hours the mean value is recorded in an electronic support and delivered to the Permanent Service for Mean Sea level (PSMSL). Periodic surveying campaigns along the year are carried out for monitoring possible vertical movement of the geodetic benchmark adjacent to the tide gauge. Puertos del Estado (Spanish Harbours) installed the tide gauge station at Ibiza har-bour in January 2003 and a near GPS reference station. The station belongs to the REDMAR network, composed at this moment by 21 stations distributed along the whole Spanish waters, including also the Canary islands (http://www.puertos.es). The tide gauge also belongs to the ESEAS (European Sea Level) network. A description of the actual infrastructure at Ibiza, Barcelona and l’Estartit har-bours is presented.The main objective is the implementation of these harbours as a precise geodetic areas for sea level monitoring and altimeter calibration. Actually is a CGPS with a radar tide gauge from Puertos del Estado and a GPS belonging to Puerto de Barcelona. A precise levelling has been made by the Cartographic Insti-tute of Catalonia, ICC. The instrumentation of sea level measurements has been improved by providing the Barcelona site with a radar tide gauge Datamar 3000C device and a Thales Navigation Internet-Enabled GPS Continuous Geodetic Ref-erence Station (iCGRS) with a choke ring antenna, located at the EPSEB of the Technical University of Catalonia, UPC. It is intended that the overall system will constitute a CGPS Station of the ESEAS and TIGA networks.

Long-Term Climatic Variations in the Almati Oblast in Central Asian Kazakhstan: Correlations between National Centers for Environmental Prediction (NCEP) Reanalysis II Results and Oblast Meteorological Station Data from 1949 to the Present. Volume 5

NASA Technical Reports Server (NTRS)

Welker, Jean E.; Au, Andrew Y.

2003-01-01

As part of a larger analysis of country systems described elsewhere, named a Crop Country Inventory, CCI, large variations in annual crop yield for selected climate sensitive agricultural regions or sub-regions within a country have been studied over extended periods in decades. These climate sensitive regions, principally responsible for large annual variations in an entire country s crop production, generally are characterized by distinctive patterns of atmospheric circulation and synoptic processes that result in large seasonal fluctuations in temperature, precipitation and soil moisture as well as other climate properties. The immediate region of interest is drought prone Kazakhstan in Central Asia, part of the Former Soviet Union, FSU. As a partial validation test in a dry southern region of Kazakhstan, the Almati Oblast was chosen. The Almati Oblast, a sub-region of Kazakhstan located in its southeast corner, is one of 14 oblasts within the Republic of Kazahstan. The climate data set used to characterize this region was taken from the results of the current maturely developed Global Climate Model, GCM. In this paper, the GCM results have been compared to the meteorological station data at the station locations, over various periods. If the empirical correlation of the data sets from both the GCM and station data is sufficiently significant, this would validate the use of the superior GCM profile mapping and integration for the climatic characterization of a sub-region. Precipitation values interpolated from NCEP Reanalysis II data, a global climate database spanning over 5 decades since 1949, have been statistically correlated with monthly-averaged station data from 1949 through 1993, and with daily station data from April through August, 1990 for the Almati Oblast in Kazakhstan. The resultant correlation is significant, which implies that the methodology may be extended to different regions globally for Crop Country Inventory studies.

Remote Sensing of Urban Land Cover/Land Use Change, Surface Thermal Responses, and Potential Meteorological and Climate Change Impacts

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Jedlovec, Gary; Meyer, Paul

2011-01-01

City growth influences the development of the urban heat island (UHI), but the effect that local meteorology has on the UHI is less well known. This paper presents some preliminary findings from a study that uses multitemporal Landsat TM and ASTER data to evaluate land cover/land use change (LULCC) over the NASA Marshall Space Flight Center (MFSC) and its Huntsville, AL metropolitan area. Landsat NLCD data for 1992 and 2001 have been used to evaluate LULCC for MSFC and the surrounding urban area. Land surface temperature (LST) and emissivity derived from NLCD data have also been analyzed to assess changes in these parameters in relation to LULCC. Additionally, LULCC, LST, and emissivity have been identified from ASTER data from 2001 and 2011 to provide a comparison with the 2001 NLCD and as a measure of current conditions within the study area. As anticipated, the multi-temporal NLCD and ASTER data show that significant changes have occurred in land covers, LST, and emissivity within and around MSFC. The patterns and arrangement of these changes, however, is significant because the juxtaposition of urban land covers within and outside of MSFC provides insight on what impacts at a local to regional scale, the inter-linkage of these changes potentially have on meteorology. To further analyze these interactions between LULCC, LST, and emissivity with the lower atmosphere, a network of eleven weather stations has been established across the MSFC property. These weather stations provide data at a 10 minute interval, and these data are uplinked for use by MSFC facilities operations and the National Weather Service. The weather data are also integrated within a larger network of meteorological stations across north Alabama. Given that the MSFC weather stations will operate for an extended period of time, they can be used to evaluate how the building of new structures, and changes in roadways, and green spaces as identified in the MSFC master plan for the future, will potentially affect land cover LSTs across the Center. Moreover, the weather stations will also provide baseline data for developing a better understanding of how localized weather factors, such as extreme rainfall and heat events, affect micrometeorology. These data can also be used to model the interrelationships between LSTs and meteorology on a longer term basis to help evaluate how changes in these parameters can be quantified from satellite data collected in the future. In turn, the overall integration of multi-temporal meteorological information with LULCC, and LST data for MSFC proper and the surrounding Huntsville urbanized area can provide a perspective on how urban land surface types affect the meteorology in the boundary layer and ultimately, the UHI. Additionally, data such as this can be used as a foundation for modeling how climate change will potentially impact local and regional meteorology and conversely, how urban LULCC can or will influence changes on climate over the north Alabama area.

Error analysis of integrated water vapor measured by CIMEL photometer

NASA Astrophysics Data System (ADS)

Berezin, I. A.; Timofeyev, Yu. M.; Virolainen, Ya. A.; Frantsuzova, I. S.; Volkova, K. A.; Poberovsky, A. V.; Holben, B. N.; Smirnov, A.; Slutsker, I.

2017-01-01

Water vapor plays a key role in weather and climate forming, which leads to the need for continuous monitoring of its content in different parts of the Earth. Intercomparison and validation of different methods for integrated water vapor (IWV) measurements are essential for determining the real accuracies of these methods. CIMEL photometers measure IWV at hundreds of ground-based stations of the AERONET network. We analyze simultaneous IWV measurements performed by a CIMEL photometer, an RPG-HATPRO MW radiometer, and a FTIR Bruker 125-HR spectrometer at the Peterhof station of St. Petersburg State University. We show that the CIMEL photometer calibrated by the manufacturer significantly underestimates the IWV obtained by other devices. We may conclude from this intercomparison that it is necessary to perform an additional calibration of the CIMEL photometer, as well as a possible correction of the interpretation technique for CIMEL measurements at the Peterhof site.

TexNet seismic network performance and reported seismicity in West Texas

NASA Astrophysics Data System (ADS)

Savvaidis, A.; Lomax, A.; Aiken, C.; Young, B.; Huang, D.; Hennings, P.

2017-12-01

In 2015, the Texas State Legislature began funding the Texas Seismological Network (TexNet). Since then, 22 new permanent broadband three-component seismic stations have been added to 17 existing stations operated by various networks [US, N4, IM]. These stations together with 4 auxiliary stations, i.e. long term deployments of 20 sec portable stations, were deployed to provide a baseline of Texas seismicity. As soon as the deployment of the new permanent stations took place in West Texas, TexNet was able to detect and characterize smaller magnitude events than was possible before, i.e. M < 2.5. As a consequence, additional portable stations were installed in the area in order to better map the current seismicity level. During the different stages of station deployment, we monitored the seismic network performance and its ability to detect earthquake activity. We found that a key limitation to the network performance is industrial noise in West Texas. For example, during daytime, phase picking and event detection rates are much lower than during nighttime at noisy sites. Regarding seismicity, the high density portable station deployment close to the earthquake activity minimizes hypocentral location uncertainties. In addition, we examined the effects of different crustal velocity models in the area of study on hypocentral location using the local network first arrivals. Considerable differences in location were obtained, which shows the importance of local networks and/or reliable crustal velocity models for West Texas. Given the levels of seismicity in West Texas, a plan to continuously monitor the study area is under development.

Climate Prediction for Brazil's Nordeste: Performance of Empirical and Numerical Modeling Methods.

NASA Astrophysics Data System (ADS)

Moura, Antonio Divino; Hastenrath, Stefan

2004-07-01

Comparisons of performance of climate forecast methods require consistency in the predictand and a long common reference period. For Brazil's Nordeste, empirical methods developed at the University of Wisconsin use preseason (October January) rainfall and January indices of the fields of meridional wind component and sea surface temperature (SST) in the tropical Atlantic and the equatorial Pacific as input to stepwise multiple regression and neural networking. These are used to predict the March June rainfall at a network of 27 stations. An experiment at the International Research Institute for Climate Prediction, Columbia University, with a numerical model (ECHAM4.5) used global SST information through February to predict the March June rainfall at three grid points in the Nordeste. The predictands for the empirical and numerical model forecasts are correlated at +0.96, and the period common to the independent portion of record of the empirical prediction and the numerical modeling is 1968 99. Over this period, predicted versus observed rainfall are evaluated in terms of correlation, root-mean-square error, absolute error, and bias. Performance is high for both approaches. Numerical modeling produces a correlation of +0.68, moderate errors, and strong negative bias. For the empirical methods, errors and bias are small, and correlations of +0.73 and +0.82 are reached between predicted and observed rainfall.

Quantifying the value of redundant measurements at GCOS Reference Upper-Air Network sites

DOE PAGES

Madonna, F.; Rosoldi, M.; Güldner, J.; ...

2014-11-19

The potential for measurement redundancy to reduce uncertainty in atmospheric variables has not been investigated comprehensively for climate observations. We evaluated the usefulness of entropy and mutual correlation concepts, as defined in information theory, for quantifying random uncertainty and redundancy in time series of the integrated water vapour (IWV) and water vapour mixing ratio profiles provided by five highly instrumented GRUAN (GCOS, Global Climate Observing System, Reference Upper-Air Network) stations in 2010–2012. Results show that the random uncertainties on the IWV measured with radiosondes, global positioning system, microwave and infrared radiometers, and Raman lidar measurements differed by less than 8%.more » Comparisons of time series of IWV content from ground-based remote sensing instruments with in situ soundings showed that microwave radiometers have the highest redundancy with the IWV time series measured by radiosondes and therefore the highest potential to reduce the random uncertainty of the radiosondes time series. Moreover, the random uncertainty of a time series from one instrument can be reduced by ~ 60% by constraining the measurements with those from another instrument. The best reduction of random uncertainty is achieved by conditioning Raman lidar measurements with microwave radiometer measurements. In conclusion, specific instruments are recommended for atmospheric water vapour measurements at GRUAN sites. This approach can be applied to the study of redundant measurements for other climate variables.« less

Extensive validation of CM SAF surface radiation products over Europe.

PubMed

Urraca, Ruben; Gracia-Amillo, Ana M; Koubli, Elena; Huld, Thomas; Trentmann, Jörg; Riihelä, Aku; Lindfors, Anders V; Palmer, Diane; Gottschalg, Ralph; Antonanzas-Torres, Fernando

2017-09-15

This work presents a validation of three satellite-based radiation products over an extensive network of 313 pyranometers across Europe, from 2005 to 2015. The products used have been developed by the Satellite Application Facility on Climate Monitoring (CM SAF) and are one geostationary climate dataset (SARAH-JRC), one polar-orbiting climate dataset (CLARA-A2) and one geostationary operational product. Further, the ERA-Interim reanalysis is also included in the comparison. The main objective is to determine the quality level of the daily means of CM SAF datasets, identifying their limitations, as well as analyzing the different factors that can interfere in the adequate validation of the products. The quality of the pyranometer was the most critical source of uncertainty identified. In this respect, the use of records from Second Class pyranometers and silicon-based photodiodes increased the absolute error and the bias, as well as the dispersion of both metrics, preventing an adequate validation of the daily means. The best spatial estimates for the three datasets were obtained in Central Europe with a Mean Absolute Deviation (MAD) within 8-13 W/m 2 , whereas the MAD always increased at high-latitudes, snow-covered surfaces, high mountain ranges and coastal areas. Overall, the SARAH-JRC's accuracy was demonstrated over a dense network of stations making it the most consistent dataset for climate monitoring applications. The operational dataset was comparable to SARAH-JRC in Central Europe, but lacked of the temporal stability of climate datasets, while CLARA-A2 did not achieve the same level of accuracy despite predictions obtained showed high uniformity with a small negative bias. The ERA-Interim reanalysis shows the by-far largest deviations from the surface reference measurements.

Methods for monitoring corals and crustose coralline algae to quantify in-situ calcification rates

USGS Publications Warehouse

Morrison, Jennifer M.; Kuffner, Ilsa B.; Hickey, T. Don

2013-01-01

The potential effect of global climate change on calcifying marine organisms, such as scleractinian (reef-building) corals, is becoming increasingly evident. Understanding the process of coral calcification and establishing baseline calcification rates are necessary to detect future changes in growth resulting from climate change or other stressors. Here we describe the methods used to establish a network of calcification-monitoring stations along the outer Florida Keys Reef Tract in 2009. In addition to detailing the initial setup and periodic monitoring of calcification stations, we discuss the utility and success of our design and offer suggestions for future deployments. Stations were designed such that whole coral colonies were securely attached to fixed apparati (n = 10 at each site) on the seafloor but also could be easily removed and reattached as needed for periodic weighing. Corals were weighed every 6 months, using the buoyant weight technique, to determine calcification rates in situ. Sites were visited in May and November to obtain winter and summer rates, respectively, and identify seasonal patterns in calcification. Calcification rates of the crustose coralline algal community also were measured by affixing commercially available plastic tiles, deployed vertically, at each station. Colonization by invertebrates and fleshy algae on the tiles was low, indicating relative specificity for the crustose coralline algal community. We also describe a new, nonlethal technique for sampling the corals, used following the completion of the monitoring period, in which two slabs were obtained from the center of each colony. Sampled corals were reattached to the seafloor, and most corals had completely recovered within 6 months. The station design and sampling methods described herein provide an effective approach to assessing coral and crustose coralline algal calcification rates across time and space, offering the ability to quantify the potential effects of ocean warming and acidification on calcification processes.

Geoscience Australia Continuous Global Positioning System (CGPS) Station Field Campaign Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruddick, R.; Twilley, B.

2016-03-01

This station formed part of the Australian Regional GPS Network (ARGN) and South Pacific Regional GPS Network (SPRGN), which is a network of continuous GPS stations operating within Australia and its Territories (including Antarctica) and the Pacific. These networks support a number of different science applications including maintenance of the Geospatial Reference Frame, both national and international, continental and tectonic plate motions, sea level rise, and global warming.

Relationships between thunderstorms and cloud-to-ground lightning in the United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Changnon, S.A.

Climatic assessments of cloud-to-ground (CG) flashes, and of the relationship between CG flashes and thunder events, as reported at 62 first-order stations in the contiguous US, are performed on the basis of data from networks of lightning sensors operated during 1986-1989. The adequacy of thunder-event data for describing thunderstorm occurrences at a point is determined. The average and extreme frequencies of CG lightning is delineated. Thunder events are found to provide poor estimates of CG lightning incidences and durations. CG flash data reveal that 20 percent (far west) and 50 percent (southeast US) of all thunder events are missed atmore » weather stations; 30-60 percent of all thunder events have durations too short; and 10 per cent (North and West), 40 percent (mountains), and 25 percent (southeast) of all CG flashes within 20 km of weather stations are not reported as thunderstorms. The use of historical thunder data, as a surrogate for lightning activity, is improper, and thunder values need to be adjusted with the relationships presented. 33 refs.« less

Land use/land cover change effects on temperature trends at U.S. Climate Normals stations

USGS Publications Warehouse

Hale, R.C.; Gallo, K.P.; Owen, T.W.; Loveland, Thomas R.

2006-01-01

Alterations in land use/land cover (LULC) in areas near meteorological observation stations can influence the measurement of climatological variables such as temperature. Urbanization near climate stations has been the focus of considerable research attention, however conversions between non-urban LULC classes may also have an impact. In this study, trends of minimum, maximum, and average temperature at 366 U.S. Climate Normals stations are analyzed based on changes in LULC defined by the U.S. Land Cover Trends Project. Results indicate relatively few significant temperature trends before periods of greatest LULC change, and these are generally evenly divided between warming and cooling trends. In contrast, after the period of greatest LULC change was observed, 95% of the stations that exhibited significant trends (minimum, maximum, or mean temperature) displayed warming trends. Copyriht 2006 by the American Geophysical Union.

Enhancing the Extreme Climate Index (ECI) to monitor climate extremes for an index-based insurance scheme across Africa

NASA Astrophysics Data System (ADS)

Helmschrot, J.; Malherbe, J.; Chamunorwa, M.; Muthige, M.; Petitta, M.; Calmanti, S.; Cucchi, M.; Syroka, J.; Iyahen, E.; Engelbrecht, F.

2017-12-01

Climate services are a key component of National Adaptation Plan (NAP) processes, which require the analysis of current climate conditions, future climate change scenarios and the identification of adaptation strategies, including the capacity to finance and implement effective adaptation options. The Extreme Climate Facility (XCF) proposed by the African Risk Capacity (ARC) developed a climate index insurance scheme, which is based on the Extreme Climate Index (ECI): an objective, multi-hazard index capable of tracking changes in the frequency or magnitude of extreme weather events, thus indicating possible shifts to a new climate regime in various regions. The main hazards covered by ECI are extreme dry, wet and heat events, with the possibility of adding other region-specific risk events. The ECI is standardized across broad geographical regions, so that extreme events occurring under different climatic regimes in Africa can be compared. Initially developed by an Italian company specialized in Climate Services, research is now conducted at the CSIR and SASSCAL, to verify and further develop the ECI for application in southern African countries, through a project initiated by the World Food Programme (WFP) and ARC. The paper will present findings on the most appropriate definitions of extremely wet and dry conditions in Africa, in terms of their impact across a multitude of sub-regional climates of the African continent. Findings of a verification analysis of the ECI, as determined through vegetation monitoring data and the SASSCAL weather station network will be discussed. Changes in the ECI under climate change will subsequently be projected, using detailed regional projections generated by the CSIR and through the Coordinated Regional Downscaling Experiment (CORDEX). This work will be concluded by the development of a web-based climate service informing African Stakeholders on climate extremes.

Rainfall variability and drought characteristics in two agro-climatic zones: An assessment of climate change challenges in Africa.

PubMed

Ayanlade, Ayansina; Radeny, Maren; Morton, John F; Muchaba, Tabitha

2018-07-15

This paper examines drought characteristics as an evidence of climate change in two agro-climatic zones of Nigeria and farmers' climate change perceptions of impacts and adaptation strategies. The results show high spatial and temporal rainfall variability for the stations. Consequently, there are several anomalies in rainfall in recent years but much more in the locations around the Guinea savanna. The inter-station and seasonality statistics reveal less variable and wetter early growing seasons and late growing seasons in the Rainforest zone, and more variable and drier growing seasons in other stations. The probability (p) of dry spells exceeding 3, 5 and 10 consecutive days is very high with 0.62≤p≥0.8 in all the stations, though, the p-values for 10day spells drop below 0.6 in Ibadan and Osogbo. The results further show that rainfall is much more reliable from the month of May until July with the coefficient of variance for rainy days <0.30, but less reliable in the months of March, August and October (CV-RD>0.30), though CV-RD appears higher in the month of August for all the stations. It is apparent that farmers' perceptions of drought fundamentally mirror climatic patterns from historical weather data. The study concludes that the adaptation facilities and equipment, hybrids of crops and animals are to be provided to farmers, at a subsidized price by the government, for them to cope with the current condition of climate change. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Long-term soil transplant simulating climate change with latitude significantly alters microbial temporal turnover.

PubMed

Liang, Yuting; Jiang, Yuji; Wang, Feng; Wen, Chongqing; Deng, Ye; Xue, Kai; Qin, Yujia; Yang, Yunfeng; Wu, Liyou; Zhou, Jizhong; Sun, Bo

2015-12-01

To understand soil microbial community stability and temporal turnover in response to climate change, a long-term soil transplant experiment was conducted in three agricultural experiment stations over large transects from a warm temperate zone (Fengqiu station in central China) to a subtropical zone (Yingtan station in southern China) and a cold temperate zone (Hailun station in northern China). Annual soil samples were collected from these three stations from 2005 to 2011, and microbial communities were analyzed by sequencing microbial 16S ribosomal RNA gene amplicons using Illumina MiSeq technology. Our results revealed a distinctly differential pattern of microbial communities in both northward and southward transplantations, along with an increase in microbial richness with climate cooling and a corresponding decrease with climate warming. The microbial succession rate was estimated by the slope (w value) of linear regression of a log-transformed microbial community similarity with time (time-decay relationship). Compared with the low turnover rate of microbial communities in situ (w=0.046, P<0.001), the succession rate at the community level was significantly higher in the northward transplant (w=0.058, P<0.001) and highest in the southward transplant (w=0.094, P<0.001). Climate warming lead to a faster succession rate of microbial communities as well as lower species richness and compositional changes compared with in situ and climate cooling, which may be related to the high metabolic rates and intense competition under higher temperature. This study provides new insights into the impacts of climate change on the fundamental temporal scaling of soil microbial communities and microbial phylogenetic biodiversity.

The Need and Opportunity for an Integrated Research, Development and Testing Center in the Alaskan High Arctic

NASA Astrophysics Data System (ADS)

Hardesty, J. O.; Ivey, M.; Helsel, F.; Dexheimer, D.; Lucero, D. A.; Cahill, C. F.; Roesler, E. L.

2017-12-01

This presentation will make the case for development of a permanent integrated High Arctic research and testing center at Oliktok Point, Alaska; taking advantage of existing assets and infrastructure, controlled airspace, an active UAS program and local partnerships. Arctic research stations provide critical monitoring and research on climate change for conditions and trends in the Arctic. The US Chair of the Arctic Council increased awareness of gaps in our understanding of Artic systems, scarce monitoring, lack of infrastructure and readiness for emergency response. Less sea ice brings competition for commercial shipping and resource extraction. Search and rescue, pollution mitigation and safe navigation need real-time, wide-area monitoring to respond to events. Multi-national responses for international traffic will drive a greater security presence to protect citizens and sovereign interests. To address research and technology gaps, there is a national need for a US High Arctic Center (USHARC) with an approach to partner stakeholders from science, safety and security to develop comprehensive solutions. The Station should offer year-round use, logistic support and access to varied ecological settings; phased adaptation to changing needs; and support testing of technologies such as multiple autonomous platforms, renewable energies and microgrids, and sensors in Arctic settings. We propose an Arctic Center at Oliktok Point, Alaska. Combined with the Toolik Field Station and Barrow Environmental Observatory, they form a US network of Arctic Stations. An Oliktok Point Station can provide complementary and unique assets that include: access via land, sea and air; coastal and terrestrial ecologies; controlled airspaces across land and ocean; medical and logistic support; atmospheric observations from an adjacent ARM facility; connections to Barrow and Toolik; fiber-optic communications; University of Alaska Fairbanks UAS Test Facility partnership; and an airstrip and hangar for UAS. World-class Arctic research requires year-round access and facilities. The US currently conducts most Arctic research at stations outside the US. A US High Arctic Station network enables monitoring that is specific to the US Arctic, to predict and understand impacts that affect people, communities and the planet.

Temperature-based modeling of reference evapotranspiration using several artificial intelligence models: application of different modeling scenarios

NASA Astrophysics Data System (ADS)

Sanikhani, Hadi; Kisi, Ozgur; Maroufpoor, Eisa; Yaseen, Zaher Mundher

2018-02-01

The establishment of an accurate computational model for predicting reference evapotranspiration (ET0) process is highly essential for several agricultural and hydrological applications, especially for the rural water resource systems, water use allocations, utilization and demand assessments, and the management of irrigation systems. In this research, six artificial intelligence (AI) models were investigated for modeling ET0 using a small number of climatic data generated from the minimum and maximum temperatures of the air and extraterrestrial radiation. The investigated models were multilayer perceptron (MLP), generalized regression neural networks (GRNN), radial basis neural networks (RBNN), integrated adaptive neuro-fuzzy inference systems with grid partitioning and subtractive clustering (ANFIS-GP and ANFIS-SC), and gene expression programming (GEP). The implemented monthly time scale data set was collected at the Antalya and Isparta stations which are located in the Mediterranean Region of Turkey. The Hargreaves-Samani (HS) equation and its calibrated version (CHS) were used to perform a verification analysis of the established AI models. The accuracy of validation was focused on multiple quantitative metrics, including root mean squared error (RMSE), mean absolute error (MAE), correlation coefficient (R 2), coefficient of residual mass (CRM), and Nash-Sutcliffe efficiency coefficient (NS). The results of the conducted models were highly practical and reliable for the investigated case studies. At the Antalya station, the performance of the GEP and GRNN models was better than the other investigated models, while the performance of the RBNN and ANFIS-SC models was best compared to the other models at the Isparta station. Except for the MLP model, all the other investigated models presented a better performance accuracy compared to the HS and CHS empirical models when applied in a cross-station scenario. A cross-station scenario examination implies the prediction of the ET0 of any station using the input data of the nearby station. The performance of the CHS models in the modeling the ET0 was better in all the cases when compared to that of the original HS.

On Deployment of Multiple Base Stations for Energy-Efficient Communication in Wireless Sensor Networks

DOE PAGES

Lin, Yunyue; Wu, Qishi; Cai, Xiaoshan; ...

2010-01-01

Data transmission from sensor nodes to a base station or a sink node often incurs significant energy consumption, which critically affects network lifetime. We generalize and solve the problem of deploying multiple base stations to maximize network lifetime in terms of two different metrics under one-hop and multihop communication models. In the one-hop communication model, the sensors far away from base stations always deplete their energy much faster than others. We propose an optimal solution and a heuristic approach based on the minimal enclosing circle algorithm to deploy a base station at the geometric center of each cluster. In themore » multihop communication model, both base station location and data routing mechanism need to be considered in maximizing network lifetime. We propose an iterative algorithm based on rigorous mathematical derivations and use linear programming to compute the optimal routing paths for data transmission. Simulation results show the distinguished performance of the proposed deployment algorithms in maximizing network lifetime.« less

Inter-decadal variability of phytoplankton biomass along the coastal West Antarctic Peninsula.

PubMed

Kim, Hyewon; Ducklow, Hugh W; Abele, Doris; Ruiz Barlett, Eduardo M; Buma, Anita G J; Meredith, Michael P; Rozema, Patrick D; Schofield, Oscar M; Venables, Hugh J; Schloss, Irene R

2018-06-28

The West Antarctic Peninsula (WAP) is a climatically sensitive region where periods of strong warming have caused significant changes in the marine ecosystem and food-web processes. Tight coupling between phytoplankton and higher trophic levels implies that the coastal WAP is a bottom-up controlled system, where changes in phytoplankton dynamics may largely impact other food-web components. Here, we analysed the inter-decadal time series of year-round chlorophyll- a (Chl) collected from three stations along the coastal WAP: Carlini Station at Potter Cove (PC) on King George Island, Palmer Station on Anvers Island and Rothera Station on Adelaide Island. There were trends towards increased phytoplankton biomass at Carlini Station (PC) and Palmer Station, while phytoplankton biomass declined significantly at Rothera Station over the studied period. The impacts of two relevant climate modes to the WAP, the El Niño-Southern Oscillation and the Southern Annular Mode, on winter and spring phytoplankton biomass appear to be different among the three sampling stations, suggesting an important role of local-scale forcing than large-scale forcing on phytoplankton dynamics at each station. The inter-annual variability of seasonal bloom progression derived from considering all three stations together captured ecologically meaningful, seasonally co-occurring bloom patterns which were primarily constrained by water-column stability strength. Our findings highlight a coupled link between phytoplankton and physical and climate dynamics along the coastal WAP, which may improve our understanding of overall WAP food-web responses to climate change and variability.This article is part of the theme issue 'The marine system of the West Antarctic Peninsula: status and strategy for progress in a region of rapid change'. © 2018 The Author(s).

UNAVCO-PBO Southwest Region Network Operations

NASA Astrophysics Data System (ADS)

Walls, C. P.; Mann, D.; Basset, A.; Sklar, J.; Jarvis, C.; Pitcher, T.; Lawrence, S.; Greathouse, M.; Feaux, K.

2012-12-01

The UNAVCO Southwest region of the Plate Boundary Observatory manages 470 continuously operating GPS stations located principally along the transform system of the San Andreas Fault, Eastern California Shear Zone and the northern Baja peninsula. In the past year, network uptime averaged 98% with greater than 99% data acquisition. Communications range from CDMA modem (314), radio (100), Vsat (30), DSL/T1/other (25) to manual download (1). Thirty-four stations have WXT520 metpacks. Sixty-four stations stream 1 Hz data over the VRS3Net typically with <0.5 second latency. Over 650 maintenance activities were performed during 341 onsite visits out of approximately 346 engineer field days. Within the past year there have been 7 incidences of minor (attempted theft) to moderate vandalism (solar panel stolen) with one total loss of receiver and communications gear. Security was enhanced at these sites through fencing and more secure station configurations. UNAVCO is working with NOAA to stream real-time GPS and met data from PBO stations with WXT520 meteorological sensors and high rate data communications. These streams support watershed and flood analyses for regional early-warning systems related to NOAA's work with California Department of Water Resources. Network-wide NOAA receives a total of 54 streams including stations in Cascadia. In 2008 PBO became the steward of 209 existing network stations ("Nucleus stations") of which 140 are in the SW region that included SCIGN, BARD, BARGEN stations. Due to the mix of incompatible equipment used between PBO and existing network stations a project was undertaken to standardize existing network GPS stations to PBO specifications by upgrading antenna cabling, power systems and enclosures. In 2012 the Nucleus upgrade project was completed.

Water Vapour Mixing Ratio Measurements in Potenza in the Frame of the International Network for the Detection of Atmospheric Composition Change - NDACC

NASA Astrophysics Data System (ADS)

De Rosa, Benedetto; Di Girolamo, Paolo; Summa, Donato; Stelitano, Dario; Mancini, Ignazio

2016-06-01

In November 2012 the University of BASILicata Raman Lidar system (BASIL) was approved to enter the International Network for the Detection of Atmospheric Composition Change (NDACC). This network includes more than 70 high-quality, remote-sensing research stations for observing and understanding the physical and chemical state of the upper troposphere and stratosphere and for assessing the impact of stratosphere changes on the underlying troposphere and on global climate. As part of this network, more than thirty groundbased Lidars deployed worldwide are routinely operated to monitor atmospheric ozone, temperature, aerosols, water vapour, and polar stratospheric clouds. In the frame of NDACC, BASIL performs measurements on a routine basis each Thursday, typically from local noon to midnight, covering a large portion of the daily cycle. Measurements from BASIL are included in the NDACC database both in terms of water vapour mixing ratio and temperature. This paper illustrates some measurement examples from BASIL, with a specific focus on water vapour measurements, with the goal to try and characterize the system performances.

Astroclimate, a Citizen Science Climate Awareness

NASA Astrophysics Data System (ADS)

Asorey, H.; Balaguera-Rojas, A.; Martínez-Méndez, A.; Núñez, L. A.; Peña-Rodríguez, J.; Salgado-Meza, P.; Sarmiento-Cano, C.; Suárez-Durán, M.

2017-07-01

Exploration and searching for life in other stellar systems have shown that its development and sustainability depend of very specific environment conditions. Due to that, preservation of the equilibrium of this conditions in our planet is very important, because small changes on it can generate high repercussions in its habitability. This work shows some preliminary results from an environmental monitoring network (RACIMO, Red Ambiental Ciudadana de Monitoreo) conformed by automatic meteorologic stations located on seven high-schools at metropolitan zone of Bucaramanga, Colombia. Data recorded by monitoring network are stored in an open web repository which can be accessed by citizens from any place with internet connection. These stations called UVAs, were developed under creative commons license, that is to say, software, hardware and data free, besides these can be built by students due to its flexibility. The UVAs are modular and re-programmable, that is, any sensor can be added to the stations and then re-configure its firmware remotely. Besides, UVAs work in automatic way, after the first setup, they will be self-sufficient and won't depend of human intervention. The data, of each UVA, are recorded with a temporal synchrony and then are upload at central repository by means of WiFi, ethernet or GSM connection. The stations can be power supplied by a solar system or the electrical grid. Currently, UVA record variables such as: pressure, temperature, humidity, irradiance, iluminance, ambient noise, rain, cloudiness, CO2 and NO2 concentration, lighting, seismic movements and its geographic position. On other hand, a calibration system has been developed to validate the data recorded by RACIMO. This project, started from an astroclimate an exoplanets habitability conditions, became an independent citizen science project to rise awareness about the very particular conditions enjoyed in our Earth planet.

Is U.S. climatic diversity well represented within the existing federal protection network?

PubMed

Batllori, Enric; Miller, Carol; Parisien, Marc-Andre; Parks, Sean A; Moritz, Max A

Establishing protection networks to ensure that biodiversity and associated ecosystem services persist under changing environments is a major challenge for conservation planning. The potential consequences of altered climates for the structure and function of ecosystems necessitates new and complementary approaches be incorporated into traditional conservation plans. The conterminous United States of America (CONUS) has an extensive system of protected areas managed by federal agencies, but a comprehensive assessment of how this network represents CONUS climate is lacking. We present a quantitative classification of the climate space that is independent from the geographic locations to evaluate the climatic representation of the existing protected area network. We use this classification to evaluate the coverage of each agency's jurisdiction and to identify current conservation deficits. Our findings reveal that the existing network poorly represents CONUS climatic diversity. Although rare climates are generally well represented by the network, the most common climates are particularly underrepresented. Overall, 83% of the area of the CONUS corresponds to climates underrepresented by the network. The addition of some currently unprotected federal lands to the network would enhance the coverage of CONUS climates. However, to fully palliate current conservation deficits, large-scale private-land conservation initiatives will be critical.

Targeting climate diversity in conservation planning to build resilience to climate change

USGS Publications Warehouse

Heller, Nicole E.; Kreitler, Jason R.; Ackerly, David; Weiss, Stuart; Recinos, Amanda; Branciforte, Ryan; Flint, Lorraine E.; Flint, Alan L.; Micheli, Elisabeth

2015-01-01

Climate change is raising challenging concerns for systematic conservation planning. Are methods based on the current spatial patterns of biodiversity effective given long-term climate change? Some conservation scientists argue that planning should focus on protecting the abiotic diversity in the landscape, which drives patterns of biological diversity, rather than focusing on the distribution of focal species, which shift in response to climate change. Climate is one important abiotic driver of biodiversity patterns, as different climates host different biological communities and genetic pools. We propose conservation networks that capture the full range of climatic diversity in a region will improve the resilience of biotic communities to climate change compared to networks that do not. In this study we used historical and future hydro-climate projections from the high resolution Basin Characterization Model to explore the utility of directly targeting climatic diversity in planning. Using the spatial planning tool, Marxan, we designed conservation networks to capture the diversity of climate types, at the regional and sub-regional scale, and compared them to networks we designed to capture the diversity of vegetation types. By focusing on the Conservation Lands Network (CLN) of the San Francisco Bay Area as a real-world case study, we compared the potential resilience of networks by examining two factors: the range of climate space captured, and climatic stability to 18 future climates, reflecting different emission scenarios and global climate models. We found that the climate-based network planned at the sub-regional scale captured a greater range of climate space and showed higher climatic stability than the vegetation and regional based-networks. At the same time, differences among network scenarios are small relative to the variance in climate stability across global climate models. Across different projected futures, topographically heterogeneous areas consistently show greater climate stability than homogenous areas. The analysis suggests that utilizing high-resolution climate and hydrological data in conservation planning improves the likely resilience of biodiversity to climate change. We used these analyses to suggest new conservation priorities for the San Francisco Bay Area.

Establishment of National Gravity Base Network of Iran

NASA Astrophysics Data System (ADS)

Hatam Chavari, Y.; Bayer, R.; Hinderer, J.; Ghazavi, K.; Sedighi, M.; Luck, B.; Djamour, Y.; Le Moign, N.; Saadat, R.; Cheraghi, H.

2009-04-01

A gravity base network is supposed to be a set of benchmarks uniformly distributed across the country and the absolute gravity values at the benchmarks are known to the best accessible accuracy. The gravity at the benchmark stations are either measured directly with absolute devices or transferred by gravity difference measurements by gravimeters from known stations. To decrease the accumulation of random measuring errors arising from these transfers, the number of base stations distributed across the country should be as small as possible. This is feasible if the stations are selected near to the national airports long distances apart but faster accessible and measurable by a gravimeter carried in an airplane between the stations. To realize the importance of such a network, various applications of a gravity base network are firstly reviewed. A gravity base network is the required reference frame for establishing 1st , 2nd and 3rd order gravity networks. Such a gravity network is used for the following purposes: a. Mapping of the structure of upper crust in geology maps. The required accuracy for the measured gravity values is about 0.2 to 0.4 mGal. b. Oil and mineral explorations. The required accuracy for the measured gravity values is about 5 µGal. c. Geotechnical studies in mining areas for exploring the underground cavities as well as archeological studies. The required accuracy is about 5 µGal and better. d. Subsurface water resource explorations and mapping crustal layers which absorb it. An accuracy of the same level of previous applications is required here too. e. Studying the tectonics of the Earth's crust. Repeated precise gravity measurements at the gravity network stations can assist us in identifying systematic height changes. The accuracy of the order of 5 µGal and more is required. f. Studying volcanoes and their evolution. Repeated precise gravity measurements at the gravity network stations can provide valuable information on the gradual upward movement of lava. g. Producing precise mean gravity anomaly for precise geoid determination. Replacing precise spirit leveling by the GPS leveling using precise geoid model is one of the forth coming application of the precise geoid. A gravity base network of 28 stations established over Iran. The stations were built mainly at bedrocks. All stations were measured by an FG5 absolute gravimeter, at least 12 hours at each station, to obtain an accuracy of a few micro gals. Several stations were repeated several times during recent years to estimate the gravity changes.

National Seismic Network of Georgia

NASA Astrophysics Data System (ADS)

Tumanova, N.; Kakhoberashvili, S.; Omarashvili, V.; Tserodze, M.; Akubardia, D.

2016-12-01

Georgia, as a part of the Southern Caucasus, is tectonically active and structurally complex region. It is one of the most active segments of the Alpine-Himalayan collision belt. The deformation and the associated seismicity are due to the continent-continent collision between the Arabian and Eurasian plates. Seismic Monitoring of country and the quality of seismic data is the major tool for the rapid response policy, population safety, basic scientific research and in the end for the sustainable development of the country. National Seismic Network of Georgia has been developing since the end of 19th century. Digital era of the network started from 2003. Recently continuous data streams from 25 stations acquired and analyzed in the real time. Data is combined to calculate rapid location and magnitude for the earthquake. Information for the bigger events (Ml>=3.5) is simultaneously transferred to the website of the monitoring center and to the related governmental agencies. To improve rapid earthquake location and magnitude estimation the seismic network was enhanced by installing additional 7 new stations. Each new station is equipped with coupled Broadband and Strong Motion seismometers and permanent GPS system as well. To select the sites for the 7 new base stations, we used standard network optimization techniques. To choose the optimal sites for new stations we've taken into account geometry of the existed seismic network, topographic conditions of the site. For each site we studied local geology (Vs30 was mandatory for each site), local noise level and seismic vault construction parameters. Due to the country elevation, stations were installed in the high mountains, no accessible in winter due to the heavy snow conditions. To secure online data transmission we used satellite data transmission as well as cell data network coverage from the different local companies. As a result we've already have the improved earthquake location and event magnitudes. We've analyzed data from each station to calculate signal-to-nose ratio. Comparing these calculations with the ones for the existed stations showed that signal-to-nose ratio for new stations has much better value. National Seismic Network of Georgia is planning to install more stations to improve seismic network coverage.

