Beale AFB, Marysville, California Revised Uniform Summary of Surface Weather Observations (RUSSWO) Parts A-F.

DTIC Science & Technology

1981-08-19

versus Visibility; Sky Cover; ( E ) Psychrometric Summaries (daily maximum and minimum temperatures, extreme maximum and minimum temperatures, psychrometric...frequency of occurance or cumulative percentage frequency of occuring tables. UNCLASSIFIED SCUPU)?y CLASaIFICATION OF THIS PAGE(Waht Dat E moli A - I...i,. -t’ r .corvi or QL.;V.A I-)tic ai t r’& iolL; recUl’d Et. Lxki-dGiuI ii.Trly ii~tervais. DAILY OBSERVATIONS S- t tr’ o. re .;,:cLt e , !’ru: at

Climate Change: A New Metric to Measure Changes in the Frequency of Extreme Temperatures using Record Data

NASA Technical Reports Server (NTRS)

Munasinghe, L.; Jun, T.; Rind, D. H.

2012-01-01

Consensus on global warming is the result of multiple and varying lines of evidence, and one key ramification is the increase in frequency of extreme climate events including record high temperatures. Here we develop a metric- called "record equivalent draws" (RED)-based on record high (low) temperature observations, and show that changes in RED approximate changes in the likelihood of extreme high (low) temperatures. Since we also show that this metric is independent of the specifics of the underlying temperature distributions, RED estimates can be aggregated across different climates to provide a genuinely global assessment of climate change. Using data on monthly average temperatures across the global landmass we find that the frequency of extreme high temperatures increased 10-fold between the first three decades of the last century (1900-1929) and the most recent decade (1999-2008). A more disaggregated analysis shows that the increase in frequency of extreme high temperatures is greater in the tropics than in higher latitudes, a pattern that is not indicated by changes in mean temperature. Our RED estimates also suggest concurrent increases in the frequency of both extreme high and extreme low temperatures during 2002-2008, a period when we observe a plateauing of global mean temperature. Using daily extreme temperature observations, we find that the frequency of extreme high temperatures is greater in the daily minimum temperature time-series compared to the daily maximum temperature time-series. There is no such observable difference in the frequency of extreme low temperatures between the daily minimum and daily maximum.

Temperature Measurements Taken by Phoenix Spacecraft

NASA Image and Video Library

2008-09-30

This chart plots the minimum daily atmospheric temperature measured by NASA Phoenix Mars Lander spacecraft since landing on Mars. As the temperature increased through the summer season, the atmospheric humidity also increased.

Trends in record-breaking temperatures for the conterminous United States

NASA Astrophysics Data System (ADS)

Rowe, Clinton M.; Derry, Logan E.

2012-08-01

In an unchanging climate, record-breaking temperatures are expected to decrease in frequency over time, as established records become increasingly more difficult to surpass. This inherent trend in the number of record-breaking events confounds the interpretation of actual trends in the presence of any underlying climate change. Here, a simple technique to remove the inherent trend is introduced so that any remaining trend can be examined separately for evidence of a climate change. As this technique does not use the standard definition of a broken record, our records* are differentiated by an asterisk. Results for the period 1961-2010 indicate that the number of record* low daily minimum temperatures has been significantly and steadily decreasing nearly everywhere across the United States while the number of record* high daily minimum temperatures has been predominantly increasing. Trends in record* low and record* high daily maximum temperatures are generally weaker and more spatially mixed in sign. These results are consistent with other studies examining changes expected in a warming climate.

Trends in extreme daily temperatures and humidex index in the United Arab Emirates over 1948-2014.

NASA Astrophysics Data System (ADS)

Yang, H. W.; Ouarda, T.

2015-12-01

This study deals with the analysis of the characteristics of extreme temperature events in the Middle East, using NCEP reanalysis gridded data, for the summer (May-October) and winter (November-April) seasons. Trends in the occurrences of three types of heat spells during 1948-2014 are studied by both Linear Regression (LR) and Mann-Kendall (MK) test. Changes in the diurnal temperature range (DTR) are also investigated. To better understand the effects of heat spells on public health, the Humidex, a combination index of ambient temperature and relative humidity, is also used. Using percentile threshold, temperature (Humidex) Type-A and Type-B heat spells are defined respectively by daily maximum and minimum temperature (Humidex). Type-C heat spells are defined as the joint occurrence of Type-A and Type-B heat spells at the same time. In the Middle East, it is found that no coherent trend in temperature Type-A heat spells is observed. However, the occurrences of temperature Type-B and C heat spells have consistently increased since 1948. For Humidex heat spells, coherently increased activities of all three types of heat spells are observed in the area. During the summer, the magnitude of the positive trends in Humidex heat spells are generally stronger than temperature heat spells. More than half of the locations in the area show significantly negative DTR trends in the summer, but the trends vary according to the region in the winter. Annual mean temperature has increased an average by 0.5°C, but it is mainly associated with the daily minimum temperature which has warmed up by 0.84°C.Daily maximum temperature showed no significant trends. The warming is hence stronger in minimum temperatures than in maximum temperatures resulting in a decrease in DTR by 0.16 °C per decade. This study indicates hence that the UAE has not become hotter, but it has become less cold during 1948 to 2014.

Retrieving air humidity, global solar radiation, and reference evapotranspiration from daily temperatures: development and validation of new methods for Mexico. Part III: reference evapotranspiration

NASA Astrophysics Data System (ADS)

Lobit, P.; Gómez Tagle, A.; Bautista, F.; Lhomme, J. P.

2017-07-01

We evaluated two methods to estimate evapotranspiration (ETo) from minimal weather records (daily maximum and minimum temperatures) in Mexico: a modified reduced set FAO-Penman-Monteith method (Allen et al. 1998, Rome, Italy) and the Hargreaves and Samani (Appl Eng Agric 1(2): 96-99, 1985) method. In the reduced set method, the FAO-Penman-Monteith equation was applied with vapor pressure and radiation estimated from temperature data using two new models (see first and second articles in this series): mean temperature as the average of maximum and minimum temperature corrected for a constant bias and constant wind speed. The Hargreaves-Samani method combines two empirical relationships: one between diurnal temperature range ΔT and shortwave radiation Rs, and another one between average temperature and the ratio ETo/Rs: both relationships were evaluated and calibrated for Mexico. After performing a sensitivity analysis to evaluate the impact of different approximations on the estimation of Rs and ETo, several model combinations were tested to predict ETo from daily maximum and minimum temperature alone. The quality of fit of these models was evaluated on 786 weather stations covering most of the territory of Mexico. The best method was found to be a combination of the FAO-Penman-Monteith reduced set equation with the new radiation estimation and vapor pressure model. As an alternative, a recalibration of the Hargreaves-Samani equation is proposed.

The creation of future daily gridded datasets of precipitation and temperature with a spatial weather generator, Cyprus 2020-2050

NASA Astrophysics Data System (ADS)

Camera, Corrado; Bruggeman, Adriana; Hadjinicolaou, Panos; Pashiardis, Stelios; Lange, Manfred

2014-05-01

High-resolution gridded daily datasets are essential for natural resource management and the analysis of climate changes and their effects. This study aimed to create gridded datasets of daily precipitation and daily minimum and maximum temperature, for the future (2020-2050). The horizontal resolution of the developed datasets is 1 x 1 km2, covering the area under control of the Republic of Cyprus (5.760 km2). The study is divided into two parts. The first consists of the evaluation of the performance of different interpolation techniques for daily rainfall and temperature data (1980-2010) for the creation of the gridded datasets. Rainfall data recorded at 145 stations and temperature data from 34 stations were used. For precipitation, inverse distance weighting (IDW) performs best for local events, while a combination of step-wise geographically weighted regression and IDW proves to be the best method for large scale events. For minimum and maximum temperature, a combination of step-wise linear multiple regression and thin plate splines is recognized as the best method. Six Regional Climate Models (RCMs) for the A1B SRES emission scenario from the EU ENSEMBLE project database were selected as sources for future climate projections. The RCMs were evaluated for their capacity to simulate Cyprus climatology for the period 1980-2010. Data for the period 2020-2050 from the three best performing RCMs were downscaled, using the change factors approach, at the location of observational stations. Daily time series were created with a stochastic rainfall and temperature generator. The RainSim V3 software (Burton et al., 2008) was used to generate spatial-temporal coherent rainfall fields. The temperature generator was developed in R and modeled temperature as a weakly stationary process with the daily mean and standard deviation conditioned on the wet and dry state of the day (Richardson, 1981). Finally gridded datasets depicting projected future climate conditions were created with the identified best interpolation methods. The difference between the input and simulated mean daily rainfall, averaged over all the stations, was 0.03 mm (2.2%), while the error related to the number of dry days was 2 (0.6%). For mean daily minimum temperature the error was 0.005 ºC (0.04%), while for maximum temperature it was 0.01 ºC (0.04%). Overall, the weather generators were found to be reliable instruments for the downscaling of precipitation and temperature. The resulting datasets indicate a decrease of the mean annual rainfall over the study area between 5 and 70 mm (1-15%) for 2020-2050, relative to 1980-2010. Average annual minimum and maximum temperature over the Republic of Cyprus are projected to increase between 1.2 and 1.5 ºC. The dataset is currently used to compute agricultural production and water use indicators, as part of the AGWATER project (AEIFORIA/GEORGO/0311(BIE)/06), co-financed by the European Regional Development Fund and the Republic of Cyprus through the Research Promotion Foundation. Burton, A., Kilsby, C.G., Fowler, H.J., Cowpertwait, P.S.P., and O'Connell, P.E.: RainSim: A spatial-temporal stochastic rainfall modelling system. Environ. Model. Software 23, 1356-1369, 2008 Richardson, C.W.: Stochastic simulation of daily precipitation, temperature, and solar radiation. Water Resour. Res. 17, 182-190, 1981.

Torrejon AB, Madrid, Spain. revised uniform summary of surface weather observations (RUSSWO). parts a-f. Final report

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

Not Available

1978-10-03

This report is a six-part statistical summary of surface weather observations for Torrejon AB, Madrid Spain. It contains the following parts: (A) Weather Conditions; Atmospheric Phenomena; (B) Precipitation, Snowfall and Snow Depth (daily amounts and extreme values); (C) Surface winds; (D) Ceiling Versus Visibility; Sky Cover; (E) Psychrometric Summaries (daily maximum and minimum temperatures, extreme maximum and minimum temperatures, psychrometric summary of wet-bulb temperature depression versus dry-bulb temperature, means and standard deviations of dry-bulb, wet-bulb and dew-point temperatures and relative humidity); and (F) Pressure Summary (means, standard, deviations, and observation counts of station pressure and sea-level pressure). Data in thismore » report are presented in tabular form, in most cases in percentage frequency of occurrence or cumulative percentage frequency of occurrence tables.« less

Thermal characteristics of wild and captive Micronesian Kingfisher nesting habitats

USGS Publications Warehouse

Kesler, Dylan C.; Haig, Susan M.

2004-01-01

To provide information for managing the captive population of endangered Guam Micronesian kingfishers (Halcyon cinnamomina cinnamomina), four biologically relevant thermal metrics were compared among captive facilities on the United States mainland and habitats used by wild Micronesian kingfishers on the island of Pohnpei (H. c. reichenbachii), Federated States of Micronesia. Additionally, aviaries where kingfishers laid eggs were compared to those in which birds did not attempt to breed. Compared to aviaries, habitats used by wild Pohnpei kingfishers had 3.2A?C higher daily maximum and minimum temperatures and the proportion of time when temperatures were in the birds' thermoneutral zone was 45% greater. No differences were found in the magnitude of temperature fluctuation in captive and wild environments. In captive environments in which birds bred, daily maximum temperatures were 2.1A?C higher and temperatures were within the thermoneutral zone 25% more often than in the aviaries where the kingfishers did not breed. No differences were found in the magnitude of temperature fluctuation or the daily minimum temperature. Results suggest that the thermal environment has the potential to influence reproduction, and that consideration should be given to increasing temperatures in captive breeding facilities to improve propagation of the endangered Micronesian kingfisher.

Summer weather characteristics and periodicity observed over the period 1888-2013 in the region of Belgrade, Serbia

NASA Astrophysics Data System (ADS)

Vujović, Dragana; Todorović, Nedeljko; Paskota, Mira

2018-04-01

With the goal of finding summer climate patterns in the region of Belgrade (Serbia) over the period 1888-2013, different techniques of multivariate statistical analysis were used in order to analyze the simultaneous changes of a number of climatologic parameters. An increasing trend of the mean daily minimum temperature was detected. In the recent decades (1960-2013), this increase was much more pronounced. The number of days with the daily minimum temperature greater or equal to 20 °C also increased significantly. Precipitation had no statistically significant trend. Spectral analysis showed a repetitive nature of the climatologic parameters which had periods that roughly can be classified into three groups, with the durations of the following: (1) 6 to 7 years, (2) 10 to 18 years, and (3) 21, 31, and 41 years. The temperature variables mainly had one period of repetitiveness of 5 to 7 years. Among other variables, the correlations of regional fluctuations of the temperature and precipitation and atmospheric circulation indices were analyzed. The North Atlantic oscillation index had the same periodicity as that of the precipitation, and it was not correlated to the temperature variables. Atlantic multidecadal oscillation index correlated well to the summer mean daily minimum and summer mean temperatures. The underlying structure of the data was analyzed by principal component analysis, which detected the following four easily interpreted dimensions: More sunshine-Higher temperature, Precipitation, Extreme heats, and Changeable summer.

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.

Quantifying Observed Temperature Extremes in the Southeastern United States

NASA Astrophysics Data System (ADS)

Sura, P.; Stefanova, L. B.; Griffin, M.; Worsnop, R.

2011-12-01

There is broad consensus that the most hazardous effects of climate change are related to a potential increase (in frequency and/or intensity) of extreme weather and climate events. In particular, the statistics of regional daily temperature extremes are of practical interest for the agricultural community and energy suppliers. This is notably true for the Southeastern United States where winter hard freezes are a relatively rare and potentially catastrophic event. Here we use a long record of quality-controlled observations collected from 272 National Weather Service (NWS) Cooperative Observing Network (COOP) stations throughout Florida, Georgia, Alabama, and South and North Carolina to provide a detailed climatology of temperature extremes in the Southeastern United States. We employ two complementary approaches. First, we analyze the effect of El Nino-Southern Oscillation (ENSO) and the Arctic Oscillation (AO) on the non-Gaussian (i.e. higher order) statistics of wintertime daily minimum and maximum temperatures. We find a significant and spatially varying impact of ENSO and AO on the non-Gaussian statistics of daily maximum and minimum temperatures throughout the domain. Second, the extremes of the temperature distributions are studied by calculating the 1st and 99th percentiles, and then analyzing the number of days with record low/high temperatures per season. This analysis of daily temperature extremes reveals oscillating, multi-decadal patterns with spatially varying centers of action.

Daily temperature records from a mesonet in the foothills of the Canadian Rocky Mountains, 2005-2010

NASA Astrophysics Data System (ADS)

Wood, Wendy H.; Marshall, Shawn J.; Whitehead, Terri L.; Fargey, Shannon E.

2018-03-01

Near-surface air temperatures were monitored from 2005 to 2010 in a mesoscale network of 230 sites in the foothills of the Rocky Mountains in southwestern Alberta, Canada. The monitoring network covers a range of elevations from 890 to 2880 m above sea level and an area of about 18 000 km2, sampling a variety of topographic settings and surface environments with an average spatial density of one station per 78 km2. This paper presents the multiyear temperature dataset from this study, with minimum, maximum, and mean daily temperature data available at https://doi.org/10.1594/PANGAEA.880611. In this paper, we describe the quality control and processing methods used to clean and filter the data and assess its accuracy. Overall data coverage for the study period is 91 %. We introduce a weather-system-dependent gap-filling technique to estimate the missing 9 % of data. Monthly and seasonal distributions of minimum, maximum, and mean daily temperature lapse rates are shown for the region.

Stream-temperature patterns of the Muddy Creek basin, Anne Arundel County, Maryland

USGS Publications Warehouse

Pluhowski, E.J.

1981-01-01

Using a water-balance equation based on a 4.25-year gaging-station record on North Fork Muddy Creek, the following mean annual values were obtained for the Muddy Creek basin: precipitation, 49.0 inches; evapotranspiration, 28.0 inches; runoff, 18.5 inches; and underflow, 2.5 inches. Average freshwater outflow from the Muddy Creek basin to the Rhode River estuary was 12.2 cfs during the period October 1, 1971, to December 31, 1975. Harmonic equations were used to describe seasonal maximum and minimum stream-temperature patterns at 12 sites in the basin. These equations were fitted to continuous water-temperature data obtained periodically at each site between November 1970 and June 1978. The harmonic equations explain at least 78 percent of the variance in maximum stream temperatures and 81 percent of the variance in minimum temperatures. Standard errors of estimate averaged 2.3C (Celsius) for daily maximum water temperatures and 2.1C for daily minimum temperatures. Mean annual water temperatures developed for a 5.4-year base period ranged from 11.9C at Muddy Creek to 13.1C at Many Fork Branch. The largest variations in stream temperatures were detected at thermograph sites below ponded reaches and where forest coverage was sparse or missing. At most sites the largest variations in daily water temperatures were recorded in April whereas the smallest were in September and October. The low thermal inertia of streams in the Muddy Creek basin tends to amplify the impact of surface energy-exchange processes on short-period stream-temperature patterns. Thus, in response to meteorologic events, wide ranging stream-temperature perturbations of as much as 6C have been documented in the basin. (USGS)

Modeling the survivability of brucella to exposure of Ultraviolet radiation and temperature

NASA Astrophysics Data System (ADS)

Howe, R.

Accumulated summation of daily Ultra Violet-B (UV-B = 290? to 320 ? ) data? from The USDA Ultraviolet Radiation Monitoring Program show good correlation (R^2 = 77%) with daily temperature data during the five month period from February through June, 1998. Exposure of disease organisms, such as brucella to the effects of accumulated UV-B radiation, can be modeled for a 5 month period from February through June, 1998. Estimates of a lethal dosage for brucell of UV-B in the environment is dependent on minimum/maximum temperature and Solar Zenith Angle for the time period. The accumulated increase in temperature over this period also effects the decomposition of an aborted fetus containing brucella. Decomposition begins at some minimum daily temperature at 27 to 30 degrees C and peaks at 39 to 40C. It is useful to view the summation of temperature as a threshold for other bacteria growth, so that accumulated temperature greater than some value causes decomposition through competition with other bacteria and brucella die from the accumulated effects of UV-B, temperature and organism competition. Results of a study (Cook 1998) to determine survivability of brucellosis in the environment through exposure of aborted bovine fetuses show no one cause can be attributed to death of the disease agent. The combination of daily increase in temperature and accumulated UV-B radiation reveal an inverse correlation to survivability data and can be modeled as an indicator of brucella survivability in the environment in arid regions.

Satellite Estimation of Daily Land Surface Water Vapor Pressure Deficit from AMSR- E

NASA Astrophysics Data System (ADS)

Jones, L. A.; Kimball, J. S.; McDonald, K. C.; Chan, S. K.; Njoku, E. G.; Oechel, W. C.

2007-12-01

Vapor pressure deficit (VPD) is a key variable for monitoring land surface water and energy exchanges, and estimating plant water stress. Multi-frequency day/night brightness temperatures from the Advanced Microwave Scanning Radiometer on EOS Aqua (AMSR-E) were used to estimate daily minimum and average near surface (2 m) air temperatures across a North American boreal-Arctic transect. A simple method for determining daily mean VPD (Pa) from AMSR-E air temperature retrievals was developed and validated against observations across a regional network of eight study sites ranging from boreal grassland and forest to arctic tundra. The method assumes that the dew point and minimum daily air temperatures tend to equilibrate in areas with low night time temperatures and relatively moist conditions. This assumption was tested by comparing the VPD algorithm results derived from site daily temperature observations against results derived from AMSR-E retrieved temperatures alone. An error analysis was conducted to determine the amount of error introduced in VPD estimates given known levels of error in satellite retrieved temperatures. Results indicate that the assumption generally holds for the high latitude study sites except for arid locations in mid-summer. VPD estimates using the method with AMSR-E retrieved temperatures compare favorably with site observations. The method can be applied to land surface temperature retrievals from any sensor with day and night surface or near-surface thermal measurements and shows potential for inferring near-surface wetness conditions where dense vegetation may hinder surface soil moisture retrievals from low-frequency microwave sensors. This work was carried out at The University of Montana, at San Diego State University, and at the Jet Propulsion Laboratory, California Institute of Technology, under contract to the National Aeronautics and Space Administration.

Temperature-induced excess mortality in Moscow, Russia.

PubMed

Revich, Boris; Shaposhnikov, Dmitri

2008-05-01

After considering the observed long-term trends in average monthly temperatures distribution in Moscow, the authors evaluated how acute mortality responded to changes in daily average, minimum and maximum temperatures throughout the year, and identified vulnerable population groups, by age and causes of death. A plot of the basic mortality-temperature relationship indicated that this relationship was V-shaped with the minimum around 18 degrees C. Each 1 degree C increment of average daily temperature above 18 degrees C resulted in an increase in deaths from all non-accidental causes by 2.8%, from coronary heart disease by 2.7%, from cerebrovascular diseases by 4.7%, and from respiratory diseases by 8.7%, with a lag of 0 or 1 day. Each 1 degrees C drop of average daily temperature from +18 degrees C to -10 degrees C resulted in an increase in deaths from all non-accidental causes by 0.49%, from coronary heart disease by 0.57%, from cerebrovascular diseases by 0.78%, and from respiratory diseases by 1.5%, with lags of maximum association varying from 3 days for non-accidental mortality to 6 days for cerebrovascular mortality. In the age group 75+ years, corresponding risks were consistently higher by 13-30%. The authors also estimated the increase in non-accidental deaths against the variation of daily temperatures. For each 1 degrees C increase of variation of temperature throughout the day, mortality increased by 0.3-1.9%, depending on other assumptions of the model.

Temperature-induced excess mortality in Moscow, Russia

NASA Astrophysics Data System (ADS)

Revich, Boris; Shaposhnikov, Dmitri

2008-05-01

After considering the observed long-term trends in average monthly temperatures distribution in Moscow, the authors evaluated how acute mortality responded to changes in daily average, minimum and maximum temperatures throughout the year, and identified vulnerable population groups, by age and causes of death. A plot of the basic mortality temperature relationship indicated that this relationship was V-shaped with the minimum around 18°C. Each 1°C increment of average daily temperature above 18°C resulted in an increase in deaths from all non-accidental causes by 2.8%, from coronary heart disease by 2.7%, from cerebrovascular diseases by 4.7%, and from respiratory diseases by 8.7%, with a lag of 0 or 1 day. Each 1°C drop of average daily temperature from +18°C to -10°C resulted in an increase in deaths from all non-accidental causes by 0.49%, from coronary heart disease by 0.57%, from cerebrovascular diseases by 0.78%, and from respiratory diseases by 1.5%, with lags of maximum association varying from 3 days for non-accidental mortality to 6 days for cerebrovascular mortality. In the age group 75+ years, corresponding risks were consistently higher by 13 30%. The authors also estimated the increase in non-accidental deaths against the variation of daily temperatures. For each 1°C increase of variation of temperature throughout the day, mortality increased by 0.3 1.9%, depending on other assumptions of the model.

Soil water content and evaporation determined by thermal parameters obtained from ground-based and remote measurements

NASA Technical Reports Server (NTRS)

Reginato, R.; Idso, S.; Vedder, J.; Jackson, R.; Blanchard, M.; Goettelman, R.

1975-01-01

A procedure is presented for calculating 24-hour totals of evaporation from wet and drying soils. Its application requires a knowledge of the daily solar radiation, the maximum and minimum, air temperatures, moist surface albedo, and maximum and minimum surface temperatures. Tests of the technique on a bare field of Avondale loam at Phoenix, Arizona showed it to be independent of season.

Forecast of Frost Days Based on Monthly Temperatures

NASA Astrophysics Data System (ADS)

Castellanos, M. T.; Tarquis, A. M.; Morató, M. C.; Saa-Requejo, A.

2009-04-01

Although frost can cause considerable crop damage and mitigation practices against forecasted frost exist, frost forecasting technologies have not changed for many years. The paper reports a new method to forecast the monthly number of frost days (FD) for several meteorological stations at Community of Madrid (Spain) based on successive application of two models. The first one is a stochastic model, autoregressive integrated moving average (ARIMA), that forecasts monthly minimum absolute temperature (tmin) and monthly average of minimum temperature (tminav) following Box-Jenkins methodology. The second model relates these monthly temperatures to minimum daily temperature distribution during one month. Three ARIMA models were identified for the time series analyzed with a stational period correspondent to one year. They present the same stational behavior (moving average differenced model) and different non-stational part: autoregressive model (Model 1), moving average differenced model (Model 2) and autoregressive and moving average model (Model 3). At the same time, the results point out that minimum daily temperature (tdmin), for the meteorological stations studied, followed a normal distribution each month with a very similar standard deviation through years. This standard deviation obtained for each station and each month could be used as a risk index for cold months. The application of Model 1 to predict minimum monthly temperatures showed the best FD forecast. This procedure provides a tool for crop managers and crop insurance companies to asses the risk of frost frequency and intensity, so that they can take steps to mitigate against frost damage and estimated the damage that frost would cost. This research was supported by Comunidad de Madrid Research Project 076/92. The cooperation of the Spanish National Meteorological Institute and the Spanish Ministerio de Agricultura, Pesca y Alimentation (MAPA) is gratefully acknowledged.

A new approach used to explore associations of current Ambrosia pollen levels with current and past meteorological elements

NASA Astrophysics Data System (ADS)

Matyasovszky, István; Makra, László; Csépe, Zoltán; Deák, Áron József; Pál-Molnár, Elemér; Fülöp, Andrea; Tusnády, Gábor

2015-09-01

The paper examines the sensitivity of daily airborne Ambrosia (ragweed) pollen levels of a current pollen season not only on daily values of meteorological variables during this season but also on the past meteorological conditions. The results obtained from a 19-year data set including daily ragweed pollen counts and ten daily meteorological variables are evaluated with special focus on the interactions between the phyto-physiological processes and the meteorological elements. Instead of a Pearson correlation measuring the strength of the linear relationship between two random variables, a generalised correlation that measures every kind of relationship between random vectors was used. These latter correlations between arrays of daily values of the ten meteorological elements and the array of daily ragweed pollen concentrations during the current pollen season were calculated. For the current pollen season, the six most important variables are two temperature variables (mean and minimum temperatures), two humidity variables (dew point depression and rainfall) and two variables characterising the mixing of the air (wind speed and the height of the planetary boundary layer). The six most important meteorological variables before the current pollen season contain four temperature variables (mean, maximum, minimum temperatures and soil temperature) and two variables that characterise large-scale weather patterns (sea level pressure and the height of the planetary boundary layer). Key periods of the past meteorological variables before the current pollen season have been identified. The importance of this kind of analysis is that a knowledge of the past meteorological conditions may contribute to a better prediction of the upcoming pollen season.

A new approach used to explore associations of current Ambrosia pollen levels with current and past meteorological elements.

PubMed

Matyasovszky, István; Makra, László; Csépe, Zoltán; Deák, Áron József; Pál-Molnár, Elemér; Fülöp, Andrea; Tusnády, Gábor

2015-09-01

The paper examines the sensitivity of daily airborne Ambrosia (ragweed) pollen levels of a current pollen season not only on daily values of meteorological variables during this season but also on the past meteorological conditions. The results obtained from a 19-year data set including daily ragweed pollen counts and ten daily meteorological variables are evaluated with special focus on the interactions between the phyto-physiological processes and the meteorological elements. Instead of a Pearson correlation measuring the strength of the linear relationship between two random variables, a generalised correlation that measures every kind of relationship between random vectors was used. These latter correlations between arrays of daily values of the ten meteorological elements and the array of daily ragweed pollen concentrations during the current pollen season were calculated. For the current pollen season, the six most important variables are two temperature variables (mean and minimum temperatures), two humidity variables (dew point depression and rainfall) and two variables characterising the mixing of the air (wind speed and the height of the planetary boundary layer). The six most important meteorological variables before the current pollen season contain four temperature variables (mean, maximum, minimum temperatures and soil temperature) and two variables that characterise large-scale weather patterns (sea level pressure and the height of the planetary boundary layer). Key periods of the past meteorological variables before the current pollen season have been identified. The importance of this kind of analysis is that a knowledge of the past meteorological conditions may contribute to a better prediction of the upcoming pollen season.

Accuracy evaluation of ClimGen weather generator and daily to hourly disaggregation methods in tropical conditions

NASA Astrophysics Data System (ADS)

Safeeq, Mohammad; Fares, Ali

2011-12-01

Daily and sub-daily weather data are often required for hydrological and environmental modeling. Various weather generator programs have been used to generate synthetic climate data where observed climate data are limited. In this study, a weather data generator, ClimGen, was evaluated for generating information on daily precipitation, temperature, and wind speed at four tropical watersheds located in Hawai`i, USA. We also evaluated different daily to sub-daily weather data disaggregation methods for precipitation, air temperature, dew point temperature, and wind speed at Mākaha watershed. The hydrologic significance values of the different disaggregation methods were evaluated using Distributed Hydrology Soil Vegetation Model. MuDRain and diurnal method performed well over uniform distribution in disaggregating daily precipitation. However, the diurnal method is more consistent if accurate estimates of hourly precipitation intensities are desired. All of the air temperature disaggregation methods performed reasonably well, but goodness-of-fit statistics were slightly better for sine curve model with 2 h lag. Cosine model performed better than random model in disaggregating daily wind speed. The largest differences in annual water balance were related to wind speed followed by precipitation and dew point temperature. Simulated hourly streamflow, evapotranspiration, and groundwater recharge were less sensitive to the method of disaggregating daily air temperature. ClimGen performed well in generating the minimum and maximum temperature and wind speed. However, for precipitation, it clearly underestimated the number of extreme rainfall events with an intensity of >100 mm/day in all four locations. ClimGen was unable to replicate the distribution of observed precipitation at three locations (Honolulu, Kahului, and Hilo). ClimGen was able to reproduce the distributions of observed minimum temperature at Kahului and wind speed at Kahului and Hilo. Although the weather data generation and disaggregation methods were concentrated in a few Hawaiian watersheds, the results presented can be used to similar mountainous location settings, as well as any specific locations aimed at furthering the site-specific performance evaluation of these tested models.

46 CFR 196.85-1 - Magazine operation and control.

Code of Federal Regulations, 2011 CFR

2011-10-01

...-1 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) OCEANOGRAPHIC RESEARCH VESSELS... shall be inspected daily. Magazine inspection results and corrective action, when taken, shall be noted in the ship's log daily. Maximum and minimum temperatures for the previous 24-hour period shall be...

Local-scale spatial modelling for interpolating climatic temperature variables to predict agricultural plant suitability

NASA Astrophysics Data System (ADS)

Webb, Mathew A.; Hall, Andrew; Kidd, Darren; Minansy, Budiman

2016-05-01

Assessment of local spatial climatic variability is important in the planning of planting locations for horticultural crops. This study investigated three regression-based calibration methods (i.e. traditional versus two optimized methods) to relate short-term 12-month data series from 170 temperature loggers and 4 weather station sites with data series from nearby long-term Australian Bureau of Meteorology climate stations. The techniques trialled to interpolate climatic temperature variables, such as frost risk, growing degree days (GDDs) and chill hours, were regression kriging (RK), regression trees (RTs) and random forests (RFs). All three calibration methods produced accurate results, with the RK-based calibration method delivering the most accurate validation measures: coefficients of determination ( R 2) of 0.92, 0.97 and 0.95 and root-mean-square errors of 1.30, 0.80 and 1.31 °C, for daily minimum, daily maximum and hourly temperatures, respectively. Compared with the traditional method of calibration using direct linear regression between short-term and long-term stations, the RK-based calibration method improved R 2 and reduced root-mean-square error (RMSE) by at least 5 % and 0.47 °C for daily minimum temperature, 1 % and 0.23 °C for daily maximum temperature and 3 % and 0.33 °C for hourly temperature. Spatial modelling indicated insignificant differences between the interpolation methods, with the RK technique tending to be the slightly better method due to the high degree of spatial autocorrelation between logger sites.

CPLFD-GDPT5: high-resolution gridded daily precipitation and temperature dataset for two largest Polish river basins

NASA Astrophysics Data System (ADS)

Berezowski, T.; Szcześniak, M.; Kardel, I.; Michałowski, R.; Okruszko, T.; Mezghani, A.; Piniewski, M.

2015-12-01

The CHASE-PL Forcing Data-Gridded Daily Precipitation and Temperature Dataset-5 km (CPLFD-GDPT5) consists of 1951-2013 daily minimum and maximum air temperatures and precipitation totals interpolated onto a 5 km grid based on daily meteorological observations from Institute of Meteorology and Water Management (IMGW-PIB; Polish stations), Deutscher Wetterdienst (DWD, German and Czech stations), ECAD and NOAA-NCDC (Slovak, Ukrainian and Belarus stations). The main purpose for constructing this product was the need for long-term aerial precipitation and temperature data for earth-system modelling, especially hydrological modelling. The spatial coverage is the union of Vistula and Odra basin and Polish territory. The number of available meteorological stations for precipitation and temperature varies in time from about 100 for temperature and 300 for precipitation in 1950 up to about 180 for temperature and 700 for precipitation in 1990. The precipitation dataset was corrected for snowfall and rainfall under-catch with the Richter method. The interpolation methods were: kriging with elevation as external drift for temperatures and indicator kriging combined with universal kriging for precipitation. The kriging cross-validation revealed low root mean squared errors expressed as a fraction of standard deviation (SD): 0.54 and 0.47 for minimum and maximum temperature, respectively and 0.79 for precipitation. The correlation scores were 0.84 for minimum temperatures, 0.88 for maximum temperatures and 0.65 for precipitation. The CPLFD-GDPT5 product is consistent with 1971-2000 climatic data published by IMGW-PIB. We also confirm good skill of the product for hydrological modelling by performing an application using the Soil and Water Assessment Tool (SWAT) in the Vistula and Odra basins. Link to the dataset: http://data.3tu.nl/repository/uuid:e939aec0-bdd1-440f-bd1e-c49ff10d0a07

Effects of microclimatic variables on the symptoms and signs onset of Moniliophthora roreri, causal agent of Moniliophthora pod rot in cacao

PubMed Central

Tixier, Philippe; Germon, Amandine; Rakotobe, Veromanitra; Phillips-Mora, Wilbert; Maximova, Siela; Avelino, Jacques

2017-01-01

Moniliophthora Pod Rot (MPR) caused by the fungus Moniliophthora roreri (Cif.) Evans et al., is one of the main limiting factors of cocoa production in Latin America. Currently insufficient information on the biology and epidemiology of the pathogen limits the development of efficient management options to control MPR. This research aims to elucidate MPR development through the following daily microclimatic variables: minimum and maximum temperatures, wetness frequency, average temperature and relative humidity in the highly susceptible cacao clone Pound-7 (incidence = 86% 2008–2013 average). A total of 55 cohorts totaling 2,268 pods of 3–10 cm length, one to two months of age, were tagged weekly. Pods were assessed throughout their lifetime, every one or two weeks, and classified in 3 different categories: healthy, diseased with no sporulation, diseased with sporulating lesions. As a first step, we used Generalized Linear Mixed Models (GLMM) to determine with no a priori the period (when and for how long) each climatic variable was better related with the appearance of symptoms and sporulation. Then the significance of the candidate variables was tested in a complete GLMM. Daily average wetness frequency from day 14 to day 1, before tagging, and daily average maximum temperature from day 4 to day 21, after tagging, were the most explanatory variables of the symptoms appearance. The former was positively linked with the symptoms appearance when the latter exhibited a maximum at 30°C. The most important variables influencing sporulation were daily average minimum temperature from day 35 to day 58 and daily average maximum temperature from day 37 to day 48, both after tagging. Minimum temperature was negatively linked with the sporulation while maximum temperature was positively linked. Results indicated that the fungal microclimatic requirements vary from the early to the late cycle stages, possibly due to the pathogen’s long latent period. This information is valuable for development of new conceptual models for MPR and improvement of control methods. PMID:28972981

Effects of microclimatic variables on the symptoms and signs onset of Moniliophthora roreri, causal agent of Moniliophthora pod rot in cacao.

PubMed

Leandro-Muñoz, Mariela E; Tixier, Philippe; Germon, Amandine; Rakotobe, Veromanitra; Phillips-Mora, Wilbert; Maximova, Siela; Avelino, Jacques

2017-01-01

Moniliophthora Pod Rot (MPR) caused by the fungus Moniliophthora roreri (Cif.) Evans et al., is one of the main limiting factors of cocoa production in Latin America. Currently insufficient information on the biology and epidemiology of the pathogen limits the development of efficient management options to control MPR. This research aims to elucidate MPR development through the following daily microclimatic variables: minimum and maximum temperatures, wetness frequency, average temperature and relative humidity in the highly susceptible cacao clone Pound-7 (incidence = 86% 2008-2013 average). A total of 55 cohorts totaling 2,268 pods of 3-10 cm length, one to two months of age, were tagged weekly. Pods were assessed throughout their lifetime, every one or two weeks, and classified in 3 different categories: healthy, diseased with no sporulation, diseased with sporulating lesions. As a first step, we used Generalized Linear Mixed Models (GLMM) to determine with no a priori the period (when and for how long) each climatic variable was better related with the appearance of symptoms and sporulation. Then the significance of the candidate variables was tested in a complete GLMM. Daily average wetness frequency from day 14 to day 1, before tagging, and daily average maximum temperature from day 4 to day 21, after tagging, were the most explanatory variables of the symptoms appearance. The former was positively linked with the symptoms appearance when the latter exhibited a maximum at 30°C. The most important variables influencing sporulation were daily average minimum temperature from day 35 to day 58 and daily average maximum temperature from day 37 to day 48, both after tagging. Minimum temperature was negatively linked with the sporulation while maximum temperature was positively linked. Results indicated that the fungal microclimatic requirements vary from the early to the late cycle stages, possibly due to the pathogen's long latent period. This information is valuable for development of new conceptual models for MPR and improvement of control methods.

Does size matter? Comparison of body temperature and activity of free-living Arabian oryx (Oryx leucoryx) and the smaller Arabian sand gazelle (Gazella subgutturosa marica) in the Saudi desert.

PubMed

Hetem, Robyn Sheila; Strauss, Willem Maartin; Fick, Linda Gayle; Maloney, Shane Kevin; Meyer, Leith Carl Rodney; Shobrak, Mohammed; Fuller, Andrea; Mitchell, Duncan

2012-04-01

Heterothermy, a variability in body temperature beyond the normal limits of homeothermy, is widely viewed as a key adaptation of arid-adapted ungulates. However, desert ungulates with a small body mass, i.e. a relatively large surface area-to-volume ratio and a small thermal inertia, are theoretically less likely to employ adaptive heterothermy than are larger ungulates. We measured body temperature and activity patterns, using implanted data loggers, in free-ranging Arabian oryx (Oryx leucoryx, ±70 kg) and the smaller Arabian sand gazelle (Gazella subgutturosa marica, ±15 kg) inhabiting the same Arabian desert environment, at the same time. Compared to oryx, sand gazelle had higher mean daily body temperatures (F(1,6) = 47.3, P = 0.0005), higher minimum daily body temperatures (F(1,6) = 42.6, P = 0.0006) and higher maximum daily body temperatures (F(1,6) = 11.0, P = 0.02). Despite these differences, both species responded similarly to changes in environmental conditions. As predicted for adaptive heterothermy, maximum daily body temperature increased (F(1,6) = 84.0, P < 0.0001), minimum daily body temperature decreased (F(1,6) = 92.2, P < 0.0001), and daily body temperature amplitude increased (F(1,6) = 97.6, P < 0.0001) as conditions got progressively hotter and drier. There were no species differences in activity levels, however, both gazelle and oryx showed a biphasic or crepuscular rhythm during the warm wet season but shifted to a more nocturnal rhythm during the hot dry season. Activity was attenuated during the heat of the day at times when both species selected cool microclimates. These two species of Arabian ungulates employ heterothermy, cathemerality and shade seeking very similarly to survive the extreme, arid conditions of Arabian deserts, despite their size difference.

9 CFR 381.304 - Operations in the thermal processing area.

Code of Federal Regulations, 2011 CFR

2011-01-01

... establishment at the time the processing cycle begins to assure that the temperature of the contents of every... processing operation times. Temperature/time recording devices shall correspond within 15 minutes to the time... (or operating process schedules) for daily production, including minimum initial temperatures and...

9 CFR 381.304 - Operations in the thermal processing area.

Code of Federal Regulations, 2013 CFR

2013-01-01

... establishment at the time the processing cycle begins to assure that the temperature of the contents of every... processing operation times. Temperature/time recording devices shall correspond within 15 minutes to the time... (or operating process schedules) for daily production, including minimum initial temperatures and...

9 CFR 381.304 - Operations in the thermal processing area.

Code of Federal Regulations, 2014 CFR

2014-01-01

... establishment at the time the processing cycle begins to assure that the temperature of the contents of every... processing operation times. Temperature/time recording devices shall correspond within 15 minutes to the time... (or operating process schedules) for daily production, including minimum initial temperatures and...

9 CFR 381.304 - Operations in the thermal processing area.

Code of Federal Regulations, 2012 CFR

2012-01-01

... establishment at the time the processing cycle begins to assure that the temperature of the contents of every... processing operation times. Temperature/time recording devices shall correspond within 15 minutes to the time... (or operating process schedules) for daily production, including minimum initial temperatures and...

Operational forecasting of daily temperatures in the Valencia Region. Part II: minimum temperatures in winter.

NASA Astrophysics Data System (ADS)

Gómez, I.; Estrela, M.

2009-09-01

Extreme temperature events have a great impact on human society. Knowledge of minimum temperatures during winter is very useful for both the general public and organisations whose workers have to operate in the open, e.g. railways, roadways, tourism, etc. Moreover, winter minimum temperatures are considered a parameter of interest and concern since persistent cold-waves can affect areas as diverse as public health, energy consumption, etc. Thus, an accurate forecasting of these temperatures could help to predict cold-wave conditions and permit the implementation of strategies aimed at minimizing the negative effects that low temperatures have on human health. The aim of this work is to evaluate the skill of the RAMS model in determining daily minimum temperatures during winter over the Valencia Region. For this, we have used the real-time configuration of this model currently running at the CEAM Foundation. To carry out the model verification process, we have analysed not only the global behaviour of the model for the whole Valencia Region, but also its behaviour for the individual stations distributed within this area. The study has been performed for the winter forecast period from 1 December 2007 - 31 March 2008. The results obtained are encouraging and indicate a good agreement between the observed and simulated minimum temperatures. Moreover, the model captures quite well the temperatures in the extreme cold episodes. Acknowledgement. This work was supported by "GRACCIE" (CSD2007-00067, Programa Consolider-Ingenio 2010), by the Spanish Ministerio de Educación y Ciencia, contract number CGL2005-03386/CLI, and by the Regional Government of Valencia Conselleria de Sanitat, contract "Simulación de las olas de calor e invasiones de frío y su regionalización en la Comunidad Valenciana" ("Heat wave and cold invasion simulation and their regionalization at Valencia Region"). The CEAM Foundation is supported by the Generalitat Valenciana and BANCAIXA (Valencia, Spain).

Heat Wave and Mortality: A Multicountry, Multicommunity Study

PubMed Central

Gasparrini, Antonio; Armstrong, Ben G.; Tawatsupa, Benjawan; Tobias, Aurelio; Lavigne, Eric; Coelho, Micheline de Sousa Zanotti Stagliorio; Pan, Xiaochuan; Kim, Ho; Hashizume, Masahiro; Honda, Yasushi; Guo, Yue-Liang Leon; Wu, Chang-Fu; Zanobetti, Antonella; Schwartz, Joel D.; Bell, Michelle L.; Scortichini, Matteo; Michelozzi, Paola; Punnasiri, Kornwipa; Li, Shanshan; Tian, Linwei; Garcia, Samuel David Osorio; Seposo, Xerxes; Overcenco, Ala; Zeka, Ariana; Goodman, Patrick; Dang, Tran Ngoc; Dung, Do Van; Mayvaneh, Fatemeh; Saldiva, Paulo Hilario Nascimento; Williams, Gail; Tong, Shilu

2017-01-01

Background: Few studies have examined variation in the associations between heat waves and mortality in an international context. Objectives: We aimed to systematically examine the impacts of heat waves on mortality with lag effects internationally. Methods: We collected daily data of temperature and mortality from 400 communities in 18 countries/regions and defined 12 types of heat waves by combining community-specific daily mean temperature ≥90th, 92.5th, 95th, and 97.5th percentiles of temperature with duration ≥2, 3, and 4 d. We used time-series analyses to estimate the community-specific heat wave–mortality relation over lags of 0–10 d. Then, we applied meta-analysis to pool heat wave effects at the country level for cumulative and lag effects for each type of heat wave definition. Results: Heat waves of all definitions had significant cumulative associations with mortality in all countries, but varied by community. The higher the temperature threshold used to define heat waves, the higher heat wave associations on mortality. However, heat wave duration did not modify the impacts. The association between heat waves and mortality appeared acutely and lasted for 3 and 4 d. Heat waves had higher associations with mortality in moderate cold and moderate hot areas than cold and hot areas. There were no added effects of heat waves on mortality in all countries/regions, except for Brazil, Moldova, and Taiwan. Heat waves defined by daily mean and maximum temperatures produced similar heat wave–mortality associations, but not daily minimum temperature. Conclusions: Results indicate that high temperatures create a substantial health burden, and effects of high temperatures over consecutive days are similar to what would be experienced if high temperature days occurred independently. People living in moderate cold and moderate hot areas are more sensitive to heat waves than those living in cold and hot areas. Daily mean and maximum temperatures had similar ability to define heat waves rather than minimum temperature. https://doi.org/10.1289/EHP1026 PMID:28886602

A basin-scale approach to estimating stream temperatures of tributaries to the lower Klamath River, California

USGS Publications Warehouse

Flint, L.E.; Flint, A.L.

2008-01-01

Stream temperature is an important component of salmonid habitat and is often above levels suitable for fish survival in the Lower Klamath River in northern California. The objective of this study was to provide boundary conditions for models that are assessing stream temperature on the main stem for the purpose of developing strategies to manage stream conditions using Total Maximum Daily Loads. For model input, hourly stream temperatures for 36 tributaries were estimated for 1 Jan. 2001 through 31 Oct. 2004. A basin-scale approach incorporating spatially distributed energy balance data was used to estimate the stream temperatures with measured air temperature and relative humidity data and simulated solar radiation, including topographic shading and corrections for cloudiness. Regression models were developed on the basis of available stream temperature data to predict temperatures for unmeasured periods of time and for unmeasured streams. The most significant factor in matching measured minimum and maximum stream temperatures was the seasonality of the estimate. Adding minimum and maximum air temperature to the regression model improved the estimate, and air temperature data over the region are available and easily distributed spatially. The addition of simulated solar radiation and vapor saturation deficit to the regression model significantly improved predictions of maximum stream temperature but was not required to predict minimum stream temperature. The average SE in estimated maximum daily stream temperature for the individual basins was 0.9 ?? 0.6??C at the 95% confidence interval. Copyright ?? 2008 by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. All rights reserved.

Climate and respiratory disease in Auckland, New Zealand.

PubMed

Gosai, Ashmita; Salinger, James; Dirks, Kim

2009-12-01

Increases in the incidence of diseases are often observed during the cold winter months, particularly in cities in temperate climates. The study aim is to describe daily, monthly and seasonal trends in respiratory hospital admissions with climate in Auckland, New Zealand. Daily hospital admissions for total respiratory infections or inflammations (RII), total bronchitis and asthma (BA), and total whooping cough and acute bronchitis (TWCAB) for various age groups and ethnicities were obtained for the Auckland Region and compared with climate parameters on daily, monthly and seasonal time scales. Seasonal and monthly relationships with minimum temperature were very strong (p<0.001) for RII over all age groups, for BA in the older age groups (14-64, 65+) and for TWCAB in the <1 year old age group. European, NZ Māori and Pacific Islanders all showed increases in admissions as temperatures decreased. Pacific Islanders were particularly susceptible to RII. There was a lag in admissions of three to seven days after a temperature event. Results show that increases in respiratory admissions are strongly linked to minimum temperatures during winter, typical of cities with temperate climates and poorly-insulated houses. There are implications for hospital bed and staffing planning in Auckland hospitals.

Changes in heat waves indices in Romania over the period 1961-2015

NASA Astrophysics Data System (ADS)

Croitoru, Adina-Eliza; Piticar, Adrian; Ciupertea, Antoniu-Flavius; Roşca, Cristina Florina

2016-11-01

In the last two decades many climate change studies have focused on extreme temperatures as they have a significant impact on environment and society. Among the weather events generated by extreme temperatures, heat waves are some of the most harmful. The main objective of this study was to detect and analyze changes in heat waves in Romania based on daily observation data (maximum and minimum temperature) over the extended summer period (May-Sept) using a set of 10 indices and to explore the spatial patterns of changes. Heat wave data series were derived from daily maximum and minimum temperature data sets recorded in 29 weather stations across Romania over a 55-year period (1961-2015). In this study, the threshold chosen was the 90th percentile calculated based on a 15-day window centered on each calendar day, and for three baseline periods (1961-1990, 1971-2000, and 1981-2010). Two heat wave definitions were considered: at least three consecutive days when maximum temperature exceeds 90th percentile, and at least three consecutive days when minimum temperature exceeds 90th percentile. For each of them, five variables were calculated: amplitude, magnitude, number of events, duration, and frequency. Finally, 10 indices resulted for further analysis. The main results are: most of the indices have statistically significant increasing trends; only one index for one weather station indicated statistically significant decreasing trend; the changes are more intense in case of heat waves detected based on maximum temperature compared to those obtained for heat waves identified based on minimum temperature; western and central regions of Romania are the most exposed to increasing heat waves.

Water Resources Data for California, 1965; Part 2: Water Quality Records

USGS Publications Warehouse

1965-01-01

Water quality information is presented for chemical quality, fluvial sediment, and water temperatures. The chemical quality includes concentrations of individual dissolved constituents and certain properties or characteristics such as hardness, sodium-adsorption-ratio, specific conductance, and pH. Fluvial sediment information is given for suspended-sediment discharges and concentrations and for particle-size distribution of suspended sediment and bed material. Water temperature data represent once-daily observations except for stations where a continuous temperature recorder furnishes information from which daily minimums and maximums are obtained.

Water Resources Data for California, 1966; Part 2: Water Quality Records

USGS Publications Warehouse

1967-01-01

Water-quality information is presented for chemical quality, fluvial sediment, and water temperatures. The chemical quality includes concentrations of individual dissolved constituents and certain properties or characteristics such as hardness, sodium-adsorption ratio, specific conductance, and pH. Fluvial-sediment information is given for suspended-sediment discharges and concentrations and for particle-size distribution of suspended sediment and bed material. Water-temperature data represent once-daily observations except for stations where a continuous temperature recorder furnishes information from which daily minimums and maximums are obtained.

Estimated winter wheat yield from crop growth predicted by LANDSAT

NASA Technical Reports Server (NTRS)

Kanemasu, E. T.

1977-01-01

An evapotranspiration and growth model for winter wheat is reported. The inputs are daily solar radiation, maximum temperature, minimum temperature, precipitation/irrigation and leaf area index. The meteorological data were obtained from National Weather Service while LAI was obtained from LANDSAT multispectral scanner. The output provides daily estimates of potential evapotranspiration, transpiration, evaporation, soil moisture (50 cm depth), percentage depletion, net photosynthesis and dry matter production. Winter wheat yields are correlated with transpiration and dry matter accumulation.

Differences between true mean temperatures and means calculated with four different approaches: a case study from three Croatian stations

NASA Astrophysics Data System (ADS)

Bonacci, Ognjen; Željković, Ivana

2018-01-01

Different countries use varied methods for daily mean temperature calculation. None of them assesses precisely the true daily mean temperature, which is defined as the integral of continuous temperature measurements in a day. Of special scientific as well as practical importance is to find out how temperatures calculated by different methods and approaches deviate from the true daily mean temperature. Five mean daily temperatures were calculated (T0, T1, T2, T3, T4) using five different equations. The mean of 24-h temperature observations during the calendar day is accepted to represent the true, daily mean T0. The differences Δ i between T0 and four other mean daily temperatures T1, T2, T3, and T4 were calculated and analysed. In the paper, analyses were done with hourly data measured in a period from 1 January 1999 to 31 December 2014 (149,016 h, 192 months and 16 years) at three Croatian meteorological stations. The stations are situated in distinct climatological areas: Zagreb Grič in a mild climate, Zavižan in the cold mountain region and Dubrovnik in the hot Mediterranean. Influence of fog on the temperature is analysed. Special attention is given to analyses of extreme (maximum and minimum) daily differences occurred at three analysed stations. Selection of the fixed local hours, which is in use for calculation of mean daily temperature, plays a crucial role in diminishing of bias from the true daily temperature.

Persistence and long-term memories of daily maximum and minimum temperatures in southern South America

NASA Astrophysics Data System (ADS)

Naumann, Gustavo; Vargas, Walter M.; Minetti, Juan L.

2011-10-01

The persistence and long-term memories in daily maximum and minimum temperature series during the instrumental period in southern South America were analysed. Here, we found a markedly seasonal pattern both for short- and long-term memories that can lead to enhanced predictability on intraseasonal timescales. In addition, well-defined spatial patterns of these properties were found in the region. Throughout the entire region, the strongest dependence was observed in autumn and early winter. In the Patagonia region only, the temperatures exhibited more memory during the spring. In general, these elements indicate that nonlinear interactions exist between the annual cycles of temperature and its anomalies. Knowledge of the spatiotemporal behaviour of these long-term memories can be used in the building of stochastic models that only use persistence. It is possible to propose two objective forecast models based on linear interactions associated with persistence and one that allows for the use of information from nonlinear interactions that are manifested in the form of forerunners.

A comparison of climatological observing windows and their impact on detecting daily temperature extrema

NASA Astrophysics Data System (ADS)

Žaknić-Ćatović, Ana; Gough, William A.

2018-04-01

Climatological observing window (COW) is defined as a time frame over which continuous or extreme air temperature measurements are collected. A 24-h time interval, ending at 00UTC or shifted to end at 06UTC, has been associated with difficulties in characterizing daily temperature extrema. A fixed 24-h COW used to obtain the temperature minima leads to potential misidentification due to fragmentation of "nighttime" into two subsequent nighttime periods due to the time discretization interval. The correct identification of air temperature extrema is achievable using a COW that identifies daily minimum over a single nighttime period and maximum over a single daytime period, as determined by sunrise and sunset. Due to a common absence of hourly air temperature observations, the accuracy of the mean temperature estimation is dependent on the accuracy of determination of diurnal air temperature extrema. Qualitative and quantitative criteria were used to examine the impact of the COW on detecting daily air temperature extrema. The timing of the 24-h observing window occasionally affects the determination of daily extrema through a mischaracterization of the diurnal minima and by extension can lead to errors in determining daily mean temperature. Hourly air temperature data for the time period from year 1987 to 2014, obtained from Toronto Buttonville Municipal Airport weather station, were used in analysis of COW impacts on detection of daily temperature extrema and calculation of annual temperature averages based on such extrema.

Weather and Climate Indicators for Coffee Rust Disease

NASA Astrophysics Data System (ADS)

Georgiou, S.; Imbach, P. A.; Avelino, J.; Anzueto, F.; del Carmen Calderón, G.