Informing climate change adaptation with insights from famine early warning (Invited)

NASA Astrophysics Data System (ADS)

Funk, C. C.; Verdin, J. P.

2010-12-01

Famine early warning systems provide a unique viewpoint for understanding the implications of climate change on food security, identifying the locations and seasons where millions of food insecure people are dependent upon climate-sensitive agricultural systems. The Famine Early Warning Systems Network (FEWS NET) is a decision support system sponsored by the Office of Food for Peace of the U.S. Agency for International Development (USAID), which distributes over two billion dollars of food aid to more than 40 countries each year. FEWS NET identifies the times and places where food aid is required by the most climatically sensitive and consequently food insecure populations of the developing world. As result, FEWS NET has developed its own "climate service", implemented by USGS, NOAA, and NASA, to support its decision making processes. The foundation of this climate service is the monitoring of current growing conditions for early identification of agricultural drought that might impact food security. Since station networks are sparse in the countries monitored, FEWS NET has a tradition (dating back to 1985) of reliance on satellite remote sensing of vegetation and rainfall. In the last ten years, climate forecasts have become an additional tool for food security assessment, extending the early warning perspective to include expected agricultural outcomes for the season ahead. More recently, research has expanded to include detailed analyses of recent observed climate trends, combined with diagnostic ocean-atmosphere studies. These studies are then used to develop interpretations of GCM scenarios and their implications for future patterns of precipitation and temperature, revealing trends towards warmer/drier climate conditions and increases in the relative frequency of drought. In some regions, like Eastern Africa, such changes seem to be already occurring, with an associated increase in food insecurity. Sub-national analyses for Kenya, for example, point to the need for adaptation through improved agricultural practices, so that increased yields can offset the impacts of rising temperatures and declining rainfall. Future work will focus on assessing temperature-PET linkages, and evaluating pathways for agricultural development.

Assessing the implementation of bias correction in the climate prediction

NASA Astrophysics Data System (ADS)

Nadrah Aqilah Tukimat, Nurul

2018-04-01

An issue of the climate changes nowadays becomes trigger and irregular. The increment of the greenhouse gases (GHGs) emission into the atmospheric system day by day gives huge impact to the fluctuated weather and global warming. It becomes significant to analyse the changes of climate parameters in the long term. However, the accuracy in the climate simulation is always be questioned to control the reliability of the projection results. Thus, the Linear Scaling (LS) as a bias correction method (BC) had been applied to treat the gaps between observed and simulated results. About two rainfall stations were selected in Pahang state there are Station Lubuk Paku and Station Temerloh. Statistical Downscaling Model (SDSM) used to perform the relationship between local weather and atmospheric parameters in projecting the long term rainfall trend. The result revealed the LS was successfully to reduce the error up to 3% and produced better climate simulated results.

Linked hydrologic and climate variations in British Columbia and Yukon.

PubMed

Whitfield, P H

2001-01-01

Climatic and hydrologic variations between the decades 1976-1985 and 1986-1995 are examined at 34 climate stations and 275 hydrology stations. The variations in climate are distributed across a broad spatial area. Temperatures were generally warmer in the most recent decade, with many stations showing significant increases during the spring and fall. No significant decreases in temperature were found. Significant increases in temperature were more frequent in the south than in the northern portions of the region. Significant changes in precipitation were also more prevalent in the south. In coastal areas, there were significant decreases in precipitation during the dry season, and significant increases during the wet season. In the BC interior, significant precipitation decreases occurred during the fall, with significant increases during the winter and spring. In the north there were few changes in precipitation. The hydrologic responses to these variations in climate follow six distinctive patterns. The spatial distribution of these patterns suggests that in different ecozones, small variations in climate, particularly temperature, elicit different hydrologic responses.

Latest developments in advanced network management and cross-sharing of next-generation flux stations

NASA Astrophysics Data System (ADS)

Burba, George; Johnson, Dave; Velgersdyk, Michael; Begashaw, Israel; Allyn, Douglas

2016-04-01

In recent years, spatial and temporal flux data coverage improved significantly and on multiple scales, from a single station to continental networks, due to standardization, automation, and management of the data collection, and better handling of the extensive amounts of generated data. However, operating budgets for flux research items, such as labor, travel, and hardware, are becoming more difficult to acquire and sustain. With more stations and networks, larger data flows from each station, and smaller operating budgets, modern tools are required to effectively and efficiently handle the entire process, including sharing data among collaborative groups. On one hand, such tools can maximize time dedicated to publications answering research questions, and minimize time and expenses spent on data acquisition, processing, quality control and overall station management. On the other hand, cross-sharing the stations with external collaborators may help leverage available funding, and promote data analyses and publications. A new low-cost, advanced system, FluxSuite, utilizes a combination of hardware, software and web-services to address these specific demands. It automates key stages of flux workflow, minimizes day-to-day site management, and modernizes the handling of data flows: (i) The system can be easily incorporated into a new flux station, or as un upgrade to many presently operating flux stations, via weatherized remotely-accessible microcomputer, SmartFlux 2, with fully digital inputs (ii) Each next-generation station will measure all parameters needed for flux computations in a digital and PTP time-synchronized mode, accepting digital signals from a number of anemometers and data loggers (iii) The field microcomputer will calculate final fully-processed flux rates in real time, including computation-intensive Fourier transforms, spectra, co-spectra, multiple rotations, stationarity, footprint, etc. (iv) Final fluxes, radiation, weather and soil data will be merged into a single quality-control file (v) Multiple flux stations can be linked into an automated time-synchronized network (vi) Flux network managers, or PI's, can see all stations in real-time, including fluxes, supporting data, automated reports, and email alerts (vii) PI's can assign rights, allow or restrict access to stations and data: selected stations can be shared via rights-managed access internally or with external institutions (viii) Researchers without stations could form "virtual networks" for specific projects by collaborating with PIs from different actual networks This presentation provides detailed examples of FluxSuite currently utilized to manage two large flux networks in China (National Academy of Sciences and Agricultural Academy of Sciences), and smaller networks with stations in the USA, Germany, Ireland, Malaysia and other locations around the globe. Very latest 2016 developments and expanded functionality are also discussed.

INEGI's Network of GPS permanent stations in Mexico

NASA Astrophysics Data System (ADS)

Gonzalez Franco, G. A.

2013-05-01

The Active National Geodetic Network administered by INEGI (Instituto Nacional de Estadística y Geografía) is a set of 24 GPS permanent stations in Mexico that was established in 1993 for a national rural cadastral project, its has been mainly used for geodetic surveys through Mexico including international borders, and has been progressing to contribute to national, regional and international reference frames through the delivering of GPS data or coordinate solutions from INEGI Processing Center to SIRGAS and NAREF. Recently GAMIT/GLOBK Processing of permanent stations in Mexico was realized from 2007-2011 to determine station's velocity. Related to natural hazards, a subset of INEGI network contributes to the project Real Time Integrated Atmosferic Water Wapor and TEC from GPS. The GPS network planned evolution consider changing to a GNSS network, adding stations to IGS, maintain the services of the present, and contribute to multidisciplinary geodetic studies through data publicly available.

Reanalysis Data Evaluation to Study Temperature Extremes in Siberia

NASA Astrophysics Data System (ADS)

Shulgina, T. M.; Gordov, E. P.

2014-12-01

Ongoing global climate changes are strongly pronounced in Siberia by significant warming in the 2nd half of 20th century and recent extreme events such as 2010 heat wave and 2013 flood in Russia's Far East. To improve our understanding of observed climate extremes and to provide to regional decision makers the reliable scientifically based information with high special and temporal resolution on climate state, we need to operate with accurate meteorological data in our study. However, from available 231 stations across Siberia only 130 of them present the homogeneous daily temperature time series. Sparse, station network, especially in high latitudes, force us to use simulated reanalysis data. However those might differ from observations. To obtain reliable information on temperature extreme "hot spots" in Siberia we have compared daily temperatures form ERA-40, ERA Interim, JRA-25, JRA-55, NCEP/DOE, MERRA Reanalysis, HadEX2 and GHCNDEX gridded datasets with observations from RIHMI-WDC/CDIAC dataset for overlap period 1981-2000. Data agreement was estimated at station coordinates to which reanalysis data were interpolated using modified Shepard method. Comparison of averaged over 20 year annual mean temperatures shows general agreement for Siberia excepting Baikal region, where reanalyses significantly underestimate observed temperature behavior. The annual temperatures closest to observed one were obtained from ERA-40 and ERA Interim. Furthermore, t-test results show homogeneity of these datasets, which allows one to combine them for long term time series analysis. In particular, we compared the combined data with observations for percentile-based extreme indices. In Western Siberia reanalysis and gridded data accurately reproduce observed daily max/min temperatures. For East Siberia, Lake Baikal area, ERA Interim data slightly underestimates TN90p and TX90p values. Results obtained allows regional decision-makers to get required high spatial resolution (0,25°×0,25°) climatic information products from the combined ERA data. The authors acknowledge partial financial support for this research from the RFBR (13-05-12034, 14-05-00502), SB RAS Integration projects (131, VIII.80.2.1.) and grant of the President of RF (№ 181).

Analysis of long term trends of precipitation estimates acquired using radar network in Turkey

NASA Astrophysics Data System (ADS)

Tugrul Yilmaz, M.; Yucel, Ismail; Kamil Yilmaz, Koray

2016-04-01

Precipitation estimates, a vital input in many hydrological and agricultural studies, can be obtained using many different platforms (ground station-, radar-, model-, satellite-based). Satellite- and model-based estimates are spatially continuous datasets, however they lack the high resolution information many applications often require. Station-based values are actual precipitation observations, however they suffer from their nature that they are point data. These datasets may be interpolated however such end-products may have large errors over remote locations with different climate/topography/etc than the areas stations are installed. Radars have the particular advantage of having high spatial resolution information over land even though accuracy of radar-based precipitation estimates depends on the Z-R relationship, mountain blockage, target distance from the radar, spurious echoes resulting from anomalous propagation of the radar beam, bright band contamination and ground clutter. A viable method to obtain spatially and temporally high resolution consistent precipitation information is merging radar and station data to take advantage of each retrieval platform. An optimally merged product is particularly important in Turkey where complex topography exerts strong controls on the precipitation regime and in turn hampers observation efforts. There are currently 10 (additional 7 are planned) weather radars over Turkey obtaining precipitation information since 2007. This study aims to optimally merge radar precipitation data with station based observations to introduce a station-radar blended precipitation product. This study was supported by TUBITAK fund # 114Y676.

Evaluation of gridding procedures for air temperature over Southern Africa

NASA Astrophysics Data System (ADS)

Eiselt, Kai-Uwe; Kaspar, Frank; Mölg, Thomas; Krähenmann, Stefan; Posada, Rafael; Riede, Jens O.

2017-06-01

Africa is considered to be highly vulnerable to climate change, yet the availability of observational data and derived products is limited. As one element of the SASSCAL initiative (Southern African Science Service Centre for Climate Change and Adaptive Land Management), a cooperation of Angola, Botswana, Namibia, Zambia, South Africa and Germany, networks of automatic weather stations have been installed or improved (http://www.sasscalweathernet.org). The increased availability of meteorological observations improves the quality of gridded products for the region. Here we compare interpolation methods for monthly minimum and maximum temperatures which were calculated from hourly measurements. Due to a lack of longterm records we focused on data ranging from September 2014 to August 2016. The best interpolation results have been achieved combining multiple linear regression (elevation, a continentality index and latitude as predictors) with three dimensional inverse distance weighted interpolation.

Status report on the establishment of the CTBTO IMS infrasound network

NASA Astrophysics Data System (ADS)

Hoffmann, Thomas L.

2005-04-01

Steady progress has been made in the establishment of the CTBTO IMS infrasound monitoring network. To date 86% of the site surveys for 60 infrasound stations in the network have been completed, 50% of the stations are transmitting continuous data to Vienna, and 40% of the stations have been certified. While the global distribution pattern of infrasound stations transmitting data to Vienna is still disperse, regional networks begin to form in North and South America as well as in the Australian and South African regions. This presentation will focus on an overview of recent progress made in the establishment of the global infrasound network, and also present some of the challenges and difficulties encountered in this program.

Quality of surface water in Missouri, water year 2012

USGS Publications Warehouse

Barr, Miya N.

2014-01-01

The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, designed and operates a series of monitoring stations on streams and springs throughout Missouri known as the Ambient Water-Quality Monitoring Network. During the 2012 water year (October 1, 2011, through September 30, 2012), data were collected at 81 stations—73 Ambient Water-Quality Monitoring Network stations, 6 alternate Ambient Water-Quality Monitoring Network stations, and 2 U.S. Geological Survey National Stream Quality Accounting Network stations. Dissolved oxygen, specific conductance, water temperature, suspended solids, suspended sediment, fecal coliform bacteria, Escherichia coli bacteria, dissolved nitrate plus nitrite as nitrogen, total phosphorus, dissolved and total recoverable lead and zinc, and select pesticide compound summaries are presented for 78 of these stations. The stations primarily have been classified into groups corresponding to the physiography of the State, primary land use, or unique station types. In addition, a summary of hydrologic conditions in the State including peak discharges, monthly mean discharges, and 7-day low flow is presented.

Quality of surface water in Missouri, water year 2013

USGS Publications Warehouse

Barr, Miya N.; Schneider, Rachel E.

2014-01-01

The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, designed and operates a series of monitoring stations on streams and springs throughout Missouri known as the Ambient Water-Quality Monitoring Network. During the 2013 water year (October 1, 2012, through September 30, 2013), data were collected at 79 stations—73 Ambient Water-Quality Monitoring Network stations, 4 alternate Ambient Water-Quality Monitoring Network stations, and 2 U.S. Geological Survey National Stream Quality Accounting Network stations. Dissolved oxygen, specific conductance, water temperature, suspended solids, suspended sediment, Escherichia coli bacteria, fecal coliform bacteria, dissolved nitrate plus nitrite as nitrogen, total phosphorus, dissolved and total recoverable lead and zinc, and select pesticide compound summaries are presented for 76 of these stations. The stations primarily have been classified into groups corresponding to the physiography of the State, primary land use, or unique station types. In addition, a summary of hydrologic conditions in the State including peak discharges, monthly mean discharges, and 7-day low flow is presented.

Cross-Layer Scheme to Control Contention Window for Per-Flow in Asymmetric Multi-Hop Networks

NASA Astrophysics Data System (ADS)

Giang, Pham Thanh; Nakagawa, Kenji

The IEEE 802.11 MAC standard for wireless ad hoc networks adopts Binary Exponential Back-off (BEB) mechanism to resolve bandwidth contention between stations. BEB mechanism controls the bandwidth allocation for each station by choosing a back-off value from one to CW according to the uniform random distribution, where CW is the contention window size. However, in asymmetric multi-hop networks, some stations are disadvantaged in opportunity of access to the shared channel and may suffer severe throughput degradation when the traffic load is large. Then, the network performance is degraded in terms of throughput and fairness. In this paper, we propose a new cross-layer scheme aiming to solve the per-flow unfairness problem and achieve good throughput performance in IEEE 802.11 multi-hop ad hoc networks. Our cross-layer scheme collects useful information from the physical, MAC and link layers of own station. This information is used to determine the optimal Contention Window (CW) size for per-station fairness. We also use this information to adjust CW size for each flow in the station in order to achieve per-flow fairness. Performance of our cross-layer scheme is examined on various asymmetric multi-hop network topologies by using Network Simulator (NS-2).

Post-installation activities in the Comprehensive Nuclear Test Ban Treaty (CTBT) International Monitoring System (IMS) infrasound network

NASA Astrophysics Data System (ADS)

Vivas Veloso, J. A.; Christie, D. R.; Hoffmann, T. L.; Campus, P.; Bell, M.; Langlois, A.; Martysevich, P.; Demirovik, E.; Carvalho, J.; Kramer, A.; Wu, Sean F.

2002-11-01

The provisional operation and maintenance of IMS infrasound stations after installation and subsequent certification has the objective to prepare the infrasound network for entry into force of the Comprehensive Nuclear-Test-Ban Treaty (CTBT). The goal is to maintain and fine tune the technical capabilities of the network, to repair faulty equipment, and to ensure that stations continue to meet the minimum specifications through evaluation of data quality and station recalibration. Due to the globally dispersed nature of the network, this program constitutes a significant undertaking that requires careful consideration of possible logistic approaches and their financial implications. Currently, 11 of the 60 IMS infrasound stations are transmitting data in the post-installation Testing & Evaluation mode. Another 5 stations are under provisional operation and are maintained in post-certification mode. It is expected that 20% of the infrasound network will be certified by the end of 2002. This presentation will focus on the different phases of post-installation activities of the IMS infrasound program and the logistical challenges to be tackled to ensure a cost-efficient management of the network. Specific topics will include Testing & Evaluation and Certification of Infrasound Stations, as well as Configuration Management and Network Sustainment.

A multi-scale automatic observatory of soil moisture and temperature served for satellite product validation in Tibetan Plateau

NASA Astrophysics Data System (ADS)

Tang, S.; Dong, L.; Lu, P.; Zhou, K.; Wang, F.; Han, S.; Min, M.; Chen, L.; Xu, N.; Chen, J.; Zhao, P.; Li, B.; Wang, Y.

2016-12-01

Due to the lack of observing data which match the satellite pixel size, the inversion accuracy of satellite products in Tibetan Plateau(TP) is difficult to be evaluated. Hence, the in situ observations are necessary to support the calibration and validation activities. Under the support of the Third Tibetan Plateau Atmospheric Scientific Experiment (TIPEX-III) projec a multi-scale automatic observatory of soil moisture and temperature served for satellite product validation (TIPEX-III-SMTN) were established in Tibetan Plateau. The observatory consists of two regional scale networks, including the Naqu network and the Geji network. The Naqu network is located in the north of TP, and characterized by alpine grasslands. The Geji network is located in the west of TP, and characterized by marshes. Naqu network includes 33 stations, which are deployed in a 75KM*75KM region according to a pre-designed pattern. At Each station, soil moisture and temperature are measured by five sensors at five soil depths. One sensor is vertically inserted into 0 2 cm depth to measure the averaged near-surface soil moisture and temperature. The other four sensors are horizontally inserted at 5, 10, 20, and 30 cm depths, respectively. The data are recorded every 10 minutes. A wireless transmission system is applied to transmit the data in real time, and a dual power supply system is adopted to keep the continuity of the observation. The construction of Naqu network has been accomplished in August, 2015, and Geji network will be established before Oct., 2016. Observations acquired from TIPEX-III-SMTN can be used to validate satellite products with different spatial resolution, and TIPEX-III-SMTN can also be used as a complementary of the existing similar networks in this area, such as CTP-SMTMN (the multiscale Soil Moistureand Temperature Monitoring Network on the central TP) . Keywords: multi-scale soil moisture soil temperature, Tibetan Plateau Acknowledgments: This work was jointly supported by CMA Special Fund for Scientific Research in the Public Interest (Grant No. GYHY201406001, GYHY201206008-01), and Climate change special fund (QHBH2014)'

Fixed point theorems of GPS carrier phase ambiguity resolution and their application to massive network processing: Ambizap

NASA Astrophysics Data System (ADS)

Blewitt, Geoffrey

2008-12-01

Precise point positioning (PPP) has become popular for Global Positioning System (GPS) geodetic network analysis because for n stations, PPP has O(n) processing time, yet solutions closely approximate those of O(n3) full network analysis. Subsequent carrier phase ambiguity resolution (AR) further improves PPP precision and accuracy; however, full-network bootstrapping AR algorithms are O(n4), limiting single network solutions to n < 100. In this contribution, fixed point theorems of AR are derived and then used to develop "Ambizap," an O(n) algorithm designed to give results that closely approximate full network AR. Ambizap has been tested to n ≈ 2800 and proves to be O(n) in this range, adding only ˜50% to PPP processing time. Tests show that a 98-station network is resolved on a 3-GHz CPU in 7 min, versus 22 h using O(n4) AR methods. Ambizap features a novel network adjustment filter, producing solutions that precisely match O(n4) full network analysis. The resulting coordinates agree to ≪1 mm with current AR methods, much smaller than the ˜3-mm RMS precision of PPP alone. A 2000-station global network can be ambiguity resolved in ˜2.5 h. Together with PPP, Ambizap enables rapid, multiple reanalysis of large networks (e.g., ˜1000-station EarthScope Plate Boundary Observatory) and facilitates the addition of extra stations to an existing network solution without need to reprocess all data. To meet future needs, PPP plus Ambizap is designed to handle ˜10,000 stations per day on a 3-GHz dual-CPU desktop PC.

Modeling The Hydrology And Water Allocation Under Climate Change In Rural River Basins: A Case Study From Nam Ngum River Basin, Laos

NASA Astrophysics Data System (ADS)

Jayasekera, D. L.; Kaluarachchi, J.; Kim, U.

2011-12-01

Rural river basins with sufficient water availability to maintain economic livelihoods can be affected with seasonal fluctuations of precipitation and sometimes by droughts. In addition, climate change impacts can also alter future water availability. General Circulation Models (GCMs) provide credible quantitative estimates of future climate conditions but such estimates are often characterized by bias and coarse scale resolution making it necessary to downscale the outputs for use in regional hydrologic models. This study develops a methodology to downscale and project future monthly precipitation in moderate scale basins where data are limited. A stochastic framework for single-site and multi-site generation of weekly rainfall is developed while preserving the historical temporal and spatial correlation structures. The spatial correlations in the simulated occurrences and the amounts are induced using spatially correlated yet serially independent random numbers. This method is applied to generate weekly precipitation data for a 100-year period in the Nam Ngum River Basin (NNRB) that has a land area of 16,780 km2 located in Lao P.D.R. This method is developed and applied using precipitation data from 1961 to 2000 for 10 selected weather stations that represents the basin rainfall characteristics. Bias-correction method, based on fitted theoretical probability distribution transformations, is applied to improve monthly mean frequency, intensity and the amount of raw GCM precipitation predicted at a given weather station using CGCM3.1 and ECHAM5 for SRES A2 emission scenario. Bias-correction procedure adjusts GCM precipitation to approximate the long-term frequency and the intensity distribution observed at a given weather station. Index of agreement and mean absolute error are determined to assess the overall ability and performance of the bias correction method. The generated precipitation series aggregated at monthly time step was perturbed by the change factors estimated using the corrected GCM and baseline scenarios for future time periods of 2011-2050 and 2051-2090. A network based hydrologic and water resources model, WEAP, was used to simulate the current water allocation and management practices to identify the impacts of climate change in the 20th century. The results of this work are used to identify the multiple challenges faced by stakeholders and planners in water allocation for competing demands in the presence of climate change impacts.

A comparison of observed extreme water levels at the German Bight elaborated through an extreme value analysis (EVA) with extremes derived from a regionally coupled ocean-atmospheric climate model (MPI-OM)

NASA Astrophysics Data System (ADS)

Möller, Jens; Heinrich, Hartmut

2017-04-01

As a consequence of climate change atmospheric and oceanographic extremes and their potential impacts on coastal regions are of growing concern for governmental authorities responsible for the transportation infrastructure. Highest risks for shipping as well as for rail and road traffic originate from combined effects of extremes of storm surges and heavy rainfall which sometimes lead to insufficient dewatering of inland waterways. The German Ministry of Transport and digital Infrastructure therefore has tasked its Network of Experts to investigate the possible evolutions of extreme threats for low lands and especially for Kiel Canal, which is an important shortcut for shipping between the North and Baltic Seas. In this study we present results of a comparison of an Extreme Value Analysis (EVA) carried out on gauge observations and values derived from a coupled Regional Ocean-Atmosphere Climate Model (MPI-OM). High water levels at the coasts of the North and Baltic Seas are one of the most important hazards which increase the risk of flooding of the low-lying land and prevents such areas from an adequate dewatering. In this study changes in the intensity (magnitude of the extremes) and duration of extreme water levels (above a selected threshold) are investigated for several gauge stations with data partly reaching back to 1843. Different methods are used for the extreme value statistics, (1) a stationary general Pareto distribution (GPD) model as well as (2) an instationary statistical model for better reproduction of the impact of climate change. Most gauge stations show an increase of the mean water level of about 1-2 mm/year, with a stronger increase of the highest water levels and a decrease (or lower increase) of the lowest water levels. Also, the duration of possible dewatering time intervals for the Kiel-Canal was analysed. The results for the historical gauge station observations are compared to the statistics of modelled water levels from the coupled atmosphere-ocean climate model MPI-OM for the time interval from 1951 to 2000. We demonstrate that for high water levels the observations and MPI-OM results are in good agreement, and we provide an estimate on the decreasing dewatering potential for Kiel Canal until the end of the 21st century.

Estimating unbiased magnitudes for the announced DPRK nuclear tests, 2006-2016

NASA Astrophysics Data System (ADS)

Peacock, Sheila; Bowers, David

2017-04-01

The seismic disturbances generated from the five (2006-2016) announced nuclear test explosions by the Democratic People's Republic of Korea (DPRK) are of moderate magnitude (body-wave magnitude mb 4-5) by global earthquake standards. An upward bias of network mean mb of low- to moderate-magnitude events is long established, and is caused by the censoring of readings from stations where the signal was below noise level at the time of the predicted arrival. This sampling bias can be overcome by maximum-likelihood methods using station thresholds at detecting (and non-detecting) stations. Bias in the mean mb can also be introduced by differences in the network of stations recording each explosion - this bias can reduced by using station corrections. We apply a maximum-likelihood (JML) inversion that jointly estimates station corrections and unbiased network mb for the five DPRK explosions recorded by the CTBTO International Monitoring Network (IMS) of seismic stations. The thresholds can either be directly measured from the noise preceding the observed signal, or determined by statistical analysis of bulletin amplitudes. The network mb of the first and smallest explosion is reduced significantly relative to the mean mb (to < 4.0 mb) by removal of the censoring bias.

Changes in the relation between snow station observations and basin scale snow water resources

NASA Astrophysics Data System (ADS)

Sexstone, G. A.; Penn, C. A.; Clow, D. W.; Moeser, D.; Liston, G. E.

2017-12-01

Snow monitoring stations that measure snow water equivalent or snow depth provide fundamental observations used for predicting water availability and flood risk in mountainous regions. In the western United States, snow station observations provided by the Natural Resources Conservation Service Snow Telemetry (SNOTEL) network are relied upon for forecasting spring and summer streamflow volume. Streamflow forecast accuracy has declined for many regions over the last several decades. Changes in snow accumulation and melt related to climate, land use, and forest cover are not accounted for in current forecasts, and are likely sources of error. Therefore, understanding and updating relations between snow station observations and basin scale snow water resources is crucial to improve accuracy of streamflow prediction. In this study, we investigated the representativeness of snow station observations when compared to simulated basin-wide snow water resources within the Rio Grande headwaters of Colorado. We used the combination of a process-based snow model (SnowModel), field-based measurements, and remote sensing observations to compare the spatiotemporal variability of simulated basin-wide snow accumulation and melt with that of SNOTEL station observations. Results indicated that observations are comparable to simulated basin-average winter precipitation but overestimate both the simulated basin-average snow water equivalent and snowmelt rate. Changes in the representation of snow station observations over time in the Rio Grande headwaters were also investigated and compared to observed streamflow and streamflow forecasting errors. Results from this study provide important insight in the context of non-stationarity for future water availability assessments and streamflow predictions.

Review: visual analytics of climate networks

NASA Astrophysics Data System (ADS)

Nocke, T.; Buschmann, S.; Donges, J. F.; Marwan, N.; Schulz, H.-J.; Tominski, C.

2015-09-01

Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing numbers of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis relating the multiple visualisation challenges to a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.

Review: visual analytics of climate networks

NASA Astrophysics Data System (ADS)

Nocke, T.; Buschmann, S.; Donges, J. F.; Marwan, N.; Schulz, H.-J.; Tominski, C.

2015-04-01

Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing amounts of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis, relating the multiple visualisation challenges with a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.

Long-term soil transplant simulating climate change with latitude significantly alters microbial temporal turnover

PubMed Central

Liang, Yuting; Jiang, Yuji; Wang, Feng; Wen, Chongqing; Deng, Ye; Xue, Kai; Qin, Yujia; Yang, Yunfeng; Wu, Liyou; Zhou, Jizhong; Sun, Bo

2015-01-01

To understand soil microbial community stability and temporal turnover in response to climate change, a long-term soil transplant experiment was conducted in three agricultural experiment stations over large transects from a warm temperate zone (Fengqiu station in central China) to a subtropical zone (Yingtan station in southern China) and a cold temperate zone (Hailun station in northern China). Annual soil samples were collected from these three stations from 2005 to 2011, and microbial communities were analyzed by sequencing microbial 16S ribosomal RNA gene amplicons using Illumina MiSeq technology. Our results revealed a distinctly differential pattern of microbial communities in both northward and southward transplantations, along with an increase in microbial richness with climate cooling and a corresponding decrease with climate warming. The microbial succession rate was estimated by the slope (w value) of linear regression of a log-transformed microbial community similarity with time (time–decay relationship). Compared with the low turnover rate of microbial communities in situ (w=0.046, P<0.001), the succession rate at the community level was significantly higher in the northward transplant (w=0.058, P<0.001) and highest in the southward transplant (w=0.094, P<0.001). Climate warming lead to a faster succession rate of microbial communities as well as lower species richness and compositional changes compared with in situ and climate cooling, which may be related to the high metabolic rates and intense competition under higher temperature. This study provides new insights into the impacts of climate change on the fundamental temporal scaling of soil microbial communities and microbial phylogenetic biodiversity. PMID:25989371

GNSS Network Time Series Analysis

NASA Astrophysics Data System (ADS)

Balodis, J.; Janpaule, I.; Haritonova, D.; Normand, M.; Silabriedis, G.; Zarinjsh, A.; Zvirgzds, J.

2012-04-01

Time series of GNSS station results of both the EUPOS®-RIGA and LATPOS networks has been developed at the Institute of Geodesy and Geoinformation (University of Latvia) using Bernese v.5.0 software. The base stations were selected among the EPN and IGS stations in surroundings of Latvia. In various day solutions the base station selection has been miscellaneous. Most frequently 5 - 8 base stations were selected from a set of stations {BOR1, JOEN, JOZE, MDVJ, METS, POLV, PULK, RIGA, TORA, VAAS, VISO, VLNS}. The rejection of "bad base stations" was performed by Bernese software depending on the quality of proper station data in proper day. This caused a reason of miscellaneous base station selection in various days. The results of time series are analysed. The question aroused on the nature of some outlying situations. The seasonal effect of the behaviour of the network has been identified when distance and elevation changes between stations has been analysed. The dependence from various influences has been recognised.

PBO Southwest Region: Baja Earthquake Response and Network Operations

NASA Astrophysics Data System (ADS)

Walls, C. P.; Basset, A.; Mann, D.; Lawrence, S.; Jarvis, C.; Feaux, K.; Jackson, M. E.

2011-12-01

The SW region of the Plate Boundary Observatory consists of 455 continuously operating GPS stations located principally along the transform system of the San Andreas fault and Eastern California Shear Zone. In the past year network uptime exceeded an average of 97% with greater than 99% data acquisition. Communications range from CDMA modem (307), radio (92), Vsat (30), DSL/T1/other (25) to manual downloads (1). Sixty-three stations stream 1 Hz data over the VRS3Net typically with <0.5 second latency. Over 620 maintenance activities were performed during 316 onsite visits out of approximately 368 engineer field days. Within the past year there have been 7 incidences of minor (attempted theft) to moderate vandalism (solar panel stolen) with one total loss of receiver and communications gear. Security was enhanced at these sites through fencing and more secure station configurations. In the past 12 months, 4 new stations were installed to replace removed stations or to augment the network at strategic locations. Following the M7.2 El Mayor-Cucapah earthquake CGPS station P796, a deep-drilled braced monument, was constructed in San Luis, AZ along the border within 5 weeks of the event. In addition, UNAVCO participated in a successful University of Arizona-led RAPID proposal for the installation of six continuous GPS stations for post-seismic observations. Six stations are installed and telemetered through a UNAM relay at the Sierra San Pedro Martir. Four of these stations have Vaisala WXT520 meteorological sensors. An additional site in the Sierra Cucapah (PTAX) that was built by CICESE, an Associate UNAVCO Member institution in Mexico, and Caltech has been integrated into PBO dataflow. The stations will be maintained as part of the PBO network in coordination with CICESE. UNAVCO is working with NOAA to upgrade PBO stations with WXT520 meteorological sensors and communications systems capable of streaming real-time GPS and met data. The real-time GPS and meteorological sensor data streaming support watershed and flood analyses for regional early-warning systems related to NOAA's work with California Department of Water Resources. Currently 19 stations are online and streaming with 7 more in preparation. In 2008 PBO became the steward of 209 existing network stations of which 140 are in the SW region that included SCIGN, BARD, BARGEN stations. Due to the mix of incompatible equipment used between PBO and existing network stations a project was undertaken to standardize existing network GPS stations to PBO specifications by upgrading power systems and enclosures. To date 96 stations have been upgraded. UNAVCO is currently funded through a USGS ARRA grant to construct 8 new GPS stations in the San Francisco Bay Area capable of streaming high rate data. At present 6 stations are built with 2 permits outstanding.

Daily precipitation grids for Austria since 1961—development and evaluation of a spatial dataset for hydroclimatic monitoring and modelling

NASA Astrophysics Data System (ADS)

Hiebl, Johann; Frei, Christoph

2018-04-01

Spatial precipitation datasets that are long-term consistent, highly resolved and extend over several decades are an increasingly popular basis for modelling and monitoring environmental processes and planning tasks in hydrology, agriculture, energy resources management, etc. Here, we present a grid dataset of daily precipitation for Austria meant to promote such applications. It has a grid spacing of 1 km, extends back till 1961 and is continuously updated. It is constructed with the classical two-tier analysis, involving separate interpolations for mean monthly precipitation and daily relative anomalies. The former was accomplished by kriging with topographic predictors as external drift utilising 1249 stations. The latter is based on angular distance weighting and uses 523 stations. The input station network was kept largely stationary over time to avoid artefacts on long-term consistency. Example cases suggest that the new analysis is at least as plausible as previously existing datasets. Cross-validation and comparison against experimental high-resolution observations (WegenerNet) suggest that the accuracy of the dataset depends on interpretation. Users interpreting grid point values as point estimates must expect systematic overestimates for light and underestimates for heavy precipitation as well as substantial random errors. Grid point estimates are typically within a factor of 1.5 from in situ observations. Interpreting grid point values as area mean values, conditional biases are reduced and the magnitude of random errors is considerably smaller. Together with a similar dataset of temperature, the new dataset (SPARTACUS) is an interesting basis for modelling environmental processes, studying climate change impacts and monitoring the climate of Austria.

Introduction to Global Urban Climatology

NASA Astrophysics Data System (ADS)

Varquez, A. C. G.; Kanda, M.; Kawano, N.; Darmanto, N. S.; Dong, Y.

2016-12-01

Urban heat island (UHI) is a widely investigated phenomenon in the field of urban climate characterized by the warming of urban areas relative to its surrounding rural environs. Being able to understand the mechanism behind the UHI formation of a city and distinguish its impact from that of global climate change is indispensable when identifying adaptation and mitigation strategies. However, the lack of UHI studies many cities especially for developing countries makes it difficult to generalize the mechanism for UHI formation. Thus, there is an impending demand for studies that focus on the simultaneous analyses of UHI and its trends throughout the world. Hence, we propose a subfield of urban climatology, called "global urban climatology" (GUC), which mainly focuses on the uniform understanding of urban climates across all cities, globally. By using globally applicable methodologies to quantify and compare urban heat islands of cities with diverse backgrounds, including their geography, climate, socio-demography, and other factors, a universal understanding of the mechanisms underlying the formation of the phenomenon can be established. The implementation of GUC involves the use of globally acquired historical observation networks, gridded meteorological parameters from climate models, global geographic information system datasets; the construction of a distributed urban parameter database; and the development of techniques necessary to model the urban climate. Research under GUC can be categorized into three approaches. The collaborative approach (1st) relies on the collection of data from micro-scale experiments conducted worldwide with the aid or development of professional social networking platforms; the analytical approach (2nd) relies on the use of global weather station datasets and their corresponding objectively analysed global outputs; and the numerical approach (3rd) relies on the global estimation of high-resolution urban-representative parameters as inputs to global weather modelling. The GUC concept, the pathways through which GUC assessments can be undertaken, and current implementations are introduced. Acknowledgment: This research was supported by the Environment Research and Technology Development Fund (S-14) of the Ministry of the Environment, Japan.

A Multidisciplinary Approach to Assessing the Causal Components of Climate Change

NASA Astrophysics Data System (ADS)

Gosnold, W. D.; Todhunter, P. E.; Dong, X.; Rundquist, B.; Majorowicz, J.; Blackwell, D. D.

2004-05-01

Separation of climate forcing by anthropogenic greenhouse gases from natural radiative climate forcing is difficult because the composite temperature signal in the meteorological and multi-proxy temperature records cannot be resolved directly into radiative forcing components. To address this problem, we have initiated a large-scale, multidisciplinary project to test coherence between ground surface temperatures (GST) reconstructed from borehole T-z profiles, surface air temperatures (SAT), soil temperatures, and solar radiation. Our hypothesis is that radiative heating and heat exchange between the ground and the air directly control the ground surface temperature. Consequently, borehole T-z measurements at multi-year intervals spanning time periods when solar radiation, soil and air temperatures have been recorded should enable comparison of the thermal energy stored in the ground to these quantities. If coherence between energy storage, solar radiation, GST, SAT and multi-proxy temperature data can be discerned for a one or two decade scale, synthesis of GST and multi-proxy data over the past several centuries may enable us to separately determine the anthropogenic and natural forcings of climate change. The data we are acquiring include: (1) New T-z measurements in boreholes previously used in paleoclimate and heat flow research in Canada and the United States from the 1970's to the present. (2) Meteorological data from the US Historical Climatology Network and the Automated Weather Data Network of the High Plains Regional Climate Center, and Environment Canada. (3) Direct and remotely sensed data on land use, environment, and soil properties at selected borehole and meteorological sites for the periods between borehole observations. The project addresses three related questions: What is the coherence between the GST, SAT, soil temperatures and solar radiation? Have microclimate changes at borehole sites and climate stations affected temperature trends? If good coherence is obtained, can the coherence between thermal energy stored in the ground and radiative forcing during the time between T-z measurements be extended several centuries into the past?

Climate intercomparison of GPS radio occultation, RS90/92 radiosondes and GRUAN from 2002 to 2013

NASA Astrophysics Data System (ADS)

Ladstädter, F.; Steiner, A. K.; Schwärz, M.; Kirchengast, G.