2014-12-01

Coffee rust is a disease that has significant impacts on the livelihoods of those who are dependent on the Central American coffee sector. Our investigation has focussed on the weather and climate indicators that favoured the high incidence of coffee rust disease in Central America in 2012 by assessing daily temperature and precipitation data available from 81 weather stations in the INSIVUMEH and ANACAFE networks located in Guatemala. The temperature data were interpolated to determine the corresponding daily data at 1250 farms located across Guatemala, between 400 and 1800 m elevation. Additionally, CHIRPS five day (pentad) data has been used to assess the anomalies between the 2012 and the climatological average precipitation data at farm locations. The weather conditions in 2012 displayed considerable variations from the climatological data. In general the minimum daily temperatures were higher than the corresponding climatology while the maximum temperatures were lower. As a result, the daily diurnal temperature range was generally lower than the corresponding climatological range, leading to an increased number of days where the temperatures fell within the optimal range for either influencing the susceptibility of the coffee plants to coffee rust development during the dry season, or for the development of lesions on the coffee leaves during the wet season. The coffee rust latency period was probably shortened as a result, and farms at high altitudes were impacted due to these increases in minimum temperature. Factors taken into consideration in developing indicators for coffee rust development include: the diurnal temperature range, altitude, the environmental lapse rate and the phenology. We will present the results of our study and discuss the potential for each of the derived weather and climatological indicators to be used within risk assessments and to eventually be considered for use within an early warning system for coffee rust disease.

Measured and predicted air temperatures at basin to regional scales in the southern Appalachian mountains

Treesearch

Paul V. Bolstad; Lloyd Swift; Fred Collins; Jacques Regniere

1998-01-01

Landscape and temporal patterns of temperature were observed for local (13 station) and regional (35 station) networks in the Southern Appalachian mountains of North America. Temperatures decreased with altitude at mean rates of 7EC/km (maximum temperature) and 3EC/km (minimum temperature). Daily lapse rates depended on the method and stations used in the calculations...

CPLFD-GDPT5: High-resolution gridded daily precipitation and temperature data set for two largest Polish river basins

NASA Astrophysics Data System (ADS)

Berezowski, Tomasz; Szcześniak, Mateusz; Kardel, Ignacy; Michałowski, Robert; Okruszko, Tomasz; Mezghani, Abdelkader; Piniewski, Mikołaj

2016-03-01

The CHASE-PL (Climate change impact assessment for selected sectors in Poland) Forcing Data-Gridded Daily Precipitation & Temperature Dataset-5 km (CPLFD-GDPT5) consists of 1951-2013 daily minimum and maximum air temperatures and precipitation totals interpolated onto a 5 km grid based on daily meteorological observations from the Institute of Meteorology and Water Management (IMGW-PIB; Polish stations), Deutscher Wetterdienst (DWD, German and Czech stations), and European Climate Assessment and Dataset (ECAD) and National Oceanic and Atmosphere Administration-National Climatic Data Center (NOAA-NCDC) (Slovak, Ukrainian, and Belarusian stations). The main purpose for constructing this product was the need for long-term aerial precipitation and temperature data for earth-system modelling, especially hydrological modelling. The spatial coverage is the union of the Vistula and Oder basins and Polish territory. The number of available meteorological stations for precipitation and temperature varies in time from about 100 for temperature and 300 for precipitation in the 1950s up to about 180 for temperature and 700 for precipitation in the 1990s. The precipitation data set was corrected for snowfall and rainfall under-catch with the Richter method. The interpolation methods were kriging with elevation as external drift for temperatures and indicator kriging combined with universal kriging for precipitation. The kriging cross validation revealed low root-mean-squared errors expressed as a fraction of standard deviation (SD): 0.54 and 0.47 for minimum and maximum temperature, respectively, and 0.79 for precipitation. The correlation scores were 0.84 for minimum temperatures, 0.88 for maximum temperatures, and 0.65 for precipitation. The CPLFD-GDPT5 product is consistent with 1971-2000 climatic data published by IMGW-PIB. We also confirm good skill of the product for hydrological modelling by performing an application using the Soil and Water Assessment Tool (SWAT) in the Vistula and Oder basins. Link to the data set: doi:10.4121/uuid:e939aec0-bdd1-440f-bd1e-c49ff10d0a07.

Geo-spatial analysis of temporal trends of temperature and its extremes over India using daily gridded (1°×1°) temperature data of 1969-2005

NASA Astrophysics Data System (ADS)

Chakraborty, Abhishek; Seshasai, M. V. R.; Rao, S. V. C. Kameswara; Dadhwal, V. K.

2017-10-01

Daily gridded (1°×1°) temperature data (1969-2005) were used to detect spatial patterns of temporal trends of maximum and minimum temperature (monthly and seasonal), growing degree days (GDDs) over the crop-growing season ( kharif, rabi, and zaid) and annual frequencies of temperature extremes over India. The direction and magnitude of trends, at each grid level, were estimated using the Mann-Kendall statistics ( α = 0.05) and further assessed at the homogeneous temperature regions using a field significance test ( α=0.05). General warming trends were observed over India with considerable variations in direction and magnitude over space and time. The spatial extent and the magnitude of the increasing trends of minimum temperature (0.02-0.04 °C year-1) were found to be higher than that of maximum temperature (0.01-0.02 °C year-1) during winter and pre-monsoon seasons. Significant negative trends of minimum temperature were found over eastern India during the monsoon months. Such trends were also observed for the maximum temperature over northern and eastern parts, particularly in the winter month of January. The general warming patterns also changed the thermal environment of the crop-growing season causing significant increase in GDDs during kharif and rabi seasons across India. The warming climate has also caused significant increase in occurrences of hot extremes such as hot days and hot nights, and significant decrease in cold extremes such as cold days and cold nights.

Meteorology Online.

ERIC Educational Resources Information Center

Kahl, Jonathan D. W.

2001-01-01

Describes an activity to learn about meteorology and weather using the internet. Discusses the National Weather Service (NWS) internet site www.weather.gov. Students examine maximum and minimum daily temperatures, wind speed, and direction. (SAH)

Climate and climate change and infectious disease risk in Thailand: A spatial study of dengue hemorrhagic fever using GIS and remotely-sensed imagery

NASA Astrophysics Data System (ADS)

Kuzera, Kristopher

The scientific community has widely accepted that climate plays a key role in the sustainability and transmission of many infectious diseases. Global climate change can potentially trigger the spread of disease into new regions and increase the intensity of disease in regions where it is endemic. This study explores the association between monthly conditions of climate change to changes in disease risk, emphasizing the potential spread of dengue fever due to climate change in Thailand. This study also develops techniques new to GIS and remote sensing that generate surfaces of daily minimum temperature toward identifying areas at greater transmission risk. Dengue fever expansion due to global warming is a serious concern for Thailand where warming temperatures may increase the size of the habitat of the disease-spreading vector, Aedes aegypti, particularly during cooler months when transmission is limited by environmental conditions. In this study, first, the association between past dengue hemorrhagic fever (DHF) and climate in Thailand is determined. Second, evidence of recent climate change is related to changes in DHF rates. Third, daily minimum temperature is derived from remote sensing toward identifying the spatial and temporal limitations of potential transmission risk. The results indicate that minimum temperature has recently experienced a rapid increase, particularly in the winter months when transmission is low. This is associated with a recent rise in winter DHF cases. As increasing minimum temperatures in these regions are anticipated to continue, we can expect dengue transmission rates to also increase throughout the year.

Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: 30-Year Average Daily Minimum Temperature, 1971-2000

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This tabular data set represents thecatchment-average for the 30-year (1971-2000) average daily minimum temperature in Celsius multiplied by 100 compiled for every MRB_E2RF1 catchment of selected Major River Basins (MRBs, Crawford and others, 2006). The source data were the United States Average Monthly or Annual Minimum Temperature, 1971 - 2000 raster data set produced by the PRISM Group at Oregon State University. The MRB_E2RF1 catchments are based on a modified version of the Environmental Protection Agency's (USEPA) ERF1_2 and include enhancements to support national and regional-scale surface-water quality modeling (Nolan and others, 2002; Brakebill and others, 2011). Data were compiled for every MRB_E2RF1 catchment for the conterminous United States covering New England and Mid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), the Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).

Catchments by Major River Basins in the Conterminous United States: 30-Year Average Daily Minimum Temperature, 1971-2000

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This tabular data set represents thecatchment-average for the 30-year (1971-2000) average daily minimum temperature in Celsius multiplied by 100 compiled for every MRB_E2RF1 catchment of selected Major River Basins (MRBs, Crawford and others, 2006). The source data were the United States Average Monthly or Annual Minimum Temperature, 1971 - 2000 raster data set produced by the PRISM Group at Oregon State University. The MRB_E2RF1 catchments are based on a modified version of the Environmental Protection Agency's (USEPA) ERF1_2 and include enhancements to support national and regional-scale surface-water quality modeling (Nolan and others, 2002; Brakebill and others, 2011). Data were compiled for every MRB_E2RF1 catchment for the conterminous United States covering New England and Mid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), the Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).

Differences between true mean daily, monthly and annual air temperatures and air temperatures calculated with three equations: a case study from three Croatian stations

NASA Astrophysics Data System (ADS)

Bonacci, Ognjen; Željković, Ivana; Trogrlić, Robert Šakić; Milković, Janja

2013-10-01

Differences between true mean daily, monthly and annual air temperatures T0 [Eq. (1)] and temperatures calculated with three different equations [(2), (3) and (4)] (commonly used in climatological practice) were investigated at three main meteorological Croatian stations from 1 January 1999 to 31 December 2011. The stations are situated in the following three climatically distinct areas: (1) Zagreb-Grič (mild continental climate), (2) Zavižan (cold mountain climate), and (3) Dubrovnik (hot Mediterranean climate). T1 [Eq. (2)] and T3 [Eq. (4)] mean temperatures are defined by the algorithms based on the weighted means of temperatures measured at irregularly spaced, yet fixed hours. T2 [Eq. (3)] is the mean temperature defined as the average of daily maximum and minimum temperature. The equation as well as the time of observations used introduces a bias into mean temperatures. The largest differences occur for mean daily temperatures. The calculated daily difference value from all three equations and all analysed stations varies from -3.73 °C to +3.56 °C, from -1.39 °C to +0.79 °C for monthly differences and from -0.76 °C to +0.30 °C for annual differences.

The 2011 heat wave in Greater Houston: Effects of land use on temperature.

PubMed

Zhou, Weihe; Ji, Shuang; Chen, Tsun-Hsuan; Hou, Yi; Zhang, Kai

2014-11-01

Effects of land use on temperatures during severe heat waves have been rarely studied. This paper examines land use-temperature associations during the 2011 heat wave in Greater Houston. We obtained high resolution of satellite-derived land use data from the US National Land Cover Database, and temperature observations at 138 weather stations from Weather Underground, Inc (WU) during the August of 2011, which was the hottest month in Houston since 1889. Land use regression and quantile regression methods were applied to the monthly averages of daily maximum/mean/minimum temperatures and 114 land use-related predictors. Although selected variables vary with temperature metric, distance to the coastline consistently appears among all models. Other variables are generally related to high developed intensity, open water or wetlands. In addition, our quantile regression analysis shows that distance to the coastline and high developed intensity areas have larger impacts on daily average temperatures at higher quantiles, and open water area has greater impacts on daily minimum temperatures at lower quantiles. By utilizing both land use regression and quantile regression on a recent heat wave in one of the largest US metropolitan areas, this paper provides a new perspective on the impacts of land use on temperatures. Our models can provide estimates of heat exposures for epidemiological studies, and our findings can be combined with demographic variables, air conditioning and relevant diseases information to identify 'hot spots' of population vulnerability for public health interventions to reduce heat-related health effects during heat waves. Copyright © 2014 Elsevier Inc. All rights reserved.

EnviroAtlas - Biological nitrogen fixation in natural/semi-natural ecosystems by 12-digit HUC for the Conterminous United States, 2006

EPA Pesticide Factsheets

This EnviroAtlas dataset contains data on the mean biological nitrogen fixation in natural/semi-natural ecosystems per 12-digit Hydrologic Unit (HUC) in 2006. Biological N fixation (BNF) in natural/semi-natural ecosystems was estimated using a correlation with actual evapotranspiration (AET). This correlation is based on a global meta-analysis of BNF in natural/semi-natural ecosystems (Cleveland et al. 1999). AET estimates for 2006 were calculated using a regression equation describing the correlation of AET with climate (average annual daily temperature, average annual minimum daily temperature, average annual maximum daily temperature, and annual precipitation) and land use/land cover variables in the conterminous US (Sanford and Selnick 2013). Data describing annual average minimum and maximum daily temperatures and total precipitation for 2006 were acquired from the PRISM climate dataset (http://prism.oregonstate.edu). Average annual climate data were then calculated for individual 12-digit USGS Hydrologic Unit Codes (HUC12s; http://water.usgs.gov/GIS/huc.html; 22 March 2011 release) using the Zonal Statistics tool in ArcMap 10.0. AET for individual HUC12s was estimated using equations described in Sanford and Selnick (2013). BNF in natural/semi-natural ecosystems within individual HUC12s was modeled with an equation describing the statistical relationship between BNF (kg N ha-1 yr-1) and actual evapotranspiration (AET; cm yr-1) and scaled to the proportion

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.

High-Resolution Dynamical Downscaling Ensemble Projections of Future Extreme Temperature Distributions for the United States

NASA Astrophysics Data System (ADS)

Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.; Kotamarthi, V. Rao

2017-12-01

The aim of this study is to examine projections of extreme temperatures over the continental United States (CONUS) for the 21st century using an ensemble of high spatial resolution dynamically downscaled model simulations with different boundary conditions. The downscaling uses the Weather Research and Forecast model at a spatial resolution of 12 km along with outputs from three different Coupled Model Intercomparison Project Phase 5 global climate models that provide boundary conditions under two different future greenhouse gas (GHG) concentration trajectories. The results from two decadal-length time slices (2045-2054 and 2085-2094) are compared with a historical decade (1995-2004). Probability density functions of daily maximum/minimum temperatures are analyzed over seven climatologically cohesive regions of the CONUS. The impacts of different boundary conditions as well as future GHG concentrations on extreme events such as heat waves and days with temperature higher than 95°F are also investigated. The results show that the intensity of extreme warm temperature in future summer is significantly increased, while the frequency of extreme cold temperature in future winter decreases. The distribution of summer daily maximum temperature experiences a significant warm-side shift and increased variability, while the distribution of winter daily minimum temperature is projected to have a less significant warm-side shift with decreased variability. Using "business-as-usual" scenario, 5-day heat waves are projected to occur at least 5-10 times per year in most CONUS and ≥95°F days will increase by 1-2 months by the end of the century.

Impacts of day versus night warming on soil microclimate: results from a semiarid temperate steppe.

PubMed

Xia, Jianyang; Chen, Shiping; Wan, Shiqiang

2010-06-15

One feature of climate warming is that increases in daily minimum temperature are greater than those in daily maximum temperature. Changes in soil microclimate in response to the asymmetrically diurnal warming scenarios can help to explain responses of ecosystem processes. In the present study, we examined the impacts of day, night, and continuous warming on soil microclimate in a temperate steppe in northern China. Our results showed that day, night, and continuous warming (approximately 13Wm(-2) with constant power mode) significantly increased daily mean soil temperature at 10cm depth by 0.71, 0.78, and 1.71 degrees C, respectively. Night warming caused greater increases in nighttime mean and daily minimum soil temperatures (0.74 and 0.99 degrees C) than day warming did (0.60 and 0.66 degrees C). However, there were no differences in the increases in daytime mean and daily maximum soil temperature between day (0.81 and 1.13 degrees C) and night (0.81 and 1.10 degrees C) warming. The differential effects of day and night warming on soil temperature varied with environmental factors, including photosynthetic active radiation, vapor-pressure deficit, and wind speed. When compared with the effect of continuous warming on soil temperature, the summed effects of day and night warming were lower during daytime, but greater at night, thus leading to equality at daily scale. Mean volumetric soil moisture at the depth of 0-40cm significantly decreased under continuous warming in both 2006 (1.44 V/V%) and 2007 (0.76 V/V%). Day warming significantly reduced volumetric soil moisture only in 2006, whereas night warming had no effect on volumetric soil moisture in both 2006 and 2007. Given the different diurnal warming patterns and variability of environmental factors among ecosystems, these results highlight the importance of incorporating the differential impacts of day and night warming on soil microclimate into the predictions of terrestrial ecosystem responses to climate warming. Copyright 2010 Elsevier B.V. All rights reserved.

A Gridded Daily Min/Max Temperature Dataset With 0.1° Resolution for the Yangtze River Valley and its Error Estimation

NASA Astrophysics Data System (ADS)

Xiong, Qiufen; Hu, Jianglin

2013-05-01

The minimum/maximum (Min/Max) temperature in the Yangtze River valley is decomposed into the climatic mean and anomaly component. A spatial interpolation is developed which combines the 3D thin-plate spline scheme for climatological mean and the 2D Barnes scheme for the anomaly component to create a daily Min/Max temperature dataset. The climatic mean field is obtained by the 3D thin-plate spline scheme because the relationship between the decreases in Min/Max temperature with elevation is robust and reliable on a long time-scale. The characteristics of the anomaly field tend to be related to elevation variation weakly, and the anomaly component is adequately analyzed by the 2D Barnes procedure, which is computationally efficient and readily tunable. With this hybridized interpolation method, a daily Min/Max temperature dataset that covers the domain from 99°E to 123°E and from 24°N to 36°N with 0.1° longitudinal and latitudinal resolution is obtained by utilizing daily Min/Max temperature data from three kinds of station observations, which are national reference climatological stations, the basic meteorological observing stations and the ordinary meteorological observing stations in 15 provinces and municipalities in the Yangtze River valley from 1971 to 2005. The error estimation of the gridded dataset is assessed by examining cross-validation statistics. The results show that the statistics of daily Min/Max temperature interpolation not only have high correlation coefficient (0.99) and interpolation efficiency (0.98), but also the mean bias error is 0.00 °C. For the maximum temperature, the root mean square error is 1.1 °C and the mean absolute error is 0.85 °C. For the minimum temperature, the root mean square error is 0.89 °C and the mean absolute error is 0.67 °C. Thus, the new dataset provides the distribution of Min/Max temperature over the Yangtze River valley with realistic, successive gridded data with 0.1° × 0.1° spatial resolution and daily temporal scale. The primary factors influencing the dataset precision are elevation and terrain complexity. In general, the gridded dataset has a relatively high precision in plains and flatlands and a relatively low precision in mountainous areas.

Soil water content and evaporation determined by thermal parameters obtained from ground-based and remote measurements

NASA Technical Reports Server (NTRS)

Reginato, R. J.; Idso, S. B.; Jackson, R. D.; Vedder, J. F.; Blanchard, M. B.; Goettelman, R.

1976-01-01

Soil water contents from both smooth and rough bare soil were estimated from remotely sensed surface soil and air temperatures. An inverse relationship between two thermal parameters and gravimetric soil water content was found for Avondale loam when its water content was between air-dry and field capacity. These parameters, daily maximum minus minimum surface soil temperature and daily maximum soil minus air temperature, appear to describe the relationship reasonably well. These two parameters also describe relative soil water evaporation (actual/potential). Surface soil temperatures showed good agreement among three measurement techniques: in situ thermocouples, a ground-based infrared radiation thermometer, and the thermal infrared band of an airborne multispectral scanner.

Does hot weather affect work-related injury? A case-crossover study in Guangzhou, China.

PubMed

Sheng, Rongrong; Li, Changchang; Wang, Qiong; Yang, Lianping; Bao, Junzhe; Wang, Kaiwen; Ma, Rui; Gao, Chuansi; Lin, Shao; Zhang, Ying; Bi, Peng; Fu, Chuandong; Huang, Cunrui

2018-04-01

Despite increasing concerns about the health effects of climate change, the extent to which workers are affected by hot weather is not well documented. This study aims to investigate the association between high temperatures and work-related injuries using data from a large subtropical city in China. We used workers' compensation claims to identify work-related injuries in Guangzhou, China during 2011-2012. To feature the heat effect, the study period was restricted to the warm seasons in Guangzhou (1 May-31 October). We conducted a time-stratified case-crossover study to examine the association between ambient outdoor temperatures, including daily maximum and minimum temperatures, and cases of work-related injury. The relationships were assessed using conditional Poisson regression models. Overall, a total of 5418 workers' compensation claims were included over the study period. Both maximum and minimum temperatures were significantly associated with work-related injuries, but associations varied by subgroup. One °C increase in maximum temperature was associated with a 1.4% (RR = 1.014, 95%CIs 1.012-1.017) increase in daily injury claims. Significant associations were seen for male and middle-aged workers, workers in small and medium-sized enterprises, and those working in manufacturing sector. And 1 °C increase in minimum temperature was associated with 1.7% (RR = 1.017, 95%CIs 1.012-1.021) increase in daily injury claims. Significant associations were observed for female and middle-aged workers, workers in large-sized enterprises, and those working in transport and construction sectors. We found a higher risk of work-related injuries due to hot weather in Guangzhou, China. This study provides important epidemiological evidence for policy-makers and industry that may assist in the formulation of occupational safety and climate adaptation strategies. Copyright © 2018 Elsevier GmbH. All rights reserved.

Variation in the daily rhythm of body temperature of free-living Arabian oryx (Oryx leucoryx): does water limitation drive heterothermy?

PubMed

Hetem, Robyn Sheila; Strauss, Willem Maartin; Fick, Linda Gayle; Maloney, Shane Kevin; Meyer, Leith Carl Rodney; Shobrak, Mohammed; Fuller, Andrea; Mitchell, Duncan

2010-10-01

Heterothermy, a variability in body temperature beyond the limits of homeothermy, has been advanced as a key adaptation of Arabian oryx (Oryx leucoryx) to their arid-zone life. We measured body temperature using implanted data loggers, for a 1-year period, in five oryx free-living in the deserts of Saudi Arabia. As predicted for adaptive heterothermy, during hot months compared to cooler months, not only were maximum daily body temperatures higher (41.1 ± 0.3 vs. 39.7 ± 0.1°C, P = 0.0002) but minimum daily body temperatures also were lower (36.1 ± 0.3 vs. 36.8 ± 0.2°C, P = 0.04), resulting in a larger daily amplitude of the body temperature rhythm (5.0 ± 0.5 vs. 2.9 ± 0.2°C, P = 0.0007), while mean daily body temperature rose by only 0.4°C. The maximum daily amplitude of the body temperature rhythm reached 7.7°C for two of our oryx during the hot-dry period, the largest amplitude ever recorded for a large mammal. Body temperature variability was influenced not only by ambient temperature but also water availability, with oryx displaying larger daily amplitudes of the body temperature rhythm during warm-dry months compared to warm-wet months (3.6 ± 0.6 vs. 2.3 ± 0.3°C, P = 0.005), even though ambient temperatures were the same. Free-living Arabian oryx therefore employ heterothermy greater than that recorded in any other large mammal, but water limitation, rather than high ambient temperature, seems to be the primary driver of this heterothermy.

Weekly Oscillation of Daily Climatology of Air Temperature: Implication for Anthropogenic Attribution

NASA Astrophysics Data System (ADS)

Jiang, S.; Wang, K.

2016-12-01

During national holiday and weekend, human activity and anthropogenic emission are expected to be much less than those during workday. Therefore, the contrast of environmental factors (i.e., air temperature and air quality) between national holiday (or weekend) and workday has been attributed to anthropogenic impact. For example, daily maximum (Tmax), minimum (Tmin) and mean (Tmean) air temperatures during the Chinese Spring Festival holiday were found to be 0. 6°C less than those of nearby workdays. We evaluated the contrasts using daily meteorological observations collected at 2479 stations in China from 1961 to 2015. The contrasts were evaluated with two methods. The first directly compared air temperatures between Chinese Spring Festival holiday and nearby workdays. The second first composited a daily climatology of air temperatures centered on the first day of Chinese Spring Festival holiday, and the seasonal cycles of air temperatures were then removed using polynomial regressions. The average of the derived daily deviation of air temperatures can be regarded as anthropogenic impact of Chinese Spring Festival holiday. We found that these two methods obtained nearly the same results. However, we found that the so-called anthropogenic impact during Chinese Spring Festival was not unique because the daily deviations of air temperatures had obvious weekly oscillations. The daily deviations of air temperature had periods of 7 days and 9 days, which explain 60% of the variance of daily deviations of Tmax, Tmin, and Tmean. These results indicate that the so-called anthropogenic impacts are primarily caused by natural variability, i.e., weekly oscillations of the air temperatures. This study also has great implication for the studies on weekend effect of the environmental factors.

Estimation of daily maximum and minimum air temperatures in urban landscapes using MODIS time series satellite data

NASA Astrophysics Data System (ADS)

Yoo, Cheolhee; Im, Jungho; Park, Seonyoung; Quackenbush, Lindi J.

2018-03-01

Urban air temperature is considered a significant variable for a variety of urban issues, and analyzing the spatial patterns of air temperature is important for urban planning and management. However, insufficient weather stations limit accurate spatial representation of temperature within a heterogeneous city. This study used a random forest machine learning approach to estimate daily maximum and minimum air temperatures (Tmax and Tmin) for two megacities with different climate characteristics: Los Angeles, USA, and Seoul, South Korea. This study used eight time-series land surface temperature (LST) data from Moderate Resolution Imaging Spectroradiometer (MODIS), with seven auxiliary variables: elevation, solar radiation, normalized difference vegetation index, latitude, longitude, aspect, and the percentage of impervious area. We found different relationships between the eight time-series LSTs with Tmax/Tmin for the two cities, and designed eight schemes with different input LST variables. The schemes were evaluated using the coefficient of determination (R2) and Root Mean Square Error (RMSE) from 10-fold cross-validation. The best schemes produced R2 of 0.850 and 0.777 and RMSE of 1.7 °C and 1.2 °C for Tmax and Tmin in Los Angeles, and R2 of 0.728 and 0.767 and RMSE of 1.1 °C and 1.2 °C for Tmax and Tmin in Seoul, respectively. LSTs obtained the day before were crucial for estimating daily urban air temperature. Estimated air temperature patterns showed that Tmax was highly dependent on the geographic factors (e.g., sea breeze, mountains) of the two cities, while Tmin showed marginally distinct temperature differences between built-up and vegetated areas in the two cities.

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.

Physiological responses to known intake of ergot alkaloids by steers at environmental temperatures within or greater than their thermoneutral zone

NASA Astrophysics Data System (ADS)

Eisemann, Joan; Huntington, Gerald; Williamson, Megan; Hanna, Michelle; Poore, Matthew

2014-11-01

Two studies separated effects of dietary ergot alkaloids from effects of feed intake or ambient temperature on respiration rate (RR), heart rate (HR), surface temperature (ST), rectal temperature (RT), blood pressure (BP), serum hormone, and plasma metabolite concentrations in beef steers. The balanced, single reversal design for each experiment used 8 beef steers fed tall fescue seed (2.5 g/kg body weight, (BW)) with (E+) or without (E-) ergot alkaloids as part of a 60:40 switchgrass hay: supplement diet. Periods were 35 d with 21 d of preliminary phase and 14 d of feeding fescue seed once daily. Measures of dependent variables were collected on d 20, 25, 29 and 35 of each period at 0730 (before feeding), 1230 and 1530. In Expt 1 steers weighed 286 kg, gained 0.61 kg BW/d, E+ supplied 2.72 mg ergot alkaloids including 1.60 mg ergovaline per steer daily, and mean minimum and maximum daily ambient temperatures were 23.6 and 32.3°C. In Expt 2 steers weighed 348 kg, gained 1.03 kg BW/d, E+ supplied 3.06 mg ergot alkaloids including 2.00 mg ergovaline daily, and mean minimum and maximum daily ambient temperatures were 11.9 and 17.4°C. Dry matter intake was not affected by fescue seed treatment (P < 0.20) in either experiment. In both experiments, E+ reduced HR (P < 0.01) and increased insulin (P = 0.07). Systolic BP minus diastolic BP decreased (P< 0.05) for E+ in both experiments, due to increased diastolic BP in Expt 1 (P < 0.03) and decreased systolic BP in Expt 2 (P < 0.07). In Expt 1, above the thermoneutral zone, E+ increased (P< 0.05) RR, RT and left side ST in comparison to E-, but in Expt 2, within the thermoneutral zone, E+ and E- did not differ (P < 0.18). Ergot alkaloids from fescue seed affect the cardiovascular system of steers separately from effects of feed intake or environmental temperature. Ergot alkaloids interact with ambient temperatures above the steers’ thermoneutral zone to exacerbate the symptoms of hyperthermic stress.

Diurnal variation of intraoral pH and temperature.

PubMed

Choi, Jung Eun; Lyons, Karl M; Kieser, Jules A; Waddell, Neil J

2017-01-01

The aim of this study was to measure continuously the intraoral pH and temperature of healthy individuals to investigate their diurnal variations. Seventeen participants (mean age, 31±9 years) wore a custom-made intraoral appliance fitted with a pH probe and thermocouple for two sets of 24 h, while carrying out normal daily activities including sleep. The continuous changes in intraoral pH and temperature were captured using a sensor placed on the palatal aspect of the upper central incisors. The collected data were categorised into different status (awake and sleep) and periods (morning, afternoon, evening and night). Both quantitative and qualitative analyses were conducted. The intraoral pH change was found to show a distinctive daily rhythm, showing a 12-h interval between maximum (7.73) and minimum (6.6) pH values. The maximum and minimum values were found to repeat after 24 h. The mean pH over 48 h (two sets of 24 h) was found to be 7.27 (±0.74). There was significant difference found in pH when subjects were awake and asleep and different periods during the day ( P <0.001). The mean intraoral temperature was 33.99 °C (±4.9), with less distinctive daily rhythm compared with pH. There was a significant difference found in temperature depending on the time of the day, except between morning and afternoon ( P =0.78). Our results showed that there is a distinctive daily, circadian-like pattern in intraoral pH variation over a 24-h period, which has been considered as one of the risk factors in sleep-related dental diseases.

Spatial and temporal variation in daily temperature indices in summer and winter seasons over India (1969-2012)

NASA Astrophysics Data System (ADS)

Kumar, Naresh; Jaswal, A. K.; Mohapatra, M.; Kore, P. A.

2017-08-01

Spatial and temporal variations in summer and winter extreme temperature indices are studied by using daily maximum and minimum temperatures data from 227 surface meteorological stations well distributed over India for the period 1969-2012. For this purpose, time series for six extreme temperature indices namely, hot days (HD), very hot days (VHD), extremely hot days (EHD), cold nights (CN), very cold nights (VCN), and extremely cold nights (ECN) are calculated for all the stations. In addition, time series for mean extreme temperature indices of summer and winter seasons are also analyzed. Study reveals high variability in spatial distribution of threshold temperatures of extreme temperature indices over the country. In general, increasing trends are observed in summer hot days indices and decreasing trends in winter cold night indices over most parts of the country. The results obtained in this study indicate warming in summer maximum and winter minimum temperatures over India. Averaged over India, trends in summer hot days indices HD, VHD, and EHD are significantly increasing (+1.0, +0.64, and +0.32 days/decade, respectively) and winter cold night indices CN, VCN, and ECN are significantly decreasing (-0.93, -0.47, and -0.15 days/decade, respectively). Also, it is observed that the impact of extreme temperature is higher along the west coast for summer and east coast for winter.

Possible future changes in South East Australian frost frequency: an inter-comparison of statistical downscaling approaches

NASA Astrophysics Data System (ADS)

Crimp, Steven; Jin, Huidong; Kokic, Philip; Bakar, Shuvo; Nicholls, Neville

2018-04-01

Anthropogenic climate change has already been shown to effect the frequency, intensity, spatial extent, duration and seasonality of extreme climate events. Understanding these changes is an important step in determining exposure, vulnerability and focus for adaptation. In an attempt to support adaptation decision-making we have examined statistical modelling techniques to improve the representation of global climate model (GCM) derived projections of minimum temperature extremes (frosts) in Australia. We examine the spatial changes in minimum temperature extreme metrics (e.g. monthly and seasonal frost frequency etc.), for a region exhibiting the strongest station trends in Australia, and compare these changes with minimum temperature extreme metrics derived from 10 GCMs, from the Coupled Model Inter-comparison Project Phase 5 (CMIP 5) datasets, and via statistical downscaling. We compare the observed trends with those derived from the "raw" GCM minimum temperature data as well as examine whether quantile matching (QM) or spatio-temporal (spTimerQM) modelling with Quantile Matching can be used to improve the correlation between observed and simulated extreme minimum temperatures. We demonstrate, that the spTimerQM modelling approach provides correlations with observed daily minimum temperatures for the period August to November of 0.22. This represents an almost fourfold improvement over either the "raw" GCM or QM results. The spTimerQM modelling approach also improves correlations with observed monthly frost frequency statistics to 0.84 as opposed to 0.37 and 0.81 for the "raw" GCM and QM results respectively. We apply the spatio-temporal model to examine future extreme minimum temperature projections for the period 2016 to 2048. The spTimerQM modelling results suggest the persistence of current levels of frost risk out to 2030, with the evidence of continuing decadal variation.

High-Resolution Dynamical Downscaling Ensemble Projections of Future Extreme Temperature Distributions for the United States

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

Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.

The aim of this study is to examine projections of extreme temperatures over the continental United States (CONUS) for the 21st century using an ensemble of high spatial resolution dynamically downscaled model simulations with different boundary conditions. The downscaling uses the Weather Research and Forecast model at a spatial resolution of 12 km along with outputs from three different Coupled Model Intercomparison Project Phase 5 global climate models that provide boundary con- ditions under two different future greenhouse gas (GHG) concentration trajectories. The results from two decadal-length time slices (2045–2054 and 2085–2094) are compared with a historical decade (1995–2004). Probabilitymore » density functions of daily maximum/minimum temperatures are analyzed over seven climatologically cohesive regions of the CONUS. The impacts of different boundary conditions as well as future GHG concentrations on extreme events such as heat waves and days with temperature higher than 95°F are also investigated. The results show that the intensity of extreme warm temperature in future summer is significantly increased, while the frequency of extreme cold temperature in future winter decreases. The distribution of summer daily maximum temperature experiences a significant warm-side shift and increased variability, while the distribution of winter daily minimum temperature is projected to have a less significant warm-side shift with decreased variability. Finally, using "business-as-usual" scenario, 5-day heat waves are projected to occur at least 5–10 times per year in most CONUS and ≥ 95°F days will increase by 1–2 months by the end of the century.« less

The impact of reforestation in the northeast United States on precipitation and surface temperature

NASA Astrophysics Data System (ADS)

Clark, Allyson

Since the 1920s, forest coverage in the northeastern United States has recovered from disease, clearing for agricultural and urban development, and the demands of the timber industry. Such a dramatic change in ground cover can influence heat and moisture fluxes to the atmosphere, as measured in altered landscapes in Australia, Israel, and the Amazon. In this study, the impacts of recent reforestation in the northeastern United States on summertime precipitation and surface temperature were quantified by comparing average modern values to 1950s values. Weak positive (negative) relationships between reforestation and average monthly precipitation and daily minimum temperatures (average daily maximum surface temperature) were found. There was no relationship between reforestation and average surface temperature. Results of the observational analysis were compared with results obtained from reforestation scenarios simulated with the BUGS5 global climate model. The single difference between the model runs was the amount of forest coverage in the northeast United States; three levels of forest were defined - a grassland state, with 0% forest coverage, a completely forested state, with approximately 100% forest coverage, and a control state, with forest coverage closely resembling modern forest coverage. The three simulations were compared, and had larger magnitude average changes in precipitation and in all temperature variables. The difference in magnitudes between the model simulations observations was much larger than the difference in the amount of reforestation in each case. Additionally, unlike in observations, a negative relationship was found between average daily minimum temperature and amount of forest coverage, implying that additional factors influence temperature and precipitation in the real world that are not accounted for in the model.

High-Resolution Dynamical Downscaling Ensemble Projections of Future Extreme Temperature Distributions for the United States

DOE PAGES

Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.; ...

2017-11-20

The aim of this study is to examine projections of extreme temperatures over the continental United States (CONUS) for the 21st century using an ensemble of high spatial resolution dynamically downscaled model simulations with different boundary conditions. The downscaling uses the Weather Research and Forecast model at a spatial resolution of 12 km along with outputs from three different Coupled Model Intercomparison Project Phase 5 global climate models that provide boundary con- ditions under two different future greenhouse gas (GHG) concentration trajectories. The results from two decadal-length time slices (2045–2054 and 2085–2094) are compared with a historical decade (1995–2004). Probabilitymore » density functions of daily maximum/minimum temperatures are analyzed over seven climatologically cohesive regions of the CONUS. The impacts of different boundary conditions as well as future GHG concentrations on extreme events such as heat waves and days with temperature higher than 95°F are also investigated. The results show that the intensity of extreme warm temperature in future summer is significantly increased, while the frequency of extreme cold temperature in future winter decreases. The distribution of summer daily maximum temperature experiences a significant warm-side shift and increased variability, while the distribution of winter daily minimum temperature is projected to have a less significant warm-side shift with decreased variability. Finally, using "business-as-usual" scenario, 5-day heat waves are projected to occur at least 5–10 times per year in most CONUS and ≥ 95°F days will increase by 1–2 months by the end of the century.« less

Association between summer temperature and body weight in Japanese adolescents and children: An ecological analysis.

PubMed

Yokoya, Masana; Higuchi, Yukito

2016-11-01

Several experimental studies reported evidence of a negative energy balance at higher temperatures. However, corresponding weight loss has not been noted in clinical practice. This study investigated the geographical association between outdoor temperature and body weight in Japanese adolescents and children. An ecological analysis was conducted using prefecture-level data on the mean body weight of Japanese adolescents and children over a 25-year period and Japanese mesh (regional) climatic data on the mean annual temperature, mean daily maximum temperature in August, and mean daily minimum temperature in January were also analyzed. Correlation analysis uncovered a stronger association between weight and the mean daily maximum temperature in August than with other climatic variables. Moreover, multiple regression analysis indicated that height and the mean daily maximum temperature in August were statistically significant predictors of weight. This suggests that geographical differences in weight in Japanese adolescents and children can be explained by the complementary relationship between height-associated weight gain and weight loss caused by summer heat. Summer temperatures may reduce the proportion of children who are overweight and contribute to geographical differences in body weight in Japanese adolescents and children. Am. J. Hum. Biol. 28:789-795, 2016. © 2016Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Daily torpor and hibernation in birds and mammals

PubMed Central

RUF, THOMAS; GEISER, FRITZ

2014-01-01

Many birds and mammals drastically reduce their energy expenditure during times of cold exposure, food shortage, or drought, by temporarily abandoning euthermia, i.e., the maintenance of high body temperatures. Traditionally, two different types of heterothermy, i.e., hypometabolic states associated with low body temperatures (torpor), have been distinguished: Daily torpor, which lasts less than 24 h and is accompanied by continued foraging, versus hibernation, with torpor bouts lasting consecutive days to several weeks in animals that usually do not forage but rely on energy stores, either food caches or body energy reserves. This classification of torpor types has been challenged however, suggesting that these phenotypes may merely represent the extremes in a continuum of traits. Here, we investigate whether variables of torpor in 214 species, 43 birds and 171 mammals form a continuum or a bimodal distribution. We use Gaussian-mixture cluster analysis as well as phylogenetically informed regressions to quantitatively assess the distinction between hibernation and daily torpor and to evaluate the impact of body mass and geographical distribution of species on torpor traits. Cluster analysis clearly confirmed the classical distinction between daily torpor and hibernation. Overall, heterothermic endotherms are small on average, but hibernators are significantly heavier than daily heterotherms and also are distributed at higher average latitudes (~35°) than daily heterotherms (~25°). Variables of torpor for an average 30-g heterotherm differed significantly between daily heterotherms and hibernators. Average maximum torpor bout duration was >30-fold longer, and mean torpor bout duration >25-fold longer in hibernators. Mean minimum body temperature differed by ~13°C, and the mean minimum torpor metabolic rate was ~35% of the BMR in daily heterotherms but only 6% of basal metabolic rate in hibernators. Consequently, our analysis strongly supports the view that hibernators and daily heterotherms are functionally distinct groups that probably have been subject to disruptive selection. Arguably, the primary physiological difference between daily torpor and hibernation, which leads to a variety of derived further distinct characteristics, is the temporal control of entry into and arousal from torpor, which is governed by the circadian clock in daily heterotherms, but apparently not in hibernators. PMID:25123049

Development of daily temperature scenarios and their impact on paddy crop evapotranspiration in Kangsabati command area

NASA Astrophysics Data System (ADS)

Dhage, P. M.; Raghuwanshi, N. S.; Singh, R.; Mishra, A.

2017-05-01

Production of the principal paddy crop in West Bengal state of India is vulnerable to climate change due to limited water resources and strong dependence on surface irrigation. Therefore, assessment of impact of temperature scenarios on crop evapotranspiration (ETc) is essential for irrigation management in Kangsabati command (West Bengal). In the present study, impact of the projected temperatures on ETc was studied under climate change scenarios. Further, the performance of the bias correction and spatial downscaling (BCSD) technique was compared with the two well-known downscaling techniques, namely, multiple linear regression (MLR) and Kernel regression (KR), for the projections of daily maximum and minimum air temperatures for four stations, namely, Purulia, Bankura, Jhargram, and Kharagpur. In National Centers for Environmental Prediction (NCEP) and General Circulation Model (GCM), 14 predictors were used in MLR and KR techniques, whereas maximum and minimum surface air temperature predictor of CanESM2 GCM was used in BCSD technique. The comparison results indicated that the performance of the BCSD technique was better than the MLR and KR techniques. Therefore, the BCSD technique was used to project the future temperatures of study locations with three Representative Concentration Pathway (RCP) scenarios for the period of 2006-2100. The warming tendencies of maximum and minimum temperatures over the Kangsabati command area were projected as 0.013 and 0.014 °C/year under RCP 2.6, 0.015 and 0.023 °C/year under RCP 4.5, and 0.056 and 0.061 °C/year under RCP 8.5 for 2011-2100 period, respectively. As a result, kharif (monsoon) crop evapotranspiration demand of Kangsabati reservoir command (project area) will increase by approximately 10, 8, and 18 % over historical demand under RCP 2.6, 4.5, and 8.5 scenarios, respectively.

Modelling the occurrence of heat waves in maximum and minimum temperatures over Spain and projections for the period 2031-60

NASA Astrophysics Data System (ADS)

Abaurrea, J.; Asín, J.; Cebrián, A. C.

2018-02-01

The occurrence of extreme heat events in maximum and minimum daily temperatures is modelled using a non-homogeneous common Poisson shock process. It is applied to five Spanish locations, representative of the most common climates over the Iberian Peninsula. The model is based on an excess over threshold approach and distinguishes three types of extreme events: only in maximum temperature, only in minimum temperature and in both of them (simultaneous events). It takes into account the dependence between the occurrence of extreme events in both temperatures and its parameters are expressed as functions of time and temperature related covariates. The fitted models allow us to characterize the occurrence of extreme heat events and to compare their evolution in the different climates during the observed period. This model is also a useful tool for obtaining local projections of the occurrence rate of extreme heat events under climate change conditions, using the future downscaled temperature trajectories generated by Earth System Models. The projections for 2031-60 under scenarios RCP4.5, RCP6.0 and RCP8.5 are obtained and analysed using the trajectories from four earth system models which have successfully passed a preliminary control analysis. Different graphical tools and summary measures of the projected daily intensities are used to quantify the climate change on a local scale. A high increase in the occurrence of extreme heat events, mainly in July and August, is projected in all the locations, all types of event and in the three scenarios, although in 2051-60 the increase is higher under RCP8.5. However, relevant differences are found between the evolution in the different climates and the types of event, with a specially high increase in the simultaneous ones.

How changes of climate extremes affect summer and winter crop yields and water productivity in the southeast USA

NASA Astrophysics Data System (ADS)

Tian, D.; Cammarano, D.

2017-12-01

Modeling changes of crop production at regional scale is important to make adaptation measures for sustainably food supply under global change. In this study, we explore how changing climate extremes in the 20th and 21st century affect maize (summer crop) and wheat (winter crop) yields in an agriculturally important region: the southeast United States. We analyze historical (1950-1999) and projected (2006-2055) precipitation and temperature extremes by calculating the changes of 18 climate extreme indices using the statistically downscaled CMIP5 data from 10 general circulation models (GCMs). To evaluate how these climate extremes affect maize and wheat yields, historical baseline and projected maize and wheat yields under RCP4.5 and RCP8.5 scenarios are simulated using the DSSAT-CERES maize and wheat models driven by the same downscaled GCMs data. All of the changes are examined at 110 locations over the study region. The results show that most of the precipitation extreme indices do not have notable change; mean precipitation, precipitation intensity, and maximum 1-day precipitation are generally increased; the number of rainy days is decreased. The temperature extreme indices mostly showed increased values on mean temperature, number of high temperature days, diurnal temperature range, consecutive high temperature days, maximum daily maximum temperature, and minimum daily minimum temperature; the number of low temperature days and number of consecutive low temperature days are decreased. The conditional probabilistic relationships between changes in crop yields and changes in extreme indices suggested different responses of crop yields to climate extremes during sowing to anthesis and anthesis to maturity periods. Wheat yields and crop water productivity for wheat are increased due to an increased CO2 concentration and minimum temperature; evapotranspiration, maize yields, and crop water productivity for wheat are decreased owing to the increased temperature extremes. We found the effects of precipitation changes on both yields are relatively uncertain.

Intra-Seasonal Variability of Climate and Peasant Perception of Climate Change in Massili Basin in Burkina Faso.

NASA Astrophysics Data System (ADS)

Kabore Bontogho, P. E.

2014-12-01

Knowledge of climate variability is relevant and challenging for farmers, decision makers and population in general. Ninety percent of Burkina Faso active population is engaged in agriculture and livestock, which accounts for 39% of gross domestic product. Located between the coordinates 1o15'-1o55' West and 12o17'- 12o50'North, Massili basin includes Ouagadougou the capital and has four dams, of which the most important dam, Loumbila is used for the capital water supply and irrigation. A change of climate may affect the water resources most likely limit the access to safe water. In order to characterize Massili basin climate variability, daily temperature and precipitation over 1960 to 2012 was analyzed using long-term records from the Ouagadougou synoptic station. By applying R-climdex and instat tools, indices were calculated by a consistent approach recommended by the World Meteorological Organization Expert Team on Climate Change Detection and Indices. The precipitation parameters computed were: the maximum 5-day precipitationamount; the number of days with precipitation amount ≥50 mm ; the maximum precipitation amount in consecutive wet days with RR≥ 1mm; the consecutives dry days;the extremely wet days ; the extreme precipitation in one day, the total precipitation in wet days; the temperature indices computed were : the maximum of the maximum daily temperature, the minimum of daily maximum temperature,the minimum of daily minimum temperature,the cold spell duration indices and the warm spell duration indicator. Results show a slight increase of the maximum 5-day precipitation, maximum precipitation amount in consecutive wet days with RR≥1mm, the onset delayed and the cessation is earlier meaning that the rainfall period is shortening. The total precipitationwas decreased in the basin but there is a slight increase in the occurrence of extremely wet days. CSDI is decreasing while warm spell duration indices are increasing. In parallel of the data analysis, a survey of 200 peasant spread within 20 villages was done to assess their perception on climate change. Farmers perception corroborate with the above results as their majority describes climate change as decrease of rainfall (79%) and increase of temperature (99%). In addition, all farmers agreed that more floods are occurring.

The use of NOAA AVHRR data for assessment of the urban heat sland effect

USGS Publications Warehouse

Gallo, K.P.; McNab, A. L.; Karl, Thomas R.; Brown, Jesslyn F.; Hood, J. J.; Tarpley, J.D.

1993-01-01

A vegetation index and a radiative surface temperature were derived from satellite data acquired at approximately 1330 LST for each of 37 cities and for their respective nearby rural regions from 28 June through 8 August 1991. Urban–rural differences for the vegetation index and the surface temperatures were computed and then compared to observed urban–rural differences in minimum air temperatures. The purpose of these comparisons was to evaluate the use of satellite data to assess the influence of the urban environment on observed minimum air temperatures (the urban heat island effect). The temporal consistency of the data, from daily data to weekly, biweekly, and monthly intervals, was also evaluated. The satellite-derived normalized difference (ND) vegetation-index data, sampled over urban and rural regions composed of a variety of land surface environments, were linearly related to the difference in observed urban and rural minimum temperatures. The relationship between the ND index and observed differences in minimum temperature was improved when analyses were restricted by elevation differences between the sample locations and when biweekly or monthly intervals were utilized. The difference in the ND index between urban and rural regions appears to be an indicator of the difference in surface properties (evaporation and heat storage capacity) between the two environments that are responsible for differences in urban and rural minimum temperatures. The urban and rural differences in the ND index explain a greater amount of the variation observed in minimum temperature differences than past analyses that utilized urban population data. The use of satellite data may contribute to a globally consistent method for analysis of urban heat island bias.

Development and Evaluation of High-Resolution Climate Simulations Over the Mountainous Northeastern United States

NASA Technical Reports Server (NTRS)

Winter, Jonathan M.; Beckage, Brian; Bucini, Gabriela; Horton, Radley M.; Clemins, Patrick J.

2016-01-01

The mountain regions of the northeastern United States are a critical socioeconomic resource for Vermont, New York State, New Hampshire, Maine, and southern Quebec. While global climate models (GCMs) are important tools for climate change risk assessment at regional scales, even the increased spatial resolution of statistically downscaled GCMs (commonly approximately 1/ 8 deg) is not sufficient for hydrologic, ecologic, and land-use modeling of small watersheds within the mountainous Northeast. To address this limitation, an ensemble of topographically downscaled, high-resolution (30"), daily 2-m maximum air temperature; 2-m minimum air temperature; and precipitation simulations are developed for the mountainous Northeast by applying an additional level of downscaling to intermediately downscaled (1/ 8 deg) data using high-resolution topography and station observations. First, observed relationships between 2-m air temperature and elevation and between precipitation and elevation are derived. Then, these relationships are combined with spatial interpolation to enhance the resolution of intermediately downscaled GCM simulations. The resulting topographically downscaled dataset is analyzed for its ability to reproduce station observations. Topographic downscaling adds value to intermediately downscaled maximum and minimum 2-m air temperature at high-elevation stations, as well as moderately improves domain-averaged maximum and minimum 2-m air temperature. Topographic downscaling also improves mean precipitation but not daily probability distributions of precipitation. Overall, the utility of topographic downscaling is dependent on the initial bias of the intermediately downscaled product and the magnitude of the elevation adjustment. As the initial bias or elevation adjustment increases, more value is added to the topographically downscaled product.

Contributions of radiative factors to enhanced dryland warming over East Asia

NASA Astrophysics Data System (ADS)

Zhang, Yanting; Guan, Xiaodan; Yu, Haipeng; Xie, Yongkun; Jin, Hongchun

2017-08-01

Enhanced near-surface atmospheric warming has occurred over East Asia in recent decades, especially in drylands. Although local factors have been confirmed to provide considerable contributions to this warming, such factors have not been sufficiently analyzed. In this study, we extracted the radiatively forced temperature (RFT) associated with the built-up greenhouse gases, aerosol emission, and various other radiative forcing over East Asia and found a close relationship between RFT and CO2. In addition, using climate model experiments, we explored the responses of temperature changes to black carbon (BC), CO2, and SO4 and found that the enhanced dryland warming induced by CO2 had the largest magnitude and was strengthened by the warming effect of BC. Moreover, the sensitivity of daily maximum and minimum temperature changes to BC, CO2, and SO4 was examined. It showed asymmetric responses of daily maximum and minimum temperature to radiative factors, which led to an obvious change of diurnal temperature range (DTR), especially in drylands. The DTR's response to CO2 is the most significant. Therefore, CO2 not only plays a dominant role in enhanced warming but also greatly affects the decrease of DTR in drylands. However, the mechanisms of these radiative factors' effects in the process of DTR change are not clear and require more investigation.

Inter-annual Variability of Temperature and Extreme Heat Events during the Nairobi Warm Season

NASA Astrophysics Data System (ADS)

Scott, A.; Misiani, H. O.; Zaitchik, B. F.; Ouma, G. O.; Anyah, R. O.; Jordan, A.

2016-12-01

Extreme heat events significantly stress all organisms in the ecosystem, and are likely to be amplified in peri-urban and urban areas. Understanding the variability and drivers behind these events is key to generating early warnings, yet in Equatorial East Africa, this information is currently unavailable. This study uses daily maximum and minimum temperature records from weather stations within Nairobi and its surroundings to characterize variability in daily minimum temperatures and the number of extreme heat events. ERA-Interim reanalysis is applied to assess the drivers of these events at event and seasonal time scales. At seasonal time scales, high temperatures in Nairobi are a function of large scale climate variability associated with the Atlantic Multi-decadal Oscillation (AMO) and Global Mean Sea Surface Temperature (GMSST). Extreme heat events, however, are more strongly associated with the El Nino Southern Oscillation (ENSO). For instance, the persistence of AMO and ENSO, in particular, provide a basis for seasonal prediction of extreme heat events/days in Nairobi. It is also apparent that the temporal signal from extreme heat events in tropics differs from classic heat wave definitions developed in the mid-latitudes, which suggests that a new approach for defining these events is necessary for tropical regions.

[Response of indica rice spikelet differentiation and degeneration to air temperature and solar radiation of different sowing dates].

PubMed

Wang, Ya Liang; Zhang, Yu Ping; Xiang, Jing; Wang, Lei; Chen, Hui Zhe; Zhang, Yi Kai; Zhang, Wen Qian; Zhu, De Feng

2017-11-01

In this study, three rice varieties, including three-line hybrid indica rice Wuyou308 and Tianyouhuazhan, and inbred indica rice Huanghuazhan were used to investigate the effects of air temperature and solar radiation on rice growth duration and spikelet differentiation and degeneration. Ten sowing-date treatments were conducted in this field experiment. The results showed that the growth duration of three indica rice varieties were more sensitive to air temperature than to day-length. With average temperature increase of 1 ℃, panicle initiation advanced 1.5 days, but the panicle growth duration had no significant correlation with the temperature and day-length. The number of spikelets and differentiated spikelets revealed significant differences among different sowing dates. Increases in average temperature, maximum temperature, minimum temperature, effective accumulated temperature, temperature gap and the solar radiation benefited dry matter accumulation and spikelet differentiation of all varieties. With increases of effective accumulated temperature, diurnal temperature gap and solar radiation by 50 ℃, 1 ℃, 50 MJ·m -2 during panicle initiation stage, the number of differentiated spikelets increased 10.5, 14.3, 17.1 respectively. The rate of degenerated spikelets had a quadratic correlation with air temperature, extreme high and low temperature aggravated spikelets degeneration, and low temperature stress made worse effect than high temperature stress. The rate of spikelet degeneration dramatically rose with the temperature falling below the critical temperature, the critical effective accumulated temperature, daily average temperature, daily maximum temperature and minimum temperature during panicle initiation were 550-600 ℃, 24.0-26.0 ℃, 32.0-34.0 ℃, 21.0-23.0 ℃, respectively. In practice, the natural condition of appropriate high temperature, large diurnal temperature gap and strong solar radiation were conducive to spikelet differentiation, and hindered the spikelet degeneration.