2015-04-01

Observations from the GPS radio occultation (GPSRO) satellite technique and from the newly established GCOS Reference Upper Air Network (GRUAN) are both candidates to serve as reference observations in the Global Climate Observing System (GCOS). Such reference observations are key to decrease existing uncertainties in upper-air climate research. There are now more than 12 years of data available from GPSRO, with the recognized properties high accuracy, global coverage, high vertical resolution, and long-term stability. These properties make GPSRO a suitable choice for comparison studies with other upper-air observational systems. The GRUAN network consists of reference radiosonde ground stations (16 at present), which adhere to the GCOS climate monitoring principles. In this study, we intercompare GPSRO temperature and humidity profiles and Vaisala RS90/92 data from the "standard" global radiosonde network over the whole 2002 to 2013 time frame. Additionally, we include the first years of GRUAN data (using Vaisala RS92), available since 2009. GPSRO profiles which occur within 3 h and 300 km of radiosonde launches are used. Overall very good agreement is found between all three data sets with temperature differences usually less than 0.2 K. In the stratosphere above 30 hPa, temperature differences are larger but still within 0.5 K. Day/night comparisons with GRUAN data reveal small deviations likely related to a warm bias of the radiosonde data at high altitudes, but also residual errors from the GPSRO retrieval process might play a role. Vaisala RS90/92 specific humidity exhibits a dry bias of up to 40% in the upper troposphere, with a smaller bias at lower altitudes within 15%. GRUAN shows a marked improvement in the bias characteristics, with less than 5% difference to GPSRO, up to 300 hPa. GPSRO dry temperature and physical temperature are validated using radiosonde data as reference. We find that GPSRO provides valuable long-term stable reference observations with well-defined error characteristics for climate applications and for anchoring other upper-air measurements.

Climate intercomparison of GPS radio occultation, RS90/92 radiosondes and GRUAN over 2002 to 2013

NASA Astrophysics Data System (ADS)

Ladstädter, F.; Steiner, A. K.; Schwärz, M.; Kirchengast, G.

2014-11-01

Observations from the GPS radio occultation (GPSRO) satellite technique and from the newly established GCOS Reference Upper Air Network (GRUAN) are both candidates to serve as reference observations in the Global Climate Observing System (GCOS). Such reference observations are key to decrease existing uncertainties in upper-air climate research. There are now more than 12 years of data available from GPSRO, with the recognized properties high accuracy, global coverage, high vertical resolution, and long-term stability. These properties make GPSRO a suitable choice for comparison studies with other upper-air observational systems. The GRUAN network consists of reference radiosonde ground stations (16 at present), which adhere to the GCOS climate monitoring principles. In this study, we intercompare GPSRO temperature and humidity profiles and Vaisala RS90/92 data from the "standard" global radiosonde network over the whole 2002 to 2013 time frame. Additionally, we include the first years of GRUAN data (using Vaisala RS92), available since 2009. GPSRO profiles which occur within 3 h and 300 km of radiosonde launches are used. Very good agreement is found between all three datasets with temperature differences usually less than 0.2 K. In the stratosphere above 30 hPa, temperature differences are larger but still within 0.5 K. Day/night comparisons with GRUAN data reveal small deviations likely related to a warm bias of the radiosonde data at high altitudes, but also residual errors from the GPSRO retrieval process might play a role. Vaisala RS90/92 specific humidity exhibits a dry bias of up to 40% in the upper troposphere, with a smaller bias at lower altitudes within 15%. GRUAN shows a marked improvement in the bias characteristics, with less than 5% difference to GPSRO up to 300 hPa. GPSRO dry temperature and physical temperature are validated using radiosonde data as reference. We find that GPSRO provides valuable long-term stable reference observations with well-defined error characteristics for climate applications and for anchoring other upper-air measurements.

Building an alternative fuel refueling network: How many stations are needed and where should they be placed?

NASA Astrophysics Data System (ADS)

Nicholas, Michael Anselm

Gasoline stations are so numerous that the fear of running out of fuel is likely not a top concern among drivers. This may not be the case with the introduction of a new alternative fuel such as hydrogen or electricity. The next three chapters, originally written as peer reviewed journal papers[1,2,3], examine the characteristics of refueling in today's gasoline network and compares these characteristics to hypothetical new alternative fuel networks. Together, they suggest that alternative fuel networks with many fewer stations than exist in the gasoline network could be acceptable to future consumers. This acceptability is measured in three ways. The first chapter examines the distance from home to the nearest station and finds that if alternative fuel stations were one-third as numerous as gasoline stations, the travel time to the nearest station was virtually identical to that of gasoline stations. The results suggest that even for station networks numbering only one-twentieth the current number of outlets, the difference in travel time with respect to gasoline is relatively small. Acceptability was examined in the second chapter by analyzing the spatial refueling patterns of gasoline. This reveals that the volume of fuel sold is greater around the highways and that the route from home to the nearest highway entrance may account for a large portion of refueling. This suggests that the first alternative fuel stations could be sited along the highway near entrances and could provide acceptable access to fuel for those who use these highway entrances to access the wider region. Subsequent stations could be sited closer to the homes of customers. The third chapter estimates acceptability, measured in terms of initial vehicle purchase price, of refueling away from one's own town. A pilot survey using a map-based questionnaire was distributed to 20 respondents. Respondents chose ten stations locations to enable their most important destinations. The alternative fuel vehicle was then compared to the equivalent gasoline vehicle. The effect on initial purchase price of the vehicle is estimated when some or all of these stations are available. Single-vehicle households put a higher premium on station availability than multi-vehicle households.

A technique to detect microclimatic inhomogeneities in historical temperature records

NASA Astrophysics Data System (ADS)

Runnalls, K. E.; Oke, T. R.

2003-04-01

A technique to identify inhomogeneities in historical temperature records caused by microclimatic changes to the surroundings of a climate station (e.g. minor instrument relocations, vegetation growth/removal, construction of houses, roads, runways) is presented. The technique uses daily maximum and minimum temperatures to estimate the magnitude of nocturnal cooling. The test station is compared to a nearby reference station by constructing time series of monthly "cooling ratios". It is argued that the cooling ratio is a particularly sensitive measure of microclimatic differences between neighbouring climate stations. Firstly, because microclimatic character is best expressed at night in stable conditions. Secondly, because larger-scale climatic influences common to both stations are removed by the use of a ratio and, because the ratio can be shown to be invariant in the mean with weather variables such as wind and cloud. Inflections (change points) in time series of cooling ratios therefore signal microclimatic change in one of the station records. Hurst rescaling is applied to the time series to aid in the identification of change points, which can then be compared to documented station history events, if sufficient metatdata is available. Results for a variety of air temperature records, ranging from rural to urban stations, are presented to illustrate the applicability of the technique.

System and Method for Network Bandwidth, Buffers and Timing Management Using Hybrid Scheduling of Traffic with Different Priorities and Guarantees

NASA Technical Reports Server (NTRS)

Bonk, Ted (Inventor); Hall, Brendan (Inventor); Smithgall, William Todd (Inventor); Varadarajan, Srivatsan (Inventor); DeLay, Benjamin F. (Inventor)

2017-01-01

Systems and methods for network bandwidth, buffers and timing management using hybrid scheduling of traffic with different priorities and guarantees are provided. In certain embodiments, a method of managing network scheduling and configuration comprises, for each transmitting end station, reserving one exclusive buffer for each virtual link to be transmitted from the transmitting end station; for each receiving end station, reserving exclusive buffers for each virtual link to be received at the receiving end station; and for each switch, reserving a exclusive buffer for each virtual link to be received at an input port of the switch. The method further comprises determining if each respective transmitting end station, receiving end station, and switch has sufficient capability to support the reserved buffers; and reporting buffer infeasibility if each respective transmitting end station, receiving end station, and switch does not have sufficient capability to support the reserved buffers.

NASA directory of observation station locations, volume 1

NASA Technical Reports Server (NTRS)

1973-01-01

Geodetic information for NASA tracking stations and for observation stations cooperating in NASA geodetic satellite programs is presented. A Geodetic Data Sheet is provided for each station, giving the position of the station and describing briefly how it was established. Geodetic positions and geocentric coordinates of these stations are tabulated on local or major geodetic datums and on selected world geodetic systems. The principal tracking facilities used by NASA, including the Spaceflight Tracking and Data Network, the Deep Space Network, and several large radio telescopes are discussed. Positions of these facilities are tabulated on their local or national datums, the Mercury Spheroid 1960, the Modified Mercury Datum 1968, and the Spaceflight Tracking and Data Network System. Observation stations in the NASA Geodetic Satellites Program are included along with stations participating in the National Geodetic Satellite Program. Positions of these facilities are given on local or preferred major datums, and on the Modified Mercury Datum 1968.

Ground-based aerosol measurements during CHARMEX/ADRIMED campaign at Granada station

NASA Astrophysics Data System (ADS)

Granados-Muñoz, Maria Jose; Bravo-Aranda, Juan Antonio; Navas-Guzman, Francisco; Guerro-Rascado, Juan Luis; Titos, Gloria; Lyamani, Hassan; Valenzuela, Antonio; Cazorla, Alberto; Olmo, Francisco Jose; Mallet, Marc; Alados-Arboledas, Lucas

2015-04-01

In the framework of ChArMEx/ADRIMED (Chemistry-Aerosol Mediterranean Experiment, http://charmex.lsce.ipsl.fr/; Aerosol Direct Radiative Impact on the regional climate in the MEDiterranean region) projects, a field experiment based on in situ and remote sensing measurements from surface and airborne platforms was performed. The ADRIMED project aimed to capture the high complexity of the Mediterranean region by using an integrated approach based on intensive experimental field campaign and spaceborne observations, radiative transfer calculations and climate modelling with Regional Climate Models better adapted than global circulation models. For this purpose, measurements were performed at different surface super-sites (including Granada station) over the Occidental Mediterranean region during summer 2013 for creating an updated database of the physical, chemical, optical properties and the vertical distribution of the major "Mediterranean aerosols". Namely, measurements at Granada station were performed on 16 and 17 July 2013, in coincidence with the overpasses of the ATR aircraft over the station. The instrumentation used for the campaign includes both remote sensing instruments (a multiwavelength Raman lidar and a sun photometer) and in-situ measurements (a nephelometer, a Multi-Angle Absorption Photometer (MAAP), an Aerodynamic particle sizer (APS), a high volume sampler of PM10 and an aethalometer). During the measurement period a mineral dust event was detected, with similar dust load on both days. According to in-situ measurements, the event reached the surface level on 16 of June. Vertically resolved lidar measurements indicated presence of mineral dust layers up to 5 km asl both on 16 and 17 June 2013. Temporal evolution analysis indicated that on 17 June the dust layer decoupled from the boundary layer and disappeared around 14:00 UTC. In addition, lidar and sun-photometer data were used to retrieve volume concentration profiles by means of LIRIC (Lidar-Radiometer Inversion Code algorithm) [Chaikovsky et al., 2008]. The retrieved volume concentration profiles were compared with data from ATR flights above the station at 14:30 UTC on 16 June and 07:30 UTC on 17 June, obtaining in general good agreement in the location of the aerosol layers and discrepancies in the volume concentration values ranging between 15 and 40 µm3/cm3 for the coarse mode. References: Chaikovsky, A., O. Dubovik, et a., (2008), Software package for the retrieval of aerosol microphysical properties in the vertical column using combined lidar/photometer data, Tech. Rep., Institute of Physics, National Academy of Sciences of Belarus. Acknowledgments: EARLINET lidar measurements are supported by the 7th Framework Programme project Aerosols, Clouds, and Trace Gases Research Infrastructure Network (ACTRIS) (grant agreement no. 262254). The field campaign was performed in the framework of work package 4 on aerosol-radiation-climate interactions of the coordinated programme ChArMEx.

Climatologies at high resolution for the earth’s land surface areas

PubMed Central

Karger, Dirk Nikolaus; Conrad, Olaf; Böhner, Jürgen; Kawohl, Tobias; Kreft, Holger; Soria-Auza, Rodrigo Wilber; Zimmermann, Niklaus E.; Linder, H. Peter; Kessler, Michael

2017-01-01

High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present the CHELSA (Climatologies at high resolution for the earth’s land surface areas) data of downscaled model output temperature and precipitation estimates of the ERA-Interim climatic reanalysis to a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperatures. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height, with a subsequent bias correction. The resulting data consist of a monthly temperature and precipitation climatology for the years 1979–2013. We compare the data derived from the CHELSA algorithm with other standard gridded products and station data from the Global Historical Climate Network. We compare the performance of the new climatologies in species distribution modelling and show that we can increase the accuracy of species range predictions. We further show that CHELSA climatological data has a similar accuracy as other products for temperature, but that its predictions of precipitation patterns are better. PMID:28872642

Climatologies at high resolution for the earth's land surface areas

NASA Astrophysics Data System (ADS)

Karger, Dirk Nikolaus; Conrad, Olaf; Böhner, Jürgen; Kawohl, Tobias; Kreft, Holger; Soria-Auza, Rodrigo Wilber; Zimmermann, Niklaus E.; Linder, H. Peter; Kessler, Michael

2017-09-01

High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present the CHELSA (Climatologies at high resolution for the earth's land surface areas) data of downscaled model output temperature and precipitation estimates of the ERA-Interim climatic reanalysis to a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperatures. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height, with a subsequent bias correction. The resulting data consist of a monthly temperature and precipitation climatology for the years 1979-2013. We compare the data derived from the CHELSA algorithm with other standard gridded products and station data from the Global Historical Climate Network. We compare the performance of the new climatologies in species distribution modelling and show that we can increase the accuracy of species range predictions. We further show that CHELSA climatological data has a similar accuracy as other products for temperature, but that its predictions of precipitation patterns are better.

Air temperature, wind speed, and wind direction in the National Petroleum Reserve—Alaska and the Arctic National Wildlife Refuge, 1998–2011

USGS Publications Warehouse

Urban, Frank E.; Clow, Gary D.

2013-01-01

This report provides air temperature, wind speed, and wind direction data collected on Federal lands in Arctic Alaska over the period August 1998 to July 2011 by the U.S. Department of the Interior's climate monitoring array, part of the Global Terrestrial Network for Permafrost. In addition to presenting data, this report also describes monitoring, data collection, and quality control methodology. This array of 16 monitoring stations spans 68.5°N to 70.5°N and 142.5°W to 161°W, an area of roughly 150,000 square kilometers. Climate summaries are presented along with provisional quality-controlled data. Data collection is ongoing and includes several additional climate variables to be released in subsequent reports, including ground temperature and soil moisture, snow depth, rainfall, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.

A multi-scale hybrid neural network retrieval model for dust storm detection, a study in Asia

NASA Astrophysics Data System (ADS)

Wong, Man Sing; Xiao, Fei; Nichol, Janet; Fung, Jimmy; Kim, Jhoon; Campbell, James; Chan, P. W.

2015-05-01

Dust storms are known to have adverse effects on human health and significant impact on weather, air quality, hydrological cycle, and ecosystem. Atmospheric dust loading is also one of the large uncertainties in global climate modeling, due to its significant impact on the radiation budget and atmospheric stability. Observations of dust storms in humid tropical south China (e.g. Hong Kong), are challenging due to high industrial pollution from the nearby Pearl River Delta region. This study develops a method for dust storm detection by combining ground station observations (PM10 concentration, AERONET data), geostationary satellite images (MTSAT), and numerical weather and climatic forecasting products (WRF/Chem). The method is based on a hybrid neural network (NN) retrieval model for two scales: (i) a NN model for near real-time detection of dust storms at broader regional scale; (ii) a NN model for detailed dust storm mapping for Hong Kong and Taiwan. A feed-forward multilayer perceptron (MLP) NN, trained using back propagation (BP) algorithm, was developed and validated by the k-fold cross validation approach. The accuracy of the near real-time detection MLP-BP network is 96.6%, and the accuracies for the detailed MLP-BP neural network for Hong Kong and Taiwan is 74.8%. This newly automated multi-scale hybrid method can be used to give advance near real-time mapping of dust storms for environmental authorities and the public. It is also beneficial for identifying spatial locations of adverse air quality conditions, and estimates of low visibility associated with dust events for port and airport authorities.

Integrated Meteorological Observation Network in Castile-León (Spain)

NASA Astrophysics Data System (ADS)

Merino, A.; Guerrero-Higueras, A. M.; Ortiz de Galisteo, J. P.; López, L.; García-Ortega, E.; Nafría, D. A.; Sánchez, J. L.

2012-04-01

In the region of Castile-Leon, in the northwest of Spain, the study of weather risks is extremely complex because of the topography, the large land area of the region and the variety of climatic features involved. Therefore, as far as the calibration and validation of the necessary tools for the identification and nowcasting of these risks are concerned, one of the most important difficulties is the lack of observed data. The same problem arises, for example, in the analysis of particularly relevant case studies. It was hence deemed necessary to create an INTEGRATED METEOROLOGICAL OBSERVATION NETWORK FOR CASTILE-LEON. The aim of this network is to integrate within one single platform all the ground truth data available. These data enable us to detect a number of weather risks in real time. The various data sources should include the networks from the weather stations run by different public institutions - national and regional ones (AEMET, Junta de Castilla y León, Universities, etc.) -, as well as the stations run by voluntary observers. The platform will contain real or cuasi-real time data from the ground weather stations, but it will also have applications to enable voluntary observers to indicate the presence or absence of certain meteors (snow, hail) or even provide detailed information about them (hailstone size, graupel, etc.). The data managed by this network have a high scientific potential, as they may be used for a number of different purposes: calibration and validation of remote sensing tools, assimilation of observation data from numerical models, study of extreme weather events, etc. An additional aim of the network is the drawing of maps of weather risks in real time. These maps are of great importance for the people involved in risk management in each region, as well as for the general public. Finally, one of the first applications developed has been the creation of observation maps in real time. These applications have been constructed using NCL (NCAR Command Language), because it is a robust tool especially designed for the treatment and visualization of scientific data. Acknowledgements The authors would like to thank the Regional Government of Castile-León for its financial support through the project LE220A11-2.

Development of gridded solar radiation data over Belgium based on Meteosat and in-situ observations

NASA Astrophysics Data System (ADS)

Journée, Michel; Vanderveken, Gilles; Bertrand, Cédric

2013-04-01

Knowledge on solar resources is highly important for all forms of solar energy applications. With the recent development in solar-based technologies national meteorological services are faced with increasing demands for high-quality and reliable site-time specific solar resource information. Traditionally, solar radiation is observed by means of networks of meteorological stations. Costs for installation and maintenance of such networks are very high and national networks comprise only few stations. Consequently the availability of ground-based solar radiation measurements has proven to be spatially and temporally inadequate for many applications. To overcome such a limitation, a major effort has been undertaken at the Royal Meteorological Institute of Belgium (RMI) to provide the solar energy industry, the electricity sector, governments, and renewable energy organizations and institutions with the most suitable and accurate information on the solar radiation resources at the Earth's surface over the Belgian territory. Only space-based observations can deliver a global coverage of the solar irradiation impinging on horizontal surface at the ground level. Because only geostationary data allow to capture the diurnal cycle of the solar irradiance at the Earth's surface, a method that combines information from Meteosat Second Generation satellites and ground-measurement has been implemented at RMI to generate high resolution solar products over Belgium on an operational basis. Besides these new products, the annual and seasonal variability of solar energy resource was evaluated, solar radiation climate zones were defined and the recent trend in solar radiation was characterized.

Tool to assess contents of ARM surface meteorology network netCDF files

DOE Office of Scientific and Technical Information (OSTI.GOV)

Staudt, A.; Kwan, T.; Tichler, J.

The Atmospheric Radiation Measurement (ARM) Program, supported by the US Department of Energy, is a major program of atmospheric measurement and modeling designed to improve the understanding of processes and properties that affect atmospheric radiation, with a particular focus on the influence of clouds and the role of cloud radiative feedback in the climate system. The ARM Program will use three highly instrumented primary measurement sites. Deployment of instrumentation at the first site, located in the Southern Great Plains of the United States, began in May of 1992. The first phase of deployment at the second site in the Tropicalmore » Western Pacific is scheduled for late in 1995. The third site will be in the North Slope of Alaska and adjacent Arctic Ocean. To meet the scientific objectives of ARM, observations from the ARM sites are combined with data from other sources; these are called external data. Among these external data sets are surface meteorological observations from the Oklahoma Mesonet, a Kansas automated weather network, the Wind Profiler Demonstration Network (WPDN), and the National Weather Service (NWS) surface stations. Before combining these data with the Surface Meteorological Observations Station (SMOS) ARM data, it was necessary to assess the contents and quality of both the ARM and the external data sets. Since these data sets had previously been converted to netCDF format for use by the ARM Science Team, a tool was written to assess the contents of the netCDF files.« less

Precipitation estimation in mountainous terrain using multivariate geostatistics. Part II: isohyetal maps

USGS Publications Warehouse

Hevesi, Joseph A.; Flint, Alan L.; Istok, Jonathan D.

1992-01-01

Values of average annual precipitation (AAP) may be important for hydrologic characterization of a potential high-level nuclear-waste repository site at Yucca Mountain, Nevada. Reliable measurements of AAP are sparse in the vicinity of Yucca Mountain, and estimates of AAP were needed for an isohyetal mapping over a 2600-square-mile watershed containing Yucca Mountain. Estimates were obtained with a multivariate geostatistical model developed using AAP and elevation data from a network of 42 precipitation stations in southern Nevada and southeastern California. An additional 1531 elevations were obtained to improve estimation accuracy. Isohyets representing estimates obtained using univariate geostatistics (kriging) defined a smooth and continuous surface. Isohyets representing estimates obtained using multivariate geostatistics (cokriging) defined an irregular surface that more accurately represented expected local orographic influences on AAP. Cokriging results included a maximum estimate within the study area of 335 mm at an elevation of 7400 ft, an average estimate of 157 mm for the study area, and an average estimate of 172 mm at eight locations in the vicinity of the potential repository site. Kriging estimates tended to be lower in comparison because the increased AAP expected for remote mountainous topography was not adequately represented by the available sample. Regression results between cokriging estimates and elevation were similar to regression results between measured AAP and elevation. The position of the cokriging 250-mm isohyet relative to the boundaries of pinyon pine and juniper woodlands provided indirect evidence of improved estimation accuracy because the cokriging result agreed well with investigations by others concerning the relationship between elevation, vegetation, and climate in the Great Basin. Calculated estimation variances were also mapped and compared to evaluate improvements in estimation accuracy. Cokriging estimation variances were reduced by an average of 54% relative to kriging variances within the study area. Cokriging reduced estimation variances at the potential repository site by 55% relative to kriging. The usefulness of an existing network of stations for measuring AAP within the study area was evaluated using cokriging variances, and twenty additional stations were located for the purpose of improving the accuracy of future isohyetal mappings. Using the expanded network of stations, the maximum cokriging estimation variance within the study area was reduced by 78% relative to the existing network, and the average estimation variance was reduced by 52%.

Madrid space station

NASA Technical Reports Server (NTRS)

Fahnestock, R. J.; Renzetti, N. A.

1975-01-01

The Madrid space station, operated under bilateral agreements between the governments of the United States and Spain, is described in both Spanish and English. The space station utilizes two tracking and data acquisition networks: the Deep Space Network (DSN) of the National Aeronautics and Space Administration and the Spaceflight Tracking and Data Network (STDN) operated under the direction of the Goddard Space Flight Center. The station, which is staffed by Spanish employees, comprises four facilities: Robledo 1, Cebreros, and Fresnedillas-Navalagamella, all with 26-meter-diameter antennas, and Robledo 2, with a 64-meter antenna.

Constructing regional climate networks in the Amazonia during recent drought events.

PubMed

Guo, Heng; Ramos, Antônio M T; Macau, Elbert E N; Zou, Yong; Guan, Shuguang

2017-01-01

Climate networks are powerful approaches to disclose tele-connections in climate systems and to predict severe climate events. Here we construct regional climate networks from precipitation data in the Amazonian region and focus on network properties under the recent drought events in 2005 and 2010. Both the networks of the entire Amazon region and the extreme networks resulted from locations severely affected by drought events suggest that network characteristics show slight difference between the two drought events. Based on network degrees of extreme drought events and that without drought conditions, we identify regions of interest that are correlated to longer expected drought period length. Moreover, we show that the spatial correlation length to the regions of interest decayed much faster in 2010 than in 2005, which is because of the dual roles played by both the Pacific and Atlantic oceans. The results suggest that hub nodes in the regional climate network of Amazonia have fewer long-range connections when more severe drought conditions appeared in 2010 than that in 2005.

Improving Earth/Prediction Models to Improve Network Processing

NASA Astrophysics Data System (ADS)

Wagner, G. S.

2017-12-01

The United States Atomic Energy Detection System (USAEDS) primaryseismic network consists of a relatively small number of arrays andthree-component stations. The relatively small number of stationsin the USAEDS primary network make it both necessary and feasibleto optimize both station and network processing.Station processing improvements include detector tuning effortsthat use Receiver Operator Characteristic (ROC) curves to helpjudiciously set acceptable Type 1 (false) vs. Type 2 (miss) errorrates. Other station processing improvements include the use ofempirical/historical observations and continuous background noisemeasurements to compute time-varying, maximum likelihood probabilityof detection thresholds.The USAEDS network processing software makes extensive use of theazimuth and slowness information provided by frequency-wavenumberanalysis at array sites, and polarization analysis at three-componentsites. Most of the improvements in USAEDS network processing aredue to improvements in the models used to predict azimuth, slowness,and probability of detection. Kriged travel-time, azimuth andslowness corrections-and associated uncertainties-are computedusing a ground truth database. Improvements in station processingand the use of improved models for azimuth, slowness, and probabilityof detection have led to significant improvements in USADES networkprocessing.

A Climate Trend Analysis of Burkina Faso

USGS Publications Warehouse

Funk, Christopher C.; Rowland, Jim; Eilerts, Gary; Adoum, Alkhalil; White, Libby

2012-01-01

This brief report, drawing from a multi-year effort by the U.S. Agency for International Development (USAID) Famine Early Warning Systems Network (FEWS NET), examines recent trends in rainfall and air temperatures. These analyses are based on quality controlled station observations. Conclusions: * Summer rains have remained steady over the past 20 years, but remain 15 percent below the 1920-69 average. * Temperatures have increased by 0.6° Celsius since 1975, amplifying the effect of droughts. * The amount of farmland per person is low, and declining. * Burkina Faso has offset rapid population growth with improved yields. * Continued yield growth would maintain current levels of per capita food production.

A climate trend analysis of Mali

USGS Publications Warehouse

Funk, Christopher C.; Rowland, Jim; Adoum, Alkhalil; Eilerts, Gary; White, Libby

2012-01-01

This brief report, drawing from a multi-year effort by the U.S. Agency for International Development (USAID) Famine Early Warning Systems Network (FEWS NET), identifies modest declines in rainfall, accompanied by increases in air temperatures. These analyses are based on quality-controlled station observations. Conclusions: * Summer rains have remained relatively steady for the past 20 years, but are 12 percent below the 1920-1969 average. * Temperatures have increased by 0.8° Celsius since 1975, amplifying the effect of droughts. * Cereal yields are low but have been improving. * Current population and agricultural trends indicate that increased yields have offset population expansion, keeping per capita cereal production steady.

Moisture status during a strong El Niño explains a tropical montane cloud forest's upper limit.

PubMed

Crausbay, Shelley D; Frazier, Abby G; Giambelluca, Thomas W; Longman, Ryan J; Hotchkiss, Sara C

2014-05-01

Growing evidence suggests short-duration climate events may drive community structure and composition more directly than long-term climate means, particularly at ecotones where taxa are close to their physiological limits. Here we use an empirical habitat model to evaluate the role of microclimate during a strong El Niño in structuring a tropical montane cloud forest's upper limit and composition in Hawai'i. We interpolate climate surfaces, derived from a high-density network of climate stations, to permanent vegetation plots. Climatic predictor variables include (1) total rainfall, (2) mean relative humidity, and (3) mean temperature representing non-El Niño periods and a strong El Niño drought. Habitat models explained species composition within the cloud forest with non-El Niño rainfall; however, the ecotone at the cloud forest's upper limit was modeled with relative humidity during a strong El Niño drought and secondarily with non-El Niño rainfall. This forest ecotone may be particularly responsive to strong, short-duration climate variability because taxa here, particularly the isohydric dominant Metrosideros polymorpha, are near their physiological limits. Overall, this study demonstrates moisture's overarching influence on a tropical montane ecosystem, and suggests that short-term climate events affecting moisture status are particularly relevant at tropical ecotones. This study further suggests that predicting the consequences of climate change here, and perhaps in other tropical montane settings, will rely on the skill and certainty around future climate models of regional rainfall, relative humidity, and El Niño.

A precise time synchronization method for 5G based on radio-over-fiber network with SDN controller

NASA Astrophysics Data System (ADS)

He, Linkuan; Wei, Baoguo; Yang, Hui; Yu, Ao; Wang, Zhengyong; Zhang, Jie

2018-02-01

There is an increasing demand on accurate time synchronization with the growing bandwidth of network service for 5G. In 5G network, it's necessary for base station to achieve accurate time synchronization to guarantee the quality of communication. In order to keep accuracy time for 5G network, we propose a time synchronization system for satellite ground station based on radio-over-fiber network (RoFN) with software defined optical network (SDON) controller. The advantage of this method is to improve the accuracy of time synchronization of ground station. The IEEE 1588 time synchronization protocol can solve the problems of high cost and lack of precision. However, in the process of time synchronization, distortion exists during the transmission of digital time signal. RoF uses analog optical transmission links and therefore analog transmission can be implemented among ground stations instead of digital transmission, which means distortion and bandwidth waste in the process of digital synchronization can be avoided. Additionally, the thought of SDN, software defined network, can optimize RoFN with centralized control and simplifying base station. Related simulation had been carried out to prove its superiority.

Estimating the urban bias of surface shelter temperatures using upper-air and satellite data. Part 1: Development of models predicting surface shelter temperatures

NASA Technical Reports Server (NTRS)

Epperson, David L.; Davis, Jerry M.; Bloomfield, Peter; Karl, Thomas R.; Mcnab, Alan L.; Gallo, Kevin P.

1995-01-01

Multiple regression techniques were used to predict surface shelter temperatures based on the time period 1986-89 using upper-air data from the European Centre for Medium-Range Weather Forecasts (ECMWF) to represent the background climate and site-specific data to represent the local landscape. Global monthly mean temperature models were developed using data from over 5000 stations available in the Global Historical Climate Network (GHCN). Monthly maximum, mean, and minimum temperature models for the United States were also developed using data from over 1000 stations available in the U.S. Cooperative (COOP) Network and comparative monthly mean temperature models were developed using over 1150 U.S. stations in the GHCN. Three-, six-, and full-variable models were developed for comparative purposes. Inferences about the variables selected for the various models were easier for the GHCN models, which displayed month-to-month consistency in which variables were selected, than for the COOP models, which were assigned a different list of variables for nearly every month. These and other results suggest that global calibration is preferred because data from the global spectrum of physical processes that control surface temperatures are incorporated in a global model. All of the models that were developed in this study validated relatively well, especially the global models. Recalibration of the models with validation data resulted in only slightly poorer regression statistics, indicating that the calibration list of variables was valid. Predictions using data from the validation dataset in the calibrated equation were better for the GHCN models, and the globally calibrated GHCN models generally provided better U.S. predictions than the U.S.-calibrated COOP models. Overall, the GHCN and COOP models explained approximately 64%-95% of the total variance of surface shelter temperatures, depending on the month and the number of model variables. In addition, root-mean-square errors (rmse's) were over 3 C for GHCN models and over 2 C for COOP models for winter months, and near 2 C for GHCN models and near 1.5 C for COOP models for summer months.

Phenology Across the LTER Network: Initial Findings, Future Directions

NASA Astrophysics Data System (ADS)

Henebry, G. M.

2007-12-01

Phenology is, in the words of Aldo Leopold, a "horizontal science" that cuts across and binds together multiple biological disciplines. It is a far-reaching but poorly understood aspect of the environmental sciences. Phenological research has been a component of the Long Term Ecological Research (LTER) Network at several sites over the years. However, it has not received the attention or resources to bring it to the forefront as an effective theme for interdisciplinary and cross-site synthesis. With the recent establishment of the USA National Phenology Network (USA-NPN), it is appropriate to assess the status of phenological knowledge across the LTER Network. A workshop funded by the LTER Network Office took place at the Sevilleta Field Station during February 26 to March 2, 2007. From the workshop three main products emerged: (1) an inventory of LTER phenology datasets, (2) establishment of a website to facilitate information interchange, and (3) a white paper recommending next steps for the LTER Network to engage the USA-NPN. This poster relates the findings and recommendations of the workshop, including a summary of phenologically explicit and phenologically implicit LTER datasets and illustrations of how the climatic envelopes described by simple weather variables can provide context for phenological comparisons within and across sites.

Effectiveness of the New Hampshire stream-gaging network in providing regional streamflow information

USGS Publications Warehouse

Olson, Scott A.

2003-01-01

The stream-gaging network in New Hampshire was analyzed for its effectiveness in providing regional information on peak-flood flow, mean-flow, and low-flow frequency. The data available for analysis were from stream-gaging stations in New Hampshire and selected stations in adjacent States. The principles of generalized-least-squares regression analysis were applied to develop regional regression equations that relate streamflow-frequency characteristics to watershed characteristics. Regression equations were developed for (1) the instantaneous peak flow with a 100-year recurrence interval, (2) the mean-annual flow, and (3) the 7-day, 10-year low flow. Active and discontinued stream-gaging stations with 10 or more years of flow data were used to develop the regression equations. Each stream-gaging station in the network was evaluated and ranked on the basis of how much the data from that station contributed to the cost-weighted sampling-error component of the regression equation. The potential effect of data from proposed and new stream-gaging stations on the sampling error also was evaluated. The stream-gaging network was evaluated for conditions in water year 2000 and for estimated conditions under various network strategies if an additional 5 years and 20 years of streamflow data were collected. The effectiveness of the stream-gaging network in providing regional streamflow information could be improved for all three flow characteristics with the collection of additional flow data, both temporally and spatially. With additional years of data collection, the greatest reduction in the average sampling error of the regional regression equations was found for the peak- and low-flow characteristics. In general, additional data collection at stream-gaging stations with unregulated flow, relatively short-term record (less than 20 years), and drainage areas smaller than 45 square miles contributed the largest cost-weighted reduction to the average sampling error of the regional estimating equations. The results of the network analyses can be used to prioritize the continued operation of active stations, the reactivation of discontinued stations, or the activation of new stations to maximize the regional information content provided by the stream-gaging network. Final decisions regarding altering the New Hampshire stream-gaging network would require the consideration of the many uses of the streamflow data serving local, State, and Federal interests.

Climate Drivers of Alaska Summer Stream Temperature

NASA Astrophysics Data System (ADS)

Bieniek, P.; Bhatt, U. S.; Plumb, E. W.; Thoman, R.; Trammell, E. J.

2016-12-01

The temperature of the water in lakes, rivers and streams has wide ranging impacts from local water quality and fish habitats to global climate change. Salmon fisheries in Alaska, a critical source of food in many subsistence communities, are sensitive to large-scale climate variability and river and stream temperatures have also been linked with salmon production in Alaska. Given current and projected climate change, understanding the mechanisms that link the large-scale climate and river and stream temperatures is essential to better understand the changes that may occur with aquatic life in Alaska's waterways on which subsistence users depend. An analysis of Alaska stream temperatures in the context of reanalysis, downscaled, station and other climate data is undertaken in this study to fill that need. Preliminary analysis identified eight stream observation sites with sufficiently long (>15 years) data available for climate-scale analysis in Alaska with one station, Terror Creek in Kodiak, having a 30-year record. Cross-correlation of summer (June-August) water temperatures between the stations are generally high even though they are spread over a large geographic region. Correlation analysis of the Terror Creek summer observations with seasonal sea surface temperatures (SSTs) in the North Pacific broadly resembles the SST anomaly fields typically associated with the Pacific Decadal Oscillation (PDO). A similar result was found for the remaining stations and in both cases PDO-like correlation patterns also occurred in the preceding spring. These preliminary results demonstrate that there is potential to diagnose the mechanisms that link the large-scale climate system and Alaska stream temperatures.

A statistical summary of data from the U.S. Geological Survey's national water quality networks

USGS Publications Warehouse

Smith, R.A.; Alexander, R.B.

1983-01-01

The U.S. Geological Survey Operates two nationwide networks to monitor water quality, the National Hydrologic Bench-Mark Network and the National Stream Quality Accounting Network (NASQAN). The Bench-Mark network is composed of 51 stations in small drainage basins which are as close as possible to their natural state, with no human influence and little likelihood of future development. Stations in the NASQAN program are located to monitor flow from accounting units (subregional drainage basins) which collectively encompass the entire land surface of the nation. Data collected at both networks include streamflow, concentrations of major inorganic constituents, nutrients, and trace metals. The goals of the two water quality sampling programs include the determination of mean constituent concentrations and transport rates as well as the analysis of long-term trends in those variables. This report presents a station-by-station statistical summary of data from the two networks for the period 1974 through 1981. (Author 's abstract)

Network modeling of PM10 concentration in Malaysia

NASA Astrophysics Data System (ADS)

Supian, Muhammad Nazirul Aiman Abu; Bakar, Sakhinah Abu; Razak, Fatimah Abdul

2017-08-01

Air pollution is not a new phenomenon in Malaysia. The Department of Environment (DOE) monitors the country's ambient air quality through a network of 51 stations. The air quality is measured using the Air Pollution Index (API) which is mainly recorded based on the concentration of particulate matter, PM10 readings. The Continuous Air Quality Monitoring (CAQM) stations are located in various places across the country. In this study, a network model of air quality based on PM10 concen tration for selected CAQM stations in Malaysia has been developed. The model is built using a graph formulation, G = (V, E) where vertex, V is a set of CAQM stations and edges, E is a set of correlation values for each pair of vertices. The network measurements such as degree distributions, closeness centrality, and betweenness centrality are computed to analyse the behaviour of the network. As a result, a rank of CAQM stations has been produced based on their centrality characteristics.

LEO Download Capacity Analysis for a Network of Adaptive Array Ground Stations

NASA Technical Reports Server (NTRS)

Ingram, Mary Ann; Barott, William C.; Popovic, Zoya; Rondineau, Sebastien; Langley, John; Romanofsky, Robert; Lee, Richard Q.; Miranda, Felix; Steffes, Paul; Mandl, Dan

2005-01-01

To lower costs and reduce latency, a network of adaptive array ground stations, distributed across the United States, is considered for the downlink of a polar-orbiting low earth orbiting (LEO) satellite. Assuming the X-band 105 Mbps transmitter of NASA s Earth Observing 1 (EO-1) satellite with a simple line-of-sight propagation model, the average daily download capacity in bits for a network of adaptive array ground stations is compared to that of a single 11 m dish in Poker Flats, Alaska. Each adaptive array ground station is assumed to have multiple steerable antennas, either mechanically steered dishes or phased arrays that are mechanically steered in azimuth and electronically steered in elevation. Phased array technologies that are being developed for this application are the space-fed lens (SFL) and the reflectarray. Optimization of the different boresight directions of the phased arrays within a ground station is shown to significantly increase capacity; for example, this optimization quadruples the capacity for a ground station with eight SFLs. Several networks comprising only two to three ground stations are shown to meet or exceed the capacity of the big dish, Cutting the data rate by half, which saves modem costs and increases the coverage area of each ground station, is shown to increase the average daily capacity of the network for some configurations.

Analysis of meteorological variables in the Australasian region using ground- and space-based GPS techniques

NASA Astrophysics Data System (ADS)

Kuleshov, Yuriy; Choy, Suelynn; Fu, Erjiang Frank; Chane-Ming, Fabrice; Liou, Yuei-An; Pavelyev, Alexander G.