Short-term load forecasting of power system

NASA Astrophysics Data System (ADS)

Xu, Xiaobin

2017-05-01

In order to ensure the scientific nature of optimization about power system, it is necessary to improve the load forecasting accuracy. Power system load forecasting is based on accurate statistical data and survey data, starting from the history and current situation of electricity consumption, with a scientific method to predict the future development trend of power load and change the law of science. Short-term load forecasting is the basis of power system operation and analysis, which is of great significance to unit combination, economic dispatch and safety check. Therefore, the load forecasting of the power system is explained in detail in this paper. First, we use the data from 2012 to 2014 to establish the partial least squares model to regression analysis the relationship between daily maximum load, daily minimum load, daily average load and each meteorological factor, and select the highest peak by observing the regression coefficient histogram Day maximum temperature, daily minimum temperature and daily average temperature as the meteorological factors to improve the accuracy of load forecasting indicators. Secondly, in the case of uncertain climate impact, we use the time series model to predict the load data for 2015, respectively, the 2009-2014 load data were sorted out, through the previous six years of the data to forecast the data for this time in 2015. The criterion for the accuracy of the prediction is the average of the standard deviations for the prediction results and average load for the previous six years. Finally, considering the climate effect, we use the BP neural network model to predict the data in 2015, and optimize the forecast results on the basis of the time series model.

Time trends in minimum mortality temperatures in Castile-La Mancha (Central Spain): 1975-2003

NASA Astrophysics Data System (ADS)

Miron, Isidro J.; Criado-Alvarez, Juan José; Diaz, Julio; Linares, Cristina; Mayoral, Sheila; Montero, Juan Carlos

2008-03-01

The relationship between air temperature and human mortality is described as non-linear, with mortality tending to rise in response to increasingly hot or cold ambient temperatures from a given minimum mortality or optimal comfort temperature, which varies from some areas to others according to their climatic and socio-demographic characteristics. Changes in these characteristics within any specific region could modify this relationship. This study sought to examine the time trend in the maximum temperature of minimum organic-cause mortality in Castile-La Mancha, from 1975 to 2003. The analysis was performed by using daily series of maximum temperatures and organic-cause mortality rates grouped into three decades (1975-1984, 1985-1994, 1995-2003) to compare confidence intervals ( p < 0.05) obtained by estimating the 10-yearly mortality rates corresponding to the maximum temperatures of minimum mortality calculated for each decade. Temporal variations in the effects of cold and heat on mortality were ascertained by means of ARIMA models (Box-Jenkins) and cross-correlation functions (CCF) at seven lags. We observed a significant decrease in comfort temperature (from 34.2°C to 27.8°C) between the first two decades in the Province of Toledo, along with a growing number of significant lags in the summer CFF (1, 3 and 5, respectively). The fall in comfort temperature is attributable to the increase in the effects of heat on mortality, due, in all likelihood, to the percentage increase in the elderly population.

Citizen science: Plant and insect phenology with regards to degree-days

USDA-ARS?s Scientific Manuscript database

Daily minimum and maximum temperatures collected from grower-collaborators were used to calculate site specific degree-days. Using our new understanding of Sparganothis phenology, plant phenology were examined relative to moth phenology, allowing us to predict moth development in parallel with plant...

THE EFFECT OF TEMPERATURE AND HUMIDITY ON THE TOBACCO POWDERY MILDEW FUNGUS

DTIC Science & Technology

The influence of temperature on the germination of conidia and on the infection of tobacco by powdery mildew was determined. For the former the...The existence of a very close correlation between the occurrence of powdery mildew in certain tobacco areas and the average daily maximum-minimum...temperatures prevailing in those areas could be shown. It was found, for example, that powdery mildew did not occur in areas in which the prevailing

Early meteorological results from the viking 2 lander.

PubMed

Hess, S L; Henry, R M; Leovy, C B; Mitchell, J L; Ryan, J A; Tillman, J E

1976-12-11

Early results from the meteorological instruments on the Viking 2 lander are presented. As on lander 1, the daily patterns of temperature, wind, and pressure have been highly repetitive during the early summer period. The average daily maximum temperature was 241 degrees K and the diurnal minimum was 191 degrees K. The wind has a vector mean of 0.7 meter per second from the southeast with a diurnal amplitude of 3 meters per second. Pressure exhibits both diurnal and semidiurnal oscillations, although of substantially smaller amplitude than those of lander 1. Departures from the repetitive diurnal patterns begin to appear on sol 37.

Estimating wheat and maize daily evapotranspiration using artificial neural network

NASA Astrophysics Data System (ADS)

Abrishami, Nazanin; Sepaskhah, Ali Reza; Shahrokhnia, Mohammad Hossein

2018-02-01

In this research, artificial neural network (ANN) is used for estimating wheat and maize daily standard evapotranspiration. Ten ANN models with different structures were designed for each crop. Daily climatic data [maximum temperature (T max), minimum temperature (T min), average temperature (T ave), maximum relative humidity (RHmax), minimum relative humidity (RHmin), average relative humidity (RHave), wind speed (U 2), sunshine hours (n), net radiation (Rn)], leaf area index (LAI), and plant height (h) were used as inputs. For five structures of ten, the evapotranspiration (ETC) values calculated by ETC = ET0 × K C equation (ET0 from Penman-Monteith equation and K C from FAO-56, ANNC) were used as outputs, and for the other five structures, the ETC values measured by weighing lysimeter (ANNM) were used as outputs. In all structures, a feed forward multiple-layer network with one or two hidden layers and sigmoid transfer function and BR or LM training algorithm was used. Favorite network was selected based on various statistical criteria. The results showed the suitable capability and acceptable accuracy of ANNs, particularly those having two hidden layers in their structure in estimating the daily evapotranspiration. Best model for estimation of maize daily evapotranspiration is «M»ANN1 C (8-4-2-1), with T max, T min, RHmax, RHmin, U 2, n, LAI, and h as input data and LM training rule and its statistical parameters (NRMSE, d, and R2) are 0.178, 0.980, and 0.982, respectively. Best model for estimation of wheat daily evapotranspiration is «W»ANN5 C (5-2-3-1), with T max, T min, Rn, LAI, and h as input data and LM training rule, its statistical parameters (NRMSE, d, and R 2) are 0.108, 0.987, and 0.981 respectively. In addition, if the calculated ETC used as the output of the network for both wheat and maize, higher accurate estimation was obtained. Therefore, ANN is suitable method for estimating evapotranspiration of wheat and maize.

Association of Day Length and Weather Conditions with Physical Activity Levels in Older Community Dwelling People

PubMed Central

Witham, Miles D.; Donnan, Peter T.; Vadiveloo, Thenmalar; Sniehotta, Falko F.; Crombie, Iain K.; Feng, Zhiqiang; McMurdo, Marion E. T.

2014-01-01

Background Weather is a potentially important determinant of physical activity. Little work has been done examining the relationship between weather and physical activity, and potential modifiers of any relationship in older people. We therefore examined the relationship between weather and physical activity in a cohort of older community-dwelling people. Methods We analysed prospectively collected cross-sectional activity data from community-dwelling people aged 65 and over in the Physical Activity Cohort Scotland. We correlated seven day triaxial accelerometry data with daily weather data (temperature, day length, sunshine, snow, rain), and a series of potential effect modifiers were tested in mixed models: environmental variables (urban vs rural dwelling, percentage of green space), psychological variables (anxiety, depression, perceived behavioural control), social variables (number of close contacts) and health status measured using the SF-36 questionnaire. Results 547 participants, mean age 78.5 years, were included in this analysis. Higher minimum daily temperature and longer day length were associated with higher activity levels; these associations remained robust to adjustment for other significant associates of activity: age, perceived behavioural control, number of social contacts and physical function. Of the potential effect modifier variables, only urban vs rural dwelling and the SF-36 measure of social functioning enhanced the association between day length and activity; no variable modified the association between minimum temperature and activity. Conclusions In older community dwelling people, minimum temperature and day length were associated with objectively measured activity. There was little evidence for moderation of these associations through potentially modifiable health, environmental, social or psychological variables. PMID:24497925

Association of day length and weather conditions with physical activity levels in older community dwelling people.

PubMed

Witham, Miles D; Donnan, Peter T; Vadiveloo, Thenmalar; Sniehotta, Falko F; Crombie, Iain K; Feng, Zhiqiang; McMurdo, Marion E T

2014-01-01

Weather is a potentially important determinant of physical activity. Little work has been done examining the relationship between weather and physical activity, and potential modifiers of any relationship in older people. We therefore examined the relationship between weather and physical activity in a cohort of older community-dwelling people. We analysed prospectively collected cross-sectional activity data from community-dwelling people aged 65 and over in the Physical Activity Cohort Scotland. We correlated seven day triaxial accelerometry data with daily weather data (temperature, day length, sunshine, snow, rain), and a series of potential effect modifiers were tested in mixed models: environmental variables (urban vs rural dwelling, percentage of green space), psychological variables (anxiety, depression, perceived behavioural control), social variables (number of close contacts) and health status measured using the SF-36 questionnaire. 547 participants, mean age 78.5 years, were included in this analysis. Higher minimum daily temperature and longer day length were associated with higher activity levels; these associations remained robust to adjustment for other significant associates of activity: age, perceived behavioural control, number of social contacts and physical function. Of the potential effect modifier variables, only urban vs rural dwelling and the SF-36 measure of social functioning enhanced the association between day length and activity; no variable modified the association between minimum temperature and activity. In older community dwelling people, minimum temperature and day length were associated with objectively measured activity. There was little evidence for moderation of these associations through potentially modifiable health, environmental, social or psychological variables.

Spatial distribution of unidirectional trends in temperature and temperature extremes in Pakistan

NASA Astrophysics Data System (ADS)

Khan, Najeebullah; Shahid, Shamsuddin; Ismail, Tarmizi bin; Wang, Xiao-Jun

2018-06-01

Pakistan is one of the most vulnerable countries of the world to temperature extremes due to its predominant arid climate and geographic location in the fast temperature rising zone. Spatial distribution of the trends in annual and seasonal temperatures and temperature extremes over Pakistan has been assessed in this study. The gauge-based gridded daily temperature data of Berkeley Earth Surface Temperature (BEST) having a spatial resolution of 1° × 1° was used for the assessment of trends over the period 1960-2013 using modified Mann-Kendall test (MMK), which can discriminate the multi-decadal oscillatory variations from secular trends. The results show an increase in the annual average of daily maximum and minimum temperatures in 92 and 99% area of Pakistan respectively at 95% level of confidence. The annual temperature is increasing faster in southern high-temperature region compared to other parts of the country. The minimum temperature is rising faster (0.17-0.37 °C/decade) compared to maximum temperature (0.17-0.29 °C/decade) and therefore declination of diurnal temperature range (DTR) (- 0.15 to - 0.08 °C/decade) in some regions. The annual numbers of both hot and cold days are increasing in whole Pakistan except in the northern sub-Himalayan region. Heat waves are on the rise, especially in the hot Sindh plains and the Southern coastal region, while the cold waves are becoming lesser in the northern cold region. Obtained results contradict with the findings of previous studies on temperature trends, which indicate the need for reassessment of climatic trends in Pakistan using the MMK test to understand the anthropogenic impacts of climate change.

Daily torpor and hibernation in birds and mammals.

PubMed

Ruf, Thomas; Geiser, Fritz

2015-08-01

Many birds and mammals drastically reduce their energy expenditure during times of cold exposure, food shortage, or drought, by temporarily abandoning euthermia, i.e. the maintenance of high body temperatures. Traditionally, two different types of heterothermy, i.e. hypometabolic states associated with low body temperature (torpor), have been distinguished: daily torpor, which lasts less than 24 h and is accompanied by continued foraging, versus hibernation, with torpor bouts lasting consecutive days to several weeks in animals that usually do not forage but rely on energy stores, either food caches or body energy reserves. This classification of torpor types has been challenged, suggesting that these phenotypes may merely represent extremes in a continuum of traits. Here, we investigate whether variables of torpor in 214 species (43 birds and 171 mammals) form a continuum or a bimodal distribution. We use Gaussian-mixture cluster analysis as well as phylogenetically informed regressions to quantitatively assess the distinction between hibernation and daily torpor and to evaluate the impact of body mass and geographical distribution of species on torpor traits. Cluster analysis clearly confirmed the classical distinction between daily torpor and hibernation. Overall, heterothermic endotherms tend to be small; hibernators are significantly heavier than daily heterotherms and also are distributed at higher average latitudes (∼35°) than daily heterotherms (∼25°). Variables of torpor for an average 30 g heterotherm differed significantly between daily heterotherms and hibernators. Average maximum torpor bout duration was >30-fold longer, and mean torpor bout duration >25-fold longer in hibernators. Mean minimum body temperature differed by ∼13°C, and the mean minimum torpor metabolic rate was ∼35% of the basal metabolic rate (BMR) in daily heterotherms but only 6% of BMR in hibernators. Consequently, our analysis strongly supports the view that hibernators and daily heterotherms are functionally distinct groups that probably have been subject to disruptive selection. Arguably, the primary physiological difference between daily torpor and hibernation, which leads to a variety of derived further distinct characteristics, is the temporal control of entry into and arousal from torpor, which is governed by the circadian clock in daily heterotherms, but apparently not in hibernators. © 2014 The Authors. Biological Reviews published by John Wiley & Sons Ltd on behalf of Cambridge Philosophical Society.

Agricultural losses related to frost events: use of the 850 hPa level temperature as an explanatory variable of the damage cost

NASA Astrophysics Data System (ADS)

Papagiannaki, K.; Lagouvardos, K.; Kotroni, V.; Papagiannakis, G.

2014-01-01

The objective of this study is to analyze frost damaging events in agriculture, by examining the relationship between the daily minimum temperature at the lower atmosphere (at the pressure level of 850 hPa) and crop production losses. Furthermore, the study suggests a methodological approach for estimating agriculture risk due to frost events, with the aim to estimate the short-term probability and magnitude of frost-related financial losses for different levels of 850 hPa temperature. Compared with near surface temperature forecasts, temperature forecast at the level of 850 hPa is less influenced by varying weather conditions, as well as by local topographical features, thus it constitutes a more consistent indicator of the forthcoming weather conditions. The analysis of the daily monetary compensations for insured crop losses caused by weather events in Greece, during the period 1999-2011, shows that frost is the major meteorological phenomenon with adverse effects on crop productivity in the largest part of the country. Two regions of different geographical latitude are further examined, to account for the differences in the temperature ranges developed within their ecological environment. Using a series of linear and logistic regressions, we found that minimum temperature (at 850 hPa level), grouped in three categories according to its magnitude, and seasonality are significant variables when trying to explain crop damage costs, as well as to predict and quantify the likelihood and magnitude of frost damaging events.

Agricultural losses related to frost events: use of the 850 hPa level temperature as an explanatory variable of the damage cost

NASA Astrophysics Data System (ADS)

Papagiannaki, K.; Lagouvardos, K.; Kotroni, V.; Papagiannakis, G.

2014-09-01

The objective of this study is the analysis of damaging frost events in agriculture, by examining the relationship between the daily minimum temperature in the lower atmosphere (at an isobaric level of 850 hPa) and crop production losses. Furthermore, the study suggests a methodological approach for estimating agriculture risk due to frost events, with the aim of estimating the short-term probability and magnitude of frost-related financial losses for different levels of 850 hPa temperature. Compared with near-surface temperature forecasts, temperature forecasts at the level of 850 hPa are less influenced by varying weather conditions or by local topographical features; thus, they constitute a more consistent indicator of the forthcoming weather conditions. The analysis of the daily monetary compensations for insured crop losses caused by weather events in Greece shows that, during the period 1999-2011, frost caused more damage to crop production than any other meteorological phenomenon. Two regions of different geographical latitudes are examined further, to account for the differences in the temperature ranges developed within their ecological environment. Using a series of linear and logistic regressions, we found that minimum temperature (at an 850 hPa level), grouped into three categories according to its magnitude, and seasonality, are significant variables when trying to explain crop damage costs, as well as to predict and quantify the likelihood and magnitude of damaging frost events.

A Method for Estimating Missing Hourly Temperatures Using Daily Maximum and Minimum Temperatures

DTIC Science & Technology

1991-08-01

work documented by USAFETAC/PR-90/006, S/urt-Termn Hourl ’y Iernpcrature Interlyolaion, by Mal Wvalter F . Miller, December 1990. In his study, Miller...temperatures for the missing hours and concluded that the best model %as one developed by Hoogenboom and [luck (1986). The Hoogcnboom/Huck model uses a...mean of the error estimate, was determined from the following equation: - 7)) BIAS = 1 N", f (14) where the difference between the observed hourly

Change in mean temperature as a predictor of extreme temperature change in the Asia-Pacific region

NASA Astrophysics Data System (ADS)

Griffiths, G. M.; Chambers, L. E.; Haylock, M. R.; Manton, M. J.; Nicholls, N.; Baek, H.-J.; Choi, Y.; della-Marta, P. M.; Gosai, A.; Iga, N.; Lata, R.; Laurent, V.; Maitrepierre, L.; Nakamigawa, H.; Ouprasitwong, N.; Solofa, D.; Tahani, L.; Thuy, D. T.; Tibig, L.; Trewin, B.; Vediapan, K.; Zhai, P.

2005-08-01

Trends (1961-2003) in daily maximum and minimum temperatures, extremes and variance were found to be spatially coherent across the Asia-Pacific region. The majority of stations exhibited significant trends: increases in mean maximum and mean minimum temperature, decreases in cold nights and cool days, and increases in warm nights. No station showed a significant increase in cold days or cold nights, but a few sites showed significant decreases in hot days and warm nights. Significant decreases were observed in both maximum and minimum temperature standard deviation in China, Korea and some stations in Japan (probably reflecting urbanization effects), but also for some Thailand and coastal Australian sites. The South Pacific convergence zone (SPCZ) region between Fiji and the Solomon Islands showed a significant increase in maximum temperature variability.Correlations between mean temperature and the frequency of extreme temperatures were strongest in the tropical Pacific Ocean from French Polynesia to Papua New Guinea, Malaysia, the Philippines, Thailand and southern Japan. Correlations were weaker at continental or higher latitude locations, which may partly reflect urbanization.For non-urban stations, the dominant distribution change for both maximum and minimum temperature involved a change in the mean, impacting on one or both extremes, with no change in standard deviation. This occurred from French Polynesia to Papua New Guinea (except for maximum temperature changes near the SPCZ), in Malaysia, the Philippines, and several outlying Japanese islands. For urbanized stations the dominant change was a change in the mean and variance, impacting on one or both extremes. This result was particularly evident for minimum temperature.The results presented here, for non-urban tropical and maritime locations in the Asia-Pacific region, support the hypothesis that changes in mean temperature may be used to predict changes in extreme temperatures. At urbanized or higher latitude locations, changes in variance should be incorporated.

Use of Regional Climate Model Output for Hydrologic Simulations

NASA Astrophysics Data System (ADS)

Hay, L. E.; Clark, M. P.; Wilby, R. L.; Gutowski, W. J.; Leavesley, G. H.; Pan, Z.; Arritt, R. W.; Takle, E. S.

2001-12-01

Daily precipitation and maximum and minimum temperature time series from a Regional Climate Model (RegCM2) were used as input to a distributed hydrologic model for a rainfall-dominated basin (Alapaha River at Statenville, Georgia) and three snowmelt-dominated basins (Animas River at Durango, Colorado; East Fork of the Carson River near Gardnerville, Nevada; and Cle Elum River near Roslyn, Washington). For comparison purposes, spatially averaged daily data sets of precipitation and maximum and minimum temperature were developed from measured data. These datasets included precipitation and temperature data for all stations that are located within the area of the RegCM2 model output used for each basin, but excluded station data used to calibrate the hydrologic model. Both the RegCM2 output and station data capture the gross aspects of the seasonal cycles of precipitation and temperature. However, in all four basins, the RegCM2- and station-based simulations of runoff show little skill on a daily basis (Nash-Sutcliffe (NS) values ranging from 0.05-0.37 for RegCM2 and -0.08-0.65 for station). When the precipitation and temperature biases are corrected in the RegCM2 output and station data sets (Bias-RegCM2 and Bias-station, respectively) the accuracy of the daily runoff simulations improve dramatically for the snowmelt-dominated basins. In the rainfall-dominated basin, runoff simulations based on the Bias-RegCM2 output show no skill (NS value of 0.09) whereas Bias-All simulated runoff improves (NS value improved from -0.08 to 0.72). These results indicate that the resolution of the RegCM2 output is appropriate for basin-scale modeling, but RegCM2 model output does not contain the day-to-day variability needed for basin-scale modeling in rainfall-dominated basins. Future work is warranted to identify the causes for systematic biases in RegCM2 simulations, develop methods to remove the biases, and improve RegCM2 simulations of daily variability in local climate.

Trends and variability of daily temperature and precipitation extremes during 1960-2012 in the Yangtze River Basin, China

NASA Astrophysics Data System (ADS)

Guan, Yinghui

2017-04-01

The variability of surface air temperature and precipitation extremes has been the focus of attention during the past several decades, and may exert a great influence on the global hydrologic cycle and energy balance through thermal forcing. Using daily minimum (TN), maximum temperature (TX) and precipitation　from 143 meteorological stations in the Yangtze River Basin (YRB), a suite of extreme climate indices recommended by the Expert Team on Climate Change Detection and Indices, which has rarely been applied in this region, were computed and analyzed during 1960-2012. The results show widespread significant changes in all temperature indices associated with warming in the YRB during 1960-2012. On the whole, cold-related indices, i.e., cold nights, cold days, frost days, icing days and cold spell duration index significantly decreased by -3.45, -1.03, -3.04, -0.42 and -1.6 days/decade, respectively. In contrast, warm-related indices such as warm nights, warm days, summer days, tropical nights and warm spell duration index significantly increased by 2.95, 1.71, 2.16, 1.05 and 0.73 days/decade. Minimum TN, maximum TN, minimum TX and maximum TX increased significantly by 0.42, 0.18, 0.19 and 0.14 °C/decade. Because of a faster increase in minimum temperature than maximum temperature, the diurnal temperature range (DTR) exhibited a significant decreasing trend of -0.09 °C/decade for the whole YRB during 1960-2012. Geographically, stations in the eastern Tibet Plateau and northeastern YRB showed stronger trends in almost all temperature indices. Time series analysis indicated that the YRB was dominated by a general cooling trend before the mid-1980s, but a warming trend afterwards. For precipitation, simple daily intensity index, very wet day precipitation, extremely wet day precipitation, extremely heavy precipitation days, maximum 1-day precipitation, maximum 5-day precipitation and maximum consecutive dry days all increased significantly during 1960-2012. In contrast, ≥ 10 mm precipitation days and maximum consecutive wet days decreased significantly, implying that the precipitation processes in YRB were dominated by precipitation events with shorter durations. Geographically, a wetting tendency was observed in the eastern Tibet Plateau and the middle and lower YRB, while the other regions experienced precipitation deficits. The increasing precipitation was mainly due to the intensification of extreme precipitation events and the decreasing precipitation may be attributed to the decrease of ≥ 10 mm precipitation days or moderate precipitation events. In addition, the regional trends were of greater magnitudes in the middle and lower YRB, indicating more frequent extreme precipitation events in these sub-regions.

Mainstem Clearwater River Study: Assessment for Salmonid Spawning, Incubation, and Rearing.

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

Conner, William P.

1989-01-01

Chinook salmon reproduced naturally in the Clearwater River until damming of the lower mainstem in 1927 impeded upstream spawning migrations and decimated the populations. Removal of the Washington Water Power Dam in 1973 reopened upriver passage. This study was initiated to determine the feasibility of re-introducing chinook salmon into the lower mainstem Clearwater River based on the temperature and flow regimes, water quality, substrate, and invertebrate production since the completion of Dworshak Dam in 1972. Temperature data obtained from the United States Geological Survey gaging stations at Peck and Spalding, Idaho, were used to calculate average minimum and maximum watermore » temperature on a daily, monthly and yearly basis. The coldest and warmest (absolute minimum and maximum) temperatures that have occurred in the past 15 years were also identified. Our analysis indicates that average lower mainstem Clearwater River water temperatures are suitable for all life stages of chinook salmon, and also for steelhead trout rearing. In some years absolute maximum water temperatures in late summer may postpone adult staging and spawning. Absolute minimum temperatures have been recorded that could decrease overwinter survival of summer chinook juveniles and fall chinook eggs depending on the quality of winter hiding cover and the prevalence of intra-gravel freezing in the lower mainstem Clearwater River.« less

Neutral atmospheric models compatible with satellite orbital decay and incoherent scatter measurements

NASA Technical Reports Server (NTRS)

Rohrbaugh, J. L.

1972-01-01

A correlation study was made of the variations of the exospheric temperature extrema with various combinations of the monthly mean and daily values of the 2800 MHz and Ca:2 solar indices. The phase and amplitude of the semi-annual component and the term dependent on Kp were found to remain almost the same for the maximum and minimum temperature. The term dependent on the 27 day component of the solar activity was found to be about four times as large for the diurnal maximum as for the minimum. Measurements at Arecibo have shown that temperature gradient changes at 125 km are consistent with the phase difference between the neutral temperature and density maxima. This is used to develop an empirical model which is compatible with both the satellite measurements and the available incoherent scatter measurements. A main feature of this model is that day length is included as a major model parameter.

Linkage Between Hourly Precipitation Events and Atmospheric Temperature Changes over China during the Warm Season

PubMed Central

Miao, Chiyuan; Sun, Qiaohong; Borthwick, Alistair G. L.; Duan, Qingyun

2016-01-01

We investigated changes in the temporospatial features of hourly precipitation during the warm season over mainland China. The frequency and amount of hourly precipitation displayed latitudinal zonation, especially for light and moderate precipitation, which showed successive downward change over time in northeastern and southern China. Changes in the precipitation amount resulted mainly from changes in frequency rather than changes in intensity. We also evaluated the linkage between hourly precipitation and temperature variations and found that hourly precipitation extreme was more sensitive to temperature than other categories of precipitation. A strong dependency of hourly precipitation on temperature occurred at temperatures colder than the median daily temperature; in such cases, regression slopes were greater than the Clausius-Clapeyron (C-C) relation of 7% per degree Celsius. Regression slopes for 31.6%, 59.8%, 96.9%, and 99.1% of all stations were greater than 7% per degree Celsius for the 75th, 90th, 99th, and 99.9th percentiles for precipitation, respectively. The mean regression slopes within the 99.9th percentile of precipitation were three times the C-C rate. Hourly precipitation showed a strong negative relationship with daily maximum temperature and the diurnal temperature range at most stations, whereas the equivalent correlation for daily minimum temperature was weak. PMID:26931350

Documentation of a deep percolation model for estimating ground-water recharge

USGS Publications Warehouse

Bauer, H.H.; Vaccaro, J.J.

1987-01-01

A deep percolation model, which operates on a daily basis, was developed to estimate long-term average groundwater recharge from precipitation. It has been designed primarily to simulate recharge in large areas with variable weather, soils, and land uses, but it can also be used at any scale. The physical and mathematical concepts of the deep percolation model, its subroutines and data requirements, and input data sequence and formats are documented. The physical processes simulated are soil moisture accumulation, evaporation from bare soil, plant transpiration, surface water runoff, snow accumulation and melt, and accumulation and evaporation of intercepted precipitation. The minimum data sets for the operation of the model are daily values of precipitation and maximum and minimum air temperature, soil thickness and available water capacity, soil texture, and land use. Long-term average annual precipitation, actual daily stream discharge, monthly estimates of base flow, Soil Conservation Service surface runoff curve numbers, land surface altitude-slope-aspect, and temperature lapse rates are optional. The program is written in the FORTRAN 77 language with no enhancements and should run on most computer systems without modifications. Documentation has been prepared so that program modifications may be made for inclusions of additional physical processes or deletion of ones not considered important. (Author 's abstract)

Estimation of daily minimum land surface air temperature using MODIS data in southern Iran

NASA Astrophysics Data System (ADS)

Didari, Shohreh; Norouzi, Hamidreza; Zand-Parsa, Shahrokh; Khanbilvardi, Reza

2017-11-01

Land surface air temperature (LSAT) is a key variable in agricultural, climatological, hydrological, and environmental studies. Many of their processes are affected by LSAT at about 5 cm from the ground surface (LSAT5cm). Most of the previous studies tried to find statistical models to estimate LSAT at 2 m height (LSAT2m) which is considered as a standardized height, and there is not enough study for LSAT5cm estimation models. Accurate measurements of LSAT5cm are generally acquired from meteorological stations, which are sparse in remote areas. Nonetheless, remote sensing data by providing rather extensive spatial coverage can complement the spatiotemporal shortcomings of meteorological stations. The main objective of this study was to find a statistical model from the previous day to accurately estimate spatial daily minimum LSAT5cm, which is very important in agricultural frost, in Fars province in southern Iran. Land surface temperature (LST) data were obtained using the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Aqua and Terra satellites at daytime and nighttime periods with normalized difference vegetation index (NDVI) data. These data along with geometric temperature and elevation information were used in a stepwise linear model to estimate minimum LSAT5cm during 2003-2011. The results revealed that utilization of MODIS Aqua nighttime data of previous day provides the most applicable and accurate model. According to the validation results, the accuracy of the proposed model was suitable during 2012 (root mean square difference ( RMSD) = 3.07 °C, {R}_{adj}^2 = 87 %). The model underestimated (overestimated) high (low) minimum LSAT5cm. The accuracy of estimation in the winter time was found to be lower than the other seasons ( RMSD = 3.55 °C), and in summer and winter, the errors were larger than in the remaining seasons.

High-resolution daily gridded datasets of air temperature and wind speed for Europe

NASA Astrophysics Data System (ADS)

Brinckmann, S.; Krähenmann, S.; Bissolli, P.

2015-08-01

New high-resolution datasets for near surface daily air temperature (minimum, maximum and mean) and daily mean wind speed for Europe (the CORDEX domain) are provided for the period 2001-2010 for the purpose of regional model validation in the framework of DecReg, a sub-project of the German MiKlip project, which aims to develop decadal climate predictions. The main input data sources are hourly SYNOP observations, partly supplemented by station data from the ECA&D dataset (http://www.ecad.eu). These data are quality tested to eliminate erroneous data and various kinds of inhomogeneities. Grids in a resolution of 0.044° (5 km) are derived by spatial interpolation of these station data into the CORDEX area. For temperature interpolation a modified version of a regression kriging method developed by Krähenmann et al. (2011) is used. At first, predictor fields of altitude, continentality and zonal mean temperature are chosen for a regression applied to monthly station data. The residuals of the monthly regression and the deviations of the daily data from the monthly averages are interpolated using simple kriging in a second and third step. For wind speed a new method based on the concept used for temperature was developed, involving predictor fields of exposure, roughness length, coastal distance and ERA Interim reanalysis wind speed at 850 hPa. Interpolation uncertainty is estimated by means of the kriging variance and regression uncertainties. Furthermore, to assess the quality of the final daily grid data, cross validation is performed. Explained variance ranges from 70 to 90 % for monthly temperature and from 50 to 60 % for monthly wind speed. The resulting RMSE for the final daily grid data amounts to 1-2 °C and 1-1.5 m s-1 (depending on season and parameter) for daily temperature parameters and daily mean wind speed, respectively. The datasets presented in this article are published at http://dx.doi.org/10.5676/DWD_CDC/DECREG0110v1.

Secular Trend of Surface Temperature at an Elevated Observatory in the Pyrenees.

NASA Astrophysics Data System (ADS)

Bücher, A.; Dessens, J.

1991-08-01

Surface temperature was measured at the Pic du Midi de Bigorre, 2862 m MSL, from the foundation of the Observatory in 1878 until the closing of the meteorological station in 1984. After testing the homogeneity of the series with the annual mean temperatures in western Europe and in southwestern France, the period 1882-1970 was retained for trend analysis.The mean annual temperature increased 0.83°C during the 89-yr period. This increase is the sum of a very significant increase in the daily minimum temperature (+ 2.11°C) and a decrease in the maximum temperature ( 0.45°C). In consequence, the most dramatic change in the temperature regime was the difference between maximum and minimum; this decreased from 8.05°C in 1882 to 5.49°C in 1970. A mean increase is observed in all seasons, but, as for western Europe, it is stronger in spring and fall than in winter and summer.Analysis of cloudiness data for the same period shows a 15% increase in annual mean cloudiness and also significant year-to-year correlations between cloudiness and the maximum and minimum temperature. In consequence, the change in the temperature regime observed at the Pic du Midi since the end of last century is most probably the result of a climatic change involving an increase in cloud cover and, maybe, an increasing greenhouse effect.

Climate trends of the North American prairie pothole region 1906-2000

USGS Publications Warehouse

Millett, B.; Johnson, W.C.; Guntenspergen, G.

2009-01-01

The Prairie Pothole Region (PPR) is unique to North America. Its millions of wetlands and abundant ecosystem goods and services are highly sensitive to wide variations of temperature and precipitation in time and space characteristic of a strongly continental climate. Precipitation and temperature gradients across the PPR are orthogonal to each other. Precipitation nearly triples from west to east from approximately 300 mm/year to 900 mm/year, while mean annual temperature ranges from approximately 1°C in the north to nearly 10°C in the south. Twentieth-century weather records for 18 PPR weather stations representing 6 ecoregions revealed several trends. The climate generally has been getting warmer and wetter and the diurnal temperature range has decreased. Minimum daily temperatures warmed by 1.0°C, while maximum daily temperatures cooled by 0.15°C. Minimum temperature warmed more in winter than in summer, while maximum temperature cooled in summer and warmed in winter. Average annual precipitation increased by 49 mm or 9%. Palmer Drought Severity Index (PDSI) trends reflected increasing moisture availability for most weather stations; however, several stations in the western Canadian Prairies recorded effectively drier conditions. The east-west moisture gradient steepened during the twentieth century with stations in the west becoming drier and stations in the east becoming wetter. If the moisture gradient continues to steepen, the area of productive wetland ecosystems will shrink. Consequences for wetlands would be especially severe if the future climate does not provide supplemental moisture to offset higher evaporative demand.

Reduced Urban Heat Island intensity under warmer conditions

NASA Astrophysics Data System (ADS)

Scott, Anna A.; Waugh, Darryn W.; Zaitchik, Ben F.

2018-06-01

The Urban Heat Island (UHI), the tendency for urban areas to be hotter than rural regions, represents a significant health concern in summer as urban populations are exposed to elevated temperatures. A number of studies suggest that the UHI increases during warmer conditions, however there has been no investigation of this for a large ensemble of cities. Here we compare urban and rural temperatures in 54 US cities for 2000–2015 and show that the intensity of the Urban Heat Island, measured here as the differences in daily-minimum or daily-maximum temperatures between urban and rural stations or ΔT, in fact tends to decrease with increasing temperature in most cities (38/54). This holds when investigating daily variability, heat extremes, and variability across climate zones and is primarily driven by changes in rural areas. We relate this change to large-scale or synoptic weather conditions, and find that the lowest ΔT nights occur during moist weather conditions. We also find that warming cities have not experienced an increasing Urban Heat Island effect.

Ambient air pollution, temperature and out-of-hospital coronary deaths in Shanghai, China.

PubMed

Dai, Jinping; Chen, Renjie; Meng, Xia; Yang, Changyuan; Zhao, Zhuohui; Kan, Haidong

2015-08-01

Few studies have evaluated the effects of ambient air pollution and temperature in triggering out-of-hospital coronary deaths (OHCDs) in China. We evaluated the associations of air pollution and temperature with daily OHCDs in Shanghai, China from 2006 to 2011. We applied an over-dispersed generalized additive model and a distributed lag nonlinear model to analyze the effects of air pollution and temperature, respectively. A 10 μg/m(3) increase in the present-day PM10, PM2.5, SO2, NO2 and CO were associated with increases in OHCD mortality of 0.49%, 0.68%, 0.88%, 1.60% and 0.08%, respectively. A 1 °C decrease below the minimum-mortality temperature corresponded to a 3.81% increase in OHCD mortality on lags days 0-21, and a 1 °C increase above minimum-mortality temperature corresponded to a 4.61% increase over lag days 0-3. No effects were found for in-hospital coronary deaths. This analysis suggests that air pollution, low temperature and high temperature may increase the risk of OHCDs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Detection of the relationship between peak temperature and extreme precipitation

NASA Astrophysics Data System (ADS)

Yu, Y.; Liu, J.; Zhiyong, Y.

2017-12-01

Under the background of climate change and human activities, the characteristics and pattern of precipitation have changed significantly in many regions. As the political and cultural center of China, the structure and character of precipitation in Jingjinji District has varied dramatically in recent years. In this paper, the daily precipitation data throughout the period 1960-2013 are selected for analyzing the spatial-temporal variability of precipitation. The results indicate that the frequency and intensity of precipitation presents an increasing trend. Based on the precipitation data, the maximum, minimum and mean precipitation in different temporal and spatial scales is calculated respectively. The temporal and spatial variation of temperature is obtained by using statistical methods. The relationship between temperature and precipitation in different range is analyzed. The curve relates daily precipitation extremes with local temperatures has a peak structure, increasing at the low-medium range of temperature variations but decreasing at high temperatures. The relationship between extreme precipitation is stronger in downtown than that in suburbs.

User's guide to the weather model: a component of the western spruce budworm modeling system.

Treesearch

W. P. Kemp; N. L. Crookston; P. W. Thomas

1989-01-01

A stochastic model useful in simulating daily maximum and minimum temperature and precipitation developed by Bruhn and others has been adapted for use in the western spruce budworm modeling system. This document describes how to use the weather model and illustrates some aspects of its behavior.

Long term spatial and temporal trends in frost day indices in Kansas, USA

USDA-ARS?s Scientific Manuscript database

Frost day indices such as number of frost days (nFDs), frost free days (nFFDs), last spring freeze (LSF), first fall freeze (FFF), and growing-season length (GSL), were calculated using daily minimum air temperature (Tmin) values from 23 centennial weather stations spread across Kansas during four t...

40 CFR 62.14455 - What if my HMIWI goes outside of a parameter limit?

Code of Federal Regulations, 2010 CFR

2010-07-01

... temperature (3-hour rolling average) simultaneously The PM, CO, and dioxin/furan emission limits. (c) Except..., daily average for batch HMIWI), and below the minimum dioxin/furan sorbent flow rate (3-hour rolling average) simultaneously The dioxin/furan emission limit. (3) Operates above the maximum charge rate (3...

Water-Quality Monitoring in Response to Young-of-the-Year Smallmouth Bass (Micropterus dolomieu) Mortality in the Susquehanna River and Major Tributaries, Pennsylvania: 2008

USGS Publications Warehouse

Chaplin, Jeffrey J.; Crawford, J. Kent; Brightbill, Robin A.

2009-01-01

Mortalities of young-of-the-year (YOY) smallmouth bass (Micropterus dolomieu) recently have occurred in the Susquehanna River due to Flavobacterium columnare, a bacterium that typically infects stressed fish. Stress factors include but are not limited to elevated water temperature and low dissolved oxygen during times critical for survival and development of smallmouth bass (May 1 through July 31). The infections were first discovered in the Susquehanna River and major tributaries in the summer months of 2005 but also were prevalent in 2007. The U.S. Geological Survey, Pennsylvania Fish and Boat Commission, Pennsylvania Department of Environmental Protection, and PPL Corporation worked together to monitor dissolved oxygen, water temperature, pH, and specific conductance on a continuous basis at seven locations from May through mid October 2008. In addition, nutrient concentrations, which may affect dissolved-oxygen concentrations, were measured once in water and streambed sediment at 25 locations. Data from water-quality meters (sondes) deployed as pairs showed daily minimum dissolved-oxygen concentration at YOY smallmouth-bass microhabitats in the Susquehanna River at Clemson Island and the Juniata River at Howe Township Park were significantly lower (p-value < 0.0001) than nearby main-channel habitats. The average daily minimum dissolved-oxygen concentration during the critical period (May 1-July 31) was 1.1 mg/L lower in the Susquehanna River microhabitat and 0.3 mg/L lower in the Juniata River. Daily minimum dissolved-oxygen concentrations were lower than the applicable national criterion (5.0 mg/L) in microhabitat in the Susquehanna River at Clemson Island on 31 days (of 92 days in the critical period) compared to no days in the corresponding main-channel habitat. In the Juniata River, daily minimum dissolved-oxygen concentration in the microhabitat was lower than 5.0 mg/L on 20 days compared to only 5 days in the main-channel habitat. The maximum time periods that dissolved oxygen was less than 5.0 mg/L in microhabitats of the Susquehanna and Juniata Rivers were 8.5 and 5.5 hours, respectively. Dissolved-oxygen concentrations lower than the national criterion generally occurred during nighttime and early-morning hours between midnight and 0800. The lowest instantaneous dissolved-oxygen concentrations measured in microhabitats during the critical period were 3.3 mg/L for the Susquehanna River at Clemson Island (June 11, 2008) and 4.1 mg/L for the Juniata River at Howe Township Park (July 22, 2008). Comparison of 2008 data to available continuous-monitoring data from 1974 to 1979 in the Susquehanna River at Harrisburg, Pa., indicates the critical period of 2008 had an average daily mean dissolved-oxygen concentration that was 1.1 mg/L lower (p-value < 0.0001) than in the 1970s and an average daily mean water temperature that was 0.8 deg C warmer (p-value = 0.0056). Streamflow was not significantly different (p-value = 0.0952) between the two time periods indicating that it is not a likely explanation for the differences in water quality. During the critical period in 2008, dissolved-oxygen concentrations were lower in the Susquehanna River at Harrisburg, Pa., than in the Delaware River at Trenton, N.J., or Allegheny River at Acmetonia near Pittsburgh, Pa. Daily minimum dissolved-oxygen concentrations were below the national criterion of 5.0 mg/L on 6 days during the critical period in the Susquehanna River at Harrisburg compared to no days in the Delaware River at Trenton and the Allegheny River at Acmetonia. Average daily mean water temperature in the Susquehanna River at Harrisburg was 1.8 deg C warmer than in the Delaware River at Trenton and 3.4 deg C warmer than in the Allegheny River at Acmetonia. These results indicate that any stress induced by dissolved oxygen or other environmental conditions is likely to be magnified by elevated temperature in the Susquehanna River at Harrisburg compared to the Delaw

Spatial and temporal evolution of climatic factors and its impacts on potential evapotranspiration in Loess Plateau of Northern Shaanxi, China.

PubMed

Li, C; Wu, P T; Li, X L; Zhou, T W; Sun, S K; Wang, Y B; Luan, X B; Yu, X

2017-07-01

Agriculture is very sensitive to climate change, and correct forecasting of climate change is a great help to accurate allocation of irrigation water. The use of irrigation water is influenced by crop water demand and precipitation. Potential evapotranspiration (ET 0 ) is a measure of the ability of the atmosphere to remove water from the surface through the processes of evaporation and transpiration, assuming no control on water supply. It plays an important role in assessing crop water requirements, regional dry-wet conditions, and other factors of water resource management. This study analyzed the spatial and temporal evolution processes and characteristics of major meteorological parameters at 10 stations in the Loess Plateau of northern Shaanxi (LPNS). By using the Mann-Kendall trend test with trend-free pre-whitening and the ArcGIS platform, the potential evapotranspiration of each station was quantified by using the Penman-Monteith equation, and the effects of climatic factors on potential evapotranspiration were assessed by analyzing the contribution rate and sensitivity of the climatic factors. The results showed that the climate in LPNS has become warmer and drier. In terms of the sensitivity of ET 0 to the variation of each climatic factor in LPNS, relative humidity (0.65) had the highest sensitivity, followed by daily maximum temperature, wind speed, sunshine hours, and daily minimum temperature (-0.05). In terms of the contribution rate of each factor to ET 0 , daily maximum temperature (5.16%) had the highest value, followed by daily minimum temperature, sunshine hours, relative humidity, and wind speed (1.14%). This study provides a reference for the management of agricultural water resources and for countermeasures to climate change. According to the climate change and the characteristics of the study area, farmers in the region should increase irrigation to guarantee crop water demand. Copyright © 2017. Published by Elsevier B.V.

Effect of heat waves on morbidity and mortality due to Parkinson's disease in Madrid: A time-series analysis.

PubMed

Linares, Cristina; Martinez-Martin, Pablo; Rodríguez-Blázquez, Carmen; Forjaz, Maria João; Carmona, Rocío; Díaz, Julio

2016-01-01

Parkinson's disease (PD) is one of the factors which are associated with a higher risk of mortality during heat waves. The use of certain neuroleptic medications to control some of this disease's complications would appear to be related to an increase in heat-related mortality. To analyse the relationship and quantify the short-term effect of high temperatures during heat wave episodes in Madrid on daily mortality and PD-related hospital admissions. We used an ecological time-series study and fit Poisson regression models. We analysed the daily number of deaths due to PD and the number of daily PD-related emergency hospital admissions in the city of Madrid, using maximum daily temperature (°C) as the main environmental variable and chemical air pollution as covariates. We controlled for trend, seasonalities, and the autoregressive nature of the series. There was a maximum daily temperature of 30°C at which PD-related admissions were at a minimum. Similarly, a temperature of 34°C coincides with an increase in the number of admissions. For PD-related admissions, the Relative Risk (RR) for every increase of 1°C above the threshold temperature was 1.13 IC95%:(1.03-1.23) at lags 1 and 5; and for daily PD-related mortality, the RR was 1.14 IC95%:(1.01-1.28) at lag 3. Our results indicate that suffering from PD is a risk factor that contributes to the excess morbidity and mortality associated with high temperatures, and is relevant from the standpoint of public health prevention plans. Copyright © 2016 Elsevier Ltd. All rights reserved.

Retrieving air humidity, global solar radiation, and reference evapotranspiration from daily temperatures: development and validation of new methods for Mexico. Part I: humidity

NASA Astrophysics Data System (ADS)

Lobit, P.; López Pérez, L.; Lhomme, J. P.; Gómez Tagle, A.

2017-07-01

This study evaluates the dew point method (Allen et al. 1998) to estimate atmospheric vapor pressure from minimum temperature, and proposes an improved model to estimate it from maximum and minimum temperature. Both methods were evaluated on 786 weather stations in Mexico. The dew point method induced positive bias in dry areas but also negative bias in coastal areas, and its average root mean square error for all evaluated stations was 0.38 kPa. The improved model assumed a bi-linear relation between estimated vapor pressure deficit (difference between saturated vapor pressure at minimum and average temperature) and measured vapor pressure deficit. The parameters of these relations were estimated from historical annual median values of relative humidity. This model removed bias and allowed for a root mean square error of 0.31 kPa. When no historical measurements of relative humidity were available, empirical relations were proposed to estimate it from latitude and altitude, with only a slight degradation on the model accuracy (RMSE = 0.33 kPa, bias = -0.07 kPa). The applicability of the method to other environments is discussed.

Predicting apricot phenology using meteorological data.

PubMed

Ruml, Mirjana; Milatović, Dragan; Vulić, Todor; Vuković, Ana

2011-09-01

The main objective of this study was to develop feasible, easy to apply models for early prediction of full flowering (FF) and maturing (MA) in apricot (Prunus armeniaca L.). Phenological data for 20 apricot cultivars grown in the Belgrade region were modeled against averages of daily temperature records over ten seasons for FF and eight seasons for MA. A much stronger correlation was found between the phenological timing and temperature at the very beginning than at the end of phenophases. Also, the length of developmental periods were better correlated to daily maximum than to daily minimum and mean air temperatures. Using prediction models based on daily maximum temperatures averaged over 30-, 45- and 60-day periods, starting from 1 January for FF prediction and from the date of FF for MA prediction, the onset of examined phenophases in apricot cultivars could be predicted from a few weeks to up to 2 months ahead with acceptable accuracy. The mean absolute differences between the observations and cross-validated predictions obtained by 30-, 45- and 60-day models were 8.6, 6.9 and 5.7 days for FF and 6.1, 3.6 and 2.8 days for MA, respectively. The validity of the results was confirmed using an independent data set for the year 2009.

Predicting apricot phenology using meteorological data

NASA Astrophysics Data System (ADS)

Ruml, Mirjana; Milatović, Dragan; Vulić, Todor; Vuković, Ana

2011-09-01

The main objective of this study was to develop feasible, easy to apply models for early prediction of full flowering (FF) and maturing (MA) in apricot ( Prunus armeniaca L.). Phenological data for 20 apricot cultivars grown in the Belgrade region were modeled against averages of daily temperature records over ten seasons for FF and eight seasons for MA. A much stronger correlation was found between the phenological timing and temperature at the very beginning than at the end of phenophases. Also, the length of developmental periods were better correlated to daily maximum than to daily minimum and mean air temperatures. Using prediction models based on daily maximum temperatures averaged over 30-, 45- and 60-day periods, starting from 1 January for FF prediction and from the date of FF for MA prediction, the onset of examined phenophases in apricot cultivars could be predicted from a few weeks to up to 2 months ahead with acceptable accuracy. The mean absolute differences between the observations and cross-validated predictions obtained by 30-, 45- and 60-day models were 8.6, 6.9 and 5.7 days for FF and 6.1, 3.6 and 2.8 days for MA, respectively. The validity of the results was confirmed using an independent data set for the year 2009.

Daily temperature and precipitation extremes in the Baltic Sea region derived from the BaltAn65+ reanalysis

NASA Astrophysics Data System (ADS)

Toll, Velle; Post, Piia

2018-04-01

Daily 2-m temperature and precipitation extremes in the Baltic Sea region for the time period of 1965-2005 is studied based on data from the BaltAn65 + high resolution atmospheric reanalysis. Moreover, the ability of regional reanalysis to capture extremes is analysed by comparing the reanalysis data to gridded observations. The shortcomings in the simulation of the minimum temperatures over the northern part of the region and in the simulation of the extreme precipitation over the Scandinavian mountains in the BaltAn65+ reanalysis data are detected and analysed. Temporal trends in the temperature and precipitation extremes in the Baltic Sea region, with the largest increases in temperature and precipitation in winter, are detected based on both gridded observations and the BaltAn65+ reanalysis data. However, the reanalysis is not able to capture all of the regional trends in the extremes in the observations due to the shortcomings in the simulation of the extremes.

Seasonal patterns in body temperature of free-living rock hyrax (Procavia capensis).

PubMed

Brown, Kelly J; Downs, Colleen T

2006-01-01

Rock hyrax (Procavia capensis) are faced with large daily fluctuations in ambient temperature during summer and winter. In this study, peritoneal body temperature of free-living rock hyrax was investigated. During winter, when low ambient temperatures and food supply prevail, rock hyrax maintained a lower core body temperature relative to summer. In winter body temperatures during the day were more variable than at night. This daytime variability is likely a result of body temperatures being raised from basking in the sun. Body temperatures recorded during winter never fell to low levels recorded in previous laboratory studies. During summer ambient temperatures exceeded the thermoneutral zone of the rock hyrax throughout most of the day, while crevice temperatures remained within the thermoneutral zone of rock hyrax. However, in summer variation in core body temperature was small. Minimum and maximum body temperatures did not coincide with minimum and maximum ambient temperatures. Constant body temperatures were also recorded when ambient temperatures reached lethal limits. During summer it is likely that rock hyrax select cooler refugia to escape lethal temperatures and to prevent excessive water loss. Body temperature of rock hyrax recorded in this study reflects the adaptability of this animal to the wide range of ambient temperatures experienced in its natural environment.

Development of a winter wheat adjustable crop calendar model. [Colorado, Idaho, Oklahoma, Montana, Kansas, Missouri, North Dakota and Texas

NASA Technical Reports Server (NTRS)

Baker, J. R. (Principal Investigator)

1979-01-01

The author has identified the following significant results. Least squares techniques were applied for parameter estimation of functions to predict winter wheat phenological stage with daily maximum temperature, minimum temperature, daylength, and precipitation as independent variables. After parameter estimation, tests were conducted using independent data. It may generally be concluded that exponential functions have little advantage over polynomials. Precipitation was not found to significantly affect the fits. The Robertson triquadratic form, in general use for spring wheat, yielded good results, but special techniques and care are required. In most instances, equations with nonlinear effects were found to yield erratic results when utilized with averaged daily environmental values as independent variables.

Changes of the time-varying percentiles of daily extreme temperature in China

NASA Astrophysics Data System (ADS)

Li, Bin; Chen, Fang; Xu, Feng; Wang, Xinrui

2017-11-01

Identifying the air temperature frequency distributions and evaluating the trends in time-varying percentiles are very important for climate change studies. In order to get a better understanding of the recent temporal and spatial pattern of the temperature changes in China, we have calculated the trends in temporal-varying percentiles of the daily extreme air temperature firstly. Then we divide all the stations to get the spatial patterns for the percentile trends using the average linkage cluster analysis method. To make a comparison, the shifts of trends percentile frequency distribution from 1961-1985 to 1986-2010 are also examined. Important results in three aspects have been achieved: (1) In terms of the trends in temporal-varying percentiles of the daily extreme air temperature, the most intense warming for daily maximum air temperature (Tmax) was detected in the upper percentiles with a significant increasing tendency magnitude (>2.5 °C/50year), and the greatest warming for daily minimum air temperature (Tmin) occurred with very strong trends exceeding 4 °C/50year. (2) The relative coherent spatial patterns for the percentile trends were found, and stations for the whole country had been divided into three clusters. The three primary clusters were distributed regularly to some extent from north to south, indicating the possible large influence of the latitude. (3) The most significant shifts of trends percentile frequency distribution from 1961-1985 to 1986-2010 was found in Tmax. More than half part of the frequency distribution show negative trends less than -0.5 °C/50year in 1961-1985, while showing trends less than 2.5 °C/50year in 1986-2010.

The impact of heat waves on surface urban heat island and local economy in Cluj-Napoca city, Romania

NASA Astrophysics Data System (ADS)

Herbel, Ioana; Croitoru, Adina-Eliza; Rus, Adina Viorica; Roşca, Cristina Florina; Harpa, Gabriela Victoria; Ciupertea, Antoniu-Flavius; Rus, Ionuţ

2017-07-01

The association between heat waves and the urban heat island effect can increase the impact on environment and society inducing biophysical hazards. Heat stress and their associated public health problems are among the most frequent. This paper explores the heat waves impact on surface urban heat island and on the local economy loss during three heat periods in Cluj-Napoca city in the summer of 2015. The heat wave events were identified based on daily maximum temperature, and they were divided into three classes considering the intensity threshold: moderate heat waves (daily maximum temperature exceeding the 90th percentile), severe heat waves (daily maximum temperature over the 95th percentile), and extremely severe heat waves (daily maximum temperature exceeding the 98th percentile). The minimum length of an event was of minimum three consecutive days. The surface urban heat island was detected based on land surface temperature derived from Landsat 8 thermal infrared data, while the economic impact was estimated based on data on work force structure and work productivity in Cluj-Napoca derived from the data released by Eurostat, National Bank of Romania, and National Institute of Statistics. The results indicate that the intensity and spatial extension of surface urban heat island could be governed by the magnitude of the heat wave event, but due to the low number of satellite images available, we should consider this information only as preliminary results. Thermal infrared remote sensing has proven to be a very efficient method to study surface urban heat island, due to the fact that the synoptic conditions associated with heat wave events usually favor cloud free image. The resolution of the OLI_TIRS sensor provided good results for a mid-extension city, but the low revisiting time is still a drawback. The potential economic loss was calculated for the working days during heat waves and the estimated loss reached more than 2.5 mil. EUR for each heat wave day at city scale, cumulating more than 38 mil. EUR for the three cases considered.

Taking the heat: thermoregulation in Asian elephants under different climatic conditions.

PubMed

Weissenböck, Nicole M; Arnold, Walter; Ruf, Thomas

2012-02-01

Some mammals indigenous to desert environments, such as camels, cope with high heat load by tolerating an increase in body temperature (T (b)) during the hot day, and by dissipating excess heat during the cooler night hours, i.e., heterothermy. Because diurnal heat storage mechanisms should be favoured by large body size, we investigated whether this response also exists in Asian elephants when exposed to warm environmental conditions of their natural habitat. We compared daily cycles of intestinal T (b) of 11 adult Asian elephants living under natural ambient temperatures (T (a)) in Thailand (mean T (a) ~ 30°C) and in 6 Asian elephants exposed to cooler conditions (mean T (a) ~ 21°C) in Germany. Elephants in Thailand had mean daily ranges of T (b) oscillations (1.15°C) that were significantly larger than in animals kept in Germany (0.51°C). This was due to both increased maximum T (b) during the day and decreased minimum T (b) at late night. Elephant's minimum T (b) lowered daily as T (a) increased and hence entered the day with a thermal reserve for additional heat storage, very similar to arid-zone ungulates. We conclude that these responses show all characteristics of heterothermy, and that this thermoregulatory strategy is not restricted to desert mammals, but is also employed by Asian elephants.