2016-07-01

Results of analysis of meteorological variables (temperature and moisture) in the Australasian region using the global positioning system (GPS) radio occultation (RO) and GPS ground-based observations verified with in situ radiosonde (RS) data are presented. The potential of using ground-based GPS observations for retrieving column integrated precipitable water vapour (PWV) over the Australian continent has been demonstrated using the Australian ground-based GPS reference stations network. Using data from the 15 ground-based GPS stations, the state of the atmosphere over Victoria during a significant weather event, the March 2010 Melbourne storm, has been investigated, and it has been shown that the GPS observations has potential for monitoring the movement of a weather front that has sharp moisture contrast. Temperature and moisture variability in the atmosphere over various climatic regions (the Indian and the Pacific Oceans, the Antarctic and Australia) has been examined using satellite-based GPS RO and in situ RS observations. Investigating recent atmospheric temperature trends over Antarctica, the time series of the collocated GPS RO and RS data were examined, and strong cooling in the lower stratosphere and warming through the troposphere over Antarctica has been identified, in agreement with outputs of climate models. With further expansion of the Global Navigation Satellite Systems (GNSS) system, it is expected that GNSS satellite- and ground-based measurements would be able to provide an order of magnitude larger amount of data which in turn could significantly advance weather forecasting services, climate monitoring and analysis in the Australasian region.

Quantifying capability of a local seismic network in terms of locations and focal mechanism solutions of weak earthquakes

NASA Astrophysics Data System (ADS)

Fojtíková, Lucia; Kristeková, Miriam; Málek, Jiří; Sokos, Efthimios; Csicsay, Kristián; Zahradník, Jiří

2016-01-01

Extension of permanent seismic networks is usually governed by a number of technical, economic, logistic, and other factors. Planned upgrade of the network can be justified by theoretical assessment of the network capability in terms of reliable estimation of the key earthquake parameters (e.g., location and focal mechanisms). It could be useful not only for scientific purposes but also as a concrete proof during the process of acquisition of the funding needed for upgrade and operation of the network. Moreover, the theoretical assessment can also identify the configuration where no improvement can be achieved with additional stations, establishing a tradeoff between the improvement and additional expenses. This paper presents suggestion of a combination of suitable methods and their application to the Little Carpathians local seismic network (Slovakia, Central Europe) monitoring epicentral zone important from the point of seismic hazard. Three configurations of the network are considered: 13 stations existing before 2011, 3 stations already added in 2011, and 7 new planned stations. Theoretical errors of the relative location are estimated by a new method, specifically developed in this paper. The resolvability of focal mechanisms determined by waveform inversion is analyzed by a recent approach based on 6D moment-tensor error ellipsoids. We consider potential seismic events situated anywhere in the studied region, thus enabling "mapping" of the expected errors. Results clearly demonstrate that the network extension remarkably decreases the errors, mainly in the planned 23-station configuration. The already made three-station extension of the network in 2011 allowed for a few real data examples. Free software made available by the authors enables similar application in any other existing or planned networks.

The extended tracking network and indications of baseline precision and accuracy in the North Andes

NASA Technical Reports Server (NTRS)

Freymueller, Jeffrey T.; Kellogg, James N.

1990-01-01

The CASA Uno Global Positioning System (GPS) experiment (January-February 1988) included an extended tracking network which covered three continents in addition to the network of scientific interest in Central and South America. The repeatability of long baselines (400-1000 km) in South America is improved by up to a factor of two in the horizontal vector baseline components by using tracking stations in the Pacific and Europe to supplement stations in North America. In every case but one, the differences between the mean solutions obtained using different tracking networks was equal to or smaller than day-to-day rms repeatabilities for the same baselines. The mean solutions obtained by using tracking stations in North America and the Pacific agreed at the 2-3 millimeter level with those using tracking stations in North America and Europe. The agreement of the extended tracking network solutions suggests that a broad distribution of tracking stations provides better geometric constraints on the satellite orbits and that solutions are not sensitive to changes in tracking network configuration when an extended network is use. A comparison of the results from the North Andes and a baseline in North America suggests that the use of a geometrically strong extended tracking network is most important when the network of interest is far from North America.

Analysis of trends in climate, streamflow, and stream temperature in north coastal California

USGS Publications Warehouse

Madej, Mary Ann; Medley, C. Nicholas; Patterson, Glenn; Parker, Melanie J.

2011-01-01

As part of a broader project analyzing trends in climate, streamflow, vegetation, salmon, and ocean conditions in northern California national park units, we compiled average monthly air temperature and precipitation data from 73 climate stations, streamflow data from 21 river gaging stations, and limited stream temperature data from salmon-bearing rivers in north coastal California. Many climate stations show a statistically significant increase in both average maximum and average minimum air temperature in early fall and midwinter during the last century. Concurrently, average September precipitation has decreased. In many coastal rivers, summer low flow has decreased and summer stream temperatures have increased, which affects summer rearing habitat for salmonids. Nevertheless, because vegetative cover has also changed during this time period, we cannot ascribe streamflow changes to climate change without first assessing water budgets. Although shifts in the timing of the centroid of runoff have been documented in snowmelt-dominated watersheds in the western United States, this was not the case in lower elevation coastal rivers analyzed in this study.

Modernization of the Slovenian National Seismic Network

NASA Astrophysics Data System (ADS)

Vidrih, R.; Godec, M.; Gosar, A.; Sincic, P.; Tasic, I.; Zivcic, M.

2003-04-01

The Environmental Agency of the Republic of Slovenia, the Seismology Office is responsible for the fast and reliable information about earthquakes, originating in the area of Slovenia and nearby. In the year 2000 the project Modernization of the Slovenian National Seismic Network started. The purpose of a modernized seismic network is to enable fast and accurate automatic location of earthquakes, to determine earthquake parameters and to collect data of local, regional and global earthquakes. The modernized network will be finished in the year 2004 and will consist of 25 Q730 remote broadband data loggers based seismic station subsystems transmitting in real-time data to the Data Center in Ljubljana, where the Seismology Office is located. The remote broadband station subsystems include 16 surface broadband seismometers CMG-40T, 5 broadband seismometers CMG-40T with strong motion accelerographs EpiSensor, 4 borehole broadband seismometers CMG-40T, all with accurate timing provided by GPS receivers. The seismic network will cover the entire Slovenian territory, involving an area of 20,256 km2. The network is planned in this way; more seismic stations will be around bigger urban centres and in regions with greater vulnerability (NW Slovenia, Krsko Brezice region). By the end of the year 2002, three old seismic stations were modernized and ten new seismic stations were built. All seismic stations transmit data to UNIX-based computers running Antelope system software. The data is transmitted in real time using TCP/IP protocols over the Goverment Wide Area Network . Real-time data is also exchanged with seismic networks in the neighbouring countries, where the data are collected from the seismic stations, close to the Slovenian border. A typical seismic station consists of the seismic shaft with the sensor and the data acquisition system and, the service shaft with communication equipment (modem, router) and power supply with a battery box. which provides energy in case of mains failure. The data acquisition systems are recording continuous time-series sampled at 200 sps, 20 sps and 1sps.

Ground and surface temperature variability for remote sensing of soil moisture in a heterogeneous landscape

USGS Publications Warehouse

Giraldo, M.A.; Bosch, D.; Madden, M.; Usery, L.; Finn, M.

2009-01-01

At the Little River Watershed (LRW) heterogeneous landscape near Tifton Georgia US an in situ network of stations operated by the US Department of Agriculture-Agriculture Research Service-Southeast Watershed Research Lab (USDA-ARS-SEWRL) was established in 2003 for the long term study of climatic and soil biophysical processes. To develop an accurate interpolation of the in situ readings that can be used to produce distributed representations of soil moisture (SM) and energy balances at the landscape scale for remote sensing studies, we studied (1) the temporal and spatial variations of ground temperature (GT) and infra red temperature (IRT) within 30 by 30 m plots around selected network stations; (2) the relationship between the readings from the eight 30 by 30 m plots and the point reading of the network stations for the variables SM, GT and IRT; and (3) the spatial and temporal variation of GT and IRT within agriculture landuses: grass, orchard, peanuts, cotton and bare soil in the surrounding landscape. The results showed high correlations between the station readings and the adjacent 30 by 30 m plot average value for SM; high seasonal independent variation in the GT and IRT behavior among the eight 30 by 30 m plots; and site specific, in-field homogeneity in each 30 by 30 m plot. We found statistical differences in the GT and IRT between the different landuses as well as high correlations between GT and IRT regardless of the landuse. Greater standard deviations for IRT than for GT (in the range of 2-4) were found within the 30 by 30 m, suggesting that when a single point reading for this variable is selected for the validation of either remote sensing data or water-energy models, errors may occur. The results confirmed that in this landscape homogeneous 30 by 30 m plots can be used as landscape spatial units for soil moisture and ground temperature studies. Under this landscape conditions small plots can account for local expressions of environmental processes, decreasing the errors and uncertainties in remote sensing estimates caused by landscape heterogeneity.

Classification of rainfall events for weather forecasting purposes in andean region of Colombia

NASA Astrophysics Data System (ADS)

Suárez Hincapié, Joan Nathalie; Romo Melo, Liliana; Vélez Upegui, Jorge Julian; Chang, Philippe

2016-04-01

This work presents a comparative analysis of the results of applying different methodologies for the identification and classification of rainfall events of different duration in meteorological records of the Colombian Andean region. In this study the work area is the urban and rural area of Manizales that counts with a monitoring hydro-meteorological network. This network is composed of forty-five (45) strategically located stations, this network is composed of forty-five (45) strategically located stations where automatic weather stations record seven climate variables: air temperature, relative humidity, wind speed and direction, rainfall, solar radiation and barometric pressure. All this information is sent wirelessly every five (5) minutes to a data warehouse located at the Institute of Environmental Studies-IDEA. With obtaining the series of rainfall recorded by the hydrometeorological station Palogrande operated by the National University of Colombia in Manizales (http://froac.manizales.unal.edu.co/bodegaIdea/); it is with this information that we proceed to perform behavior analysis of other meteorological variables, monitored at surface level and that influence the occurrence of such rainfall events. To classify rainfall events different methodologies were used: The first according to Monjo (2009) where the index n of the heavy rainfall was calculated through which various types of precipitation are defined according to the intensity variability. A second methodology that permitted to produce a classification in terms of a parameter β introduced by Rice and Holmberg (1973) and adapted by Llasat and Puigcerver, (1985, 1997) and the last one where a rainfall classification is performed according to the value of its intensity following the issues raised by Linsley (1977) where the rains can be considered light, moderate and strong fall rates to 2.5 mm / h; from 2.5 to 7.6 mm / h and above this value respectively for the previous classifications. The main contribution which is done with this research is the obtainment elements to optimize and to improve the spatial resolution of the results obtained with mesoscale models such as the Weather Research & Forecasting Model- WRF, used in Colombia for the purposes of weather forecasting and that in addition produces other tools used in current issues such as risk management.

Background noise spectra of global seismic stations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wada, M.M.; Claassen, J.P.

1996-08-01

Over an extended period of time station noise spectra were collected from various sources for use in estimating the detection and location performance of global networks of seismic stations. As the database of noise spectra enlarged and duplicate entries became available, an effort was mounted to more carefully select station noise spectra while discarding others. This report discusses the methodology and criteria by which the noise spectra were selected. It also identifies and illustrates the station noise spectra which survived the selection process and which currently contribute to the modeling efforts. The resulting catalog of noise statistics not only benefitsmore » those who model network performance but also those who wish to select stations on the basis of their noise level as may occur in designing networks or in selecting seismological data for analysis on the basis of station noise level. In view of the various ways by which station noise were estimated by the different contributors, it is advisable that future efforts which predict network performance have available station noise data and spectral estimation methods which are compatible with the statistics underlying seismic noise. This appropriately requires (1) averaging noise over seasonal and/or diurnal cycles, (2) averaging noise over time intervals comparable to those employed by actual detectors, and (3) using logarithmic measures of the noise.« less

Optimal base station placement for wireless sensor networks with successive interference cancellation.

PubMed

Shi, Lei; Zhang, Jianjun; Shi, Yi; Ding, Xu; Wei, Zhenchun

2015-01-14

We consider the base station placement problem for wireless sensor networks with successive interference cancellation (SIC) to improve throughput. We build a mathematical model for SIC. Although this model cannot be solved directly, it enables us to identify a necessary condition for SIC on distances from sensor nodes to the base station. Based on this relationship, we propose to divide the feasible region of the base station into small pieces and choose a point within each piece for base station placement. The point with the largest throughput is identified as the solution. The complexity of this algorithm is polynomial. Simulation results show that this algorithm can achieve about 25% improvement compared with the case that the base station is placed at the center of the network coverage area when using SIC.

Gravity data from the Sierra Vista Subwatershed, Upper San Pedro Basin, Arizona

USGS Publications Warehouse

Kennedy, Jeffrey R.

2015-01-01

This report (1) summarizes changes to the Sierra Vista Subwatershed regional time-lapse gravity network with respect to station locations and (2) presents 2014 and 2015 gravity measurements and gravity values at each station. A prior gravity network, established between 2000 and 2005, was revised in 2014 to cover a larger number of stations over a smaller geographic area in order to decrease measurement and interpolation uncertainty. The network currently consists of 59 gravity stations, including 14 absolute-gravity stations. Following above-average rainfall during summer 2014, gravity increased at all but one of the absolute-gravity stations that were observed in both June 2014 and January 2015. This increase in gravity indicates increased groundwater storage in the aquifer and (or) unsaturated zone as a result of rainfall and infiltration.

An EarthScope Plate Boundary Observatory Progress Report

NASA Astrophysics Data System (ADS)

Jackson, M.; Anderson, G.; Blume, F.; Walls, C.; Coyle, B.; Feaux, K.; Friesen, B.; Phillips, D.; Hafner, K.; Johnson, W.; Mencin, D.; Pauk, B.; Dittmann, T.

2007-12-01

UNAVCO is building and operating the Plate Boundary Observatory (PBO), part of the NSF-funded EarthScope project to understand the structure, dynamics, and evolution of the North American continent. When complete in October 2008, the 875 GPS, 103 strain and seismic, and 28 tiltmeters stations will comprise the largest integrated geodetic and seismic network in United States and the second largest in the world. Data from the PBO network will facilitate research into plate boundary deformation with unprecedented scope and detail. As of 1 September 2007, UNAVCO had completed 680 PBO GPS stations and had upgraded 89% of the planned PBO Nucleus stations. Highlights of the past year's work include the expansion of the Alaska subnetwork to 95 continuously-operating stations, including coverage of Akutan and Augustine volcanoes and reconnaissance for future installations on Unimak Island; the installation of nine new stations on Mt. St. Helens; and the arrival of 33 permits for station installations on BLM land in Nevada. The Augustine network provided critical data on magmatic and volcanic processes associated with the 2005-2006 volcanic crisis, and has expanded to a total of 11 stations. Please visit http://pboweb.unavco.org/?pageid=3 for further information on PBO GPS network construction activities. As of September 2007, 41 PBO borehole stations had been installed and three laser strainmeter stations were operating, with a total of 60 borehole stations and 4 laser strainmeters expected by October 2007. In response to direction from the EarthScope community, UNAVCO installed a dense network of six stations along the San Jacinto Fault near Anza, California; installed three of four planned borehole strainmeter stations on Mt. St. Helens; and has densified coverage of the Parkfield area. Please visit http://pboweb.unavco.org/?pageid=8 for more information on PBO strainmeter network construction progress. The combined PBO/Nucleus GPS network provides 350 GB of raw standard rate data, with special downloads of more than 250 GB of high-rate GPS data following large earthquakes in Russia, Tonga, and Peru, as well as for community requests. The standard rate GPS data are processed routinely to generate data products including station position time series, velocity vectors, and related information, and all data products are available from the UNAVCO Facility archive. The PBO seismic network seismic network has provided 201 GB of raw data, which are available via Antelope and Earthworm from PBO and via the IRIS Data Management Center (DMC); we provide data to seismic networks operated from Caltech, UCSD, UCSB, University of Washington, and the Pacific Geosciences Center in Sidney, BC. The PBO strainmeter network has provided 93 GB of raw data, available in both raw native format and SEED format from the Northern California Earthquake Data Center and the IRIS DMC, along with higher-level products such as cleaned strain time series and related information. Please visit http://pboweb.unavco.org/gps_data and http://pboweb.unavco.org/strain_data for more information on PBO GPS and strainmeter/seismic data products, respectively.

Climate, snowpack, and streamflow of Priest River Experimental Forest, revisited

Treesearch

Wade T. Tinkham; Robert Denner; Russell T. Graham

2015-01-01

The climate record of Priest River Experimental Forest has the potential to provide a century-long history of northern Rocky Mountain forest ecosystems. The record, which began in 1911 with the Benton Flat Nursery control weather station, included observations of temperature, precipitation, humidity, and wind. Later, other observations stations were added to the...

47 CFR Alphabetical Index - Part 76

Code of Federal Regulations, 2010 CFR

2010-10-01

...: Notification 76.94 Network programming 76.5 Network programs: nonduplication protection 76.92 Network station....209 Possession of rules 76.301 Prime time 76.5 Program carriages, STV 76.64 Programming, Network 76.5... candidates for 76.205 PURPOSE—Part 76 76.1 Q Qualified TV station, Showing 76.55 R Rate regulation standards...

Climate change and soil salinity: The case of coastal Bangladesh.

PubMed

Dasgupta, Susmita; Hossain, Md Moqbul; Huq, Mainul; Wheeler, David

2015-12-01

This paper estimates location-specific soil salinity in coastal Bangladesh for 2050. The analysis was conducted in two stages: First, changes in soil salinity for the period 2001-2009 were assessed using information recorded at 41 soil monitoring stations by the Soil Research Development Institute. Using these data, a spatial econometric model was estimated linking soil salinity with the salinity of nearby rivers, land elevation, temperature, and rainfall. Second, future soil salinity for 69 coastal sub-districts was projected from climate-induced changes in river salinity and projections of rainfall and temperature based on time trends for 20 Bangladesh Meteorological Department weather stations in the coastal region. The findings indicate that climate change poses a major soil salinization risk in coastal Bangladesh. Across 41 monitoring stations, the annual median projected change in soil salinity is 39 % by 2050. Above the median, 25 % of all stations have projected changes of 51 % or higher.

Index of stations: surface-water data-collection network of Texas, September 1998

USGS Publications Warehouse

Gandara, Susan C.; Barbie, Dana L.

1999-01-01

As of September 30, 1998, the surface-water data-collection network of Texas (table 1) included 313 continuous-recording streamflow stations (D), 22 gage-height record only stations (G), 23 crest-stage partial-record stations (C), 39 flood-hydrograph partial-record stations (H), 25 low-flow partial-record stations (L), 1 continuous-recording temperature station (M1), 25 continuous-recording temperature and conductivity stations (M2), 3 continuous-recording temperature, conductivity, and dissolved oxygen stations (M3), 13 continuous-recording temperature, conductivity, dissolved oxygen, and pH stations (M4), 5 daily chemical-quality stations (Qd), 133 periodic chemical-quality stations (Qp), 16 reservoir/lake surveys for water quality (Qs), and 70 continuous or daily reservoir-content stations (R). Plate 1 identifies the major river basins in Texas and shows the location of the stations listed in table 1.

Weather and Climate Monitoring Protocol, Channel Islands National Park, California

USGS Publications Warehouse

McEachern, Kathryn; Power, Paula; Dye, Linda; Rudolph, Rocky

2008-01-01

Weather and climate are strong drivers of population dynamics, plant and animal spatial distributions, community interactions, and ecosystem states. Information on local weather and climate is crucial in interpreting trends and patterns in the natural environment for resource management, research, and visitor enjoyment. This document describes the weather and climate monitoring program at the Channel Islands National Park (fig. 1), initiated in the 1990s. Manual and automated stations, which continue to evolve as technology changes, are being used for this program. The document reviews the history of weather data collection on each of the five Channel Islands National Park islands, presents program administrative structure, and provides an overview of procedures for data collection, archival, retrieval, and reporting. This program overview is accompanied by the 'Channel Islands National Park Remote Automated Weather Station Field Handbook' and the 'Channel Islands National Park Ranger Weather Station Field Handbook'. These Handbooks are maintained separately at the Channel Island National Park as 'live documents' that are updated as needed to provide a current working manual of weather and climate monitoring procedures. They are available on request from the Weather Program Manager (Channel Islands National Park, 1901 Spinnaker Dr., Ventura, CA 93001; 805.658.5700). The two Field Handbooks describe in detail protocols for managing the four remote automated weather stations (RAWS) and the seven manual Ranger Weather Stations on the islands, including standard operating procedures for equipment maintenance and calibration; manufacturer operating manuals; data retrieval and archiving; metada collection and archival; and local, agency, and vendor contracts.

Internal seismological stations for monitoring a comprehensive test ban theory

NASA Astrophysics Data System (ADS)

Dahlman, O.; Israelson, H.

1980-06-01

Verification of the compliance with a Comprehensive Test Ban on nuclear explosions is expected to be carried out by a seismological verification system of some fifty globally distributed teleseismic stations designed to monitor underground explosions at large distances (beyond 2000 km). It is attempted to assess various technical purposes that such internal stations might serve in relation to a global network of seismological stations. The assessment is based on estimates of the detection capabilities of hypothetical networks of internal stations. Estimates pertaining to currently used detection techniques (P waves) indicate that a limited number (less than 30) of such stations would not improve significantly upon the detection capability that a global network of stations would have throughout the territories of the US and the USSR. Recently available and not yet fully analyzed data indicate however that very high detection capabilities might be obtained in certain regions.

Biological dosimetry to determine the UV radiation climate inside the MIR station and its role in vitamin D biosynthesis

NASA Astrophysics Data System (ADS)

Rettberg, P.; Horneck, G.; Zittermann, A.; Heer, M.

1998-11-01

The vitamin D synthesis in the human skin, is absolutely dependent on UVB radiation. Natural UVB from sunlight is normally absent in the closed environment of a space station like MIR. Therefore it was necessary to investigate the UV radiation climate inside the station resulting from different lamps as well as from occasional solar irradiation behind a UV-transparent quartz window. Biofilms, biologically weighting and integrating UV dosimeters successfully applied on Earth (e.g. in Antarctica) and in space (D-2, Biopan I) were used to determine the biological effectiveness of the UV radiation climate at different locations in the space station. Biofilms were also used to determine the personal UV dose of an individual cosmonaut. These UV data were correlated with the concentration of vitamin D in the cosmonaut's blood and the dietary vitamin D intake. The results showed that the UV radiation climate inside the Mir station is not sufficient for an adequate supply of vitamin D, which should therefore be secured either by vitamin D supplementat and/or by the regular exposure to special UV lamps like those in sun-beds. The use of natural solar UV radiation through the quartz window for `sunbathing' is dangerous and should be avoided even for short exposure periods.

Semipermanent GPS (SPGPS) as a volcano monitoring tool: Rationale, method, and applications

USGS Publications Warehouse

Dzurisin, Daniel; Lisowski, Michael; Wicks, Charles W.

2017-01-01

Semipermanent GPS (SPGPS) is an alternative to conventional campaign or survey-mode GPS (SGPS) and to continuous GPS (CGPS) that offers several advantages for monitoring ground deformation. Unlike CGPS installations, SPGPS stations can be deployed quickly in response to changing volcanic conditions or earthquake activity such as a swarm or aftershock sequence. SPGPS networks can be more focused or more extensive than CGPS installations, because SPGPS equipment can be moved from station to station quickly to increase the total number of stations observed in a given time period. SPGPS networks are less intrusive on the landscape than CGPS installations, which makes it easier to satisfy land-use restrictions in ecologically sensitive areas. SPGPS observations are preferred over SGPS measurements because they provide better precision with only a modest increase in the amount of time, equipment, and personnel required in the field. We describe three applications of the SPGPS method that demonstrate its utility and flexibility. At the Yellowstone caldera, Wyoming, a 9-station SPGPS network serves to densify larger preexisting networks of CGPS and SGPS stations. At the Three Sisters volcanic center, Oregon, a 14-station SPGPS network complements an SGPS network and extends the geographic coverage provided by 3 CGPS stations permitted under wilderness land-use restrictions. In the Basin and Range province in northwest Nevada, a 6-station SPGPS network has been established in response to a prolonged earthquake swarm in an area with only sparse preexisting geodetic coverage. At Three Sisters, the estimated precision of station velocities based on annual ~ 3 month summertime SPGPS occupations from 2009 to 2015 is approximately half that for nearby CGPS stations. Conversely, SPGPS-derived station velocities are about twice as precise as those based on annual ~ 1 week SGPS measurements. After 5 years of SPGPS observations at Three Sisters, the precision of velocity determinations is estimated to be 0.5 mm/yr in longitude, 0.6 mm/yr in latitude, and 0.8 mm/yr in height. We conclude that an optimal approach to monitoring volcano deformation includes complementary CGPS and SPGPS networks, periodic InSAR observations, and measurements from in situ borehole sensors such as tiltmeters or strainmeters. This comprehensive approach provides the spatial and temporal detail necessary to adequately characterize a complex and evolving deformation pattern. Such information is essential to multi-parameter models of magmatic or tectonic processes that can help to guide research efforts, and also to inform hazards assessments and land-use planning decisions.

Hydrologic Record Extension of Water-Level Data in the Everglades Depth Estimation Network (EDEN) Using Artificial Neural Network Models, 2000-2006

USGS Publications Warehouse

Conrads, Paul; Roehl, Edwin A.

2007-01-01

The Everglades Depth Estimation Network (EDEN) is an integrated network of real-time water-level gaging stations, ground-elevation models, and water-surface models designed to provide scientists, engineers, and water-resource managers with current (2000-present) water-depth information for the entire freshwater portion of the greater Everglades. The U.S. Geological Survey Greater Everglades Priority Ecosystem Science provides support for EDEN and the goal of providing quality assured monitoring data for the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. To increase the accuracy of the water-surface models, 25 real-time water-level gaging stations were added to the network of 253 established water-level gaging stations. To incorporate the data from the newly added stations to the 7-year EDEN database in the greater Everglades, the short-term water-level records (generally less than 1 year) needed to be simulated back in time (hindcasted) to be concurrent with data from the established gaging stations in the database. A three-step modeling approach using artificial neural network models was used to estimate the water levels at the new stations. The artificial neural network models used static variables that represent the gaging station location and percent vegetation in addition to dynamic variables that represent water-level data from the established EDEN gaging stations. The final step of the modeling approach was to simulate the computed error of the initial estimate to increase the accuracy of the final water-level estimate. The three-step modeling approach for estimating water levels at the new EDEN gaging stations produced satisfactory results. The coefficients of determination (R2) for 21 of the 25 estimates were greater than 0.95, and all of the estimates (25 of 25) were greater than 0.82. The model estimates showed good agreement with the measured data. For some new EDEN stations with limited measured data, the record extension (hindcasts) included periods beyond the range of the data used to train the artificial neural network models. The comparison of the hindcasts with long-term water-level data proximal to the new EDEN gaging stations indicated that the water-level estimates were reasonable. The percent model error (root mean square error divided by the range of the measured data) was less than 6 percent, and for the majority of stations (20 of 25), the percent model error was less than 1 percent.

Semipermanent GPS (SPGPS) as a volcano monitoring tool: Rationale, method, and applications

NASA Astrophysics Data System (ADS)

Dzurisin, Daniel; Lisowski, Michael; Wicks, Charles W.

2017-09-01

Semipermanent GPS (SPGPS) is an alternative to conventional campaign or survey-mode GPS (SGPS) and to continuous GPS (CGPS) that offers several advantages for monitoring ground deformation. Unlike CGPS installations, SPGPS stations can be deployed quickly in response to changing volcanic conditions or earthquake activity such as a swarm or aftershock sequence. SPGPS networks can be more focused or more extensive than CGPS installations, because SPGPS equipment can be moved from station to station quickly to increase the total number of stations observed in a given time period. SPGPS networks are less intrusive on the landscape than CGPS installations, which makes it easier to satisfy land-use restrictions in ecologically sensitive areas. SPGPS observations are preferred over SGPS measurements because they provide better precision with only a modest increase in the amount of time, equipment, and personnel required in the field. We describe three applications of the SPGPS method that demonstrate its utility and flexibility. At the Yellowstone caldera, Wyoming, a 9-station SPGPS network serves to densify larger preexisting networks of CGPS and SGPS stations. At the Three Sisters volcanic center, Oregon, a 14-station SPGPS network complements an SGPS network and extends the geographic coverage provided by 3 CGPS stations permitted under wilderness land-use restrictions. In the Basin and Range province in northwest Nevada, a 6-station SPGPS network has been established in response to a prolonged earthquake swarm in an area with only sparse preexisting geodetic coverage. At Three Sisters, the estimated precision of station velocities based on annual 3 month summertime SPGPS occupations from 2009 to 2015 is approximately half that for nearby CGPS stations. Conversely, SPGPS-derived station velocities are about twice as precise as those based on annual 1 week SGPS measurements. After 5 years of SPGPS observations at Three Sisters, the precision of velocity determinations is estimated to be 0.5 mm/yr in longitude, 0.6 mm/yr in latitude, and 0.8 mm/yr in height. We conclude that an optimal approach to monitoring volcano deformation includes complementary CGPS and SPGPS networks, periodic InSAR observations, and measurements from in situ borehole sensors such as tiltmeters or strainmeters. This comprehensive approach provides the spatial and temporal detail necessary to adequately characterize a complex and evolving deformation pattern. Such information is essential to multi-parameter models of magmatic or tectonic processes that can help to guide research efforts, and also to inform hazards assessments and land-use planning decisions.

Transformational leadership and group interaction as climate antecedents: a social network analysis.

PubMed

Zohar, Dov; Tenne-Gazit, Orly

2008-07-01

In order to test the social mechanisms through which organizational climate emerges, this article introduces a model that combines transformational leadership and social interaction as antecedents of climate strength (i.e., the degree of within-unit agreement about climate perceptions). Despite their longstanding status as primary variables, both antecedents have received limited empirical research. The sample consisted of 45 platoons of infantry soldiers from 5 different brigades, using safety climate as the exemplar. Results indicate a partially mediated model between transformational leadership and climate strength, with density of group communication network as the mediating variable. In addition, the results showed independent effects for group centralization of the communication and friendship networks, which exerted incremental effects on climate strength over transformational leadership. Whereas centralization of the communication network was found to be negatively related to climate strength, centralization of the friendship network was positively related to it. Theoretical and practical implications are discussed.

Comparison of hybrid spectral-decomposition artificial neural network models for understanding climatic forcing of groundwater levels

NASA Astrophysics Data System (ADS)

Abrokwah, K.; O'Reilly, A. M.

2017-12-01

Groundwater is an important resource that is extracted every day because of its invaluable use for domestic, industrial and agricultural purposes. The need for sustaining groundwater resources is clearly indicated by declining water levels and has led to modeling and forecasting accurate groundwater levels. In this study, spectral decomposition of climatic forcing time series was used to develop hybrid wavelet analysis (WA) and moving window average (MWA) artificial neural network (ANN) models. These techniques are explored by modeling historical groundwater levels in order to provide understanding of potential causes of the observed groundwater-level fluctuations. Selection of the appropriate decomposition level for WA and window size for MWA helps in understanding the important time scales of climatic forcing, such as rainfall, that influence water levels. Discrete wavelet transform (DWT) is used to decompose the input time-series data into various levels of approximate and details wavelet coefficients, whilst MWA acts as a low-pass signal-filtering technique for removing high-frequency signals from the input data. The variables used to develop and validate the models were daily average rainfall measurements from five National Atmospheric and Oceanic Administration (NOAA) weather stations and daily water-level measurements from two wells recorded from 1978 to 2008 in central Florida, USA. Using different decomposition levels and different window sizes, several WA-ANN and MWA-ANN models for simulating the water levels were created and their relative performances compared against each other. The WA-ANN models performed better than the corresponding MWA-ANN models; also higher decomposition levels of the input signal by the DWT gave the best results. The results obtained show the applicability and feasibility of hybrid WA-ANN and MWA-ANN models for simulating daily water levels using only climatic forcing time series as model inputs.

Modeling soil temperature change in Seward Peninsula, Alaska

NASA Astrophysics Data System (ADS)

Debolskiy, M. V.; Nicolsky, D.; Romanovsky, V. E.; Muskett, R. R.; Panda, S. K.

2017-12-01

Increasing demand for assessment of climate change-induced permafrost degradation and its consequences promotes creation of high-resolution modeling products of soil temperature changes. This is especially relevant for areas with highly vulnerable warm discontinuous permafrost in the Western Alaska. In this study, we apply ecotype-based modeling approach to simulate high-resolution permafrost distribution and its temporal dynamics in Seward Peninsula, Alaska. To model soil temperature dynamics, we use a transient soil heat transfer model developed at the Geophysical Institute Permafrost Laboratory (GIPL-2). The model solves one dimensional nonlinear heat equation with phase change. The developed model is forced with combination of historical climate and different future scenarios for 1900-2100 with 2x2 km resolution prepared by Scenarios Network for Alaska and Arctic Planning (2017). Vegetation, snow and soil properties are calibrated by ecotype and up-scaled by using Alaska Existing Vegetation Type map for Western Alaska (Flemming, 2015) with 30x30 m resolution provided by Geographic Information Network of Alaska (UAF). The calibrated ecotypes cover over 75% of the study area. We calibrate the model using a data assimilation technique utilizing available observations of air, surface and sub-surface temperatures and snow cover collected by various agencies and research groups (USGS, Geophysical Institute, USDA). The calibration approach takes into account a natural variability between stations in the same ecotype and finds an optimal set of model parameters (snow and soil properties) within the study area. This approach allows reduction in microscale heterogeneity and aggregated soil temperature data from shallow boreholes which is highly dependent on local conditions. As a result of this study we present a series of preliminary high resolution maps for the Seward Peninsula showing changes in the active layer depth and ground temperatures for the current climate and future climate change scenarios.

The NSF Earthscope USArray Instrumentation Network

NASA Astrophysics Data System (ADS)

Davis, G. A.; Vernon, F.

2012-12-01

Since 2004, the Transportable Array component of the USArray Instrumentation Network has collected high resolution seismic data in near real-time from over 400 geographically distributed seismic stations. The deployed footprint of the array has steadily migrated across the continental United States, starting on the west coast and gradually moving eastward. As the network footprint shifts, stations from various regional seismic networks have been incorporated into the dataset. In 2009, an infrasound and barometric sensor component was added to existing core stations and to all new deployments. The ongoing success of the project can be attributed to a number of factors, including reliable communications to each site, on-site data buffering, largely homogenous data logging hardware, and a common phase-locked time reference between all stations. Continuous data quality is ensured by thorough human and automated review of data from the primary sensors and over 24 state-of-health parameters from each station. The staff at the Array Network Facility have developed a number of tools to visualize data and troubleshoot problematic stations remotely. In the event of an emergency or maintenance on the server hardware, data acquisition can be shifted to alternate data centers through the use of virtualization technologies.

An overview of the technical design of MSAT mobile satellite communications services

NASA Astrophysics Data System (ADS)

Davies, N. George

The Canadian MSAT mobile satellite communications system is being implemented in cooperation with the American Mobile Satellite Consortium (AMSC). Two satellites are to be jointly acquired and each satellite is expected to backup the other. This paper describes the technical concepts of the services to be offered and the baseline planning of the infrastructure for the ground segment. MSAT service requirements are analyzed for mobile radio, telephone, data, and aeronautical services. The MSAT system will use nine beams in a narrow range of L-band frequencies with frequency reuse. Beams may be added to cover flight information areas in the Atlantic and Pacific oceans. The elements of the network architecture are: a network control centre, data hub stations, gateway stations, base stations, mobile terminals, and a signalling system to interconnect the elements of the system. The network control center will manage the network and allocate space segment capacity; data hub stations will support a switched packet mobile data service; the gateway stations will provide interconnection to the public telephone system and data networks; and the base stations will support private circuit switched voice and data services. Several alternative designs for the signalling system are described.

A near-optimum procedure for selecting stations in a streamgaging network

USGS Publications Warehouse

Lanfear, Kenneth J.

2005-01-01

Two questions are fundamental to Federal government goals for a network of streamgages which are operated by the U.S. Geological Survey: (1) how well does the present network of streamagaging stations meet defined Federal goals and (2) what is the optimum set of stations to add or reactivate to support remaining goals? The solution involves an incremental-stepping procedure that is based on Basic Feasible Incremental Solutions (BFIS?s) where each BFIS satisfies at least one Federal streamgaging goal. A set of minimum Federal goals for streamgaging is defined to include water measurements for legal compacts and decrees, flooding, water budgets, regionalization of streamflow characteristics, and water quality. Fully satisfying all these goals by using the assumptions outlined in this paper would require adding 887 new streamgaging stations to the U.S. Geological Survey network and reactivating an additional 857 stations that are currently inactive.

Web Information Systems for Monitoring and Control of Indoor Air Quality at Subway Stations

NASA Astrophysics Data System (ADS)

Choi, Gi Heung; Choi, Gi Sang; Jang, Joo Hyoung

In crowded subway stations indoor air quality (IAQ) is a key factor for ensuring the safety, health and comfort of passengers. In this study, a framework for web-based information system in VDN environment for monitoring and control of IAQ in subway stations is suggested. Since physical variables that describing IAQ need to be closely monitored and controlled in multiple locations in subway stations, concept of distributed monitoring and control network using wireless media needs to be implemented. Connecting remote wireless sensor network and device (LonWorks) networks to the IP network based on the concept of VDN can provide a powerful, integrated, distributed monitoring and control performance, making a web-based information system possible.

The Deep Space Network

NASA Technical Reports Server (NTRS)

1979-01-01

Deep Space Network progress in flight project support, tracking and data acquisition, research and technology, network engineering, hardware and software implementation, and operations is cited. Topics covered include: tracking and ground based navigation; spacecraft/ground communication; station control and operations technology; ground communications; and deep space stations.

Detecting urban warming signals in climate records

NASA Astrophysics Data System (ADS)

He, Yuting; Jia, Gensuo; Hu, Yonghong; Zhou, Zijiang

2013-07-01

Determining whether air temperatures recorded at meteorological stations have been contaminated by the urbanization process is still a controversial issue at the global scale. With support of historical remote sensing data, this study examined the impacts of urban expansion on the trends of air temperature at 69 meteorological stations in Beijing, Tianjin, and Hebei Province over the last three decades. There were significant positive relations between the two factors at all stations. Stronger warming was detected at the meteorological stations that experienced greater urbanization, i.e., those with a higher urbanization rate. While the total urban area affects the absolute temperature values, the change of the urban area (urbanization rate) likely affects the temperature trend. Increases of approximately 10% in urban area around the meteorological stations likely contributed to the 0.13°C rise in air temperature records in addition to regional climate warming. This study also provides a new approach to selecting reference stations based on remotely sensed urban fractions. Generally, the urbanization-induced warming contributed to approximately 44.1% of the overall warming trends in the plain region of study area during the past 30 years, and the regional climate warming was 0.30°C (10 yr)-1 in the last three decades.

WWLLN and Earth Networks new combined Global Lightning Network: First Look

NASA Astrophysics Data System (ADS)

Holzworth, R. H., II; Brundell, J. B.; Sloop, C.; Heckman, S.; Rodger, C. J.