[Characteristics of evaporation over broadleaved Korean pine forest in Changbai Mountains, Northeast China during snow cover period in winter].

PubMed

Li, Hui-dong; Guan, De-xin; Wang, An-zhi; Wu, Jia-Bing; Jin, Chang-jie; ShiI, Ting-ting

2013-04-01

Based on the measurement data of water vapor flux by open-path eddy covariance system and of the micrometeorological factors in broad-leaved Korean pine forest in Changbai Mountains during the snow cover period from 2002 to 2005, this paper analyzed the dynamics of snow cover evaporation and the relationships between the evaporation and meteorological factors. The energy balanced ratio during the snow cover period was 79. 9% , and the latent heat flux accounted for 21. 4% of net radiation. The diurnal variation of the evaporation presented a single-peak curve, and the evaporation rate during snow-melting period was higher than that during stable snow cover period. The half-hour evaporation presented liner relationship with net radiation and quadratic relationship with air temperature. The daily evaporation presented quadratic relationship with net radiation and exponential relationship with air temperature. The daily evaporation presented a dynamic trend of decreasing-stable-increasing, with the maximum at increasing stage and the minimum at stable stage. The maximum value of the daily evaporation was 0.73 mm d-1, and the minimum value was 0. 004 mm d-1. During the snow cover periods of 2002-2003, 2003-2004 and 2004-2005, the annual evaporation was 27.6, 25.5, and 22.9 mm, accounting for 37.9% , 19.5% , and 30. 0% of the precipitation in the same periods, respectively. The mean value of the daily evaporation in the three periods was 0. 17, 0. 19, and 0. 17 mm d-1, respectively.

A three-stage hybrid model for regionalization, trends and sensitivity analyses of temperature anomalies in China from 1966 to 2015

NASA Astrophysics Data System (ADS)

Wu, Feifei; Yang, XiaoHua; Shen, Zhenyao

2018-06-01

Temperature anomalies have received increasing attention due to their potentially severe impacts on ecosystems, economy and human health. To facilitate objective regionalization and examine regional temperature anomalies, a three-stage hybrid model with stages of regionalization, trends and sensitivity analyses was developed. Annual mean and extreme temperatures were analyzed using the daily data collected from 537 stations in China from 1966 to 2015, including the annual mean, minimum and maximum temperatures (Tm, TNm and TXm) as well as the extreme minimum and maximum temperatures (TNe and TXe). The results showed the following: (1) subregions with coherent temperature changes were identified using the rotated empirical orthogonal function analysis and K-means clustering algorithm. The numbers of subregions were 6, 7, 8, 9 and 8 for Tm, TNm, TXm, TNe and TXe, respectively. (2) Significant increases in temperature were observed in most regions of China from 1966 to 2015, although warming slowed down over the last decade. This warming primarily featured a remarkable increase in its minimum temperature. For Tm and TNm, 95% of the stations showed a significant upward trend at the 99% confidence level. TNe increased the fastest, at a rate of 0.56 °C/decade, whereas 21% of the stations in TXe showed a downward trend. (3) The mean temperatures (Tm, TNm and TXm) in the high-latitude regions increased more quickly than those in the low-latitude regions. The maximum temperature increased significantly at high elevations, whereas the minimum temperature increased greatly at middle-low elevations. The most pronounced warming occurred in eastern China in TNe and northwestern China in TXe, with mean elevations of 51 m and 2098 m, respectively. A cooling trend in TXe was observed at the northwestern end of China. The warming rate in TNe varied the most among the subregions (0.63 °C/decade).

The effect of birthplace on heat tolerance and mortality in Milan, Italy, 1980 1989

NASA Astrophysics Data System (ADS)

Vigotti, Maria Angela; Muggeo, Vito M. R.; Cusimano, Rosanna

2006-07-01

The temperature mortality relationship follows a well-known J-V shaped pattern with mortality excesses recorded at cold and hot temperatures, and minimum at some optimal value, referred as Minimum Mortality Temperature (MMT). As the MMT, which is used to measure the population heat-tolerance, is higher for people living in warmer places, it has been argued that populations will adapt to temperature changes. We tested this notion by taking advantage of a huge migratory flow that occurred in Italy during the 1950s, when a large number of unemployed people moved from the southern to the industrializing north-western regions. We have analyzed mortality temperature relationships in Milan residents, split by groups identified by area of birth. In order to obtain estimates of the temperature-related risks, log-linear models have been used to fit daily death count data as a function of different explanatory variables. Results suggest that mortality risks differ by birthplace, regardless of the place of residence, namely heat tolerance in adult life could be modulated by outdoor temperature experienced early in life. This indicates that no complete adaptation might occur with rising external environmental temperatures.

Evaluation of temperature differences for paired stations of the U.S. Climate Reference Network

USGS Publications Warehouse

Gallo, K.P.

2005-01-01

Adjustments to data observed at pairs of climate stations have been recommended to remove the biases introduced by differences between the stations in time of observation, temperature instrumentatios, latitude, and elevation. A new network of climate stations, located in rural settings, permits comparisons of temperatures for several pairs of stations without two of the biases (time of observation and instrurtientation). The daily, monthly, and annual minimum, maximum, and mean temperatures were compared for five pairs of stations included in the U.S. Climate Reference Network. Significant differences were found between the paired stations in the annual minimum, maximum, and mean temperatures for all five pairs of stations. Adjustments for latitude and elevation differences contributed to greater differences in mean annual temperature for four of the five stations. Lapse rates computed from the mean annual temperature differences between station pairs differed from a constant value, whether or not latitude adjustments were made to the data. The results suggest that microclimate influences on temperatures observed at nearby (horizontally and vertically) stations are potentially much greater than influences that might be due to latitude or elevation differences between the stations. ?? 2005 American Meteorological Society.

Correlation Dimension Estimates of Global and Local Temperature Data.

NASA Astrophysics Data System (ADS)

Wang, Qiang

1995-11-01

The author has attempted to detect the presence of low-dimensional deterministic chaos in temperature data by estimating the correlation dimension with the Hill estimate that has been recently developed by Mikosch and Wang. There is no convincing evidence of low dimensionality with either global dataset (Southern Hemisphere monthly average temperatures from 1858 to 1984) or local temperature dataset (daily minimums at Auckland, New Zealand). Any apparent reduction in the dimension estimates appears to be due large1y, if not entirely, to effects of statistical bias, but neither is it a purely random stochastic process. The dimension of the climatic attractor may be significantly larger than 10.

Impact of air pollution and temperature on adverse birth outcomes: Madrid, 2001-2009.

PubMed

Arroyo, Virginia; Díaz, Julio; Carmona, Rocío; Ortiz, Cristina; Linares, Cristina

2016-11-01

Low birth weight (<2500 g) (LBW), premature birth (<37 weeks of gestation) (PB), and late foetal death (<24 h of life) (LFD) are causes of perinatal morbi-mortality, with short- and long-term social and economic health impacts. This study sought to identify gestational windows of susceptibility during pregnancy and to analyse and quantify the impact of different air pollutants, noise and temperature on the adverse birth outcomes. Time-series study to assess the impact of mean daily PM 2.5 , NO 2 and O 3 (μg/m 3 ), mean daily diurnal (Leqd) and nocturnal (Leqn) noise levels (dB(A)), maximum and minimum daily temperatures (°C) on the number of births with LBW, PB or LFD in Madrid across the period 2001-2009. We controlled for linear trend, seasonality and autoregression. Poisson regression models were fitted for quantification of the results. The final models were expressed as relative risk (RR) and population attributable risk (PAR). Leqd was observed to have the following impacts in LBW: at onset of gestation, in the second trimester and in the week of birth itself. NO 2 had an impact in the second trimester. In the case of PB, the following: Leqd in the second trimester, Leqn in the week before birth and PM 2.5 in the second trimester. In the case of LFD, impacts were observed for both PM 2.5 in the third trimester, and minimum temperature. O 3 proved significant in the first trimester for LBW and PB, and in the second trimester for LFD. Pollutants concentrations, noise and temperature influenced the weekly average of new-borns with LBW, PB and LFD in Madrid. Special note should be taken of the effect of diurnal noise on LBW across the entire pregnancy. The exposure of pregnant population to the environmental factors analysed should therefore be controlled with a view to reducing perinatal morbi-mortality. Copyright © 2016 Elsevier Ltd. All rights reserved.

Role of resolution in regional climate change projections over China

NASA Astrophysics Data System (ADS)

Shi, Ying; Wang, Guiling; Gao, Xuejie

2017-11-01

This paper investigates the sensitivity of projected future climate changes over China to the horizontal resolution of a regional climate model RegCM4.4 (RegCM), using RCP8.5 as an example. Model validation shows that RegCM performs better in reproducing the spatial distribution and magnitude of present-day temperature, precipitation and climate extremes than the driving global climate model HadGEM2-ES (HadGEM, at 1.875° × 1.25° degree resolution), but little difference is found between the simulations at 50 and 25 km resolutions. Comparison with observational data at different resolutions confirmed the added value of the RCM and finer model resolutions in better capturing the probability distribution of precipitation. However, HadGEM and RegCM at both resolutions project a similar pattern of significant future warming during both winter and summer, and a similar pattern of winter precipitation changes including dominant increase in most areas of northern China and little change or decrease in the southern part. Projected precipitation changes in summer diverge among the three models, especially over eastern China, with a general increase in HadGEM, little change in RegCM at 50 km, and a mix of increase and decrease in RegCM at 25 km resolution. Changes of temperature-related extremes (annual total number of daily maximum temperature > 25 °C, the maximum value of daily maximum temperature, the minimum value of daily minimum temperature in the three simulations especially in the two RegCM simulations are very similar to each other; so are the precipitation-related extremes (maximum consecutive dry days, maximum consecutive 5-day precipitation and extremely wet days' total amount). Overall, results from this study indicate a very low sensitivity of projected changes in this region to model resolution. While fine resolution is critical for capturing the spatial variability of the control climate, it may not be as important for capturing the climate response to homogeneous forcing (in this case greenhouse gas concentration changes).

WRF model forecasts and their use for hydroclimate monitoring over southern South America

NASA Astrophysics Data System (ADS)

Muller, Omar; Lovino, Miguel; Berbery, E. Hugo

2017-04-01

Weather forecasting and monitoring systems based on regional models are becoming increasingly relevant for decision support in agriculture and water management. This work evaluates the predictive and monitoring capabilities of a system based on WRF model simulations at 15 km grid spacing over a domain that encompasses La Plata Basin (LPB) in southern South America, where agriculture and water resources are essential. The model's skill up to a lead-time of 7 days is evaluated with daily precipitation and 2m temperature in-situ observations. Results show high prediction performance with 7 days lead-time throughout the domain and particularly over LPB, where about 70% of rain and no-rain days are correctly predicted. The scores tend to be better over humid climates than over arid-to-semiarid climates. Compared to the arid-semiarid climate, the humid climate has a higher probability of detection and less false alarms. The ranges of the skill scores are similar to those found over the United States, suggesting that proper choice of parameterizations lead to no loss of performance of the model. Daily mean, minimum and maximum forecast temperatures are highly correlated with observations up to 7 day lead time. The best performance is for daily mean temperature, followed by minimum temperature and a slightly weaker performance for maximum temperature over arid regions. The usefulness of WRF products for hydroclimate monitoring was tested for an unprecedented drought in southern Brazil and for a slightly above normal precipitation season in northeastern Argentina. In both cases the model products reproduce the observed precipitation conditions with consistent impacts on soil moisture, evapotranspiration and runoff. This evaluation validates the model's usefulness to fore-cast weather up to one week and to monitor climate conditions in real time. The scores suggest that the forecast lead-time can be extended into week two, while bias correction methods can reduce part of the systematic errors.

Long-term trends in daily temperature extremes in Iraq

NASA Astrophysics Data System (ADS)

Salman, Saleem A.; Shahid, Shamsuddin; Ismail, Tarmizi; Chung, Eun-Sung; Al-Abadi, Alaa M.

2017-12-01

The existence of long-term persistence (LTP) in hydro-climatic time series can lead to considerable change in significance of trends. Therefore, past findings of climatic trend studies that did not consider LTP became a disputable issue. A study has been conducted to assess the trends in temperature and temperature extremes in Iraq in recent years (1965-2015) using both ordinary Mann-Kendal (MK) test; and the modified Mann-Kendall (m-MK) test, which can differentiate the multi-decadal oscillatory variations from secular trends. Trends in annual and seasonal minimum and maximum temperatures, diurnal temperature range (DTR), and 14 temperature-related extremes were assessed. MK test detected the significant increases in minimum and maximum temperature at all stations, where m-MK test detected at 86% and 80% of all stations, respectively. The temperature in Iraq is increasing 2 to 7 times faster than global temperature rise. The minimum temperature is increasing more (0.48-1.17 °C/decade) than maximum temperature (0.25-1.01 °C/decade). Temperature rise is higher in northern Iraq and in summer. The hot extremes particularly warm nights are increasing all over Iraq at a rate of 2.92-10.69 days/decade, respectively. On the other hand, numbers of cold days are decreasing at some stations at a rate of - 2.65 to - 8.40 days/decade. The use of m-MK test along with MK test confirms the significant increase in temperature and some of the temperature extremes in Iraq. This study suggests that trends in many temperature extremes in the region estimated in previous studies using MK test may be due to natural variability of climate, which empathizes the need for validation of the trends by considering LTP in time series.

Modeling physical and chemical climate of the northeastern United States for a geographic information system

Treesearch

Scott V. Ollinger; John D. Aber; Anthony C. Federer; Gary M. Lovett; Jennifer M. Ellis

1995-01-01

A model of physical and chemical climate was developed for New York and New England that can be used in a GIs for integration with ecosystem models. The variables included are monthly average maximum and minimum daily temperatures, precipitation, humidity, and solar radiation, as well as annual atmospheric deposition of sulfur and nitrogen. Equations generated from...

Regional and seasonal limitations for Mars intrinsic ecopoiesis.

PubMed

Badescu, Viorel

2005-04-01

Mars ecopoiesis is a human controlled process consisting in changes needed for anaerobic life to be established on planet surface. The daily minimum temperature on present day Mars is well below the water freezing point, due to the low thermal inertia of the surface. A simple time-dependent model to evaluate the ground temperature is developed here. It takes into account the incident solar radiation, the greenhouse effect and surface thermal inertia. The model is applied to two modified Martian atmospheres. Increasing surface thermal inertia seems to be necessary for Mars intrinsic ecopoiesis. This can be done either by removing the regolith layer covering the bedrock or by regolith compression. The Northern hemisphere of the terraformed Mars appears to be more hospitable than the Southern hemisphere, because the amplitude of the daily temperature excursion there is lower and the freezing temperature appears at higher latitudes. A regional (and seasonal) terraforming of Mars is suggested. c2005 Elsevier Ltd. All rights reserved.

Air pollution and emergency room visits for asthma in Santa Clara County, California.

PubMed Central

Lipsett, M; Hurley, S; Ostro, B

1997-01-01

During the winters of 1986-1987 through 1991-1992, rainfall throughout much of Northern California was subnormal, resulting in intermittent accumulation of air pollution, much of which was attributable to residential wood combustion (RWC). This investigation examined whether there was a relationship between ambient air pollution in Santa Clara County, California and emergency room visits for asthma during the winters of 1988-1989 through 1991-1992. Emergency room (ER) records from three acute-care hospitals were abstracted to compile daily visits for asthma and a control diagnosis (gastroenteritis) for 3-month periods during each winter. Air monitoring data included daily coefficient of haze (COH) and every-other-day particulate matter with aerodynamic diameter equal to or less than 10 microns (PM10, 24-hr average), as well as hourly nitrogen dioxide and ozone concentrations. Daily COH measurements were used to predict values for missing days of PM10 to develop a complete PM10 time series. Daily data were also obtained for temperature, precipitation, and relative humidity. In time-series analyses using Poisson regression, consistent relationships were found between ER visits for asthma and PM10. Same-day nitrogen dioxide concentrations were also associated with asthma ER visits, while ozone was not. Because there was a significant interaction between PM10 and minimum temperature in this data set, estimates of relative risks (RRs) for PM10-associated asthma ER visits were temperature-dependent. A 60 micrograms/m3 change in PM10 (2-day lag) corresponded to RRs of 1.43 (95% CI = 1.18-1.69) at 20 degrees F, representing the low end of the temperature distribution, 1.27 (95% CI = 1.13-1.42) at 30 degrees F, and 1.11 (95% CI = 1.03-1.19) at 41 degrees F, the mean of the observed minimum temperature. ER visits for gastroenteritis were not significantly associated with any pollutant variable. Several sensitivity analyses, including the use of robust regressions and of nonparametric methods for fitting time trends and temperature effects in the data, supported these findings. These results demonstrate an association between ambient wintertime PM10 and exacerbations of asthma in an area where one of the principal sources of PM10 is RWC. Images Figure 1. PMID:9105797

Microclimate variables of the ambient environment deliver the actual estimates of the extrinsic incubation period of Plasmodium vivax and Plasmodium falciparum: a study from a malaria-endemic urban setting, Chennai in India.

PubMed

Thomas, Shalu; Ravishankaran, Sangamithra; Justin, N A Johnson Amala; Asokan, Aswin; Kalsingh, T Maria Jusler; Mathai, Manu Thomas; Valecha, Neena; Montgomery, Jacqui; Thomas, Matthew B; Eapen, Alex

2018-05-16

Environmental factors such as temperature, relative humidity and their daily variation influence a range of mosquito life history traits and hence, malaria transmission. The standard way of characterizing environmental factors with meteorological station data need not be the actual microclimates experienced by mosquitoes within local transmission settings. A year-long study was conducted in Chennai, India to characterize local temperature and relative humidity (RH). Data loggers (Hobos) were placed in a range of probable indoor and outdoor resting sites of Anopheles stephensi. Recordings were taken hourly to estimate mean temperature and RH, together with daily temperature range (DTR) and daily relative humidity range. The temperature data were used to explore the predicted variation in extrinsic incubation period (EIP) of Plasmodium falciparum and Plasmodium vivax between microhabitats and across the year. Mean daily temperatures within the indoor settings were significantly warmer than those recorded outdoors. DTR in indoor environments was observed to be modest and ranged from 2 to 6 °C. Differences in EIP between microhabitats were most notable during the hottest summer months of April-June, with parasite development predicted to be impaired for tiled houses and overhead tanks. Overall, the prevailing warm and stable conditions suggest rapid parasite development rate regardless of where mosquitoes might rest. Taking account of seasonal and local environmental variation, the predicted EIP of P. falciparum varied from a minimum of 9.1 days to a maximum of 15.3 days, while the EIP of P. vivax varied from 8.0 to 24.3 days. This study provides a detailed picture of the actual microclimates experienced by mosquitoes in an urban slum malaria setting. The data indicate differences between microhabitats that could impact mosquito and parasite life history traits. The predicted effects for EIP are often relatively subtle, but variation between minimum and maximum EIPs can play a role in disease transmission, depending on the time of year and where mosquitoes rest. Appropriate characterization of the local microclimate conditions would be the key to fully understand the effects of environment on local transmission ecology.

Urban Heat Wave Hazard Assessment

NASA Astrophysics Data System (ADS)

Quattrochi, D. A.; Jedlovec, G.; Crane, D. L.; Meyer, P. J.; LaFontaine, F.

2016-12-01

Heat waves are one of the largest causes of environmentally-related deaths globally and are likely to become more numerous as a result of climate change. The intensification of heat waves by the urban heat island effect and elevated humidity, combined with urban demographics, are key elements leading to these disasters. Better warning of the potential hazards may help lower risks associated with heat waves. Moderate resolution thermal data from NASA satellites is used to derive high spatial resolution estimates of apparent temperature (heat index) over urban regions. These data, combined with demographic data, are used to produce a daily heat hazard/risk map for selected cities. MODIS data are used to derive daily composite maximum and minimum land surface temperature (LST) fields to represent the amplitude of the diurnal temperature cycle and identify extreme heat days. Compositing routines are used to generate representative daily maximum and minimum LSTs for the urban environment. The limited effect of relative humidity on the apparent temperature (typically 10-15%) allows for the use of modeled moisture fields to convert LST to apparent temperature without loss of spatial variability. The daily max/min apparent temperature fields are used to identify abnormally extreme heat days relative to climatological values in order to produce a heat wave hazard map. Reference to climatological values normalizes the hazard for a particular region (e.g., the impact of an extreme heat day). A heat wave hazard map has been produced for several case study periods and then computed on a quasi-operational basis during the summer of 2016 for Atlanta, GA, Chicago, IL, St. Louis, MO, and Huntsville, AL. A hazard does not become a risk until someone or something is exposed to that hazard at a level that might do harm. Demographic information is used to assess the urban risk associated with the heat wave hazard. Collectively, the heat wave hazard product can warn people in urban regions who do not have the means to provide air conditioning or take other means to stay cool. The heat wave risk product is conveyed to users via a website that describes current and historical heat wave information and is updated in real time as needed. These risk maps can be used for better monitoring of public health risk from extreme heat events in urban areas.

Air pollution and mortality: results from a study of Santiago, Chile.

PubMed

Ostro, B; Sanchez, J M; Aranda, C; Eskeland, G S

1996-01-01

In 1986, the U.S. EPA issued an air quality standard for particulate matter that included only particulates below 10 microns in diameter (PM10). Unfortunately, epidemiological research investigating the health effects associated with PM10 has been limited by the lack of available daily data from outdoor monitoring stations. Evidence of high concentrations of PM10 in Eastern Europe and in metropolitan areas such as Mexico City and Santiago, Chile underscores the need to evaluate the association between air pollution and mortality. Over the last few years, daily measures of ambient PM10 have been collected in Santiago. Our analysis examines the relationship between PM10 and daily mortality between 1989 and 1991. In addition to total daily mortality, the data were compiled to record total mortality for all males, all females, and those over 65, and mortality from either respiratory disease or cardiovascular disease. Multiple regression analysis was used to explain mortality, with particular attention to controlling for the influence of season and temperature. The results suggest a strong association between PM10 and all of the alternative measures of mortality. The association persists after controlling for daily minimum temperature and binary variables indicating temperature extremes, the day of the week, the month, and the year. Additional sensitivity analyses suggest a fairly robust relationship. In general, a 10 micrograms/m3 change in daily PM10 was associated with a 1% increase in mortality. This relative risk is consistent with the results of recent studies undertaken in the United States.

Rice yields in tropical/subtropical Asia exhibit large but opposing sensitivities to minimum and maximum temperatures

PubMed Central

Welch, Jarrod R.; Vincent, Jeffrey R.; Auffhammer, Maximilian; Moya, Piedad F.; Dobermann, Achim; Dawe, David

2010-01-01

Data from farmer-managed fields have not been used previously to disentangle the impacts of daily minimum and maximum temperatures and solar radiation on rice yields in tropical/subtropical Asia. We used a multiple regression model to analyze data from 227 intensively managed irrigated rice farms in six important rice-producing countries. The farm-level detail, observed over multiple growing seasons, enabled us to construct farm-specific weather variables, control for unobserved factors that either were unique to each farm but did not vary over time or were common to all farms at a given site but varied by season and year, and obtain more precise estimates by including farm- and site-specific economic variables. Temperature and radiation had statistically significant impacts during both the vegetative and ripening phases of the rice plant. Higher minimum temperature reduced yield, whereas higher maximum temperature raised it; radiation impact varied by growth phase. Combined, these effects imply that yield at most sites would have grown more rapidly during the high-yielding season but less rapidly during the low-yielding season if observed temperature and radiation trends at the end of the 20th century had not occurred, with temperature trends being more influential. Looking ahead, they imply a net negative impact on yield from moderate warming in coming decades. Beyond that, the impact would likely become more negative, because prior research indicates that the impact of maximum temperature becomes negative at higher levels. Diurnal temperature variation must be considered when investigating the impacts of climate change on irrigated rice in Asia. PMID:20696908

Artificial Intelligence Techniques for Predicting and Mapping Daily Pan Evaporation

NASA Astrophysics Data System (ADS)

Arunkumar, R.; Jothiprakash, V.; Sharma, Kirty

2017-09-01

In this study, Artificial Intelligence techniques such as Artificial Neural Network (ANN), Model Tree (MT) and Genetic Programming (GP) are used to develop daily pan evaporation time-series (TS) prediction and cause-effect (CE) mapping models. Ten years of observed daily meteorological data such as maximum temperature, minimum temperature, relative humidity, sunshine hours, dew point temperature and pan evaporation are used for developing the models. For each technique, several models are developed by changing the number of inputs and other model parameters. The performance of each model is evaluated using standard statistical measures such as Mean Square Error, Mean Absolute Error, Normalized Mean Square Error and correlation coefficient (R). The results showed that daily TS-GP (4) model predicted better with a correlation coefficient of 0.959 than other TS models. Among various CE models, CE-ANN (6-10-1) resulted better than MT and GP models with a correlation coefficient of 0.881. Because of the complex non-linear inter-relationship among various meteorological variables, CE mapping models could not achieve the performance of TS models. From this study, it was found that GP performs better for recognizing single pattern (time series modelling), whereas ANN is better for modelling multiple patterns (cause-effect modelling) in the data.

A longitudinal ecological study of seasonal influenza deaths in relation to climate conditions in the United States from 1999 through 2011.

PubMed

Geier, David A; Kern, Janet K; Geier, Mark R

2018-01-01

Introduction: Influenza is an acute respiratory disease with significant annual global morbidity/mortality. Influenza transmission occurs in distinct seasonal patterns suggesting an importance of climate conditions on disease pathogenesis. This hypothesis-testing study evaluated microenvironment conditions within different demographic/geographical groups on seasonal influenza deaths in the United States. Materials and methods: The United States Centers for Disease Control and Prevention (CDC) Wonder online computer interface was utilized to integrate and analyze potential correlations in data generated from 1999 through 2011 for climate conditions of mean daily sunlight (KJ/m 2 ), mean daily maximum air temperature ( o C), mean daily minimum air temperature ( o C), and mean daily precipitation (mm) from the North America Land Data Assimilation System (NLDAS) database and on influenza mortality (ICD-10 codes:J09, J10, or J11) from the Underlying Cause of Death database. Results and discussion: Significant inverse correlations between the climate conditions of temperature, sunlight, and precipitation and seasonal influenza death rate were observed. Similar effects were observed among males and females, but when the data were separated by race and urbanization status significant differences were observed. Conclusion: This study highlights key factors that can help shape public health policy to deal with seasonal influenza in the United States and beyond.

Statistical downscaling of mean temperature, maximum temperature, and minimum temperature on the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Lin, Jiang; Miao, Chiyuan

2017-04-01

Climate change is considered to be one of the greatest environmental threats. This has urged scientific communities to focus on the hot topic. Global climate models (GCMs) are the primary tool used for studying climate change. However, GCMs are limited because of their coarse spatial resolution and inability to resolve important sub-grid scale features such as terrain and clouds. Statistical downscaling methods can be used to downscale large-scale variables to local-scale. In this study, we assess the applicability of the widely used Statistical Downscaling Model (SDSM) for the Loess Plateau, China. The observed variables included daily mean temperature (TMEAN), maximum temperature (TMAX) and minimum temperature (TMIN) from 1961 to 2005. The and the daily atmospheric data were taken from reanalysis data from 1961 to 2005, and global climate model outputs from Beijing Normal University Earth System Model (BNU-ESM) from 1961 to 2099 and from observations . The results show that SDSM performs well for these three climatic variables on the Loess Plateau. After downscaling, the root mean square errors for TMEAN, TMAX, TMIN for BNU-ESM were reduced by 70.9%, 75.1%, and 67.2%, respectively. All the rates of change in TMEAN, TMAX and TMIN during the 21st century decreased after SDSM downscaling. We also show that SDSM can effectively reduce uncertainty, compared with the raw model outputs. TMEAN uncertainty was reduced by 27.1%, 26.8%, and 16.3% for the future scenarios of RCP 2.6, RCP 4.5 and RCP 8.5, respectively. The corresponding reductions in uncertainty were 23.6%, 30.7%, and 18.7% for TMAX, ; and 37.6%, 31.8%, and 23.2% for TMIN.