2016-12-01

Lightning VLF sferic waveforms detected around the world by WWLLN (World Wide Lightning Location Network) and by Earth Networks WTLN receivers are being analyzed in real time to calculate the time of group arrival (TOGA) of the sferic wave packet at each station. These times (TOGAs) are then used for time-of-arrival analysis to determine the source lightning location. Beginning in 2016 we have successfully implemented the operational software to allow the incorporation of waveforms from hundreds of Earth Networks sensors into the normal WWLLN TOGA processing, resulting in a new global lightning distribution which has over twice as many stroke locations as the WWLLN-only data set. The combined global lightning network shows marked improvement over the WWLLN-only data set in regions such as central and southern Africa, and over the Indian subcontinent. As of July 2016 the new data set is typically running at about 230% of WWLLN-only in terms of total strokes, and some days over 250%, using data from 65 to 70 WWLLN stations, combined with the VLF channel from about 160 Earth Networks stations. The Earth Networks lightning network includes nearly 1000 receiving stations, so it is anticipated we will be able to further increase the total stations being used for the new combined network while still maintaining a relatively smooth global distribution of the sensors. Detailed comparisons of the new data set with WWLLN-only data, as well as with independent lightning location networks including WTLN in the CONUS and NZLDN in New Zealand will be presented.

Novel Methods to Explore Building Energy Sensitivity to Climate and Heat Waves Using PNNL's BEND Model

NASA Astrophysics Data System (ADS)

Burleyson, C. D.; Voisin, N.; Taylor, T.; Xie, Y.; Kraucunas, I.

2017-12-01

The DOE's Pacific Northwest National Laboratory (PNNL) has been developing the Building ENergy Demand (BEND) model to simulate energy usage in residential and commercial buildings responding to changes in weather, climate, population, and building technologies. At its core, BEND is a mechanism to aggregate EnergyPlus simulations of a large number of individual buildings with a diversity of characteristics over large spatial scales. We have completed a series of experiments to explore methods to calibrate the BEND model, measure its ability to capture interannual variability in energy demand due to weather using simulations of two distinct weather years, and understand the sensitivity to the number and location of weather stations used to force the model. The use of weather from "representative cities" reduces computational costs, but often fails to capture spatial heterogeneity that may be important for simulations aimed at understanding how building stocks respond to a changing climate (Fig. 1). We quantify the potential reduction in temperature and load biases from using an increasing number of weather stations across the western U.S., ranging from 8 to roughly 150. Using 8 stations results in an average absolute summertime temperature bias of 4.0°C. The mean absolute bias drops to 1.5°C using all available stations. Temperature biases of this magnitude translate to absolute summertime mean simulated load biases as high as 13.8%. Additionally, using only 8 representative weather stations can lead to a 20-40% bias of peak building loads under heat wave or cold snap conditions, a significant error for capacity expansion planners who may rely on these types of simulations. This analysis suggests that using 4 stations per climate zone may be sufficient for most purposes. Our novel approach, which requires no new EnergyPlus simulations, could be useful to other researchers designing or calibrating aggregate building model simulations - particularly those looking at the impact of future climate scenarios. Fig. 1. An example of temperature bias that results from using 8 representative weather stations: (a) surface temperature from NLDAS on 5-July 2008 at 2000 UTC; (b) temperature from 8 representative stations at the same time mapped to all counties within a given IECC climate zone; (c) the difference between (a) and (b).

Estimating network effect in geocenter motion: Applications

NASA Astrophysics Data System (ADS)

Zannat, Umma Jamila; Tregoning, Paul

2017-10-01

The network effect is the error associated with the subsampling of the Earth surface by space geodetic networks. It is an obstacle toward the precise measurement of geocenter motion, that is, the relative motion between the center of mass of the Earth system and the center of figure of the Earth surface. In a complementary paper, we proposed a theoretical approach to estimate the magnitude of this effect from the displacement fields predicted by geophysical models. Here we evaluate the effectiveness of our estimate for two illustrative physical processes: coseismic displacements inducing instantaneous changes in the Helmert parameters and elastic deformation due to surface water movements causing secular drifts in those parameters. For the first, we consider simplified models of the 2004 Sumatra-Andaman and the 2011 Tōhoku-Oki earthquakes, and for the second, we use the observations of the Gravity Recovery and Climate Experiment, complemented by an ocean model. In both case studies, it is found that the magnitude of the network effect, even for a large global network, is often as large as the magnitude of the changes in the Helmert parameters themselves. However, we also show that our proposed modification to the definition of the center of network frame to include weights proportional to the area of the Earth surface that the stations represent can significantly reduce the network effect in most cases.

Detecting Earthquakes over a Seismic Network using Single-Station Similarity Measures

NASA Astrophysics Data System (ADS)

Bergen, Karianne J.; Beroza, Gregory C.

2018-03-01

New blind waveform-similarity-based detection methods, such as Fingerprint and Similarity Thresholding (FAST), have shown promise for detecting weak signals in long-duration, continuous waveform data. While blind detectors are capable of identifying similar or repeating waveforms without templates, they can also be susceptible to false detections due to local correlated noise. In this work, we present a set of three new methods that allow us to extend single-station similarity-based detection over a seismic network; event-pair extraction, pairwise pseudo-association, and event resolution complete a post-processing pipeline that combines single-station similarity measures (e.g. FAST sparse similarity matrix) from each station in a network into a list of candidate events. The core technique, pairwise pseudo-association, leverages the pairwise structure of event detections in its network detection model, which allows it to identify events observed at multiple stations in the network without modeling the expected move-out. Though our approach is general, we apply it to extend FAST over a sparse seismic network. We demonstrate that our network-based extension of FAST is both sensitive and maintains a low false detection rate. As a test case, we apply our approach to two weeks of continuous waveform data from five stations during the foreshock sequence prior to the 2014 Mw 8.2 Iquique earthquake. Our method identifies nearly five times as many events as the local seismicity catalog (including 95% of the catalog events), and less than 1% of these candidate events are false detections.

NASA's Next Generation Space Geodesy Network

NASA Technical Reports Server (NTRS)

Desai, S. D.; Gross, R. S.; Hilliard, L.; Lemoine, F. G.; Long, J. L.; Ma, C.; McGarry, J. F.; Merkowitz, S. M.; Murphy, D.; Noll, C. E.;

NetMOD version 1.0 user's manual

DOE Office of Scientific and Technical Information (OSTI.GOV)

Merchant, Bion John

2014-01-01

NetMOD (Network Monitoring for Optimal Detection) is a Java-based software package for conducting simulation of seismic networks. Specifically, NetMOD simulates the detection capabilities of seismic monitoring networks. Network simulations have long been used to study network resilience to station outages and to determine where additional stations are needed to reduce monitoring thresholds. NetMOD makes use of geophysical models to determine the source characteristics, signal attenuation along the path between the source and station, and the performance and noise properties of the station. These geophysical models are combined to simulate the relative amplitudes of signal and noise that are observed atmore » each of the stations. From these signal-to-noise ratios (SNR), the probability of detection can be computed given a detection threshold. This manual describes how to configure and operate NetMOD to perform seismic detection simulations. In addition, NetMOD is distributed with a simulation dataset for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) International Monitoring System (IMS) seismic network for the purpose of demonstrating NetMOD's capabilities and providing user training. The tutorial sections of this manual use this dataset when describing how to perform the steps involved when running a simulation.« less

Development of Sub-Daily Intensity Duration Frequency (IDF) Curves for Major Urban Areas in India

NASA Astrophysics Data System (ADS)

Ali, H.; Mishra, V.

2014-12-01

Extreme precipitation events disrupt urban transportation and cause enormous damage to infrastructure. Urban areas are fast responding catchments due to significant impervious surface. Stormwater designs based on daily rainfall data provide inadequate information. We, therefore, develop intensity-duration-frequency curves using sub-daily (1 hour to 12 hour) rainfall data for 57 major urban areas in India. While rain gage stations data from urban areas are most suitable, but stations are unevenly distributed and their data have gaps and inconsistencies. Therefore, we used hourly rainfall data from the Modern Era Retrospective-analysis for Research and Applications (MERRA), which provides a long term data (1979 onwards). Since reanalysis products have uncertainty associated with them we need to enhance their accuracy before their application. We compared daily rain gage station data obtained from Global Surface Summary of Day Data (GSOD) available for 65 stations for the period of 2000-2010 with gridded daily rainfall data provided by Indian Meteorological Department (IMD). 3-hourly data from NOAA/Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) were aggregated to daily for comparison with GSOD station data . TMPA is found to be best correlated with GSOD data. We used TMPA data to correct MERRA's hourly precipitation, which were applied to develop IDF curves. We compared results with IDF curves from empirical methods and found substantial disparities in the existing stormwater designs in India.

Evaluation of stream chemistry trends in US Geological Survey reference watersheds, 1970-2010.

PubMed

Mast, M Alisa

2013-11-01

The Hydrologic Benchmark Network (HBN) is a long-term monitoring program established by the US Geological Survey in the 1960s to track changes in the streamflow and stream chemistry in undeveloped watersheds across the USA. Trends in stream chemistry were tested at 15 HBN stations over two periods (1970-2010 and 1990-2010) using the parametric Load Estimator (LOADEST) model and the nonparametric seasonal Kendall test. Trends in annual streamflow and precipitation chemistry also were tested to help identify likely drivers of changes in stream chemistry. At stations in the northeastern USA, there were significant declines in stream sulfate, which were consistent with declines in sulfate deposition resulting from the reductions in SO₂ emissions mandated under the Clean Air Act Amendments. Sulfate declines in stream water were smaller than declines in deposition suggesting sulfate may be accumulating in watershed soils and thereby delaying the stream response to improvements in deposition. Trends in stream chemistry at stations in other part of the country generally were attributed to climate variability or land disturbance. Despite declines in sulfate deposition, increasing stream sulfate was observed at several stations and appeared to be linked to periods of drought or declining streamflow. Falling water tables might have enhanced oxidation of organic matter in wetlands or pyrite in mineralized bedrock thereby increasing sulfate export in surface water. Increasing sulfate and nitrate at a station in the western USA were attributed to release of soluble salts and nutrients from soils following a large wildfire in the watershed.

The deep space network

NASA Technical Reports Server (NTRS)

1974-01-01

The progress is reported of Deep Space Network (DSN) research in the following areas: (1) flight project support, (2) spacecraft/ground communications, (3) station control and operations technology, (4) network control and processing, and (5) deep space stations. A description of the DSN functions and facilities is included.

Optimal Base Station Placement for Wireless Sensor Networks with Successive Interference Cancellation

PubMed Central

Shi, Lei; Zhang, Jianjun; Shi, Yi; Ding, Xu; Wei, Zhenchun

2015-01-01

We consider the base station placement problem for wireless sensor networks with successive interference cancellation (SIC) to improve throughput. We build a mathematical model for SIC. Although this model cannot be solved directly, it enables us to identify a necessary condition for SIC on distances from sensor nodes to the base station. Based on this relationship, we propose to divide the feasible region of the base station into small pieces and choose a point within each piece for base station placement. The point with the largest throughput is identified as the solution. The complexity of this algorithm is polynomial. Simulation results show that this algorithm can achieve about 25% improvement compared with the case that the base station is placed at the center of the network coverage area when using SIC. PMID:25594600

Milliwatt radioisotope power supply for the PASCAL Mars surface stations

NASA Astrophysics Data System (ADS)

Allen, Daniel T.; Murbach, Marcus S.

2001-02-01

A milliwatt power supply is being developed based on the 1 watt Light-Weight Radioisotope Heater Unit (RHU), which has already been used to provide heating alone on numerous spacecraft. In the past year the power supply has been integrated into the design of the proposed PASCAL Mars Network Mission, which is intended to place 24 surface climate monitoring stations on Mars. The PASCAL Mars mission calls for the individual surface stations to be transported together in one spacecraft on a trajectory direct from launch to orbit around Mars. From orbit around Mars each surface station will be deployed on a SCRAMP (slotted compression ramp) probe and, after aerodynamic and parachute deceleration, land at a preselected location on the planet. During descent sounding data and still images will be accumulated, and, once on the surface, the station will take measurements of pressure, temperature and overhead atmospheric optical depth for a period of 10 Mars years (18.8 Earth years). Power for periodic data acquisition and transmission to orbital then to Earth relay will come from a bank of ultracapacitors which will be continuously recharged by the radioisotope power supply. This electronic system has been designed and a breadboard built. In the ultimate design the electronics will be arrayed on the exterior surface of the radioisotope power supply in order to take advantage of the reject heat. This assembly in turn is packaged within the SCRAMP, and that assembly comprises the surface station. An electrically heated but otherwise prototypical power supply was operated in combination with the surface station breadboard system, which included the ultracapacitors. Other issues addressed in this work have been the capability of the generator to withstand the mechanical shock of the landing on Mars and the effectiveness of the generator's multi-foil vacuum thermal insulation. .

Chemical, physical, biochemical, and bacteriological characteristics at selected stream sites in Puerto Rico, 1976-77

USGS Publications Warehouse

Quinones, F.; Vasquez, Pedro; Pena-Cortes, Rafael

1978-01-01

In 1969, the Caribbean District of the U.S. Geological Survey, in cooperation with the Commonwealth of Puerto Rico, initiated the operation of a network to monitor some parameters indicative of water-quality changes at selected stream sites. In 1974, at the request of the Environmental Quality Board of Puerto Rico, the network was modified to conform with the Environmental Protection Agency National Water Quality Surveillance System. The purpose of the present network is to monitor changes in water quality between the upstream and downstream stations. The expanded network consisted of 58 stations. During 1976, five had been discontinued. One other was added late in 1976. Most of the stations in the original network have been maintained, thus providing some degree of continuity. The monitoring stations used in this report are shown on a map and listed in a table. The results of the network operation are summarized for the period July 1976 to August 1977. (Woodard-USGS)

Impacts of uncertainties in European gridded precipitation observations on regional climate analysis.

PubMed

Prein, Andreas F; Gobiet, Andreas

2017-01-01

Gridded precipitation data sets are frequently used to evaluate climate models or to remove model output biases. Although precipitation data are error prone due to the high spatio-temporal variability of precipitation and due to considerable measurement errors, relatively few attempts have been made to account for observational uncertainty in model evaluation or in bias correction studies. In this study, we compare three types of European daily data sets featuring two Pan-European data sets and a set that combines eight very high-resolution station-based regional data sets. Furthermore, we investigate seven widely used, larger scale global data sets. Our results demonstrate that the differences between these data sets have the same magnitude as precipitation errors found in regional climate models. Therefore, including observational uncertainties is essential for climate studies, climate model evaluation, and statistical post-processing. Following our results, we suggest the following guidelines for regional precipitation assessments. (1) Include multiple observational data sets from different sources (e.g. station, satellite, reanalysis based) to estimate observational uncertainties. (2) Use data sets with high station densities to minimize the effect of precipitation undersampling (may induce about 60% error in data sparse regions). The information content of a gridded data set is mainly related to its underlying station density and not to its grid spacing. (3) Consider undercatch errors of up to 80% in high latitudes and mountainous regions. (4) Analyses of small-scale features and extremes are especially uncertain in gridded data sets. For higher confidence, use climate-mean and larger scale statistics. In conclusion, neglecting observational uncertainties potentially misguides climate model development and can severely affect the results of climate change impact assessments.

A Statewide Private Microwave Wide Area Network for Real-time Natural Hazard Monitoring

NASA Astrophysics Data System (ADS)

Williams, M. C.; Kent, G.; Smith, K. D.; Plank, G.; Slater, D.; Torrisi, J.; Presser, R.; Straley, K.

2013-12-01

The Nevada Seismological Laboratory (NSL) at the University of Nevada, Reno, operates the Nevada Seismic Network, a collection of ground motion instruments installed throughout Nevada and California, for the purposes of detecting, locating, and notifying the public of earthquakes in the state. To perform these tasks effectively, NSL has designed and built a statewide wireless microwave wide-area network (WAN) in order to receive ground motion data in near real-time. This network consists of radio access points, backhauls, and backbone communication sites transmitting time-series, images, and datalogger diagnostics to our data center servers in Reno. This privately managed communication network greatly reduces the dependence on third-party infrastructure (e.g. commercial cellular networks), and is vital for emergency management response and system uptime. Any individual seismograph or data collection device is networked through a wireless point-to-multipoint connection to a remote access point (AP) using a low-cost radio/routerboard combination. Additional point-to-point connections from AP's to radio backhauls and/or mountaintop backbone sites allow the Data Center in Reno to communicate with and receive data directly from each datalogger. Dataloggers, radios, and routers can be configured using tablets on-site, or via desktop computers at the Data Center. Redundant mountaintop links can be added to the network and facilitate the re-routing of data (similar to a meshed network) in the event of a faulty, failing, or noisy communication site. All routers, radios, and servers, including those at the Data Center, have redundant power and can operate independently in the event of a grid power or public Internet outage. A managed server room at the Data Center processes earthquake data for notifications and acts as a data source for remote users. Consisting of about 500 hosts, and spanning hundreds of miles, this WAN provides network operators access to each router and datalogger in our seismic network not only for data collection, but also for maintenance and quality control. This has resulted in several partnerships with other agencies. In addition to our seismic station network for earthquake monitoring, we currently manage ~400 more channels of data (many running at 500 Hz) for the National Center for Nuclear Security (NCNS) Source Physics Experiments, a series of chemical explosions at the Nevada National Security Site. Some of our mountaintop stations have been experimentally equipped with near-infrared high-definition fire cameras for wildfire monitoring, and have recently recorded the Bison and Pedlar fires in northwest Nevada. Data for the Nevada EPSCor climate program also utilizes the NSL WAN. Real-time access to data for these experiments greatly reduces the effort required for data archival, quality control, and monitoring equipment failures. Future plans include increasing density of stations in urban areas such as Reno and Las Vegas, and expanding coverage to Tahoe and eastern Nevada.

On the long-range dependence properties of annual precipitation using a global network of instrumental measurements

NASA Astrophysics Data System (ADS)

Tyralis, Hristos; Dimitriadis, Panayiotis; Koutsoyiannis, Demetris; O'Connell, Patrick Enda; Tzouka, Katerina; Iliopoulou, Theano

2018-01-01

The long-range dependence (LRD) is considered an inherent property of geophysical processes, whose presence increases uncertainty. Here we examine the spatial behaviour of LRD in precipitation by regressing the Hurst parameter estimate of mean annual precipitation instrumental data which span from 1916-2015 and cover a big area of the earth's surface on location characteristics of the instrumental data stations. Furthermore, we apply the Mann-Kendall test under the LRD assumption (MKt-LRD) to reassess the significance of observed trends. To summarize the results, the LRD is spatially clustered, it seems to depend mostly on the location of the stations, while the predictive value of the regression model is good. Thus when investigating for LRD properties we recommend that the local characteristics should be considered. The application of the MKt-LRD suggests that no significant monotonic trend appears in global precipitation, excluding the climate type D (snow) regions in which positive significant trends appear.

Optimization of municipal pressure pumping station layout and sewage pipe network design

NASA Astrophysics Data System (ADS)

Tian, Jiandong; Cheng, Jilin; Gong, Yi

2018-03-01

Accelerated urbanization places extraordinary demands on sewer networks; thus optimization research to improve the design of these systems has practical significance. In this article, a subsystem nonlinear programming model is developed to optimize pumping station layout and sewage pipe network design. The subsystem model is expanded into a large-scale complex nonlinear programming system model to find the minimum total annual cost of the pumping station and network of all pipe segments. A comparative analysis is conducted using the sewage network in Taizhou City, China, as an example. The proposed method demonstrated that significant cost savings could have been realized if the studied system had been optimized using the techniques described in this article. Therefore, the method has practical value for optimizing urban sewage projects and provides a reference for theoretical research on optimization of urban drainage pumping station layouts.

Digital intelligent booster for DCC miniature train networks

NASA Astrophysics Data System (ADS)

Ursu, M. P.; Condruz, D. A.

2017-08-01

Modern miniature trains are now driven by means of the DCC (Digital Command and Control) system, which allows the human operator or a personal computer to launch commands to each individual train or even to control different features of the same train. The digital command station encodes these commands and sends them to the trains by means of electrical pulses via the rails of the railway network. Due to the development of the miniature railway network, it may happen that the power requirement of the increasing number of digital locomotives, carriages and accessories exceeds the nominal output power of the digital command station. This digital intelligent booster relieves the digital command station from powering the entire railway network all by itself, and it automatically handles the multiple powered sections of the network. This electronic device is also able to detect and process short-circuits and overload conditions, without the intervention of the digital command station.

Coastal Vertical Land motion in the German Bight

NASA Astrophysics Data System (ADS)

Becker, Matthias; Fenoglio, Luciana; Reckeweg, Florian

2017-04-01

In the framework of the ESA Sea Level Climate Change Initiative (CCI) we analyse a set of GNSS equipped tide gauges at the German Bight. Main goals are the determination of tropospheric zenith delay corrections for altimetric observations, precise coordinates in ITRF2008 and vertical land motion (VLM) rates of the tide gauge stations. These are to be used for georeferencing the tide gauges and the correction of tide gauge observations for VLM. The set of stations includes 38 GNSS stations. 19 stations are in the German Bight, where 15 of them belong to the Bundesanstalt für Gewässerkunde, 3 to EUREF and 1 to GREF. These stations are collocated with tide gauges (TGs). The other 19 GNSS stations in the network belong to EUREF, IGS and GREF. We analyse data in the time span from 2008 till the end of 2016 with the Bernese PPP processing approach. Data are partly rather noisy and disturbed by offsets and data gaps at the coastal TG sites. Special effort is therefore put into a proper estimation of the VLM. We use FODITS (Ostini2012), HECTOR (Bos et al, 2013), CATS (Williams, 2003) and the MIDAS approach of Blewitt (2016) to robustly derive rates and realistic error estimates. The results are compared to those published by the European Permanent Network (EPN), ITRF and the Système d'Observation du Niveau des Eaux Littorales (SONEL) for common stations. Vertical motion is small in general, at the -1 to -2 mm/yr level for most coastal stations. A comparison of the standard deviations of the velocity differences to EPN with the mean values of the estimated velocity standard deviations for our solution shows a very good agreement of the estimated velocities and their standard deviations with the reference solution from EPN. In the comparison with results by SONEL the standard deviation of the differences is slightly higher. The discrepancies may arise from differences in the time span analyzed and gaps, offsets and data preprocessing. The combined estimation of functional and stochastic parameters is rather sensitive to the characteristics of the time series and thus the estimated velocity also depends on the applied stochastic model and on the selected parameters. The GPS vertical land motion rates are finally compared to the difference between sea level rates measured by co-located altimetry and by tide gauge station data, which gives another estimation of VLM.

Evolving plans for the USA National Phenology Network

USGS Publications Warehouse

Betancourt, Julio L.; Schwartz, Mark D.; Breshears, David D.; Brewer, Carol A.; Frazer, Gary; Gross, John E.; Mazer, Susan J.; Reed, Bradley C.; Wilson, Bruce E.

2007-01-01

Phenology is the study of periodic plant and animal life cycle events, how these are influenced by seasonal and interannual variations in climate, and how they modulate the abundance, diversity, and interactions of organisms. The USA National Phenology Network (USA-NPN) is currently being organized to engage federal agencies, environmental networks and field stations, educational institutions, and citizen scientists. The first USA-NPN planning workshop was held August 2005, in Tucson, Ariz. (Betancourt et al. [2005]; http://www.uwm.edu/Dept/Geography/npn/; by 1 June 2007, also see http://www.usanpn.org). With sponsorship from the U.S. National Science Foundation, the U.S. Geological Survey (USGS), the U.S. Fish and Wildlife Service, and NASA, the second USA-NPN planning workshop was held at the University of Wisconsin-Milwaukee on 10–12 October 2006 to (1) develop lists of target species and observation protocols; (2) identify existing networks that could comprise the backbone of nationwide observations by 2008; (3) develop opportunities for education, citizen science, and outreach beginning in spring 2007; (4) design strategies for implementing the remote sensing component of USA-NPN; and (5) draft a data management and cyberinfrastructure plan.

The GPS Topex/Poseidon precise orbit determination experiment - Implications for design of GPS global networks

NASA Technical Reports Server (NTRS)

Lindqwister, Ulf J.; Lichten, Stephen M.; Davis, Edgar S.; Theiss, Harold L.

1993-01-01

Topex/Poseidon, a cooperative satellite mission between United States and France, aims to determine global ocean circulation patterns and to study their influence on world climate through precise measurements of sea surface height above the geoid with an on-board altimeter. To achieve the mission science aims, a goal of 13-cm orbit altitude accuracy was set. Topex/Poseidon includes a Global Positioning System (GPS) precise orbit determination (POD) system that has now demonstrated altitude accuracy better than 5 cm. The GPS POD system includes an on-board GPS receiver and a 6-station GPS global tracking network. This paper reviews early GPS results and discusses multi-mission capabilities available from a future enhanced global GPS network, which would provide ground-based geodetic and atmospheric calibrations needed for NASA deep space missions while also supplying tracking data for future low Earth orbiters. Benefits of the enhanced global GPS network include lower operations costs for deep space tracking and many scientific and societal benefits from the low Earth orbiter missions, including improved understanding of ocean circulation, ocean-weather interactions, the El Nino effect, the Earth thermal balance, and weather forecasting.

Estimation of dew point temperature using neuro-fuzzy and neural network techniques

NASA Astrophysics Data System (ADS)

Kisi, Ozgur; Kim, Sungwon; Shiri, Jalal

2013-11-01

This study investigates the ability of two different artificial neural network (ANN) models, generalized regression neural networks model (GRNNM) and Kohonen self-organizing feature maps neural networks model (KSOFM), and two different adaptive neural fuzzy inference system (ANFIS) models, ANFIS model with sub-clustering identification (ANFIS-SC) and ANFIS model with grid partitioning identification (ANFIS-GP), for estimating daily dew point temperature. The climatic data that consisted of 8 years of daily records of air temperature, sunshine hours, wind speed, saturation vapor pressure, relative humidity, and dew point temperature from three weather stations, Daego, Pohang, and Ulsan, in South Korea were used in the study. The estimates of ANN and ANFIS models were compared according to the three different statistics, root mean square errors, mean absolute errors, and determination coefficient. Comparison results revealed that the ANFIS-SC, ANFIS-GP, and GRNNM models showed almost the same accuracy and they performed better than the KSOFM model. Results also indicated that the sunshine hours, wind speed, and saturation vapor pressure have little effect on dew point temperature. It was found that the dew point temperature could be successfully estimated by using T mean and R H variables.

Complex networks as a unified framework for descriptive analysis and predictive modeling in climate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steinhaeuser, Karsten J K; Chawla, Nitesh; Ganguly, Auroop R

The analysis of climate data has relied heavily on hypothesis-driven statistical methods, while projections of future climate are based primarily on physics-based computational models. However, in recent years a wealth of new datasets has become available. Therefore, we take a more data-centric approach and propose a unified framework for studying climate, with an aim towards characterizing observed phenomena as well as discovering new knowledge in the climate domain. Specifically, we posit that complex networks are well-suited for both descriptive analysis and predictive modeling tasks. We show that the structural properties of climate networks have useful interpretation within the domain. Further,more » we extract clusters from these networks and demonstrate their predictive power as climate indices. Our experimental results establish that the network clusters are statistically significantly better predictors than clusters derived using a more traditional clustering approach. Using complex networks as data representation thus enables the unique opportunity for descriptive and predictive modeling to inform each other.« less

Downscaling of daily precipitation using a hybrid model of Artificial Neural Network, Wavelet, and Quantile Mapping in Gharehsoo River Basin, Iran

NASA Astrophysics Data System (ADS)

Taie Semiromi, M.; Koch, M.

2017-12-01

Although linear/regression statistical downscaling methods are very straightforward and widely used, and they can be applied to a single predictor-predictand pair or spatial fields of predictors-predictands, the greatest constraint is the requirement of a normal distribution of the predictor and the predictand values, which means that it cannot be used to predict the distribution of daily rainfall because it is typically non-normal. To tacked with such a limitation, the current study aims to introduce a new developed hybrid technique taking advantages from Artificial Neural Networks (ANNs), Wavelet and Quantile Mapping (QM) for downscaling of daily precipitation for 10 rain-gauge stations located in Gharehsoo River Basin, Iran. With the purpose of daily precipitation downscaling, the study makes use of Second Generation Canadian Earth System Model (CanESM2) developed by Canadian Centre for Climate Modeling and Analysis (CCCma). Climate projections are available for three representative concentration pathways (RCPs) namely RCP 2.6, RCP 4.5 and RCP 8.5 for up to 2100. In this regard, 26 National Centers for Environmental Prediction (NCEP) reanalysis large-scale variables which have potential physical relationships with precipitation, were selected as candidate predictors. Afterwards, predictor screening was conducted using correlation, partial correlation and explained variance between predictors and predictand (precipitation). Depending on each rain-gauge station between two and three predictors were selected which their decomposed details (D) and approximation (A) obtained from discrete wavelet analysis were fed as inputs to the neural networks. After downscaling of daily precipitation, bias correction was conducted using quantile mapping. Out of the complete time series available, i.e. 1978-2005, two third of which namely 1978-1996 was used for calibration of QM and the reminder, i.e. 1997-2005 was considered for the validation. Result showed that the proposed hybrid method supported by QM for bias-correction could quite satisfactorily simulate daily precipitation. Also, results indicated that under all RCPs, precipitation will be more or less than 12% decreased by 2100. However, precipitation will be less decreased under RCP 8.5 compared with RCP 4.5.

Single-frequency receivers as master permanent stations in GNSS networks: precision and accuracy of the positioning in mixed networks

NASA Astrophysics Data System (ADS)

Dabove, Paolo; Manzino, Ambrogio Maria

2015-04-01

The use of GPS/GNSS instruments is a common practice in the world at both a commercial and academic research level. Since last ten years, Continuous Operating Reference Stations (CORSs) networks were born in order to achieve the possibility to extend a precise positioning more than 15 km far from the master station. In this context, the Geomatics Research Group of DIATI at the Politecnico di Torino has carried out several experiments in order to evaluate the achievable precision obtainable with different GNSS receivers (geodetic and mass-market) and antennas if a CORSs network is considered. This work starts from the research above described, in particular focusing the attention on the usefulness of single frequency permanent stations in order to thicken the existing CORSs, especially for monitoring purposes. Two different types of CORSs network are available today in Italy: the first one is the so called "regional network" and the second one is the "national network", where the mean inter-station distances are about 25/30 and 50/70 km respectively. These distances are useful for many applications (e.g. mobile mapping) if geodetic instruments are considered but become less useful if mass-market instruments are used or if the inter-station distance between master and rover increases. In this context, some innovative GNSS networks were developed and tested, analyzing the performance of rover's positioning in terms of quality, accuracy and reliability both in real-time and post-processing approach. The use of single frequency GNSS receivers leads to have some limits, especially due to a limited baseline length, the possibility to obtain a correct fixing of the phase ambiguity for the network and to fix the phase ambiguity correctly also for the rover. These factors play a crucial role in order to reach a positioning with a good level of accuracy (as centimetric o better) in a short time and with an high reliability. The goal of this work is to investigate about the real effect and how is the contribute of L1 mass-market permanent stations to the CORSs Network both for geodetic and low-cost receivers; in particular is described how the use of the network products which are generated by the network (in real-time and post-processing) can improve the accuracy and precision of a rover 5, 10 and 15 km far from the nearest station. Some tests have been carried out considering different types of receivers (geodetic and mass market) and antennas (patch and geodetic). The tests have been conducted considering several positioning approaches (static, stop and go and real time) in order to make the analysis more complete. Good and interesting results were obtained: the followed approach will be useful for many types of applications (landslides monitoring, traffic control), especially where the inter-station distances of GNSS permanent station are greater than 30 km.

Newberry EGS Seismic Velocity Model

DOE Data Explorer

Templeton, Dennise

2013-10-01

We use ambient noise correlation (ANC) to create a detailed image of the subsurface seismic velocity at the Newberry EGS site down to 5 km. We collected continuous data for the 22 stations in the Newberry network, together with 12 additional stations from the nearby CC, UO and UW networks. The data were instrument corrected, whitened and converted to single bit traces before cross correlation according to the methodology in Benson (2007). There are 231 unique paths connecting the 22 stations of the Newberry network. The additional networks extended that to 402 unique paths crossing beneath the Newberry site.

Quantifying climatic controls on river network topology across scales

NASA Astrophysics Data System (ADS)

Ranjbar Moshfeghi, S.; Hooshyar, M.; Wang, D.; Singh, A.

2017-12-01

Branching structure of river networks is an important topologic and geomorphologic feature that depends on several factors (e.g. climate, tectonic). However, mechanisms that cause these drainage patterns in river networks are poorly understood. In this study, we investigate the effects of varying climatic forcing on river network topology and geomorphology. For this, we select 20 catchments across the United States with different long-term climatic conditions quantified by climate aridity index (AI), defined here as the ratio of mean annual potential evaporation (Ep) to precipitation (P), capturing variation in runoff and vegetation cover. The river networks of these catchments are extracted, using a curvature-based method, from high-resolution (1 m) digital elevation models and several metrics such as drainage density, branching angle, and width functions are computed. We also use a multiscale-entropy-based approach to quantify the topologic irregularity and structural richness of these river networks. Our results reveal systematic impacts of climate forcing on the structure of river networks.

Extending Resolution of Fault Slip With Geodetic Networks Through Optimal Network Design

NASA Astrophysics Data System (ADS)

Sathiakumar, Sharadha; Barbot, Sylvain Denis; Agram, Piyush

2017-12-01

Geodetic networks consisting of high precision and high rate Global Navigation Satellite Systems (GNSS) stations continuously monitor seismically active regions of the world. These networks measure surface displacements and the amount of geodetic strain accumulated in the region and give insight into the seismic potential. SuGar (Sumatra GPS Array) in Sumatra, GEONET (GNSS Earth Observation Network System) in Japan, and PBO (Plate Boundary Observatory) in California are some examples of established networks around the world that are constantly expanding with the addition of new stations to improve the quality of measurements. However, installing new stations to existing networks is tedious and expensive. Therefore, it is important to choose suitable locations for new stations to increase the precision obtained in measuring the geophysical parameters of interest. Here we describe a methodology to design optimal geodetic networks that augment the existing system and use it to investigate seismo-tectonics at convergent and transform boundaries considering land-based and seafloor geodesy. The proposed network design optimization would be pivotal to better understand seismic and tsunami hazards around the world. Land-based and seafloor networks can monitor fault slip around subduction zones with significant resolution, but transform faults are more challenging to monitor due to their near-vertical geometry.

Citizen Science Seismic Stations for Monitoring Regional and Local Events

NASA Astrophysics Data System (ADS)

Zucca, J. J.; Myers, S.; Srikrishna, D.

2016-12-01

The earth has tens of thousands of seismometers installed on its surface or in boreholes that are operated by many organizations for many purposes including the study of earthquakes, volcanos, and nuclear explosions. Although global networks such as the Global Seismic Network and the International Monitoring System do an excellent job of monitoring nuclear test explosions and other seismic events, their thresholds could be lowered with the addition of more stations. In recent years there has been interest in citizen-science approaches to augment government-sponsored monitoring networks (see, for example, Stubbs and Drell, 2013). A modestly-priced seismic station that could be purchased by citizen scientists could enhance regional and local coverage of the GSN, IMS, and other networks if those stations are of high enough quality and distributed optimally. In this paper we present a minimum set of hardware and software specifications that a citizen seismograph station would need in order to add value to global networks. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Online decision support based on modeling with the aim of increased irrigation efficiency

NASA Astrophysics Data System (ADS)

Dövényi-Nagy, Tamás; Bakó, Károly; Molnár, Krisztina; Rácz, Csaba; Vasvári, Gyula; Nagy, János; Dobos, Attila

2015-04-01

The significant changes in the structure of ownership and control of irrigation infrastructure in the past decades resultted in the decrease of total irrigable and irrigated area (Szilárd, 1999). In this paper, the development of a model-based online service is described whose aim is to aid reasonable irrigation practice and increase water use efficiency. In order to establish a scientific background for irrigation, an agrometeorological station network has been built up by the Agrometeorological and Agroecological Monitoring Centre. A website has been launched in order to provide direct access for local agricultural producers to both the measured weather parameters and results of model based calculations. The public site provides information for general use, registered partners get a handy model based toolkit for decision support at the plot level concerning irrigation, plant protection or frost forecast. The agrometeorological reference station network was established in the recent years by the Agrometeorological and Agroecological Monitoring Centre and is distributed to cover most of the irrigated cropland areas of Hungary. From the spatial aspect, the stations have been deployed mainly in Eastern Hungary with concentrated irrigation infrastructure. The meteorological stations' locations have been carefully chosen to represent their environment in terms of soil, climatic and topographic factors, thereby assuring relevant and up-to-date input data for the models. The measured parameters range from classic meteorological data (air temperature, relative humidity, solar irradiation, wind speed etc.) to specific data which are not available from other services in the region, such as soil temperature, soil water content in multiple depths and leaf wetness. In addition to the basic grid of reference stations, specific stations under irrigated conditions have been deployed to calibrate and validate the models. A specific modeling framework (MetAgro) has been developed to allow the integration of several public available models and algorithms adapted to local climate (Rácz et al., 2013). The service, the server side framework, scripts and the front-end, providing access to the measured and modeled data, are based on own developments or free available and/or open source softwares and services like Apache, PHP, MySQL and Google Maps API. MetAgro intends to accomplish functionalities of three different areas of usage: research, education and practice. The members differ in educational background, knowledge of models and possibilities to access relevant input data. The system and interfaces must reflect these differences that is accomplished by the degradation of modeling: choosing the place of the farm and the crop already gives some general results, but with every additional parameter given the results are more reliable. The system 'MetAgro' provides a basis for improved decision-making with regard to irrigation on cropland. Based on experiences and feedback, the online application was proved to be useful in the design and practice of reasonable irrigation. In addition to its use in irrigation practice, MetAgro is also a valuable tool for research and education.

Application of the Artificial Neural Network model for prediction of monthly Standardized Precipitation and Evapotranspiration Index using hydrometeorological parameters and climate indices in eastern Australia

NASA Astrophysics Data System (ADS)

Deo, Ravinesh C.; Şahin, Mehmet

2015-07-01

The forecasting of drought based on cumulative influence of rainfall, temperature and evaporation is greatly beneficial for mitigating adverse consequences on water-sensitive sectors such as agriculture, ecosystems, wildlife, tourism, recreation, crop health and hydrologic engineering. Predictive models of drought indices help in assessing water scarcity situations, drought identification and severity characterization. In this paper, we tested the feasibility of the Artificial Neural Network (ANN) as a data-driven model for predicting the monthly Standardized Precipitation and Evapotranspiration Index (SPEI) for eight candidate stations in eastern Australia using predictive variable data from 1915 to 2005 (training) and simulated data for the period 2006-2012. The predictive variables were: monthly rainfall totals, mean temperature, minimum temperature, maximum temperature and evapotranspiration, which were supplemented by large-scale climate indices (Southern Oscillation Index, Pacific Decadal Oscillation, Southern Annular Mode and Indian Ocean Dipole) and the Sea Surface Temperatures (Nino 3.0, 3.4 and 4.0). A total of 30 ANN models were developed with 3-layer ANN networks. To determine the best combination of learning algorithms, hidden transfer and output functions of the optimum model, the Levenberg-Marquardt and Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton backpropagation algorithms were utilized to train the network, tangent and logarithmic sigmoid equations used as the activation functions and the linear, logarithmic and tangent sigmoid equations used as the output function. The best ANN architecture had 18 input neurons, 43 hidden neurons and 1 output neuron, trained using the Levenberg-Marquardt learning algorithm using tangent sigmoid equation as the activation and output functions. An evaluation of the model performance based on statistical rules yielded time-averaged Coefficient of Determination, Root Mean Squared Error and the Mean Absolute Error ranging from 0.9945-0.9990, 0.0466-0.1117, and 0.0013-0.0130, respectively for individual stations. Also, the Willmott's Index of Agreement and the Nash-Sutcliffe Coefficient of Efficiency were between 0.932-0.959 and 0.977-0.998, respectively. When checked for the severity (S), duration (D) and peak intensity (I) of drought events determined from the simulated and observed SPEI, differences in drought parameters ranged from - 1.41-0.64%, - 2.17-1.92% and - 3.21-1.21%, respectively. Based on performance evaluation measures, we aver that the Artificial Neural Network model is a useful data-driven tool for forecasting monthly SPEI and its drought-related properties in the region of study.

Human Impacts and Climate Change Influence Nestedness and Modularity in Food-Web and Mutualistic Networks.

PubMed

Takemoto, Kazuhiro; Kajihara, Kosuke

2016-01-01

Theoretical studies have indicated that nestedness and modularity-non-random structural patterns of ecological networks-influence the stability of ecosystems against perturbations; as such, climate change and human activity, as well as other sources of environmental perturbations, affect the nestedness and modularity of ecological networks. However, the effects of climate change and human activities on ecological networks are poorly understood. Here, we used a spatial analysis approach to examine the effects of climate change and human activities on the structural patterns of food webs and mutualistic networks, and found that ecological network structure is globally affected by climate change and human impacts, in addition to current climate. In pollination networks, for instance, nestedness increased and modularity decreased in response to increased human impacts. Modularity in seed-dispersal networks decreased with temperature change (i.e., warming), whereas food web nestedness increased and modularity declined in response to global warming. Although our findings are preliminary owing to data-analysis limitations, they enhance our understanding of the effects of environmental change on ecological communities.

Carbon Speciation and Anthropogenic Influences in Haitian Rivers and Inland Waters

NASA Astrophysics Data System (ADS)

Markowitz, M.; Paine, J.; McGillis, W. R.; Hsueh, D. Y.

2014-12-01

Climate, geography, and land use patterns all contribute to the social, economic, and environmental challenges in Haiti. Water quality remains a predominant issue, and the health of freshwater systems has been linked to the cycling and transformation of carbon. A speciation dominated by carbonates and bicarbonates is conducive to higher alkalinity waters, which is part of an environmental signature in which cholera and other bacteria thrive. Numerous human activities such as deforestation, biomass burning, and agricultural practices have radically changed the abundances of carbon on land and rivers in Haiti. In Haitian small mountainous rivers, carbon speciation is also influenced by the weathering of limestone and other carbonate rocks. Additionally, rain events and natural disturbances such as earthquakes have shown to drastically increase the amount of carbon in rivers and coastal waters. Since 2010, a network of both satellite and autonomous hydrometeorological stations has been deployed to monitor the climate in southwestern Haiti. Additionally, various hydrological parameters from river, reservoir, and coastal sites have been measured during field visits. Research will be continued into the wet season, providing temporal analysis needed for quantifying the abundances and transformations of carbon. Together, data from weather stations and field sites can be contextualized with local land use patterns and other human activities to offer unique insights on the carbon system. Findings may offer new perspectives on the relationships between hydrologic cycles, human health, and environmental sustainability in Haiti.

Landscape Conservation Cooperatives: Creating a Collaborative Conservation Vision in the Face of Climate Change Uncertainty

NASA Astrophysics Data System (ADS)

Athearn, N.; Schlafmann, D.

2015-12-01

The 22 Landscape Conservation Cooperatives (LCCs) form a "network of networks," each defined by the characteristics of its ecoregion and its unique community of conservation managers, practitioners, and scientists. As self-directed partnerships, LCCs are strongly influenced not only by the landscape but by the evolving cultures and values that define the multi-faceted relationships between people and place. LCCs maintain an ecologically connected network across these diverse landscapes by transcending borders and leveraging resources. Natural resource managers are challenged to make decisions in the face of multiple uncertainties, and several partners across the network have recognized that climate change is one important uncertainty that spans boundaries - both across the conservation community and beyond. The impacts of climate change across the LCC Network are likely to be as diverse as the network itself - manifesting as, for example, sea level rise, ocean acidification, loss of sea ice, and shifts in climate patterns and timing - but synergies are being leveraged within and between LCCs and national climate-focused programs to systematically address the needs of the network to support a collaborative conservation vision that addresses multiple landscape-scale stressors in the face of climate uncertainties. This vision is being achieved by leveraging the convening power of the LCCs and collaborating with DOI Climate Science Centers and others. Selected case studies will demonstrate how the network finds strength in its differences, but also reveals powerful collaborative opportunities through integrated science, shared conservation strategies, and strategic approaches for translating targeted science to conservation action. These examples exemplify past successes as well as ongoing efforts as the network continues to bring about effective application of climate science to achieve conservation outcomes across the LCC Network in an uncertain future climate.

Optimal Base Station Density of Dense Network: From the Viewpoint of Interference and Load.

PubMed

Feng, Jianyuan; Feng, Zhiyong

2017-09-11

Network densification is attracting increasing attention recently due to its ability to improve network capacity by spatial reuse and relieve congestion by offloading. However, excessive densification and aggressive offloading can also cause the degradation of network performance due to problems of interference and load. In this paper, with consideration of load issues, we study the optimal base station density that maximizes the throughput of the network. The expected link rate and the utilization ratio of the contention-based channel are derived as the functions of base station density using the Poisson Point Process (PPP) and Markov Chain. They reveal the rules of deployment. Based on these results, we obtain the throughput of the network and indicate the optimal deployment density under different network conditions. Extensive simulations are conducted to validate our analysis and show the substantial performance gain obtained by the proposed deployment scheme. These results can provide guidance for the network densification.

Percolation Features on Climate Network under Attacks of El Niño Events

NASA Astrophysics Data System (ADS)

Lu, Z.

2015-12-01

Percolation theory under different attacks is one of the main research areas in complex networks but never be applied to investigate climate network. In this study, for the first time we construct a climate network of surface air temperature field to analyze its percolation features. Here, we regard El Niño event as a kind of naturally attacks generated from Pacific Ocean to attack its upper climate network. We find that El Niño event leads an abrupt percolation phase transition to the climate network which makes it splitting and unstable suddenly. Comparing the results of the climate network under three different forms of attacks, including most connected attack (MA), localized attack (LA) and random attack (RA) respectively, it is found that both MA and LA lead first-order transition and RA leads second-order transition to the climate network. Furthermore, we find that most real attacks consist of all these three forms of attacks. With El Niño event emerging, the ratios of LA and MA increase and dominate the style of attack while RA decreasing. It means the percolation phase transition due to El Niño events is close to first-order transition mostly affected by LA and MA. Our research may help us further understand two questions from perspective of percolation on network: (1) Why not all warming in Pacific Ocean but El Niño events could affect the climate. (2) Why the climate affected by El Niño events changes abruptly.

Developing a robust wireless sensor network structure for environmental sensing

NASA Astrophysics Data System (ADS)

Zhang, Z.; Oroza, C.; Glaser, S. D.; Bales, R. C.; Conklin, M. H.

2013-12-01

The American River Hydrologic Observatory is being strategically deployed as a real-time ground-based measurement network that delivers accurate and timely information on snow conditions and other hydrologic attributes with a previously unheard of granularity of time and space. The basin-scale network involves 18 sub-networks set out at physiographically representative locations spanning the seasonally snow-covered half of the 5000 km2 American river basin. Each sub-network, covering about a 1-km2 area, consists of 10 wirelessly networked sensing nodes that continuously measure and telemeter temperature, and snow depth; plus selected locations are equipped with sensors for relative humidity, solar radiation, and soil moisture at several depths. The sensor locations were chosen to maximize the variance sampled for snow depth within the basin. Network design and deployment involves an iterative but efficient process. After sensor-station locations are determined, a robust network of interlinking sensor stations and signal repeaters must be constructed to route sensor data to a central base station with a two-way communicable data uplink. Data can then be uploaded from site to remote servers in real time through satellite and cell modems. Signal repeaters are placed for robustness of a self-healing network with redundant signal paths to the base station. Manual, trial-and-error heuristic approaches for node placement are inefficient and labor intensive. In that approach field personnel must restructure the network in real time and wait for new network statistics to be calculated at the base station before finalizing a placement, acting without knowledge of the global topography or overall network structure. We show how digital elevation plus high-definition aerial photographs to give foliage coverage can optimize planning of signal repeater placements and guarantee a robust network structure prior to the physical deployment. We can also 'stress test' the final network by simulating the failure of an individual node and investigating the effect and the self-healing ability of the stressed network. The resulting sensor network can survive temporary service interruption from a small subset of signal repeaters and sensor stations. The robustness and the resilient of the network performance ensure the integrity of the dataset and the real-time transmissibility during harsh conditions.

Landsat's international partners

USGS Publications Warehouse

Byrnes, Raymond A.

2012-01-01

Since the launch of the first Landsat satellite 40 years ago, International Cooperators (ICs) have formed a key strategic alliance with the U.S. Geological Survey (USGS) to not only engage in Landsat data downlink services but also to enable a foundation for scientific and technical collaboration. The map below shows the locations of all ground stations operated by the United States and IC ground station network for the direct downlink and distribution of Landsat 5 (L5) and Landsat 7 (L7) image data. The circles show the approximate area over which each station has the capability for direct reception of Landsat data. The red circles show the components of the L5 ground station network, the green circles show components of the L7 station network, and the dashed circles show stations with dual (L5 and L7) status. The yellow circles show L5 short-term ("campaign") stations that contribute to the USGS Landsat archive. Ground stations in South Dakota and Australia currently serve as the primary data capture facilities for the USGS Landsat Ground Network (LGN). The Landsat Ground Station (LGS) is located at the USGS Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota. The Alice Springs (ASN) ground station is located at the Geoscience Australia facility in Alice Springs, Australia. These sites receive the image data, via X-band Radio Frequency (RF) link, and the spacecraft housekeeping data, via S-band RF link. LGS also provides tracking services and a command link to the spacecrafts.

Local topography increasingly influences the mass balance of a retreating cirque glacier

USGS Publications Warehouse

Florentine, Caitlyn; Harper, Joel T.; Fagre, Daniel B.; Moore, Johnnie; Peitzsch, Erich H.

2018-01-01

Local topographically driven processes – such as wind drifting, avalanching, and shading – are known to alter the relationship between the mass balance of small cirque glaciers and regional climate. Yet partitioning such local effects from regional climate influence has proven difficult, creating uncertainty in the climate representativeness of some glaciers. We address this problem for Sperry Glacier in Glacier National Park, USA, using field-measured surface mass balance, geodetic constraints on mass balance, and regional climate data recorded at a network of meteorological and snow stations. Geodetically derived mass changes during 1950–1960, 1960–2005, and 2005–2014 document average mass change rates during each period at −0.22 ± 0.12, −0.18 ± 0.05, and −0.10 ± 0.03 m w.e. yr−1, respectively. A correlation of field-measured mass balance and regional climate variables closely (i.e., within 0.08 m w.e. yr−1) predicts the geodetically measured mass loss from 2005 to 2014. However, this correlation overestimates glacier mass balance for 1950–1960 by +1.20 ± 0.95 m w.e. yr−1. Our analysis suggests that local effects, not represented in regional climate variables, have become a more dominant driver of the net mass balance as the glacier lost 0.50 km2 and retreated further into its cirque.

RadNet Air Quality (Fixed Station) Data

EPA Pesticide Factsheets

RadNet is a national network of monitoring stations that regularly collect air for analysis of radioactivity. The RadNet network, which has stations in each State, has been used to track environmental releases of radioactivity from nuclear weapons tests and nuclear accidents. RadNet also documents the status and trends of environmental radioactivity

New solutions for climate network visualization

NASA Astrophysics Data System (ADS)

Nocke, Thomas; Buschmann, Stefan; Donges, Jonathan F.; Marwan, Norbert

2016-04-01

An increasing amount of climate and climate impact research methods deals with geo-referenced networks, including energy, trade, supply-chain, disease dissemination and climatic tele-connection networks. At the same time, the size and complexity of these networks increases, resulting in networks of more than hundred thousand or even millions of edges, which are often temporally evolving, have additional data at nodes and edges, and can consist of multiple layers even in real 3D. This gives challenges to both the static representation and the interactive exploration of these networks, first of all avoiding edge clutter ("edge spagetti") and allowing interactivity even for unfiltered networks. Within this presentation, we illustrate potential solutions to these challenges. Therefore, we give a glimpse on a questionnaire performed with climate and complex system scientists with respect to their network visualization requirements, and on a review of available state-of-the-art visualization techniques and tools for this purpose (see as well Nocke et al., 2015). In the main part, we present alternative visualization solutions for several use cases (global, regional, and multi-layered climate networks) including alternative geographic projections, edge bundling, and 3-D network support (based on CGV and GTX tools), and implementation details to reach interactive frame rates. References: Nocke, T., S. Buschmann, J. F. Donges, N. Marwan, H.-J. Schulz, and C. Tominski: Review: Visual analytics of climate networks, Nonlinear Processes in Geophysics, 22, 545-570, doi:10.5194/npg-22-545-2015, 2015

Linking Climate Risk, Policy Networks and Adaptation Planning in Public Lands

NASA Astrophysics Data System (ADS)

Lubell, M.; Schwartz, M.; Peters, C.

2014-12-01

Federal public land management agencies in the United States have engaged a variety of planning efforts to address climate adaptation. A major goal of these efforts is to build policy networks that enable land managers to access information and expertise needed for responding to local climate risks. This paper investigates whether the perceived and modeled climate risk faced by different land managers is leading to larger networks or more participating in climate adaptation. In theory, the benefits of climate planning networks are larger when land managers are facing more potential changes. The basic hypothesis is tested with a survey of public land managers from hundreds of local and regional public lands management units in the Southwestern United States, as well as other stakeholders involved with climate adaptation planning. All survey respondents report their perceptions of climate risk along a variety of dimensions, as well as their participation in climate adaptation planning and information sharing networks. For a subset of respondents, we have spatially explicity GIS data about their location, which will be linked with downscaled climate model data. With the focus on climate change, the analysis is a subset of the overall idea of linking social and ecological systems.

ACTS TDMA network control. [Advanced Communication Technology Satellite

NASA Technical Reports Server (NTRS)

Inukai, T.; Campanella, S. J.

1984-01-01

This paper presents basic network control concepts for the Advanced Communications Technology Satellite (ACTS) System. Two experimental systems, called the low-burst-rate and high-burst-rate systems, along with ACTS ground system features, are described. The network control issues addressed include frame structures, acquisition and synchronization procedures, coordinated station burst-time plan and satellite-time plan changes, on-board clock control based on ground drift measurements, rain fade control by means of adaptive forward-error-correction (FEC) coding and transmit power augmentation, and reassignment of channel capacities on demand. The NASA ground system, which includes a primary station, diversity station, and master control station, is also described.

GNSS-Derived Water Vapour for Riyadh from SOLA IGS Station

NASA Astrophysics Data System (ADS)

Maghrabi, Abdullrahman; Alothman, Abdulaziz; Fernandes, Rui; Aodah, Souad

2017-04-01

Water vapor is the most abundant and highly variable component of the important gases in the atmosphere. It influences many physical and thermodynamical processes in the atmosphere and plays an important role in the hydrological cycle and has effects on our climate and weather systems. Water vapour affects the electromagnetic radiation through the atmosphere, which is of significance in fields of astronomy, radar, communications and remote sensing. Precipitable water vapor (PWV) is the amount of water obtained if all the water vapor in the atmosphere were to be compressed to the point at which it condenses into liquid. PWV is difficult to measure adequately due to its variable distribution both spatially and temporally. Most of the current techniques (e.g., radiosondes or satellites) are only available at few locations and not continuously (few observations per day at most). However, in the last decades, GPS observations have been proven to accurately measure the ZTD (Zenith Tropospheric Delay) at high frequencies (normally every 5 minutes) above the station. This quantity can be converted to PWV if temperature and pressure is know at the station location. In early 2004, King Abdulaziz City for Science and Technology (KACST) established a GPS network for geodetic and geophysical applications to contribute to the International GNSS Service IGS. In this study, we will present the first PWV measurements obtained from Global Navigation Satellite System GNSS receiver at the Solar Village (SOLA), 60 km from Riyadh. GNSS observations for the period between 2004-2006 are used to study the daily and seasonal variations of ZTD, and consequently of PWV in SOLA. In addition, we also compare the GNSS-derived PWV with sunphotometer and radiosonde estimates at SOLA in order to evaluate the compatibility of these techniques in a dry climate as the one in Riyadh.

Evaluation of representativeness of near-surface winds in station measurements, global and regional reanalysis for Germany

NASA Astrophysics Data System (ADS)

Kaspar, Frank; Kaiser-Weiss, Andrea K.; Heene, Vera; Borsche, Michael; Keller, Jan

2015-04-01

Within the preparation activities for a European COPERNICUS Climate Change Service (C3S) several ongoing research projects analyse the potential of global and regional model-based climate reanalyses for applications. A user survey in the FP7-project CORE-CLIMAX revealed that surface wind (10 m) is among the most frequently used parameters of global reanalysis products. The FP7 project UERRA (Uncertainties in Ensembles of Regional Re-Analysis) has the focus on regional European reanalysis and the associated uncertainties, also from a user perspective. Especially in the field of renewable energy planning and production there is a need for climatological information across all spatial scales, i.e., from climatology at a certain site to the spatial scale of national or continental renewable energy production. Here, we focus on a comparison of wind measurements of the Germany's meteorological service (Deutscher Wetterdienst, DWD) with global reanalyses of ECWMF and a regional reanalysis for Europe based on DWD's NWP-model COSMO (performed by the Hans-Ertel-Center for Weather Research, University of Bonn). Reanalyses can provide valuable additional information on larger scale variability, e.g. multi-annual variation over Germany. However, changes in the observing system, model errors and biases have to be carefully considered. On the other hand, the ground-based observation networks partly suffer from change of the station distribution, changes in instrumentation, measurements procedures and quality control as well as local changes which might modify their spatial representativeness. All these effects might often been unknown or hard to characterize, although plenty of the meta-data information has been recorded for the German stations. One focus of the presentation will be the added-value of the regional reanalysis.

Assessment of Observational Uncertainty in Extreme Precipitation Events over the Continental United States

NASA Astrophysics Data System (ADS)

Slinskey, E. A.; Loikith, P. C.; Waliser, D. E.; Goodman, A.

2017-12-01

Extreme precipitation events are associated with numerous societal and environmental impacts. Furthermore, anthropogenic climate change is projected to alter precipitation intensity across portions of the Continental United States (CONUS). Therefore, a spatial understanding and intuitive means of monitoring extreme precipitation over time is critical. Towards this end, we apply an event-based indicator, developed as a part of NASA's support of the ongoing efforts of the US National Climate Assessment, which assigns categories to extreme precipitation events based on 3-day storm totals as a basis for dataset intercomparison. To assess observational uncertainty across a wide range of historical precipitation measurement approaches, we intercompare in situ station data from the Global Historical Climatology Network (GHCN), satellite-derived precipitation data from NASA's Tropical Rainfall Measuring Mission (TRMM), gridded in situ station data from the Parameter-elevation Regressions on Independent Slopes Model (PRISM), global reanalysis from NASA's Modern Era Retrospective-Analysis version 2 (MERRA 2), and regional reanalysis with gauge data assimilation from NCEP's North American Regional Reanalysis (NARR). Results suggest considerable variability across the five-dataset suite in the frequency, spatial extent, and magnitude of extreme precipitation events. Consistent with expectations, higher resolution datasets were found to resemble station data best and capture a greater frequency of high-end extreme events relative to lower spatial resolution datasets. The degree of dataset agreement varies regionally, however all datasets successfully capture the seasonal cycle of precipitation extremes across the CONUS. These intercomparison results provide additional insight about observational uncertainty and the ability of a range of precipitation measurement and analysis products to capture extreme precipitation event climatology. While the event category threshold is fixed in this analysis, preliminary results from the development of a flexible categorization scheme, that scales with grid resolution, are presented.

Overview of 2010-2013 spring campaigns of Seven South East Asian Studies (7-SEAS) in the northern Southeast Asia

NASA Astrophysics Data System (ADS)

Lin, N.; Tsay, S.; Hsu, N. C.; Holben, B. N.; Anh, N.; Reid, J. S.; Sheu, G.; Chi, K.; Wang, S.; Lee, C.; Wang, L.; Wang, J.; Chen, W.; Welton, E. J.; Liang, S.; Sopajaree, K.; Maring, H. B.; Janjai, S.; Chantara, S.

2013-12-01

The Seven South East Asian Studies (7-SEAS) is a grass-root program and seeks to perform interdisciplinary research in the field of aerosol-meteorology and climate interaction in the Southeast Asian region, particularly for the impact of biomass burning on cloud, atmospheric radiation, hydrological cycle, and regional climate. Participating countries include Indonesia, Malaysia, Philippines, Singapore, Thailand, Taiwan, Vietnam, and USA. A series of field experiments have been conducted during springtime biomass burning seasons in northern Southeast Asia, i.e., Dongsha Experiment in 2010, Son La Campaigns in 2011 and 2012, and BASELInE (Biomass-burning Aerosols & Stratocumulus Environment: Lifecycles and Interactions Experiment) in 2013, respectively. Given an example, during 2010 Dongsha Experiment, a monitoring network for ground-based measurements was established, including five stations from northern Thailand and central Vietnam to Taiwan, with a supersite at the Dongsha Island (i.e. Pratas Island) in South China Sea (or East Sea). Aerosol chemistry sampling was performed for each station for characterizing the compositions of PM2.5/PM10 (some for TSP) including water-soluble ions, metal elements, BC/OC, Hg and dioxins. This experiment provides a relatively complete and first dataset of aerosol chemistry and physical observations conducted in the source/sink region for below marine boundary layer and lower free troposphere of biomass burning/air pollutants in the northern SE Asia. This presentation will give an overview of these 7-SEAS activities and their results, particularly for the characterization of biomass-burning aerosol at source regions in northern Thailand and northern Vietnam, and receptor stations in Taiwan, which is rarely studied.

Climate-change scenarios

USGS Publications Warehouse

Wagner, Frederic H.; Stohlgren, T.J.; Baldwin, C.K.; Mearns, L.O.; Wagner, Frederic H.

2003-01-01

Three procedures were used to develop a set of plausible scenarios of anthropogenic climate change by the year 2100 that could be posed to the sectors selected for assessment (Fig. 2.2). First, a workshop of climatologists with expertise in western North American climates was convened from September 10-12, 1998 at the National Center for Ecological Analysis and Synthesis in Santa Barbara, CA to discuss and propose a set of scenarios for the Rocky Mountain/Great Basin (RMGB) region.Secondly, the 20th-century climate record was analyzed to determine what trends might have occurred during the period. Since CO2 and other greenhouse gases increased during the century, it was reasonable to examine whether the changes projected for the 21st century had begun to appear during the 20th, at least qualitatively though not quantitatively.Third, on the assumption of a two-fold increase in atmospheric CO2 by 2100, climate-change scenarios for the 21st century were projected with two, state-of-the-art computer models that simulate the complex interactions between earth, atmosphere, and ocean to produce the earth’s climate system. Each of the last two procedures has its strengths and weaknesses, and each can function to some degree as a check on the other. The historical analysis has the advantage of using empirical measurements of actual climate change taken over an extensive network of measuring stations. These make it possible to subdivide a large region like the RMGB into subreqions to assess the uniformity of climate and climate change over the region. And the historical measurements can to some degree serve as a check on the GCM simulations when the two are compared over the same time period.

SIRGAS: ITRF densification in Latin America and the Caribbean

NASA Astrophysics Data System (ADS)

Brunini, C.; Costa, S.; Mackern, V.; Martínez, W.; Sánchez, L.; Seemüller, W.; da Silva, A.

2009-04-01

The continental reference frame of SIRGAS (Sistema de Referencia Geocéntrico para las Américas) is at present realized by the SIRGAS Continuously Operating Network (SIRGAS-CON) composed by about 200 stations distributed over all Latin America and the Caribbean. SIRGAS member countries are qualifying their national reference frames by installing continuously operating GNSS stations, which have to be consistently integrated into the continental network. As the number of these stations is rapidly increasing, the processing strategy of the SIRGAS-CON network was redefined during the SIRGAS 2008 General Meeting in May 2008. The new strategy relies upon the definition of two hierarchy levels: a) A core network (SIRGAS-CON-C) with homogeneous continental coverage and stabile site locations ensures the long-term stability of the reference frame and provides the primary link to the ITRS. Stations belonging to this network have been selected so that each country contributes with a number of stations defined according to its surface and guarantying that the selected stations are the best in operability, continuity, reliability, and geographical coverage. b) Several densification sub-networks (SIRGAS-CON-D) improve the accessibility to the reference frame. The SIRGAS-CON-D sub-networks shall correspond to the national reference frames, i.e., as an optimum there shall be as many sub-networks as countries in the region. The goal is that each country processes its own continuously stations following the SIRGAS processing guidelines, which are defined in accordance with the IERS and IGS standards and conventions. Since at present not all of the countries are operating a processing centre, the existing stations are classified in three densification networks (a Northern, a middle, and a Southern one), which are processed by three local processing centres until new ones are installed. As SIRGAS is defined as a densification of the ITRS, stations included in the core network, as well as in the densification sub-networks match the requirements, characteristics, and processing performance of the ITRF. The SIRGAS-CON-C network is processed by DGFI (Deutsches Geodätisches Forschungsinstitut, Germany) as the IGS-RNAAC-SIR. The Local Processing Centres are for the Northern sub-network IGAC (Instituto Geográfico Augustín Codazzi, Colombia), for the middle sub-network IBGE (Instituto Brasileiro de Geografia e Estátistica, Brazil), and for the Southern sub-network IGG-CIMA (Instituto de Geodesia y Geodinámica, Universidad Nacional de Cuyo, Argentina). These four Processing Centres deliver loosely constrained weekly solutions for station coordinates (i.e., satellite orbits, satellite clock offsets, and Earth orientation parameters are fixed to the final weekly IGS solutions and coordinates for all sites are constrained to 1 m). The individual contributions are integrated in a unified solution by the SIRGAS Combination Centres (DGFI and IBGE) according to the following strategy: 1) Individual solutions are reviewed/corrected for possible format problems, data inconsistencies, etc. 2) Constraints imposed in the delivered normal equations are removed. 3) Sub-networks are individually aligned to the IGS05 reference frame by applying the No Net Rotation (NNR) and No Net Translation (NNT) conditions. 4) Coordinates obtained in (3) for each sub-network are compared to IGS05 values and to each other in order to identify possible outliers. 5) Stations with large residuals (more than 10 mm in the N-E component, and more than 20 mm in the Up component) are reduced from the normal equations. Steps (3), (4), and (5) are done iteratively. 6) Since at present the four Analysis Centres are processing GPS observations only and all of them use the Bernese Software for computing weekly solutions, relative weighting factors are not applied in the combination. 7) Individual normal equations are accumulated and solved for computing a loosely constrained weekly solution for station coordinates (i.e., coordinates for all stations are constrained to 1 m). This solution in SINEX format is submitted to IGS for the global polyhedron. 8) Combination obtained in (7) is constrained by applying NNR+NNT conditions with respect to the IGS05 stations included the SIRGAS region to provide constrained coordinates for all SIRGAS-CON (core + densification) stations. The applied IGS05 reference coordinates correspond to the weekly IGS solution for the global network, i.e., coordinates included in the igsYYPwwww.snx files. This constrained solution provides the final weekly SIRGAS-CON coordinates for practical applications. The DGFI (i.e. IGS RNAAC SIR) weekly combinations are delivered to the IGS Data Centres for combination in the global polyhedron, and made available for users as official SIRGAS products, respectively. The IBGE weekly combinations provide control and back-up. The above described analysis strategy is applied since GPS week 1495. Before (since June 1996 to August 2008), the SIRGAS-CON network was totally processed by DGFI. Until now, results show a very good agreement with previous computations; however, the present sub-networks distribution has two main disadvantages: 1) Not all SIRGAS-CON stations are included in the same number of individual solutions, i.e., they are unequally weighted in the weekly combinations, and 2) since there are not enough Local Processing Centres, the required redundancy (each station processed by at least three processing centres) is not fulfilled. Therefore, efforts are being made to install additional Local Processing Centres in Latin American countries as Argentina, Ecuador, Mexico, Peru, Uruguay, and Venezuela.

A theoretical study on the bottlenecks of GPS phase ambiguity resolution in a CORS RTK Network

NASA Astrophysics Data System (ADS)

Odijk, D.; Teunissen, P.

2011-01-01

Crucial to the performance of GPS Network RTK positioning is that a user receives and applies correction information from a CORS Network. These corrections are necessary for the user to account for the atmospheric (ionospheric and tropospheric) delays and possibly orbit errors between his approximate location and the locations of the CORS Network stations. In order to provide the most precise corrections to users, the CORS Network processing should be based on integer resolution of the carrier phase ambiguities between the network's CORS stations. One of the main challenges is to reduce the convergence time, thus being able to quickly resolve the integer carrier phase ambiguities between the network's reference stations. Ideally, the network ambiguity resolution should be conducted within one single observation epoch, thus truly in real time. Unfortunately, single-epoch CORS Network RTK ambiguity resolution is currently not feasible and in the present contribution we study the bottlenecks preventing this. For current dual-frequency GPS the primary cause of these CORS Network integer ambiguity initialization times is the lack of a sufficiently large number of visible satellites. Although an increase in satellite number shortens the ambiguity convergence times, instantaneous CORS Network RTK ambiguity resolution is not feasible even with 14 satellites. It is further shown that increasing the number of stations within the CORS Network itself does not help ambiguity resolution much, since every new station introduces new ambiguities. The problem with CORS Network RTK ambiguity resolution is the presence of the atmospheric (mainly ionospheric) delays themselves and the fact that there are no external corrections that are sufficiently precise. We also show that external satellite clock corrections hardly contribute to CORS Network RTK ambiguity resolution, despite their quality, since the network satellite clock parameters and the ambiguities are almost completely uncorrelated. One positive is that the foreseen modernized GPS will have a very beneficial effect on CORS ambiguity resolution, because of an additional frequency with improved code precision.

Advancements in Micrometeorological Technique for Monitoring CH4 Release from Remote Permafrost Regions: Principles, Emerging Research, and Latest Updates

NASA Astrophysics Data System (ADS)

Burba, George; Budishchev, Artem; Gioli, Beniamino; Haapanala, Sami; Helbig, Manuel; Losacco, Salvatore; Mammarella, Ivan; Moreaux, Virginie; Murphy, Patrick; Oechel, Walter; Peltola, Olli; Rinne, Janne; Sonnentag, Oliver; Sturtevant, Cove; Vesala, Timo; Zona, Donatella; Zulueta, Rommel

2014-05-01

Flux stations have been widely used to monitor release and uptake rates of CO2, CH4, H2O and other gases from various ecosystems for climate research for over 30 years. The stations provide accurate and continuous measurements of gas exchange at time scales ranging from 15 or 30 minutes to multiple years, and at spatial scales ranging from thousands m2 to multiple km2, depending on the measurement height. The stations can nearly instantaneously detect rapid changes in gas release due to weather or man-triggered events (pressure changes, ice breakage and melts, ebullition events, etc.). They can also detect slow changes related to seasonal dynamics and man-triggered processes (seasonal freeze and thaw, long-term permafrost degradation, etc.). From 1980s to mid-2000s, station configuration, data collection and processing were highly-customized, site-specific and greatly dependent on "school-of-thought" practiced by a particular researcher. In the past 3-5 years, due to significant efforts of global and regional flux networks and technological developments, the methodology became fairly standardized. Majority of current stations compute gas emission and uptake rates using eddy covariance method, as one of the most direct micrometeorological techniques. Over 600 such flux stations operate in over 120 countries, using permanent and mobile towers or moving platforms (e.g., automobiles, helicopters, airplanes, ships, etc.). With increasing atmospheric temperatures in the Arctic likely resulting in a higher rate of permafrost degradation, measurements of gas exchange dynamics become particularly important. The permafrost regions store a significant amount of organic materials under anaerobic conditions, leading to large CH4 production and accumulation in the upper layers of bedrock, soil and ice. These regions may become a significant potential source of global CH4 release under a warming climate over the following decades and centuries. Present measurements of CH4 release in permafrost regions have mostly been made with static chamber techniques, and few were done with the eddy covariance approach using closed-path analyzers. Although chambers and closed-path analyzers have advantages, both techniques have significant limitations, especially for remote or portable research in cold regions. Static chamber measurements are discrete in time and space, and particularly difficult to use over polygonal tundra with highly non-uniform micro-topography and active soil layer. Closed-path gas analyzers for measuring CH4 eddy fluxes require climate control, employ high-power pumps, and generally require grid power and infrastructure. As a result, spatial coverage of eddy covariance CH4 flux measurements in cold regions remains limited. Existing stations are often located near grid power sources and roads rather than in the middle of the methane-producing ecosystem, while those that are placed appropriately may require extraordinary efforts to build and maintain them, with large investments into manpower and infrastructure. In this presentation, basic principles of eddy covariance flux measurements are explained, along with details on the CH4, CO2 and H2O exchange measurements using low-power flux stations. Also included are latest updates on the emerging research utilizing such stations in remote permafrost regions, and on the 2013-2014 development of fully automated remote unattended flux station capable of processing data on-the-go to continuously output final CH4 release rates.

NASDA knowledge-based network planning system

NASA Technical Reports Server (NTRS)

Yamaya, K.; Fujiwara, M.; Kosugi, S.; Yambe, M.; Ohmori, M.

1993-01-01

One of the SODS (space operation and data system) sub-systems, NP (network planning) was the first expert system used by NASDA (national space development agency of Japan) for tracking and control of satellite. The major responsibilities of the NP system are: first, the allocation of network and satellite control resources and, second, the generation of the network operation plan data (NOP) used in automated control of the stations and control center facilities. Up to now, the first task of network resource scheduling was done by network operators. NP system automatically generates schedules using its knowledge base, which contains information on satellite orbits, station availability, which computer is dedicated to which satellite, and how many stations must be available for a particular satellite pass or a certain time period. The NP system is introduced.

U.S. Geological Survey Catskill/Delaware Water-Quality Network: Water-Quality Report Water Year 2006

USGS Publications Warehouse

McHale, Michael R.; Siemion, Jason

2010-01-01

The U.S. Geological Survey operates a 60-station streamgaging network in the New York City Catskill/Delaware Water Supply System. Water-quality samples were collected at 13 of the stations in the Catskill/Delaware streamgaging network to provide resource managers with water-quality and water-quantity data from the water-supply system that supplies about 85 percent of the water needed by the more than 9 million residents of New York City. This report summarizes water-quality data collected at those 13 stations plus one additional station operated as a part of the U.S. Environmental Protection Agency's Regional Long-Term Monitoring Network for the 2006 water year (October 1, 2005 to September 30, 2006). An average of 62 water-quality samples were collected at each station during the 2006 water year, including grab samples collected every other week and storm samples collected with automated samplers. On average, 8 storms were sampled at each station during the 2006 water year. The 2006 calendar year was the second warmest on record and the summer of 2006 was the wettest on record for the northeastern United States. A large storm on June 26-28, 2006, caused extensive flooding in the western part of the network where record peak flows were measured at several watersheds.

A Gap-Filling Procedure for Hydrologic Data Based on Kalman Filtering and Expectation Maximization: Application to Data from the Wireless Sensor Networks of the Sierra Nevada

NASA Astrophysics Data System (ADS)

Coogan, A.; Avanzi, F.; Akella, R.; Conklin, M. H.; Bales, R. C.; Glaser, S. D.

2017-12-01

Automatic meteorological and snow stations provide large amounts of information at dense temporal resolution, but data quality is often compromised by noise and missing values. We present a new gap-filling and cleaning procedure for networks of these stations based on Kalman filtering and expectation maximization. Our method utilizes a multi-sensor, regime-switching Kalman filter to learn a latent process that captures dependencies between nearby stations and handles sharp changes in snowfall rate. Since the latent process is inferred using observations across working stations in the network, it can be used to fill in large data gaps for a malfunctioning station. The procedure was tested on meteorological and snow data from Wireless Sensor Networks (WSN) in the American River basin of the Sierra Nevada. Data include air temperature, relative humidity, and snow depth from dense networks of 10 to 12 stations within 1 km2 swaths. Both wet and dry water years have similar data issues. Data with artificially created gaps was used to quantify the method's performance. Our multi-sensor approach performs better than a single-sensor one, especially with large data gaps, as it learns and exploits the dominant underlying processes in snowpack at each site.

Statistical evaluation of the performance of gridded monthly precipitation products from reanalysis data, satellite estimates, and merged analyses over China

NASA Astrophysics Data System (ADS)

Deng, Xueliang; Nie, Suping; Deng, Weitao; Cao, Weihua

2018-04-01

In this study, we compared the following four different gridded monthly precipitation products: the National Centers for Environmental Prediction version 2 (NCEP-2) reanalysis data, the satellite-based Climate Prediction Center Morphing technique (CMORPH) data, the merged satellite-gauge Global Precipitation Climatology Project (GPCP) data, and the merged satellite-gauge-model data from the Beijing Climate Center Merged Estimation of Precipitation (BMEP). We evaluated the performances of these products using monthly precipitation observations spanning the period of January 2003 to December 2013 from a dense, national, rain gauge network in China. Our assessment involved several statistical techniques, including spatial pattern, temporal variation, bias, root-mean-square error (RMSE), and correlation coefficient (CC) analysis. The results show that NCEP-2, GPCP, and BMEP generally overestimate monthly precipitation at the national scale and CMORPH underestimates it. However, all of the datasets successfully characterized the northwest to southeast increase in the monthly precipitation over China. Because they include precipitation gauge information from the Global Telecommunication System (GTS) network, GPCP and BMEP have much smaller biases, lower RMSEs, and higher CCs than NCEP-2 and CMORPH. When the seasonal and regional variations are considered, NCEP-2 has a larger error over southern China during the summer. CMORPH poorly reproduces the magnitude of the precipitation over southeastern China and the temporal correlation over western and northwestern China during all seasons. BMEP has a lower RMSE and higher CC than GPCP over eastern and southern China, where the station network is dense. In contrast, BMEP has a lower CC than GPCP over western and northwestern China, where the gauge network is relatively sparse.

Black Carbon Measurements From Ireland's Transboundary Network (TXB)

NASA Astrophysics Data System (ADS)

Spohn, T. K.; Martin, D.; O'Dowd, C. D. D.

2017-12-01

Black Carbon (BC) is carbonaceous aerosol formed by incomplete fossil fuel combustion. Named for its light absorbing properties, it acts to trap heat in the atmosphere, thus behaving like a greenhouse gas, and is considered a strong, short-lived climate forcer by the International Panel on Climate Change (IPCC). Carbonaceous aerosols from biomass burning (BB) such as forest fires and residential wood burning, also known as brown carbon, affect the ultra violet (UV) light absorption in the atmosphere as well. In 2016 a three node black carbon monitoring network was established in Ireland as part of a Transboundary Monitoring Network (TXB). The three sites (Mace Head, Malin Head, and Carnsore Point) are coastal locations on opposing sides of the country, and offer the opportunity to assess typical northern hemispheric background concentrations as well national and European pollution events. The instruments deployed in this network (Magee Scientific AE33) facilitate elimination of the changes in response due to `aerosol loading' effects; and a real-time calculation of the `loading compensation' parameter which offers insights into aerosol optical properties. Additionally, these instruments have an inbuilt algorithm, which estimates the difference in absorption in the ultraviolet wavelengths (mostly by brown carbon) and the near infrared wavelengths (only by black carbon).Presented here are the first results of the BC measurements from the three Irish stations, including instrument validation, seasonal variation as well as local, regional, and transboundary influences based on air mass trajectories as well as concurrent in-situ observations (meteorological parameters, particle number, and aerosol composition). A comparison of the instrumental algorithm to off-line sensitivity calculations will also be made to assess the contribution of biomass burning to BC pollution events.

ILRS Station Reporting

NASA Technical Reports Server (NTRS)

Noll, Carey E.; Pearlman, Michael Reisman; Torrence, Mark H.

2013-01-01

Network stations provided system configuration documentation upon joining the ILRS. This information, found in the various site and system log files available on the ILRS website, is essential to the ILRS analysis centers, combination centers, and general user community. Therefore, it is imperative that the station personnel inform the ILRS community in a timely fashion when changes to the system occur. This poster provides some information about the various documentation that must be maintained. The ILRS network consists of over fifty global sites actively ranging to over sixty satellites as well as five lunar reflectors. Information about these stations are available on the ILRS website (http://ilrs.gsfc.nasa.gov/network/stations/index.html). The ILRS Analysis Centers must have current information about the stations and their system configuration in order to use their data in generation of derived products. However, not all information available on the ILRS website is as up-to-date as necessary for correct analysis of their data.

A Review on Climate Change in Weather Stations of Guilan Province Using Mann-Kendal Methodand GIS

NASA Astrophysics Data System (ADS)

Behzadi, Jalal

2016-07-01

Climate has always been changing during the life time of the earth, and has appeared in the form of ice age, hurricanes, severe and sudden temperature changes, precipitation and other climatic elements, and has dramatically influenced the environment, and in some cases has caused severe changes and even destructions. Some of the most important aspects of climate changes can be found in precipitation types of different regions in the world and especially Guilan, which is influenced by drastic land conversions and greenhouse gases. Also, agriculture division, industrial activities and unnecessary land conversions are thought to have a huge influence on climate change. Climate change is a result of abnormalcies of metorologyl parameters. Generally, the element of precipitation is somehow included in most theories about climate change. The present study aims to reveal precipitation abnormalcies in Guilan which lead to climate change, and possible deviations of precipitation parameter based on annual, seasonal and monthly series have been evaluated. The Mann-Kendal test has been used to reveal likely deviations leading to climate change. The trend of precipitation changes in long-term has been identifiedusing this method. Also, the beginning and end of these changes have been studied in five stations as representatives of all the thirteen weather stations. Then,the areas which have experienced climate change have been identified using the GIS software along with the severity of the changes with an emphasis on drought. These results can be used in planning and identifying the effects of these changes on the environment. Keywords: Climate Change, Guilan, Mann-Kendal, GIS

Measurements and modelling of base station power consumption under real traffic loads.

PubMed

Lorincz, Josip; Garma, Tonko; Petrovic, Goran

2012-01-01

Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient.

Measurements and Modelling of Base Station Power Consumption under Real Traffic Loads †

PubMed Central

Lorincz, Josip; Garma, Tonko; Petrovic, Goran

2012-01-01

Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient. PMID:22666026

Performance analysis of local area networks

NASA Technical Reports Server (NTRS)

Alkhatib, Hasan S.; Hall, Mary Grace

1990-01-01

A simulation of the TCP/IP protocol running on a CSMA/CD data link layer was described. The simulation was implemented using the simula language, and object oriented discrete event language. It allows the user to set the number of stations at run time, as well as some station parameters. Those parameters are the interrupt time and the dma transfer rate for each station. In addition, the user may configure the network at run time with stations of differing characteristics. Two types are available, and the parameters of both types are read from input files at run time. The parameters include the dma transfer rate, interrupt time, data rate, average message size, maximum frame size and the average interarrival time of messages per station. The information collected for the network is the throughput and the mean delay per packet. For each station, the number of messages attempted as well as the number of messages successfully transmitted is collected in addition to the throughput and mean packet delay per station.

Quality of surface water in Missouri, water year 2010

USGS Publications Warehouse

Barr, Miya N.

2011-01-01

The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, designs and operates a series of monitoring stations on streams throughout Missouri known as the Ambient Water-Quality Monitoring Network. During the 2010 water year (October 1, 2009 through September 30, 2010), data were collected at 75 stations-72 Ambient Water-Quality Monitoring Network stations, 2 U.S. Geological Survey National Stream Quality Accounting Network stations, and 1 spring sampled in cooperation with the U.S. Forest Service. Dissolved oxygen, specific conductance, water temperature, suspended solids, suspended sediment, fecal coliform bacteria, Escherichia coli bacteria, dissolved nitrate plus nitrite, total phosphorus, dissolved and total recoverable lead and zinc, and select pesticide compound summaries are presented for 72 of these stations. The stations primarily have been classified into groups corresponding to the physiography of the State, primary land use, or unique station types. In addition, a summary of hydrologic conditions in the State including peak discharges, monthly mean discharges, and 7-day low flow is presented.

Detecting earthquakes over a seismic network using single-station similarity measures

NASA Astrophysics Data System (ADS)

Bergen, Karianne J.; Beroza, Gregory C.

2018-06-01

New blind waveform-similarity-based detection methods, such as Fingerprint and Similarity Thresholding (FAST), have shown promise for detecting weak signals in long-duration, continuous waveform data. While blind detectors are capable of identifying similar or repeating waveforms without templates, they can also be susceptible to false detections due to local correlated noise. In this work, we present a set of three new methods that allow us to extend single-station similarity-based detection over a seismic network; event-pair extraction, pairwise pseudo-association, and event resolution complete a post-processing pipeline that combines single-station similarity measures (e.g. FAST sparse similarity matrix) from each station in a network into a list of candidate events. The core technique, pairwise pseudo-association, leverages the pairwise structure of event detections in its network detection model, which allows it to identify events observed at multiple stations in the network without modeling the expected moveout. Though our approach is general, we apply it to extend FAST over a sparse seismic network. We demonstrate that our network-based extension of FAST is both sensitive and maintains a low false detection rate. As a test case, we apply our approach to 2 weeks of continuous waveform data from five stations during the foreshock sequence prior to the 2014 Mw 8.2 Iquique earthquake. Our method identifies nearly five times as many events as the local seismicity catalogue (including 95 per cent of the catalogue events), and less than 1 per cent of these candidate events are false detections.

Evaluating meteorological data from weather stations, and from satellites and global models for a multi-site epidemiological study.

PubMed

Colston, Josh M; Ahmed, Tahmeed; Mahopo, Cloupas; Kang, Gagandeep; Kosek, Margaret; de Sousa Junior, Francisco; Shrestha, Prakash Sunder; Svensen, Erling; Turab, Ali; Zaitchik, Benjamin

2018-04-21

Longitudinal and time series analyses are needed to characterize the associations between hydrometeorological parameters and health outcomes. Earth Observation (EO) climate data products derived from satellites and global model-based reanalysis have the potential to be used as surrogates in situations and locations where weather-station based observations are inadequate or incomplete. However, these products often lack direct evaluation at specific sites of epidemiological interest. Standard evaluation metrics of correlation, agreement, bias and error were applied to a set of ten hydrometeorological variables extracted from two quasi-global, commonly used climate data products - the Global Land Data Assimilation System (GLDAS) and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) - to evaluate their performance relative to weather-station derived estimates at the specific geographic locations of the eight sites in a multi-site cohort study. These metrics were calculated for both daily estimates and 7-day averages and for a rotavirus-peak-season subset. Then the variables from the two sources were each used as predictors in longitudinal regression models to test their association with rotavirus infection in the cohort after adjusting for covariates. The availability and completeness of station-based validation data varied depending on the variable and study site. The performance of the two gridded climate models varied considerably within the same location and for the same variable across locations, according to different evaluation criteria and for the peak-season compared to the full dataset in ways that showed no obvious pattern. They also differed in the statistical significance of their association with the rotavirus outcome. For some variables, the station-based records showed a strong association while the EO-derived estimates showed none, while for others, the opposite was true. Researchers wishing to utilize publicly available climate data - whether EO-derived or station based - are advised to recognize their specific limitations both in the analysis and the interpretation of the results. Epidemiologists engaged in prospective research into environmentally driven diseases should install their own weather monitoring stations at their study sites whenever possible, in order to circumvent the constraints of choosing between distant or incomplete station data or unverified EO estimates. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

A climate trend analysis of Senegal

USGS Publications Warehouse

Funk, Christopher C.; Rowland, Jim; Adoum, Alkhalil; Eilerts, Gary; Verdin, James; White, Libby

2012-01-01

This brief report, drawing from a multi-year effort by the U.S. Agency for International Development (USAID) Famine Early Warning Systems Network (FEWS NET), identifies modest declines in rainfall, accompanied by increases in air temperatures. These analyses are based on quality-controlled station observations. Conclusions: * Summer rains have remained steady in Senegal over the past 20 years but are 15 percent below the 1920-1969 average. * Temperatures have increased by 0.9° Celsius since 1975, amplifying the effect of droughts. * Cereal yields are low but have been improving. * The amount of farmland per person is low and declining rapidly. * Current population and agriculture trends could lead to a 30-percent reduction in per capita cereal production by 2025.

Quantifying the spatio-temporal pattern of the ground impact of space weather events using dynamical networks formed from the SuperMAG database of ground based magnetometer stations.

NASA Astrophysics Data System (ADS)

Dods, Joe; Chapman, Sandra; Gjerloev, Jesper

2016-04-01

Quantitative understanding of the full spatial-temporal pattern of space weather is important in order to estimate the ground impact. Geomagnetic indices such as AE track the peak of a geomagnetic storm or substorm, but cannot capture the full spatial-temporal pattern. Observations by the ~100 ground based magnetometers in the northern hemisphere have the potential to capture the detailed evolution of a given space weather event. We present the first analysis of the full available set of ground based magnetometer observations of substorms using dynamical networks. SuperMAG offers a database containing ground station magnetometer data at a cadence of 1min from 100s stations situated across the globe. We use this data to form dynamic networks which capture spatial dynamics on timescales from the fast reconfiguration seen in the aurora, to that of the substorm cycle. Windowed linear cross-correlation between pairs of magnetometer time series along with a threshold is used to determine which stations are correlated and hence connected in the network. Variations in ground conductivity and differences in the response functions of magnetometers at individual stations are overcome by normalizing to long term averages of the cross-correlation. These results are tested against surrogate data in which phases have been randomised. The network is then a collection of connected points (ground stations); the structure of the network and its variation as a function of time quantify the detailed dynamical processes of the substorm. The network properties can be captured quantitatively in time dependent dimensionless network parameters and we will discuss their behaviour for examples of 'typical' substorms and storms. The network parameters provide a detailed benchmark to compare data with models of substorm dynamics, and can provide new insights on the similarities and differences between substorms and how they correlate with external driving and the internal state of the magnetosphere. We can also investigate the solar wind control of the magnetospheric-ionospheric convection system using dynamical networks. The dynamical networks are first interpolated onto a regular grid. Statistically averaged network responses are then formed for a variety of solar wind conditions, including investigating the network response to southward turnings. [1] Dods, J., S. C. Chapman, and J. W. Gjerloev (2015), Network analysis of geomagnetic substorms using the SuperMAG database of ground-based magnetometer stations, J. Geophys. Res. Space Physics, 120, 7774-7784, doi:10.1002/2015JA021456

Employing Tropospheric Numerical Weather Prediction Model for High-Precision GNSS Positioning

NASA Astrophysics Data System (ADS)

Alves, Daniele; Gouveia, Tayna; Abreu, Pedro; Magário, Jackes

2014-05-01

In the past few years is increasing the necessity of realizing high accuracy positioning. In this sense, the spatial technologies have being widely used. The GNSS (Global Navigation Satellite System) has revolutionized the geodetic positioning activities. Among the existent methods one can emphasize the Precise Point Positioning (PPP) and network-based positioning. But, to get high accuracy employing these methods, mainly in real time, is indispensable to realize the atmospheric modeling (ionosphere and troposphere) accordingly. Related to troposphere, there are the empirical models (for example Saastamoinen and Hopfield). But when highly accuracy results (error of few centimeters) are desired, maybe these models are not appropriated to the Brazilian reality. In order to minimize this limitation arises the NWP (Numerical Weather Prediction) models. In Brazil the CPTEC/INPE (Center for Weather Prediction and Climate Studies / Brazilian Institute for Spatial Researches) provides a regional NWP model, currently used to produce Zenithal Tropospheric Delay (ZTD) predictions (http://satelite.cptec.inpe.br/zenital/). The actual version, called eta15km model, has a spatial resolution of 15 km and temporal resolution of 3 hours. In this paper the main goal is to accomplish experiments and analysis concerning the use of troposphere NWP model (eta15km model) in PPP and network-based positioning. Concerning PPP it was used data from dozens of stations over the Brazilian territory, including Amazon forest. The results obtained with NWP model were compared with Hopfield one. NWP model presented the best results in all experiments. Related to network-based positioning it was used data from GNSS/SP Network in São Paulo State, Brazil. This network presents the best configuration in the country to realize this kind of positioning. Actually the network is composed by twenty stations (http://www.fct.unesp.br/#!/pesquisa/grupos-de-estudo-e-pesquisa/gege//gnss-sp-network2789/). The results obtained employing NWP model also were compared to Hopfield one, and the results were very interesting. The theoretical concepts, experiments, results and analysis will be presented in this paper.

On the usability of frequency distributions and source attribution of Cs-137 detections encountered in the IMS radio-nuclide network for radionuclide event screening and climate change monitoring

NASA Astrophysics Data System (ADS)

Becker, A.; Wotawa, G.; Zähringer, M.

2009-04-01

Under the provisions of the Comprehensive Nuclear-Test-Ban Treaty (CTBT), airborne radioactivity is measured by means of high purity Germanium gamma ray detectors deployed in a global monitoring network. Almost 60 of the scheduled 80 stations have been put in provisional operations by the end of 2008. Each station daily sends the 24 hour samples' spectroscopic data to the Vienna based Provisional Technical Secretariat (PTS) of the CTBT Organization (CTBTO) for review for treaty-relevant nuclides. Cs-137 is one of these relevant isotopes. Its typical minimum detectable concentration is in the order of a few Bq/m3. However, this isotope is also known to occur in atmospheric trace concentrations, due to known non CTBT relevant processes and sources related to, for example, the re-suspension of cesium from historic nuclear tests and/or the Chernobyl reactor disaster, temporarily enhanced by bio-mass burning (Wotawa et al. 2006). Properly attributed cesium detections can be used as a proxy to detect Aeolian dust events (Igarashi et al, 2001) that potentially carry cesium from all aforementioned sources but are also known to play an important role for the radiative forcing in the atmosphere (shadow effect), at the surface (albedo) and the carbon dioxide cycle when interacting with oceanic phytoplankton (Mikami and Shi, 2005). In this context this paper provides a systematic attribution of recent Cs-137 detections in the PTS monitoring network in order to Characterize those stations which are regularly affected by Cs-137 Provide input for procedures that distinguish CTBT relevant detection from other sources (event screening) Explore on the capability of certain stations to use their Cs-137 detections as a proxy to detect aeolian dust events and to flag the belonging filters to be relevant for further investigations in this field (-> EGU-2009 Session CL16/AS4.6/GM10.1: Aeolian dust: initiator, player, and recorder of environmental change). References Igarashi, Y., M. Aoyama, K. Hirose,M. Takashi and S. Yabuki, 2001: Is It Possible to Use 90Sr and 137Cs As Tracers for the Aeolian Dust Transport? Water, Air, & Soil Pollution 130, 349-354. Mikami, M. and G. Shi, 2005: Preliminary summary of aeolian dust experiment on climate impact -Japan-Sino joint project ADEC. Geophysical Research Abstracts, 7, 05985 Wotawa, G., L.-E. De Geer, A. Becker, R.D'Amours, M. Jean, R. Servranck and K. Ungar, 2006: Inter- and intra-continental transport of radioactive cesium released by boreal forest fires, Geophys. Res. Lett. 33, L12806, doi: 10.1029/2006GL026206 Disclaimer The views expressed in this publication are those of the author and do not necessarily reflect the views of the CTBTO Preparatory Commission.

Quality of surface water in Missouri, water year 2009

USGS Publications Warehouse

Barr, Miya N.

2010-01-01

The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, designs and operates a series of monitoring stations on streams throughout Missouri known as the Ambient Water-Quality Monitoring Network. During the 2009 water year (October 1, 2008, through September 30, 2009), data were collected at 75 stations-69 Ambient Water-Quality Monitoring Network stations, 2 U.S. Geological Survey National Stream Quality Accounting Network stations, 1 spring sampled in cooperation with the U.S. Forest Service, and 3 stations sampled in cooperation with the Elk River Watershed Improvement Association. Dissolved oxygen, specific conductance, water temperature, suspended solids, suspended sediment, fecal coliform bacteria, Escherichia coli bacteria, dissolved nitrate plus nitrite, total phosphorus, dissolved and total recoverable lead and zinc, and select pesticide compound summaries are presented for 72 of these stations. The stations primarily have been classified into groups corresponding to the physiography of the State, primary land use, or unique station types. In addition, a summary of hydrologic conditions in the State including peak discharges, monthly mean discharges, and seven-day low flow is presented.

Reconstruction of mass balance variations for Franz Josef Glacier, New Zealand, 1913 to 1989

DOE Office of Scientific and Technical Information (OSTI.GOV)

Woo, Mingko Woo; Fitzharris, B.B.

1992-11-01

A model of mass balance is constructed for the Franz Josef Glacier on the west coast of New Zealand. It uses daily data from a nearby, but short-record climate station. The model is extended back to 1913 by creating hybrid climate data from a long-record, but more distant, climate station. Its monthly data provide long-term temperature and precipitation trends, and daily fluctuations are simulated using a stochastic approach that is tuned to the characteristics of the short-record station. The glacier model provides estimates of equilibrium-line altitudes which are in reasonable agreement with those observed, and variations of cumulative mass balancemore » that correspond with patterns of advance and retreat of the glacier terminus.« less

Network operating system

NASA Technical Reports Server (NTRS)

1985-01-01

Long-term and short-term objectives for the development of a network operating system for the Space Station are stated. The short-term objective is to develop a prototype network operating system for a 100 megabit/second fiber optic data bus. The long-term objective is to establish guidelines for writing a detailed specification for a Space Station network operating system. Major milestones are noted. Information is given in outline form.

47 CFR 25.135 - Licensing provisions for earth station networks in the non-voice, non-geostationary mobile...

Code of Federal Regulations, 2013 CFR

2013-10-01

... Applications and Licenses Earth Stations § 25.135 Licensing provisions for earth station networks in the non... systems shall not transmit communications to or from user transceivers in the United States unless such communications are authorized under a service contract with the holder of a pertinent FCC blanket license or...

47 CFR 25.135 - Licensing provisions for earth station networks in the non-voice, non-geostationary mobile...

Code of Federal Regulations, 2010 CFR

2010-10-01

... Applications and Licenses Earth Stations § 25.135 Licensing provisions for earth station networks in the non... systems shall not transmit communications to or from user transceivers in the United States unless such communications are authorized under a service contract with the holder of a pertinent FCC blanket license or...

47 CFR 25.135 - Licensing provisions for earth station networks in the non-voice, non-geostationary mobile...

Code of Federal Regulations, 2012 CFR

2012-10-01

... Applications and Licenses Earth Stations § 25.135 Licensing provisions for earth station networks in the non... systems shall not transmit communications to or from user transceivers in the United States unless such communications are authorized under a service contract with the holder of a pertinent FCC blanket license or...

47 CFR 25.135 - Licensing provisions for earth station networks in the non-voice, non-geostationary mobile...

Code of Federal Regulations, 2011 CFR

2011-10-01

... Applications and Licenses Earth Stations § 25.135 Licensing provisions for earth station networks in the non... systems shall not transmit communications to or from user transceivers in the United States unless such communications are authorized under a service contract with the holder of a pertinent FCC blanket license or...

Designing optimal greenhouse gas monitoring networks for Australia

NASA Astrophysics Data System (ADS)

Ziehn, T.; Law, R. M.; Rayner, P. J.; Roff, G.

2016-01-01

Atmospheric transport inversion is commonly used to infer greenhouse gas (GHG) flux estimates from concentration measurements. The optimal location of ground-based observing stations that supply these measurements can be determined by network design. Here, we use a Lagrangian particle dispersion model (LPDM) in reverse mode together with a Bayesian inverse modelling framework to derive optimal GHG observing networks for Australia. This extends the network design for carbon dioxide (CO2) performed by Ziehn et al. (2014) to also minimise the uncertainty on the flux estimates for methane (CH4) and nitrous oxide (N2O), both individually and in a combined network using multiple objectives. Optimal networks are generated by adding up to five new stations to the base network, which is defined as two existing stations, Cape Grim and Gunn Point, in southern and northern Australia respectively. The individual networks for CO2, CH4 and N2O and the combined observing network show large similarities because the flux uncertainties for each GHG are dominated by regions of biologically productive land. There is little penalty, in terms of flux uncertainty reduction, for the combined network compared to individually designed networks. The location of the stations in the combined network is sensitive to variations in the assumed data uncertainty across locations. A simple assessment of economic costs has been included in our network design approach, considering both establishment and maintenance costs. Our results suggest that, while site logistics change the optimal network, there is only a small impact on the flux uncertainty reductions achieved with increasing network size.

Potential relocation of climatic environments suggests high rates of climate displacement within the North American protection network.

PubMed

Batllori, Enric; Parisien, Marc-André; Parks, Sean A; Moritz, Max A; Miller, Carol

2017-08-01

Ongoing climate change may undermine the effectiveness of protected area networks in preserving the set of biotic components and ecological processes they harbor, thereby jeopardizing their conservation capacity into the future. Metrics of climate change, particularly rates and spatial patterns of climatic alteration, can help assess potential threats. Here, we perform a continent-wide climate change vulnerability assessment whereby we compare the baseline climate of the protected area network in North America (Canada, United States, México-NAM) to the projected end-of-century climate (2071-2100). We estimated the projected pace at which climatic conditions may redistribute across NAM (i.e., climate velocity), and identified future nearest climate analogs to quantify patterns of climate relocation within, among, and outside protected areas. Also, we interpret climatic relocation patterns in terms of associated land-cover types. Our analysis suggests that the conservation capacity of the NAM protection network is likely to be severely compromised by a changing climate. The majority of protected areas (~80%) might be exposed to high rates of climate displacement that could promote important shifts in species abundance or distribution. A small fraction of protected areas (<10%) could be critical for future conservation plans, as they will host climates that represent analogs of conditions currently characterizing almost a fifth of the protected areas across NAM. However, the majority of nearest climatic analogs for protected areas are in nonprotected locations. Therefore, unprotected landscapes could pose additional threats, beyond climate forcing itself, as sensitive biota may have to migrate farther than what is prescribed by the climate velocity to reach a protected area destination. To mitigate future threats to the conservation capacity of the NAM protected area network, conservation plans will need to capitalize on opportunities provided by the existing availability of natural land-cover types outside the current network of NAM protected areas. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Climate and ET: Does Plant Water Requirements Increase during Droughts?

NASA Astrophysics Data System (ADS)

Fipps, G.

2015-12-01

Municipalities, engineering consultants and State agencies use reference evapotranspiration (ETo) data (directly and indirectly) for long-term water planning, for designing hydraulic structures, and for establishing regulatory guidance and conservation programs intended to reduce water waste. The use ETo data for agricultural and landscape irrigation scheduling is becoming more common in Texas as ETo-based controllers and automation technologies become more affordable. Until recently, most ETo data has been available as monthly values averaged over many years. Today, automated weather stations and irrigation controllers equipped with specialized instrumentation allow for real-time ETo measurements. With the expected rise in global warming and increased frequency of extreme climate variability in the coming decades, conservation and efficient use of water resources is essential and must make use of the most accurate and representative data available. 2011 marked the driest year on record in the State of Texas. Compounding the lack of rainfall was record heat during the Summer of 2011. An analysis of real time ETo (reference evapotranspiration) data in Texas found that ET was 30 to 50% higher than historic averages during the 2011 Summer. The implications are quite serious, as most current water planning and drought contingency plans do not take into consideration increases in ET during such periods, and irrigation planning and capacity sizing are based on historic averages of consumptive use. This paper examines the relationship between ET and climate during this extreme climatic event. While the solar radiation was near normal levels, temperature and wind was much higher and dew points much lower than norms. The variability and statistical difference between average monthly ETo data and daily, monthly and seasonal ETo measurements (from 2006 to 2014) for selected weather stations of the Texas ET Network. This study will also examine the suitability of using average ETo rates for use in regional water planning and in irrigation scheduling.

Quantification of precipitation measurement discontinuity induced by wind shields on national gauges

USGS Publications Warehouse

Yang, Daqing; Goodison, Barry E.; Metcalfe, John R.; Louie, Paul; Leavesley, George H.; Emerson, Douglas G.; Hanson, Clayton L.; Golubev, Valentin S.; Elomaa, Esko; Gunther, Thilo; Pangburn, Timothy; Kang, Ersi; Milkovic, Janja

1999-01-01

Various combinations of wind shields and national precipitation gauges commonly used in countries of the northern hemisphere have been studied in this paper, using the combined intercomparison data collected at 14 sites during the World Meteorological Organization's (WMO) Solid Precipitation Measurement Intercomparison Project. The results show that wind shields improve gauge catch of precipitation, particularly for snow. Shielded gauges, on average, measure 20–70% more snow than unshielded gauges. Without a doubt, the use of wind shields on precipitation gauges has introduced a significant discontinuity into precipitation records, particularly in cold and windy regions. This discontinuity is not constant and it varies with wind speed, temperature, and precipitation type. Adjustment for this discontinuity is necessary to obtain homogenous precipitation data for climate change and hydrological studies. The relation of the relative catch ratio (RCR, ratio of measurements of shielded gauge to unshielded gauge) versus wind speed and temperature has been developed for Alter and Tretyakov wind shields. Strong linear relations between measurements of shielded gauge and unshielded gauge have also been found for different precipitation types. The linear relation does not fully take into account the varying effect of wind and temperature on gauge catch. Overadjustment by the linear relation may occur at those sites with lower wind speeds, and underadjustment may occur at those stations with higher wind speeds. The RCR technique is anticipated to be more applicable in a wide range of climate conditions. The RCR technique and the linear relation have been tested at selected WMO intercomparison stations, and reasonable agreement between the adjusted amounts and the shielded gauge measurements was obtained at most of the sites. Test application of the developed methodologies to a regional or national network is therefore recommended to further evaluate their applicability in different climate conditions. Significant increase of precipitation is expected due to the adjustment particularly in high latitudes and other cold regions. This will have a meaningful impact on climate variation and change analyses.

The Centennial Trends Greater Horn of Africa precipitation dataset.

PubMed

Funk, Chris; Nicholson, Sharon E; Landsfeld, Martin; Klotter, Douglas; Peterson, Pete; Harrison, Laura

2015-01-01

East Africa is a drought prone, food and water insecure region with a highly variable climate. This complexity makes rainfall estimation challenging, and this challenge is compounded by low rain gauge densities and inhomogeneous monitoring networks. The dearth of observations is particularly problematic over the past decade, since the number of records in globally accessible archives has fallen precipitously. This lack of data coincides with an increasing scientific and humanitarian need to place recent seasonal and multi-annual East African precipitation extremes in a deep historic context. To serve this need, scientists from the UC Santa Barbara Climate Hazards Group and Florida State University have pooled their station archives and expertise to produce a high quality gridded 'Centennial Trends' precipitation dataset. Additional observations have been acquired from the national meteorological agencies and augmented with data provided by other universities. Extensive quality control of the data was carried out and seasonal anomalies interpolated using kriging. This paper documents the CenTrends methodology and data.

The Centennial Trends Greater Horn of Africa precipitation dataset

USGS Publications Warehouse

Funk, Chris; Nicholson, Sharon E.; Landsfeld, Martin F.; Klotter, Douglas; Peterson, Pete J.; Harrison, Laura

2015-01-01

East Africa is a drought prone, food and water insecure region with a highly variable climate. This complexity makes rainfall estimation challenging, and this challenge is compounded by low rain gauge densities and inhomogeneous monitoring networks. The dearth of observations is particularly problematic over the past decade, since the number of records in globally accessible archives has fallen precipitously. This lack of data coincides with an increasing scientific and humanitarian need to place recent seasonal and multi-annual East African precipitation extremes in a deep historic context. To serve this need, scientists from the UC Santa Barbara Climate Hazards Group and Florida State University have pooled their station archives and expertise to produce a high quality gridded ‘Centennial Trends’ precipitation dataset. Additional observations have been acquired from the national meteorological agencies and augmented with data provided by other universities. Extensive quality control of the data was carried out and seasonal anomalies interpolated using kriging. This paper documents the CenTrends methodology and data.

Investigation of the 16-year and 18-year ZTD Time Series Derived from GPS Data Processing

NASA Astrophysics Data System (ADS)

Bałdysz, Zofia; Nykiel, Grzegorz; Figurski, Mariusz; Szafranek, Karolina; KroszczyńSki, Krzysztof

2015-08-01

The GPS system can play an important role in activities related to the monitoring of climate. Long time series, coherent strategy, and very high quality of tropospheric parameter Zenith Tropospheric Delay (ZTD) estimated on the basis of GPS data analysis allows to investigate its usefulness for climate research as a direct GPS product. This paper presents results of analysis of 16-year time series derived from EUREF Permanent Network (EPN) reprocessing performed by the Military University of Technology. For 58 stations Lomb-Scargle periodograms were performed in order to obtain information about the oscillations in ZTD time series. Seasonal components and linear trend were estimated using Least Square Estimation (LSE) and Mann—Kendall trend test was used to confirm the presence of a linear trend designated by LSE method. In order to verify the impact of the length of time series on trend value, comparison between 16 and 18 years were performed.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arrowsmith, Stephen John; Young, Christopher J.; Ballard, Sanford

The standard paradigm for seismic event monitoring breaks the event detection problem down into a series of processing stages that can be categorized at the highest level into station-level processing and network-level processing algorithms (e.g., Le Bras and Wuster (2002)). At the station-level, waveforms are typically processed to detect signals and identify phases, which may subsequently be updated based on network processing. At the network-level, phase picks are associated to form events, which are subsequently located. Furthermore, waveforms are typically directly exploited only at the station-level, while network-level operations rely on earth models to associate and locate the events thatmore » generated the phase picks.« less

A Network Selection Algorithm Considering Power Consumption in Hybrid Wireless Networks

NASA Astrophysics Data System (ADS)

Joe, Inwhee; Kim, Won-Tae; Hong, Seokjoon

In this paper, we propose a novel network selection algorithm considering power consumption in hybrid wireless networks for vertical handover. CDMA, WiBro, WLAN networks are candidate networks for this selection algorithm. This algorithm is composed of the power consumption prediction algorithm and the final network selection algorithm. The power consumption prediction algorithm estimates the expected lifetime of the mobile station based on the current battery level, traffic class and power consumption for each network interface card of the mobile station. If the expected lifetime of the mobile station in a certain network is not long enough compared the handover delay, this particular network will be removed from the candidate network list, thereby preventing unnecessary handovers in the preprocessing procedure. On the other hand, the final network selection algorithm consists of AHP (Analytic Hierarchical Process) and GRA (Grey Relational Analysis). The global factors of the network selection structure are QoS, cost and lifetime. If user preference is lifetime, our selection algorithm selects the network that offers longest service duration due to low power consumption. Also, we conduct some simulations using the OPNET simulation tool. The simulation results show that the proposed algorithm provides longer lifetime in the hybrid wireless network environment.

Predicting the performance of local seismic networks using Matlab and Google Earth.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chael, Eric Paul

2009-11-01

We have used Matlab and Google Earth to construct a prototype application for modeling the performance of local seismic networks for monitoring small, contained explosions. Published equations based on refraction experiments provide estimates of peak ground velocities as a function of event distance and charge weight. Matlab routines implement these relations to calculate the amplitudes across a network of stations from sources distributed over a geographic grid. The amplitudes are then compared to ambient noise levels at the stations, and scaled to determine the smallest yield that could be detected at each source location by a specified minimum number ofmore » stations. We use Google Earth as the primary user interface, both for positioning the stations of a hypothetical local network, and for displaying the resulting detection threshold contours.« less

Prediction of onset and cessation of austral summer rainfall and dry spell frequency analysis in semiarid Botswana

NASA Astrophysics Data System (ADS)

Byakatonda, Jimmy; Parida, B. P.; Kenabatho, Piet K.; Moalafhi, D. B.

2018-01-01

Uncertainties in rainfall have increased in the recent past exacerbating climate risks which are projected to be higher in semiarid environments. This study investigates the associated features of rainfall such as rain onset, cessation, length of the rain season (LRS), and dry spell frequency (DSF) as part of climate risk management in Botswana. Their trends were analysed using Mann-Kendall test statistic and Sen's Slope estimator. The rainfall-evapotranspiration relationships were used in formulating the rain onset and cessation criteria. To understand some of the complexities arising from such uncertainties, artificial neural network (ANN) is used to predict onset and cessation of rain. Results reveal higher coefficients of variation in onset dates as compared to cessation of rain. Pandamatenga experiences the earliest onset on 28th of November while Tsabong the latest on 14th of January. Likewise, earliest cessation is observed at Tshane on 22nd of February and the latest on 30th of March at Shakawe. The shortest LRS of 45 days is registered at Tsabong whereas the northern locations show LRS greater than 100 days. Stations across the country experience strong negative correlation between onset and LRS of - 0.9. DSF shows increasing trends in 50% of the stations but only significant at Mahalapye, Pandamatenga, and Shakawe. Combining the LRS criteria and DSF, Kasane, Pandamatenga, and Shakawe were identified to be suitable for rainfed agriculture in Botswana especially for short to medium maturing cereal varieties. Predictions of onset and cessation indicate the possibility of delayed onset by 2-5 weeks in the next 5 years. Information generated from this study could help Botswana in climate risk management in the context of rainfed farming.

Simulated building energy demand biases resulting from the use of representative weather stations

DOE PAGES

Burleyson, Casey D.; Voisin, Nathalie; Taylor, Z. Todd; ...

2017-11-06

Numerical building models are typically forced with weather data from a limited number of “representative cities” or weather stations representing different climate regions. The use of representative weather stations reduces computational costs, but often fails to capture spatial heterogeneity in weather that may be important for simulations aimed at understanding how building stocks respond to a changing climate. Here, we quantify the potential reduction in temperature and load biases from using an increasing number of weather stations over the western U.S. Our novel approach is based on deriving temperature and load time series using incrementally more weather stations, ranging frommore » 8 to roughly 150, to evaluate the ability to capture weather patterns across different seasons. Using 8 stations across the western U.S., one from each IECC climate zone, results in an average absolute summertime temperature bias of ~4.0 °C with respect to a high-resolution gridded dataset. The mean absolute bias drops to ~1.5 °C using all available weather stations. Temperature biases of this magnitude could translate to absolute summertime mean simulated load biases as high as 13.5%. Increasing the size of the domain over which biases are calculated reduces their magnitude as positive and negative biases may cancel out. Using 8 representative weather stations can lead to a 20–40% bias of peak building loads during both summer and winter, a significant error for capacity expansion planners who may use these types of simulations. Using weather stations close to population centers reduces both mean and peak load biases. Our approach could be used by others designing aggregate building simulations to understand the sensitivity to their choice of weather stations used to drive the models.« less

Simulated building energy demand biases resulting from the use of representative weather stations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burleyson, Casey D.; Voisin, Nathalie; Taylor, Z. Todd

Numerical building models are typically forced with weather data from a limited number of “representative cities” or weather stations representing different climate regions. The use of representative weather stations reduces computational costs, but often fails to capture spatial heterogeneity in weather that may be important for simulations aimed at understanding how building stocks respond to a changing climate. Here, we quantify the potential reduction in temperature and load biases from using an increasing number of weather stations over the western U.S. Our novel approach is based on deriving temperature and load time series using incrementally more weather stations, ranging frommore » 8 to roughly 150, to evaluate the ability to capture weather patterns across different seasons. Using 8 stations across the western U.S., one from each IECC climate zone, results in an average absolute summertime temperature bias of ~4.0 °C with respect to a high-resolution gridded dataset. The mean absolute bias drops to ~1.5 °C using all available weather stations. Temperature biases of this magnitude could translate to absolute summertime mean simulated load biases as high as 13.5%. Increasing the size of the domain over which biases are calculated reduces their magnitude as positive and negative biases may cancel out. Using 8 representative weather stations can lead to a 20–40% bias of peak building loads during both summer and winter, a significant error for capacity expansion planners who may use these types of simulations. Using weather stations close to population centers reduces both mean and peak load biases. Our approach could be used by others designing aggregate building simulations to understand the sensitivity to their choice of weather stations used to drive the models.« less

Simulated building energy demand biases resulting from the use of representative weather stations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burleyson, Casey D.; Voisin, Nathalie; Taylor, Z. Todd

Numerical building models are typically forced with weather data from a limited number of “representative cities” or weather stations representing different climate regions. The use of representative weather stations reduces computational costs, but often fails to capture spatial heterogeneity in weather that may be important for simulations aimed at understanding how building stocks respond to a changing climate. We quantify the potential reduction in bias from using an increasing number of weather stations over the western U.S. The approach is based on deriving temperature and load time series using incrementally more weather stations, ranging from 8 to roughly 150, tomore » capture weather across different seasons. Using 8 stations, one from each climate zone, across the western U.S. results in an average absolute summertime temperature bias of 7.2°F with respect to a spatially-resolved gridded dataset. The mean absolute bias drops to 2.8°F using all available weather stations. Temperature biases of this magnitude could translate to absolute summertime mean simulated load biases as high as 13.8%, a significant error for capacity expansion planners who may use these types of simulations. Increasing the size of the domain over which biases are calculated reduces their magnitude as positive and negative biases may cancel out. Using 8 representative weather stations can lead to a 20-40% overestimation of peak building loads during both summer and winter. Using weather stations close to population centers reduces both mean and peak load biases. This approach could be used by others designing aggregate building simulations to understand the sensitivity to their choice of weather stations used to drive the models.« less

Atmospheric inversion for cost effective quantification of city CO2 emissions

NASA Astrophysics Data System (ADS)

Wu, L.; Broquet, G.; Ciais, P.; Bellassen, V.; Vogel, F.; Chevallier, F.; Xueref-Remy, I.; Wang, Y.

2015-11-01

Cities, currently covering only a very small portion (< 3 %) of the world's land surface, directly release to the atmosphere about 44 % of global energy-related CO2, and are associated with 71-76 % of CO2 emissions from global final energy use. Although many cities have set voluntary climate plans, their CO2 emissions are not evaluated by Monitoring, Reporting and Verification (MRV) procedures that play a key role for market- or policy-based mitigation actions. Here we propose a monitoring tool that could support the development of such procedures at the city scale. It is based on an atmospheric inversion method that exploits inventory data and continuous atmospheric CO2 concentration measurements from a network of stations within and around cities to estimate city CO2 emissions. We examine the cost-effectiveness and the performance of such a tool. The instruments presently used to measure CO2 concentrations at research stations are expensive. However, cheaper sensors are currently developed and should be useable for the monitoring of CO2 emissions from a megacity in the near-term. Our assessment of the inversion method is thus based on the use of several types of hypothetical networks, with a range of numbers of sensors sampling at 25 m a.g.l. The study case for this assessment is the monitoring of the emissions of the Paris metropolitan area (~ 12 million inhabitants and 11.4 Tg C emitted in 2010) during the month of January 2011. The performance of the inversion is evaluated in terms of uncertainties in the estimates of total and sectoral CO2 emissions. These uncertainties are compared to a notional ambitious target to diagnose annual total city emissions with an uncertainty of 5 % (2-sigma). We find that, with 10 stations only, which is the typical size of current pilot networks that are deployed in some cities, the uncertainty for the 1-month total city CO2 emissions is significantly reduced by the inversion by ~ 42 % but still corresponds to an annual uncertainty that is two times larger than the target of 5 %. By extending the network from 10 to 70 stations, the inversion can meet this requirement. As for major sectoral CO2 emissions, the uncertainties in the inverted emissions using 70 stations are reduced significantly over that obtained using 10 stations by 32 % for commercial and residential buildings, by 33 % for road transport and by 18 % for the production of energy by power plants, respectively. With 70 stations, the uncertainties from the inversion become of 15 % 2-sigma annual uncertainty for dispersed building emissions, and 18 % for emissions from road transport and energy production. The inversion performance could be further improved by optimal design of station locations and/or by assimilating additional atmospheric measurements of species that are co-emitted with CO2 by fossil fuel combustion processes with a specific signature from each sector, such as carbon monoxide (CO). Atmospheric inversions based on continuous CO2 measurements from a large number of cheap sensors can thus deliver a valuable quantification tool for the monitoring and/or the verification of city CO2 emissions (baseline) and CO2 emission reductions (commitments).

The surface climatology of the Ross Ice Shelf Antarctica.

PubMed

Costanza, Carol A; Lazzara, Matthew A; Keller, Linda M; Cassano, John J

2016-12-01

The University of Wisconsin-Madison Antarctic Automatic Weather Station (AWS) project has been making meteorological surface observations on the Ross Ice Shelf (RIS) for approximately 30 years. This network offers the most continuous set of routine measurements of surface meteorological variables in this region. The Ross Island area is excluded from this study. The surface climate of the RIS is described using the AWS measurements. Temperature, pressure, and wind data are analysed on daily, monthly, seasonal, and annual time periods for 13 AWS across the RIS. The AWS are separated into three representative regions - central, coastal, and the area along the Transantarctic Mountains - in order to describe specific characteristics of sections of the RIS. The climatology describes general characteristics of the region and significant changes over time. The central AWS experiences the coldest mean temperature, and the lowest resultant wind speed. These AWSs also experience the coldest potential temperatures with a minimum of 209.3 K at Gill AWS. The AWS along the Transantarctic Mountains experiences the warmest mean temperature, the highest mean sea-level pressure, and the highest mean resultant wind speed. Finally, the coastal AWS experiences the lowest mean pressure. Climate indices (MEI, SAM, and SAO) are compared to temperature and pressure data of four of the AWS with the longest observation periods, and significant correlation is found for most AWS in sea-level pressure and temperature. This climatology study highlights characteristics that influence the climate of the RIS, and the challenges of maintaining a long-term Antarctic AWS network. Results from this effort are essential for the broader Antarctic meteorology community for future research.

Ecological networks are more sensitive to plant than to animal extinction under climate change

PubMed Central

Schleuning, Matthias; Fründ, Jochen; Schweiger, Oliver; Welk, Erik; Albrecht, Jörg; Albrecht, Matthias; Beil, Marion; Benadi, Gita; Blüthgen, Nico; Bruelheide, Helge; Böhning-Gaese, Katrin; Dehling, D. Matthias; Dormann, Carsten F.; Exeler, Nina; Farwig, Nina; Harpke, Alexander; Hickler, Thomas; Kratochwil, Anselm; Kuhlmann, Michael; Kühn, Ingolf; Michez, Denis; Mudri-Stojnić, Sonja; Plein, Michaela; Rasmont, Pierre; Schwabe, Angelika; Settele, Josef; Vujić, Ante; Weiner, Christiane N.; Wiemers, Martin; Hof, Christian

2016-01-01

Impacts of climate change on individual species are increasingly well documented, but we lack understanding of how these effects propagate through ecological communities. Here we combine species distribution models with ecological network analyses to test potential impacts of climate change on >700 plant and animal species in pollination and seed-dispersal networks from central Europe. We discover that animal species that interact with a low diversity of plant species have narrow climatic niches and are most vulnerable to climate change. In contrast, biotic specialization of plants is not related to climatic niche breadth and vulnerability. A simulation model incorporating different scenarios of species coextinction and capacities for partner switches shows that projected plant extinctions under climate change are more likely to trigger animal coextinctions than vice versa. This result demonstrates that impacts of climate change on biodiversity can be amplified via extinction cascades from plants to animals in ecological networks. PMID:28008919

Ecological networks are more sensitive to plant than to animal extinction under climate change.

PubMed

Schleuning, Matthias; Fründ, Jochen; Schweiger, Oliver; Welk, Erik; Albrecht, Jörg; Albrecht, Matthias; Beil, Marion; Benadi, Gita; Blüthgen, Nico; Bruelheide, Helge; Böhning-Gaese, Katrin; Dehling, D Matthias; Dormann, Carsten F; Exeler, Nina; Farwig, Nina; Harpke, Alexander; Hickler, Thomas; Kratochwil, Anselm; Kuhlmann, Michael; Kühn, Ingolf; Michez, Denis; Mudri-Stojnić, Sonja; Plein, Michaela; Rasmont, Pierre; Schwabe, Angelika; Settele, Josef; Vujić, Ante; Weiner, Christiane N; Wiemers, Martin; Hof, Christian

2016-12-23

Impacts of climate change on individual species are increasingly well documented, but we lack understanding of how these effects propagate through ecological communities. Here we combine species distribution models with ecological network analyses to test potential impacts of climate change on >700 plant and animal species in pollination and seed-dispersal networks from central Europe. We discover that animal species that interact with a low diversity of plant species have narrow climatic niches and are most vulnerable to climate change. In contrast, biotic specialization of plants is not related to climatic niche breadth and vulnerability. A simulation model incorporating different scenarios of species coextinction and capacities for partner switches shows that projected plant extinctions under climate change are more likely to trigger animal coextinctions than vice versa. This result demonstrates that impacts of climate change on biodiversity can be amplified via extinction cascades from plants to animals in ecological networks.

Status report on the establishment of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) International Monitoring System (IMS) infrasound network

NASA Astrophysics Data System (ADS)

Vivas Veloso, J. A.; Christie, D. R.; Campus, P.; Bell, M.; Hoffmann, T. L.; Langlois, A.; Martysevich, P.; Demirovik, E.; Carvalho, J.; Kramer, A.

2002-11-01

The infrasound component of the International Monitoring System (IMS) for Comprehensive Nuclear-Test-Ban Treaty verification aims for global detection and localization of low-frequency sound waves originating from atmospheric nuclear explosions. The infrasound network will consist of 60 array stations, distributed as evenly as possible over the globe to assure at least two-station detection capability for 1-kton explosions at any point on earth. This network will be larger and more sensitive than any other previously operated infrasound network. As of today, 85% of the site surveys for IMS infrasound stations have been completed, 25% of the stations have been installed, and 8% of the installations have been certified and are transmitting high-quality continuous data to the International Data Center in Vienna. By the end of 2002, 20% of the infrasound network is expected to be certified and operating in post-certification mode. This presentation will discuss the current status and progress made in the site survey, installation, and certification programs for IMS infrasound stations. A review will be presented of the challenges and difficulties encountered in these programs, together with practical solutions to these problems.

Feasibility study of earthquake early warning (EEW) in Hawaii

USGS Publications Warehouse

Thelen, Weston A.; Hotovec-Ellis, Alicia J.; Bodin, Paul

2016-09-30

The effects of earthquake shaking on the population and infrastructure across the State of Hawaii could be catastrophic, and the high seismic hazard in the region emphasizes the likelihood of such an event. Earthquake early warning (EEW) has the potential to give several seconds of warning before strong shaking starts, and thus reduce loss of life and damage to property. The two approaches to EEW are (1) a network approach (such as ShakeAlert or ElarmS) where the regional seismic network is used to detect the earthquake and distribute the alarm and (2) a local approach where a critical facility has a single seismometer (or small array) and a warning system on the premises.The network approach, also referred to here as ShakeAlert or ElarmS, uses the closest stations within a regional seismic network to detect and characterize an earthquake. Most parameters used for a network approach require observations on multiple stations (typically 3 or 4), which slows down the alarm time slightly, but the alarms are generally more reliable than with single-station EEW approaches. The network approach also benefits from having stations closer to the source of any potentially damaging earthquake, so that alarms can be sent ahead to anyone who subscribes to receive the notification. Thus, a fully implemented ShakeAlert system can provide seconds of warning for both critical facilities and general populations ahead of damaging earthquake shaking.The cost to implement and maintain a fully operational ShakeAlert system is high compared to a local approach or single-station solution, but the benefits of a ShakeAlert system would be felt statewide—the warning times for strong shaking are potentially longer for most sources at most locations.The local approach, referred to herein as “single station,” uses measurements from a single seismometer to assess whether strong earthquake shaking can be expected. Because of the reliance on a single station, false alarms are more common than when using a regional network of seismometers. Given the current network, a single-station approach provides more warning for damaging earthquakes that occur close to the station, but it would have limited benefit compared to a fully implemented ShakeAlert system. For Honolulu, for example, the single-station approach provides an advantage over ShakeAlert only for earthquakes that occur in a narrow zone extending northeast and southwest of O‘ahu. Instrumentation and alarms associated with the single-station approach are typically maintained and assessed within the target facility, and thus no outside connectivity is required. A single-station approach, then, is unlikely to help broader populations beyond the individuals at the target facility, but they have the benefit of being commercially available for relatively little cost. The USGS Hawaiian Volcano Observatory (HVO) is the Advanced National Seismic System (ANSS) regional seismic network responsible for locating and characterizing earthquakes across the State of Hawaii. During 2014 and 2015, HVO tested a network-based EEW algorithm within the current seismic network in order to assess the suitability for building a full EEW system. Using the current seismic instrumentation and processing setup at HVO, it is possible for a network approach to release an alarm a little more than 3 seconds after the earthquake is recorded on the fourth seismometer. Presently, earthquakes having M≥3 detected with the ElarmS algorithm have an average location error of approximately 4.5 km and an average magnitude error of -0.3 compared to the reviewed catalog locations from the HVO. Additional stations and upgrades to existing seismic stations would serve to improve solution precision and warning times and additional staffing would be required to provide support for a robust, network-based EEW system. For a critical facility on the Island of Hawaiʻi, such as the telescopes atop Mauna Kea, one phased approach to mitigate losses could be to immediately install a single station system to establish some level of warning. Subsequently, supporting the implementation of a full network-based EEW system on the Island of Hawaiʻi would provide additional benefit in the form of improved warning times once the system is fully installed and operational, which may take several years. Distributed populations across the Hawaiian Islands, including those outside the major cities and far from the likely earthquake source areas, would likely only benefit from a network approach such as ShakeAlert to provide warnings of strong shaking.

Climate Variation at Flagstaff, Arizona - 1950 to 2007

USGS Publications Warehouse

Hereford, Richard

2007-01-01

INTRODUCTION Much scientific research demonstrates the existence of recent climate variation, particularly global warming. Climate prediction models forecast that climate will change; it will become warmer, droughts will increase in number and severity, and extreme climate events will recur often?desiccating aridity, extremely wet, unusually warm, or even frigid at times. However, the global models apply to average conditions in large grids approximately 150 miles on an edge (Thorpe, 2005), and how or whether specific areas within a grid are affected is unclear. Flagstaff's climate is mentioned in the context of global change, but information is lacking on the amount and trend of changes in precipitation, snowfall, and temperature. The purpose of this report is to understand what may be happening to Flagstaff's climate by reviewing local climate history. Flagstaff is in north-central Arizona south of San Francisco Mountain, which reaches 12,633 feet, the highest in Arizona (fig. 1). At 6,900 feet, surrounded by ponderosa pine forest, Flagstaff enjoys a four-season climate; winter-daytime temperatures are cool, averaging 45 degrees (Fahrenheit). Summer-daytime temperatures are comfortable, averaging 80 degrees, which is pleasant compared with nearby low-elevation deserts. Flagstaff?s precipitation averages 22-inches per year with a range of 9 to 39 inches. Snowfall occurs each season, averaging 97 inches annually. This report, written for the non-technical reader, interprets climate variation at Flagstaff as observed at the National Weather Service (NWS) station at Pulliam Field (or Airport), a first-order weather station staffed by meteorologists (Staudenmaier and others, 2007). The station is on a flat-topped ridge surrounded by forest 5-miles south of Flagstaff at an elevation of 7,003 feet. Data used in this analysis are daily measurements of precipitation (including snowfall) and temperature (maximum and minimum) covering the period from 1950, when the station began operation, through spring 2007. Conversations with Byron Peterson and Michael Staudenmaier of the NWS helped us understand the difficulties of collecting consistent weather data, operation of the station, and Flagstaff's climate. Weather is the daily or even instantaneous state of temperature and precipitation. Climate is the average or accumulation of these parameters over longer time scales such as a week, month, or year. Seasonal (winter, spring, summer, and fall) and annual averages of temperature and accumulated precipitation describe the temporal variation of Flagstaff's climate, which is shown graphically with time series (figs. 2, 4, 6, 8-15). These plots show precipitation or temperature on the ordinate plotted against time on the abscissa, which is a year for annually repeating data or the year of a particular season. The plots reveal changing patterns of precipitation and temperature related to droughts, wet episodes, and rising temperatures.

Spatial heterogeneity of climate change as an experiential basis for skepticism

PubMed Central

Kaufmann, Robert K.; Mann, Michael L.; Gopal, Sucharita; Liederman, Jackie A.; Howe, Peter D.; Pretis, Felix; Gilmore, Michelle

2017-01-01

We postulate that skepticism about climate change is partially caused by the spatial heterogeneity of climate change, which exposes experiential learners to climate heuristics that differ from the global average. This hypothesis is tested by formalizing an index that measures local changes in climate using station data and comparing this index with survey-based model estimates of county-level opinion about whether global warming is happening. Results indicate that more stations exhibit cooling and warming than predicted by random chance and that spatial variations in these changes can account for spatial variations in the percentage of the population that believes that “global warming is happening.” This effect is diminished in areas that have experienced more record low temperatures than record highs since 2005. Together, these results suggest that skepticism about climate change is driven partially by personal experiences; an accurate heuristic for local changes in climate identifies obstacles to communicating ongoing changes in climate to the public and how these communications might be improved. PMID:27994143

Spatial heterogeneity of climate change as an experiential basis for skepticism.

PubMed

Kaufmann, Robert K; Mann, Michael L; Gopal, Sucharita; Liederman, Jackie A; Howe, Peter D; Pretis, Felix; Tang, Xiaojing; Gilmore, Michelle

2017-01-03

We postulate that skepticism about climate change is partially caused by the spatial heterogeneity of climate change, which exposes experiential learners to climate heuristics that differ from the global average. This hypothesis is tested by formalizing an index that measures local changes in climate using station data and comparing this index with survey-based model estimates of county-level opinion about whether global warming is happening. Results indicate that more stations exhibit cooling and warming than predicted by random chance and that spatial variations in these changes can account for spatial variations in the percentage of the population that believes that "global warming is happening." This effect is diminished in areas that have experienced more record low temperatures than record highs since 2005. Together, these results suggest that skepticism about climate change is driven partially by personal experiences; an accurate heuristic for local changes in climate identifies obstacles to communicating ongoing changes in climate to the public and how these communications might be improved.

Critical Climate-Sensitive and Important Grain-Producing Regions: Grain Production/Yield Variations Due to Climate Fluctuations. Volume 1

NASA Technical Reports Server (NTRS)

Welker, J. E.

2004-01-01

Ideally, the Crop Country Inventory, CCI, is a methodology for the pre-harvest prediction of large variations in a country s crop production. This is accomplished by monitoring the historical climatic fluctuations, especially during the crop calendar period, in a climate sensitive large crop production region or sub-country, rather than the entire country. The argument can be made that the climatic fluctuations in the climatic sensitive region are responsible for the major annual crop country variations and that the remainder of the country, without major climatic fluctuations for a given year, can be assumed to be a steady-state crop producer. The principal data set that has been used is the Global Climate Mode (GCM) data from the National Center for Environmental Prediction (NCEP), taken over the last half century. As a test of its accuracy, GCM data can and has been correlated with the actual meteorological station data at the station site.

CPC - Monitoring & Data: Pacific Island Climate Data

Science.gov Websites

Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Web resources and services. HOME > Monitoring and Data > Pacific Islands Climate Data & Maps island stations. NOAA/ National Weather Service NOAA Center for Weather and Climate Prediction Climate

Green Infrastructure Concept for JABODETABEKJUR Metropolitan Area

NASA Astrophysics Data System (ADS)

Tanuwidjaja, Gunawan; Gates Chang, Bill

2017-07-01

Sixty “Mega Cities” would emerge by 2015 catering of 600 million populations, and were threatened by the climate change, because of cyclones, flooding, etc. Jakarta became a metro region covering Jakarta, Bogor, Tangerang, Bekasi, Depok and Cianjur. Jakarta metropolitan faced the very high population growth, urban sprawling, traffic jams, flooding, green open space reduction, environmental degradation, urban slums and illegal street hawkers. Flooding and traffic congestions were the two most important issues to solve. SWOT analysis and urban design solutions were produced to create a sustainable solution. Related to transportation issues, Singapore Mass Rapid Transport (MRT) concept was evaluated. Meanwhile the Netherlands’ polder concept as well as Singapore’s Integrated Water Management were also analyzed. The development of above ground MRT as well as Busway could be developed to connect Jakarta Metropolitan Region. The networks were developed on the main toll road networks. The MRT and Busway would eventually replace the need of automobile use in the future. The Transit - Oriented - Development (TOD) with high density can be suggested to be concentrated nearby the MRT and Busway interchange stations. The Netherlands’ polder and were adopted for urban’ low-lying lands in Jakarta Metropolitan Region, A polder system was defined as the Integrated Man-made Drainage System consisting Dikes, Drains, Retention Ponds, Outfall Structures or Pumping Stations. The polder system was proposed to be extended to Tangerang and Bekasi area.

Decadal changes in the frequency of major floods in near-natural catchments across North America and Europe

NASA Astrophysics Data System (ADS)

Hodgkins, Glenn A.; Hannaford, Jamie; Whitfield, Paul H.; Burn, Donald H.; Fleig, Anne; Stahl, Kerstin; Renard, Benjamin; Korhonen, Johanna; Murphy, Conor; Crochet, Philippe; Wilson, Donna; Madsen, Henrik

2013-04-01

Recent major floods in North America and Europe have received much press, with some concluding that these floods are more frequent in recent years as a result of anthropogenic warming. There has therefore been considerable scientific effort invested in establishing whether observed flood records show evidence of trends or variability in flood frequency, and to determine whether these patterns can be linked to climatic changes. However, the river catchments used in many published studies are influenced by direct human alteration such as reservoir regulation and urbanisation, which can confound the interpretation of climate-driven variability. Furthermore, a majority of previous studies have analysed changes in low magnitude floods, such as the annual peak flow, at a national scale. Few studies are known that have analysed changes in large floods (greater than 25-year floods) on a continental scale. To fill this research gap, the current study is analysing flood flows from reference hydrologic networks (RHNs) or RHN-like gauges across a large study domain embracing North America and much of Europe. RHNs comprise gauging stations with minimally disturbed catchment conditions, which have a near-natural flow regime and provide good quality data; RHN analyses thus allow hydro-climatic variability to be distinguished from direct artificial disturbances or data inhomogeneities. One of the key innovations in this study is the definition of an RHN-like network on a continental scale. The network incorporates existing, well-established RHNs in Canada, the US, the UK, Ireland and Norway, alongside RHN-like catchments from Europe (France, Switzerland, Iceland, Denmark, Sweden, Finland), which have been incorporated in the network following a major effort to ensure RHN-like status of candidate gauges through consultation with local experts. As the aim of the study is to examine long-term variability in the number of major floods, annual exceedances of 25-, 50-, and 100-year floods during the last 40-100 years are estimated for all study gauges across North America and Europe. These are then pooled, and regional and continental flood frequency time series computed, including separate groups for different types of hydrological regime (pluvial, nival, mixed etc). Preliminary results will be presented, focusing on whether there is evidence for interdecadal variability in the occurrence of flooding at the large scale in Europe and North America. The unique intercontinental dataset is an example of successful international collaboration on hydro-climatic data exchange, which is potentially a step towards establishing RHN-like networks on a global scale. Such networks will make a valuable contribution to the understanding of hydrological change in future.

Land-mobile satellite communication system

NASA Technical Reports Server (NTRS)

Yan, Tsun-Yee (Inventor); Rafferty, William (Inventor); Dessouky, Khaled I. (Inventor); Wang, Charles C. (Inventor); Cheng, Unjeng (Inventor)

1993-01-01

A satellite communications system includes an orbiting communications satellite for relaying communications to and from a plurality of ground stations, and a network management center for making connections via the satellite between the ground stations in response to connection requests received via the satellite from the ground stations, the network management center being configured to provide both open-end service and closed-end service. The network management center of one embodiment is configured to provides both types of service according to a predefined channel access protocol that enables the ground stations to request the type of service desired. The channel access protocol may be configured to adaptively allocate channels to open-end service and closed-end service according to changes in the traffic pattern and include a free-access tree algorithm that coordinates collision resolution among the ground stations.

Wireless Headset Communication System

NASA Technical Reports Server (NTRS)

Lau, Wilfred K.; Swanson, Richard; Christensen, Kurt K.

1995-01-01

System combines features of pagers, walkie-talkies, and cordless telephones. Wireless headset communication system uses digital modulation on spread spectrum to avoid interference among units. Consists of base station, 4 radio/antenna modules, and as many as 16 remote units with headsets. Base station serves as network controller, audio-mixing network, and interface to such outside services as computers, telephone networks, and other base stations. Developed for use at Kennedy Space Center, system also useful in industrial maintenance, emergency operations, construction, and airport operations. Also, digital capabilities exploited; by adding bar-code readers for use in taking inventories.

Television in the After School Hours. A Study of Programming and Advertising for Children on Independent Stations Across the United States.

ERIC Educational Resources Information Center

Barcus, F. Earle

A study analyzed the programing and advertising matter in the after-school hours on independent commercial television stations unaffiliated with the major networks. These stations, primarily UHF, relied almost entirely on syndicated programing that is often reruns of former network programs. These programs draw large after-school audiences. By…

Real-time operation of the NSF EarthScope USArray Transportable Array

NASA Astrophysics Data System (ADS)

Astiz, L.; Eakins, J. A.; Vernon, F. L.; Martynov, V.; Newman, R. L.; Cox, T. A.; Mulder, T. L.; Busby, R. W.

2007-05-01

The Transportable Array (TA) component of USArray uses real-time telemetry to send data to the Array Network Facility (ANF) through a variety of satellite, mobile phone, wireless and wired communication links. The ANF is responsible for the timely delivery of metadata and waveform data to the IRIS DMC from the growing number of Transportable Array stations. The IRIS DMC makes these data available to the research community. The network has increased in size to 327 stations with 259 out of the 400 new TA sites installed (as of 28 February 2007). Starting in Fall 2007, equipment will start to roll from current stations to new locations to the east of the current footprint. Use of the Antelope software package has allowed the ANF to maintain and operate this extremely dynamic network configuration, facilitating the collection and transfer of data, the generation and merging of the metadata as well as the real-time monitoring of state of health of TA station data-loggers and their command and control. Four regional networks (ANZA, BDSN, SCSN, and UNR) as well as the USNSN contribute data to the Transportable Array in real-time. Although the real-time data flow to the IRIS DMC has been 93.4% over the last year, the ANF and the TA field teams have extended every effort and have managed to recover an additional 4.8% by recovering data from the local data storage device (Baler 14) at each station. Once the missing data is recovered, we then generate station-channel-day volume seed files, which are resent to the DMC to bring the total data recovery rate to 98.4%. The total network uptime is above 99%. Analyst review of automatic locations for the USArray network is being done at the ANF as part of the data quality monitoring strategy. All events are associated with the USGS and regional network bulletins. As of February 2007, around 13,000 weekly picks are being fully reviewed by analysts at the ANF and over 19,000 events have been recorded. We find a small percentage (about 10 %) of events that cannot be associated with existing bulletins. This information is used by the regional network operators to help them determine which TA stations may be beneficial to permanently add to their seismic networks. Operation of the USArray at the ANF has benefited by the real-time interface with the ORB and the Datascope database using PHP for display on the ANF website (http:anf.ucsd.edu) to provide station and system state-of- health information to field teams. Information available for all stations includes: location, maps, photographs, equipment deployed, communications, distribution of events recorded by each station, and displays of daily, weekly, and yearly state of health parameters as well as station noise spectra generated by the DMC.

The last millennia climate dynamics in Central Asia as a function of recent geochemical response of lacustrine sedimentation

NASA Astrophysics Data System (ADS)

Kalugin, I.; Darin, A.; Ovchinnikov, D.; Myglan, V.; Babich, V.

2010-09-01

Our knowledge of climate change with associated forcing during the last thousand-years remains limited because that cannot be studied thoroughly by instrumental data. So it is an actual task to find high resolution paleoclimate records and to compare it with recent patterns of short-period oscillations. Combination of lake sediments and tree rings appears to be effective for understanding of regional climate forcings. There are several dendrochronologies (up to 1700 years long) and comparable annual reconstructions by Teletskoye Lake sediments (1500 years) in Altai region. They are calibrated by data from 14 local weather stations (time series up to 80 years) and Barnaul station (170 years) as well. We used tree-ring series together with element contents in sediments as an additional proxy for calculation of transfer function, considering that tree-ring series are responded to summer temperature in this climatic zone. Such combined version allows taking one more independent environmental indication for objective reconstructions. Element content in sediments is provided by X-ray Fluorescence on Synchrotron Radiation microanalysis with scanning step up to 0.1mm. Age model is based on three strong dates: AD 1963 by 137Cs, and AD 897 and 1540 by radiocarbon. Time series of both annual temperature and precipitation from AD 450 to 2000 are obtained from Teletskoye Lake sediments by multiple regression and artificial neural network methods using transfer function trained by meteodata. Revealed climatic proxies (Br, U and Ti content, Sr/Rb ratio and X-ray density) appear to be fundamental for silt-clay organic-bearing sediments because the same correlation is determined in standard samples from European as well as from Siberian, Chinese and Mongolian cores. The characteristic periods for northern hemisphere such as medieval warming and Little Ice Age known in the Europe and in other Asian areas (China) are revealed in Siberian region. The spectral analysis of temperatures and humidity time series revealed the subdecade up to multidecade periods of harmonious fluctuations over the both instrumental (170 years) and restored (1500) time intervals. Some of cycles coincide within both dataset as well as with global cyclicity of atmospheric circulation.

Decoding the spatial signatures of multi-scale climate variability - a climate network perspective

NASA Astrophysics Data System (ADS)

Donner, R. V.; Jajcay, N.; Wiedermann, M.; Ekhtiari, N.; Palus, M.

2017-12-01

During the last years, the application of complex networks as a versatile tool for analyzing complex spatio-temporal data has gained increasing interest. Establishing this approach as a new paradigm in climatology has already provided valuable insights into key spatio-temporal climate variability patterns across scales, including novel perspectives on the dynamics of the El Nino Southern Oscillation or the emergence of extreme precipitation patterns in monsoonal regions. In this work, we report first attempts to employ network analysis for disentangling multi-scale climate variability. Specifically, we introduce the concept of scale-specific climate networks, which comprises a sequence of networks representing the statistical association structure between variations at distinct time scales. For this purpose, we consider global surface air temperature reanalysis data and subject the corresponding time series at each grid point to a complex-valued continuous wavelet transform. From this time-scale decomposition, we obtain three types of signals per grid point and scale - amplitude, phase and reconstructed signal, the statistical similarity of which is then represented by three complex networks associated with each scale. We provide a detailed analysis of the resulting connectivity patterns reflecting the spatial organization of climate variability at each chosen time-scale. Global network characteristics like transitivity or network entropy are shown to provide a new view on the (global average) relevance of different time scales in climate dynamics. Beyond expected trends originating from the increasing smoothness of fluctuations at longer scales, network-based statistics reveal different degrees of fragmentation of spatial co-variability patterns at different scales and zonal shifts among the key players of climate variability from tropically to extra-tropically dominated patterns when moving from inter-annual to decadal scales and beyond. The obtained results demonstrate the potential usefulness of systematically exploiting scale-specific climate networks, whose general patterns are in line with existing climatological knowledge, but provide vast opportunities for further quantifications at local, regional and global scales that are yet to be explored.

Evaluating Pseudorange Multipath at CGPS Stations Spanning Mexico

NASA Astrophysics Data System (ADS)

Vazquez, G.; Bennett, R. A.; Spinler, J. C.

2013-12-01

A research study was conducted in order to quantify and analyze the amount of pseudorange multipath at continuous Global Positioning System (CGPS) stations spanning Mexico. These CGPS stations are administered by a variety of organizations, including government agencies and public universities, and thus serve a wide range of positioning needs. Despite the diversity of the networks and their intended audiences, a core function of all of the networks is to provide a stable framework for high-precision positioning in support of diverse commercial and scientific applications. CGPS data from a large number of publicly available networks located in Mexico were studied. These include the RGNA (National Active Geodetic Network) administered by INEGI (National Institute of Statistics and Geography), the PBO network (Plate Boundary Observatory) funded by the National Science Foundation (NSF) and operated by UNAVCO (University NAVstar Consortium), the Southern California Integrated GPS Network (SCIGN), which is a collaboration effort of the United States Geological Survey (USGS), Scripps Institution of Oceanography and the Jet Propulsion Laboratory (JPL), the UNAM network, operated by the National Seismological System (SSN) and the Institute of Geophysics of the National Autonomous University of Mexico (UNAM), the Suominet Geodetic Network (SNG) and the CORS (Continuously Operating Reference Station) network, operated by the Federal Aviation Administration (FAA). A total of 54 CGPS stations were evaluated, where dual-frequency geodetic-grade receivers collected GPS data continuously during the period from 1994 to 2013. It is usually assumed that despite carefully selected locations, all CGPS stations are to some extent, affected by the presence of signal multipath. In addition, the geographic distribution of stations provides a nation-wide access to the International Terrestrial Reference Frame (ITRF). For real-time kinematic (RTK) and rapid static applications that depend on the pseudo-range observable, the accuracy with which a roaming user may locate their assets with respect to the ITRF may be limited by site-specific multipath. The issue is particularly critical for users depending on pseudorange measurements for 'real-time' (or 'near-real-time') kinematic GPS positioning, where ambiguity resolution is a critical step. Therefore, to identify the most and the least affected GPS stations we analyzed the averaged daily root mean square pseudorange multipath variations (MP1-RMS and MP2-RMS) for all feasible satellites tracked by the CGPS networks. We investigated the sources of multipath, including changes associated with hardware replacement (i.e., receiver and antenna type) and receiver firmware upgrades.

Completing and sustaining IMS network for the CTBT Verification Regime

NASA Astrophysics Data System (ADS)

Meral Ozel, N.

2015-12-01

The CTBT International Monitoring System is to be comprised of 337 facilities located all over the world for the purpose of detecting and locating nuclear test explosions. Major challenges remain, namely the completion of the network where most of the remaining stations have either environmental, logistical and/or political issues to surmont (89% of the stations have already been built) and the sustainment of a reliable and state-of the-art network covering 4 technologies - seismic, infrasound , hydroacoustic and radionuclide. To have a credible and trustworthy verification system ready for entry into force of the Treaty, the CTBTO is protecting and enhancing its investment of its global network of stations and is providing effective data to the International Data Centre (IDC) and Member States. Regarding the protection of the CTBTO's investment and enhanced sustainment of IMS station operations, the IMS Division is enhancing the capabilities of the monitoring system by applying advances in instrumentation and introducing new software applications that are fit for purpose. Some examples are the development of noble gas laboratory systems to process and analyse subsoil samples, development of a mobile noble gas system for onsite inspection purposes, optimization of Beta Gamma detectors for Xenon detection, assessing and improving the efficiency of wind noise reduction systems for infrasound stations, development and testing of infrasound stations with a self-calibrating capability, and research into the use of modular designs for the hydroacoustic network.

Automatic benchmarking of homogenization packages applied to synthetic monthly series within the frame of the MULTITEST project

NASA Astrophysics Data System (ADS)

Guijarro, José A.; López, José A.; Aguilar, Enric; Domonkos, Peter; Venema, Victor; Sigró, Javier; Brunet, Manola

2017-04-01

After the successful inter-comparison of homogenization methods carried out in the COST Action ES0601 (HOME), many methods kept improving their algorithms, suggesting the need of performing new inter-comparison exercises. However, manual applications of the methodologies to a large number of testing networks cannot be afforded without involving the work of many researchers over an extended time. The alternative is to make the comparisons as automatic as possible, as in the MULTITEST project, which, funded by the Spanish Ministry of Economy and Competitiveness, tests homogenization methods by applying them to a large number of synthetic networks of monthly temperature and precipitation. One hundred networks of 10 series were sampled from different master networks containing 100 series of 720 values (60 years times 12 months). Three master temperature networks were built with different degree of cross-correlations between the series in order to simulate conditions of different station densities or climatic heterogeneity. Also three master synthetic networks were developed for precipitation, this time mimicking the characteristics of three different climates: Atlantic temperate, Mediterranean and monsoonal. Inhomogeneities were introduced in every network sampled from the master networks, and all publicly available homogenization methods that we could run in an automatic way were applied to them: ACMANT 3.0, Climatol 3.0, MASH 3.03, RHTestV4, USHCN v52d and HOMER 2.6. Most of them were tested with different settings, and their comparative results can be inspected in box-plot graphics of Root Mean Squared Errors and trend biases computed between the homogenized data and their original homogeneous series. In a first stage, inhomogeneities were applied to the synthetic homogeneous series with five different settings with increasing difficulty and realism: i) big shifts in half of the series; ii) the same with a strong seasonality; iii) short term platforms and local trends; iv) random number of shifts with random size and location in all series; and v) the same plus seasonality of random amplitude. The shifts were additive for temperature and multiplicative for precipitation. The second stage is dedicated to study the impact of the number of series in the networks, seasonalities other than sinusoidal, and the occurrence of simultaneous shifts in a high number of series. Finally, tests will be performed on a longer and more realistic benchmark, with varying number of missing data along time, similar to that used in the COST Action ES0601. These inter-comparisons will be valuable both to the users and to the developers of the tested packages, who can see how their algorithms behave under varied climate conditions.

Impacts of the Indian Rivers Inter-link Project on Sediment Transport to River Deltas

NASA Astrophysics Data System (ADS)

Higgins, S.; Overeem, I.; Syvitski, J. P.

2015-12-01

The Indian Rivers Inter-link project is a proposal by the Indian government to link several of India's major rivers via a network of reservoirs and canals. Variations of the IRI have been discussed since 1980, but the current plan has recently received increased support from the Indian government. Construction on three canals has controversially begun. If the Inter-link project moves forward, fourteen canals will divert water from tributaries of the Ganges and Brahmaputra rivers to areas in the west, where fresh water is needed for irrigation. Additional canals would transport Himalayan sediments 500 km south to the Mahanadi delta and more than 1000 km south to the Godavari and Krishna deltas. We investigate the impacts of the proposed diversions on sediment transport to the Mahanadi/Brahmani, Godavari, and Krishna deltas in India and the Ganges-Brahmaputra Delta in Bangladesh. We map the entire river network and the proposed new nodes and connections. Changing watersheds are delineated using the Terrain Analysis Using Digital Elevation Models (TauDEM) Suite. Climate data comes from interpolation between observed precipitation stations located in China, Nepal, India, Bhutan and Bangladesh. Changes in water discharge due to the proposed canals are simulated using HydroTrend, a climate-driven hydrological water balance and transport model that incorporates drainage area, discharge, relief, temperature, basin-average lithology, and anthropogenic influences. Simulated river discharge is validated against observations from gauging stations archived by the Global Runoff Data Center (GRDC). HydroTrend is then used to investigate sediment transport changes that may result from the proposed canals. We also quantify changes in contributing areas for the outlets of nine major Indian rivers, showing that more than 50% of the land in India will contribute a portion of its runoff to a new outlet should the entire canal system be constructed.

Improving the Detectability of the Catalan Seismic Network for Local Seismic Activity Monitoring

NASA Astrophysics Data System (ADS)

Jara, Jose Antonio; Frontera, Tànit; Batlló, Josep; Goula, Xavier

2016-04-01

The seismic survey of the territory of Catalonia is mainly performed by the regional seismic network operated by the Cartographic and Geologic Institute of Catalonia (ICGC). After successive deployments and upgrades, the current network consists of 16 permanent stations equipped with 3 component broadband seismometers (STS2, STS2.5, CMG3ESP and CMG3T), 24 bits digitizers (Nanometrics Trident) and VSAT telemetry. Data are continuously sent in real-time via Hispasat 1D satellite to the ICGC datacenter in Barcelona. Additionally, data from other 10 stations of neighboring areas (Spain, France and Andorra) are continuously received since 2011 via Internet or VSAT, contributing both to detect and to locate events affecting the region. More than 300 local events with Ml ≥ 0.7 have been yearly detected and located in the region. Nevertheless, small magnitude earthquakes, especially those located in the south and south-west of Catalonia may still go undetected by the automatic detection system (DAS), based on Earthworm (USGS). Thus, in order to improve the detection and characterization of these missed events, one or two new stations should be installed. Before making the decision about where to install these new stations, the performance of each existing station is evaluated taking into account the fraction of detected events using the station records, compared to the total number of events in the catalogue, occurred during the station operation time from January 1, 2011 to December 31, 2014. These evaluations allow us to build an Event Detection Probability Map (EDPM), a required tool to simulate EDPMs resulting from different network topology scenarios depending on where these new stations are sited, and becoming essential for the decision-making process to increase and optimize the event detection probability of the seismic network.

Modeling and Simulating Passenger Behavior for a Station Closure in a Rail Transit Network

PubMed Central

Yin, Haodong; Han, Baoming; Li, Dewei; Wu, Jianjun; Sun, Huijun

2016-01-01

A station closure is an abnormal operational situation in which the entrances or exits of a rail transit station have to be closed for some time due to an unexpected incident. A novel approach is developed to estimate the impacts of the alternative station closure scenarios on both passenger behavioral choices at the individual level and passenger demand at the disaggregate level in a rail transit network. Therefore, the contributions of this study are two-fold: (1) A basic passenger behavior optimization model is mathematically constructed based on 0–1 integer programming to describe passengers’ responses to alternative origin station closure scenarios and destination station closure scenarios; this model also considers the availability of multi-mode transportation and the uncertain duration of the station closure; (2) An integrated solution algorithm based on the passenger simulation is developed to solve the proposed model and to estimate the effects of a station closure on passenger demand in a rail transit network. Furthermore, 13 groups of numerical experiments based on the Beijing rail transit network are performed as case studies with 2,074,267 records of smart card data. The comparisons of the model outputs and the manual survey show that the accuracy of our proposed behavior optimization model is approximately 80%. The results also show that our model can be used to capture the passenger behavior and to quantitatively estimate the effects of alternative closure scenarios on passenger flow demand for the rail transit network. Moreover, the closure duration and its overestimation greatly influence the individual behavioral choices of the affected passengers and the passenger demand. Furthermore, if the rail transit operator can more accurately estimate the closure duration (namely, as g approaches 1), the impact of the closure can be somewhat mitigated. PMID:27935963