Modification of the degree-day formula for diurnal meltwater generation and refreezing

NASA Astrophysics Data System (ADS)

Žaknić-Ćatović, Ana; Howard, Ken W. F.; Ćatović, Zlatko

2018-02-01

The standard degree-day, temperature-index approach to calculating snowmelt generation and refreezing (the SDD method) is convenient and popularly used but seriously miscalculates the volumes of water that change phase on days when temperatures fluctuate either side of the freezing point. Additionally, the SDD method does not provide any estimate of the duration of daily melting and refreezing events. A modified version of the standard formula is introduced (the MDD method) that overcomes such problems by removing dependence on a single temperature index (the average daily temperature estimated over a 24-h period beginning at midnight) and instead transfers reliance onto daily air temperature extremes (maximum and minimum temperatures) at known times of occurrence. In this way, the modified formula retains the simplicity of the standard approach while targeting those segments of the diurnal air temperature curve that directly relate to periods of melting and freezing. Newly introduced temperature and time degree-day parameters allow the duration of melting and refreezing events to be estimated. The MDD method was evaluated for two sites in the snow-belt region of Canada where the availability of hourly records of daily temperature allowed the required MDD input parameters to be calculated reliably and thus used for comparative purposes. During testing, the MDD input parameters were obtained from daily temperature extremes and their times of occurrence, using two alternative approaches to synthetic air temperature curve generation, one linear, the other trigonometric. Very good agreement was obtained in both cases and confirms the value of the MDD approach. However, there is no significant benefit to be gained by using air temperature approximating functions more complicated than the linear method for supplementing the missing continuous air temperature measurements. Finally, the MDD approach is not seen as a replacement for the regular SDD method, so much as tool that can be applied when the SDD methodology is likely to become unreliable. This is best achieved by using a hybrid SDD-MDD algorithm that invokes the MDD approach only when the necessary conditions arise.

Climate Impacts on Extreme Energy Consumption of Different Types of Buildings

PubMed Central

Li, Mingcai; Shi, Jun; Guo, Jun; Cao, Jingfu; Niu, Jide; Xiong, Mingming

2015-01-01

Exploring changes of building energy consumption and its relationships with climate can provide basis for energy-saving and carbon emission reduction. Heating and cooling energy consumption of different types of buildings during 1981-2010 in Tianjin city, was simulated by using TRNSYS software. Daily or hourly extreme energy consumption was determined by percentile methods, and the climate impact on extreme energy consumption was analyzed. The results showed that days of extreme heating consumption showed apparent decrease during the recent 30 years for residential and large venue buildings, whereas days of extreme cooling consumption increased in large venue building. No significant variations were found for the days of extreme energy consumption for commercial building, although a decreasing trend in extreme heating energy consumption. Daily extreme energy consumption for large venue building had no relationship with climate parameters, whereas extreme energy consumption for commercial and residential buildings was related to various climate parameters. Further multiple regression analysis suggested heating energy consumption for commercial building was affected by maximum temperature, dry bulb temperature, solar radiation and minimum temperature, which together can explain 71.5 % of the variation of the daily extreme heating energy consumption. The daily extreme cooling energy consumption for commercial building was only related to the wet bulb temperature (R2= 0.382). The daily extreme heating energy consumption for residential building was affected by 4 climate parameters, but the dry bulb temperature had the main impact. The impacts of climate on hourly extreme heating energy consumption has a 1-3 hour delay in all three types of buildings, but no delay was found in the impacts of climate on hourly extreme cooling energy consumption for the selected buildings. PMID:25923205

Climate impacts on extreme energy consumption of different types of buildings.

PubMed

Li, Mingcai; Shi, Jun; Guo, Jun; Cao, Jingfu; Niu, Jide; Xiong, Mingming

2015-01-01

Exploring changes of building energy consumption and its relationships with climate can provide basis for energy-saving and carbon emission reduction. Heating and cooling energy consumption of different types of buildings during 1981-2010 in Tianjin city, was simulated by using TRNSYS software. Daily or hourly extreme energy consumption was determined by percentile methods, and the climate impact on extreme energy consumption was analyzed. The results showed that days of extreme heating consumption showed apparent decrease during the recent 30 years for residential and large venue buildings, whereas days of extreme cooling consumption increased in large venue building. No significant variations were found for the days of extreme energy consumption for commercial building, although a decreasing trend in extreme heating energy consumption. Daily extreme energy consumption for large venue building had no relationship with climate parameters, whereas extreme energy consumption for commercial and residential buildings was related to various climate parameters. Further multiple regression analysis suggested heating energy consumption for commercial building was affected by maximum temperature, dry bulb temperature, solar radiation and minimum temperature, which together can explain 71.5 % of the variation of the daily extreme heating energy consumption. The daily extreme cooling energy consumption for commercial building was only related to the wet bulb temperature (R2= 0.382). The daily extreme heating energy consumption for residential building was affected by 4 climate parameters, but the dry bulb temperature had the main impact. The impacts of climate on hourly extreme heating energy consumption has a 1-3 hour delay in all three types of buildings, but no delay was found in the impacts of climate on hourly extreme cooling energy consumption for the selected buildings.

A comparison of weather variables linked to infectious disease patterns using laboratory addresses and patient residence addresses.

PubMed

Djennad, Abdelmajid; Lo Iacono, Giovanni; Sarran, Christophe; Fleming, Lora E; Kessel, Anthony; Haines, Andy; Nichols, Gordon L

2018-04-27

To understand the impact of weather on infectious diseases, information on weather parameters at patient locations is needed, but this is not always accessible due to confidentiality or data availability. Weather parameters at nearby locations are often used as a proxy, but the accuracy of this practice is not known. Daily Campylobacter and Cryptosporidium cases across England and Wales were linked to local temperature and rainfall at the residence postcodes of the patients and at the corresponding postcodes of the laboratory where the patient's specimen was tested. The paired values of daily rainfall and temperature for the laboratory versus residence postcodes were interpolated from weather station data, and the results were analysed for agreement using linear regression. We also assessed potential dependency of the findings on the relative geographic distance between the patient's residence and the laboratory. There was significant and strong agreement between the daily values of rainfall and temperature at diagnostic laboratories with the values at the patient residence postcodes for samples containing the pathogens Campylobacter or Cryptosporidium. For rainfall, the R-squared was 0.96 for the former and 0.97 for the latter, and for maximum daily temperature, the R-squared was 0.99 for both. The overall mean distance between the patient residence and the laboratory was 11.9 km; however, the distribution of these distances exhibited a heavy tail, with some rare situations where the distance between the patient residence and the laboratory was larger than 500 km. These large distances impact the distributions of the weather variable discrepancies (i.e. the differences between weather parameters estimated at patient residence postcodes and those at laboratory postcodes), with discrepancies up to ±10 °C for the minimum and maximum temperature and 20 mm for rainfall. Nevertheless, the distributions of discrepancies (estimated separately for minimum and maximum temperature and rainfall), based on the cases where the distance between the patient residence and the laboratory was within 20 km, still exhibited tails somewhat longer than the corresponding exponential fits suggesting modest small scale variations in temperature and rainfall. The findings confirm that, for the purposes of studying the relationships between meteorological variables and infectious diseases using data based on laboratory postcodes, the weather results are sufficiently similar to justify the use of laboratory postcode as a surrogate for domestic postcode. Exclusion of the small percentage of cases where there is a large distance between the residence and the laboratory could increase the precision of estimates, but there are generally strong associations between daily weather parameters at residence and laboratory.

Fasting-induced daily torpor in desert hamsters (Phodopus roborovskii).

PubMed

Chi, Qing-Sheng; Wan, Xin-Rong; Geiser, Fritz; Wang, De-Hua

2016-09-01

Daily torpor is frequently expressed in small rodents when facing energetically unfavorable ambient conditions. Desert hamsters (Phodopus roborovskii, ~20g) appear to be an exception as they have been described as homeothermic. However, we hypothesized that they can use torpor because we observed reversible decreases of body temperature (Tb) in fasted hamsters. To test this hypothesis we (i) randomly exposed fasted summer-acclimated hamsters to ambient temperatures (Tas) ranging from 5 to 30°C or (ii) supplied them with different rations of food at Ta 23°C. All desert hamsters showed heterothermy with the lowest mean Tb of 31.4±1.9°C (minimum, 29.0°C) and 31.8±2.0°C (minimum, 29.0°C) when fasted at Ta of 23°C and 19°C, respectively. Below Ta 19°C, the lowest Tb and metabolic rate increased and the proportion of hamsters using heterothermy declined. At Ta 5°C, nearly all hamsters remained normothermic by increasing heat production, suggesting that the heterothermy only occurs in moderately cold conditions, perhaps to avoid freezing at extremely low Tas. During heterothermy, Tbs below 31°C with metabolic rates below 25% of those during normothermia were detected in four individuals at Ta of 19°C and 23°C. Consequently, by definition, our observations confirm that fasted desert hamsters are capable of shallow daily torpor. The negative correlation between the lowest Tbs and amount of food supply shows that heterothermy was mainly triggered by food shortage. Our data indicate that summer-acclimated desert hamsters can express fasting-induced shallow daily torpor, which may be of significance for energy conservation and survival in the wild. Copyright © 2016 Elsevier Inc. All rights reserved.

Developmental models for estimating ecological responses to environmental variability: structural, parametric, and experimental issues.

PubMed

Moore, Julia L; Remais, Justin V

2014-03-01

Developmental models that account for the metabolic effect of temperature variability on poikilotherms, such as degree-day models, have been widely used to study organism emergence, range and development, particularly in agricultural and vector-borne disease contexts. Though simple and easy to use, structural and parametric issues can influence the outputs of such models, often substantially. Because the underlying assumptions and limitations of these models have rarely been considered, this paper reviews the structural, parametric, and experimental issues that arise when using degree-day models, including the implications of particular structural or parametric choices, as well as assumptions that underlie commonly used models. Linear and non-linear developmental functions are compared, as are common methods used to incorporate temperature thresholds and calculate daily degree-days. Substantial differences in predicted emergence time arose when using linear versus non-linear developmental functions to model the emergence time in a model organism. The optimal method for calculating degree-days depends upon where key temperature threshold parameters fall relative to the daily minimum and maximum temperatures, as well as the shape of the daily temperature curve. No method is shown to be universally superior, though one commonly used method, the daily average method, consistently provides accurate results. The sensitivity of model projections to these methodological issues highlights the need to make structural and parametric selections based on a careful consideration of the specific biological response of the organism under study, and the specific temperature conditions of the geographic regions of interest. When degree-day model limitations are considered and model assumptions met, the models can be a powerful tool for studying temperature-dependent development.

Box Model of a Series of Salt Ponds, as Applied to the Alviso Salt Pond Complex, South San Francisco Bay, California

USGS Publications Warehouse

Lionberger, Megan A.; Schoellhamer, David H.; Shellenbarger, Gregory; Orlando, James L.; Ganju, Neil K.

2007-01-01

This report documents the development and application of a box model to simulate water level, salinity, and temperature of the Alviso Salt Pond Complex in South San Francisco Bay. These ponds were purchased for restoration in 2003 and currently are managed by the U.S. Fish and Wildlife Service to maintain existing wildlife habitat and prevent a build up of salt during the development of a long-term restoration plan. The model was developed for the purpose of aiding pond managers during the current interim management period to achieve these goals. A previously developed box model of a salt pond, SPOOM, which calculates daily pond volume and salinity, was reconfigured to simulate multiple connected ponds and a temperature subroutine was added. The updated model simulates rainfall, evaporation, water flowing between the ponds and the adjacent tidal slough network, and water flowing from one pond to the next by gravity and pumps. Theoretical and measured relations between discharge and corresponding differences in water level are used to simulate most flows between ponds and between ponds and sloughs. The principle of conservation of mass is used to calculate daily pond volume and salinity. The model configuration includes management actions specified in the Interim Stewardship Plan for the ponds. The temperature subroutine calculates hourly net heat transfer to or from a pond resulting in a rise or drop in pond temperature and daily average, minimum, and maximum pond temperatures are recorded. Simulated temperature was compared with hourly measured data from pond 3 of the Napa?Sonoma Salt Pond Complex and monthly measured data from pond A14 of the Alviso Salt-Pond Complex. Comparison showed good agreement of measured and simulated pond temperature on the daily and monthly time scales.

The effect of future reduction in aerosol emissions on climate extremes in China

NASA Astrophysics Data System (ADS)

Wang, Zhili; Lin, Lei; Yang, Meilin; Xu, Yangyang

2016-11-01

This study investigates the effect of reduced aerosol emissions on projected temperature and precipitation extremes in China during 2031-2050 and 2081-2100 relative to present-day conditions using the daily data output from the Community Earth System Model ensemble simulations under the Representative Concentration Pathway (RCP) 8.5 with an applied aerosol reduction and RCP8.5 with fixed 2005 aerosol emissions (RCP8.5_FixA) scenarios. The reduced aerosol emissions of RCP8.5 magnify the warming effect due to greenhouse gases (GHG) and lead to significant increases in temperature extremes, such as the maximum of daily maximum temperature (TXx), minimum of daily minimum temperature (TNn), and tropical nights (TR), and precipitation extremes, such as the maximum 5-day precipitation amount, number of heavy precipitation days, and annual total precipitation from days ˃95th percentile, in China. The projected TXx, TNn, and TR averaged over China increase by 1.2 ± 0.2 °C (4.4 ± 0.2 °C), 1.3 ± 0.2 °C (4.8 ± 0.2 °C), and 8.2 ± 1.2 (30.9 ± 1.4) days, respectively, during 2031-2050 (2081-2100) under the RCP8.5_FixA scenario, whereas the corresponding values are 1.6 ± 0.1 °C (5.3 ± 0.2 °C), 1.8 ± 0.2 °C (5.6 ± 0.2 °C), and 11.9 ± 0.9 (38.4 ± 1.0) days under the RCP8.5 scenario. Nationally averaged increases in all of those extreme precipitation indices above due to the aerosol reduction account for more than 30 % of the extreme precipitation increases under the RCP8.5 scenario. Moreover, the aerosol reduction leads to decreases in frost days and consecutive dry days averaged over China. There are great regional differences in changes of climate extremes caused by the aerosol reduction. When normalized by global mean surface temperature changes, aerosols have larger effects on temperature and precipitation extremes over China than GHG.

Minimum number of days required for a reliable estimate of daily step count and energy expenditure, in people with MS who walk unaided.

PubMed

Norris, Michelle; Anderson, Ross; Motl, Robert W; Hayes, Sara; Coote, Susan

2017-03-01

The purpose of this study was to examine the minimum number of days needed to reliably estimate daily step count and energy expenditure (EE), in people with multiple sclerosis (MS) who walked unaided. Seven days of activity monitor data were collected for 26 participants with MS (age=44.5±11.9years; time since diagnosis=6.5±6.2years; Patient Determined Disease Steps=≤3). Mean daily step count and mean daily EE (kcal) were calculated for all combinations of days (127 combinations), and compared to the respective 7-day mean daily step count or mean daily EE using intra-class correlations (ICC), the Generalizability Theory and Bland-Altman. For step count, ICC values of 0.94-0.98 and a G-coefficient of 0.81 indicate a minimum of any random 2-day combination is required to reliably calculate mean daily step count. For EE, ICC values of 0.96-0.99 and a G-coefficient of 0.83 indicate a minimum of any random 4-day combination is required to reliably calculate mean daily EE. For Bland-Altman analyses all combinations of days, bar single day combinations, resulted in a mean bias within ±10%, when expressed as a percentage of the 7-day mean daily step count or mean daily EE. A minimum of 2days for step count and 4days for EE, regardless of day type, is needed to reliably estimate daily step count and daily EE, in people with MS who walk unaided. Copyright © 2017 Elsevier B.V. All rights reserved.

Vegetation greenness impacts on maximum and minimum temperatures in northeast Colorado

USGS Publications Warehouse

Hanamean, J. R.; Pielke, R.A.; Castro, C. L.; Ojima, D.S.; Reed, Bradley C.; Gao, Z.

2003-01-01

The impact of vegetation on the microclimate has not been adequately considered in the analysis of temperature forecasting and modelling. To fill part of this gap, the following study was undertaken.A daily 850–700 mb layer mean temperature, computed from the National Center for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis, and satellite-derived greenness values, as defined by NDVI (Normalised Difference Vegetation Index), were correlated with surface maximum and minimum temperatures at six sites in northeast Colorado for the years 1989–98. The NDVI values, representing landscape greenness, act as a proxy for latent heat partitioning via transpiration. These sites encompass a wide array of environments, from irrigated-urban to short-grass prairie. The explained variance (r2 value) of surface maximum and minimum temperature by only the 850–700 mb layer mean temperature was subtracted from the corresponding explained variance by the 850–700 mb layer mean temperature and NDVI values. The subtraction shows that by including NDVI values in the analysis, the r2 values, and thus the degree of explanation of the surface temperatures, increase by a mean of 6% for the maxima and 8% for the minima over the period March–October. At most sites, there is a seasonal dependence in the explained variance of the maximum temperatures because of the seasonal cycle of plant growth and senescence. Between individual sites, the highest increase in explained variance occurred at the site with the least amount of anthropogenic influence. This work suggests the vegetation state needs to be included as a factor in surface temperature forecasting, numerical modeling, and climate change assessments.

Use of regional climate model output for hydrologic simulations

USGS Publications Warehouse

Hay, L.E.; Clark, M.P.; Wilby, R.L.; Gutowski, W.J.; Leavesley, G.H.; Pan, Z.; Arritt, R.W.; Takle, E.S.

2002-01-01

Daily precipitation and maximum and minimum temperature time series from a regional climate model (RegCM2) configured using the continental United States as a domain and run on a 52-km (approximately) spatial resolution were used as input to a distributed hydrologic model for one rainfall-dominated basin (Alapaha River at Statenville, Georgia) and three snowmelt-dominated basins (Animas River at Durango. Colorado; east fork of the Carson River near Gardnerville, Nevada: and Cle Elum River near Roslyn, Washington). For comparison purposes, spatially averaged daily datasets of precipitation and maximum and minimum temperature were developed from measured data for each basin. These datasets included precipitation and temperature data for all stations (hereafter, All-Sta) located within the area of the RegCM2 output used for each basin, but excluded station data used to calibrate the hydrologic model. Both the RegCM2 output and All-Sta data capture the gross aspects of the seasonal cycles of precipitation and temperature. However, in all four basins, the RegCM2- and All-Sta-based simulations of runoff show little skill on a daily basis [Nash-Sutcliffe (NS) values range from 0.05 to 0.37 for RegCM2 and -0.08 to 0.65 for All-Sta]. When the precipitation and temperature biases are corrected in the RegCM2 output and All-Sta data (Bias-RegCM2 and Bias-All, respectively) the accuracy of the daily runoff simulations improve dramatically for the snowmelt-dominated basins (NS values range from 0.41 to 0.66 for RegCM2 and 0.60 to 0.76 for All-Sta). In the rainfall-dominated basin, runoff simulations based on the Bias-RegCM2 output show no skill (NS value of 0.09) whereas Bias-All simulated runoff improves (NS value improved from - 0.08 to 0.72). These results indicate that measured data at the coarse resolution of the RegCM2 output can be made appropriate for basin-scale modeling through bias correction (essentially a magnitude correction). However, RegCM2 output, even when bias corrected, does not contain the day-to-day variability present in the All-Sta dataset that is necessary for basin-scale modeling. Future work is warranted to identify the causes for systematic biases in RegCM2 simulations, develop methods to remove the biases, and improve RegCM2 simulations of daily variability in local climate.

Relative air temperature analysis external building on Gowa Campus

NASA Astrophysics Data System (ADS)

Mustamin, Tayeb; Rahim, Ramli; Baharuddin; Jamala, Nurul; Kusno, Asniawaty

2018-03-01

This study aims to data analyze the relative temperature and humidity of the air outside the building. Data retrieval taken from weather monitoring device (monitoring) Vaisala, RTU (Remote Terminal Unit), Which is part of the AWS (Automatic Weather Stations) Then Processing data processed and analyzed by using Microsoft Excel program in the form of graph / picture fluctuation Which shows the average value, standard deviation, maximum value, and minimum value. Results of data processing then grouped in the form: Daily, and monthly, based on time intervals every 30 minutes. The results showed Outside air temperatures in March, April, May and September 2016 Which entered in the thermal comfort zone according to SNI standard (Indonesian National Standard) only at 06.00-10.00. In late March to early April Thermal comfort zone also occurs at 15.30-18.00. The highest maximum air temperature occurred in September 2016 at 11.01-11.30 And the lowest minimum value in September 2016, time 6:00 to 6:30. The result of the next analysis shows the level of data conformity with thermal comfort zone based on SNI (Indonesian National Standard) every month.

Thermoregulation of alpacas bred in Italy

NASA Astrophysics Data System (ADS)

Mattiello, Silvana; Formis, Elena; Barbieri, Sara

2011-03-01

The present study monitored daily and seasonal variations of rectal temperature in response to different environmental temperatures in alpacas bred in the Italian Apennines at 300 m a.s.l. In each season, the rectal temperature of 33 clinically healthy alpacas was measured three times/day (morning, midday, afternoon). Ambient temperatures were also recorded. Rectal temperatures ranged from a minimum value of 35.1 to a maximum of 39.4°C, with a maximum daily thermal excursion (ΔTrec) of 3.2°C. Temperatures increased throughout the day, with highly significant differences recorded in both young and adult animals between all the time bands ( P < 0.001). These differences were particularly dramatic for adults in summer, when the mean rectal temperature in the morning was 36.3 ± 0.13°C, probably as a consequence of recent shearing. Significant ΔTrec differences were recorded depending on the season in both young and adult animals ( P < 0.001), with the highest ΔTrec values recorded in summer (although the highest daily ambient excursion value was recorded in winter). In conclusion, similarly to alpacas bred in their natural environment, alpacas bred in Italy show a wide thermal neutrality zone, which is probably an adaptive response, that allows the animals to save energy. In the Italian Apennines, in order to prevent situations of hypothermia, with possible detrimental effects on alpacas' health and welfare, shearing should be carried out only in warm seasons.

Temperature Observation Time and Type Influence Estimates of Heat-Related Mortality in Seven U.S. Cities.

PubMed

Davis, Robert E; Hondula, David M; Patel, Anjali P

2016-06-01

Extreme heat is a leading weather-related cause of mortality in the United States, but little guidance is available regarding how temperature variable selection impacts heat-mortality relationships. We examined how the strength of the relationship between daily heat-related mortality and temperature varies as a function of temperature observation time, lag, and calculation method. Long time series of daily mortality counts and hourly temperature for seven U.S. cities with different climates were examined using a generalized additive model. The temperature effect was modeled separately for each hour of the day (with up to 3-day lags) along with different methods of calculating daily maximum, minimum, and mean temperature. We estimated the temperature effect on mortality for each variable by comparing the 99th versus 85th temperature percentiles, as determined from the annual time series. In three northern cities (Boston, MA; Philadelphia, PA; and Seattle, WA) that appeared to have the greatest sensitivity to heat, hourly estimates were consistent with a diurnal pattern in the heat-mortality response, with strongest associations for afternoon or maximum temperature at lag 0 (day of death) or afternoon and evening of lag 1 (day before death). In warmer, southern cities, stronger associations were found with morning temperatures, but overall the relationships were weaker. The strongest temperature-mortality relationships were associated with maximum temperature, although mean temperature results were comparable. There were systematic and substantial differences in the association between temperature and mortality based on the time and type of temperature observation. Because the strongest hourly temperature-mortality relationships were not always found at times typically associated with daily maximum temperatures, temperature variables should be selected independently for each study location. In general, heat-mortality was more closely coupled to afternoon and maximum temperatures in most cities we examined, particularly those typically prone to heat-related mortality. Davis RE, Hondula DM, Patel AP. 2016. Temperature observation time and type influence estimates of heat-related mortality in seven U.S. cities. Environ Health Perspect 124:795-804; http://dx.doi.org/10.1289/ehp.1509946.

Using air/water/sediment temperature contrasts to identify groundwater seepage locations in small streams

NASA Astrophysics Data System (ADS)

Karan, S.; Sebok, E.; Engesgaard, P. K.

2016-12-01

For identifying groundwater seepage locations in small streams within a headwater catchment, we present a method expanding on the linear regression of air and stream temperatures. Thus, by measuring the temperatures in dual-depth; in the stream column and at the streambed-water interface (SWI), we apply metrics from linear regression analysis of temperatures between air/stream and air/SWI (linear regression slope, intercept and coefficient of determination), and the daily mean temperatures (temperature variance and the average difference between the minimum and maximum daily temperatures). Our study show that using metrics from single-depth stream temperature measurements only are not sufficient to identify substantial groundwater seepage locations within a headwater stream. Conversely, comparing the metrics from dual-depth temperatures show significant differences so that at groundwater seepage locations, temperatures at the SWI, merely explain 43-75 % of the variation opposed to ≥91 % at the corresponding stream column temperatures. The figure showing a box-plot of the variation in daily mean temperature depict that at several locations there is great variation in the range the upper and lower loggers due to groundwater seepage. In general, the linear regression show that at these locations at the SWI, the slopes (<0.25) and intercepts (>6.5oC) are substantially lower and higher, while the mean diel amplitudes (<0.98oC) are decreased compared to remaining locations. The dual-depth approach was applied in a post-glacial fluvial setting, where metrics analyses overall corresponded to field measurements of groundwater fluxes deduced from vertical streambed temperatures and stream flow accretions. Thus, we propose a method reliably identifying groundwater seepage locations along streambed in such settings.

High-resolution daily gridded data sets of air temperature and wind speed for Europe

NASA Astrophysics Data System (ADS)

Brinckmann, Sven; Krähenmann, Stefan; Bissolli, Peter

2016-10-01

New high-resolution data sets for near-surface daily air temperature (minimum, maximum and mean) and daily mean wind speed for Europe (the CORDEX domain) are provided for the period 2001-2010 for the purpose of regional model validation in the framework of DecReg, a sub-project of the German MiKlip project, which aims to develop decadal climate predictions. The main input data sources are SYNOP observations, partly supplemented by station data from the ECA&D data set (http://www.ecad.eu). These data are quality tested to eliminate erroneous data. By spatial interpolation of these station observations, grid data in a resolution of 0.044° (≈ 5km) on a rotated grid with virtual North Pole at 39.25° N, 162° W are derived. For temperature interpolation a modified version of a regression kriging method developed by Krähenmann et al.(2011) is used. At first, predictor fields of altitude, continentality and zonal mean temperature are used for a regression applied to monthly station data. The residuals of the monthly regression and the deviations of the daily data from the monthly averages are interpolated using simple kriging in a second and third step. For wind speed a new method based on the concept used for temperature was developed, involving predictor fields of exposure, roughness length, coastal distance and ERA-Interim reanalysis wind speed at 850 hPa. Interpolation uncertainty is estimated by means of the kriging variance and regression uncertainties. Furthermore, to assess the quality of the final daily grid data, cross validation is performed. Variance explained by the regression ranges from 70 to 90 % for monthly temperature and from 50 to 60 % for monthly wind speed. The resulting RMSE for the final daily grid data amounts to 1-2 K and 1-1.5 ms-1 (depending on season and parameter) for daily temperature parameters and daily mean wind speed, respectively. The data sets presented in this article are published at doi:10.5676/DWD_CDC/DECREG0110v2.

Seasonal, daily activity, and habitat use by three sympatric pit vipers (Serpentes, Viperidae) from southern Brazil.

PubMed

Rocha, Marcelo C; Hartmann, Paulo A; Winck, Gisele R; Cechin, Sonia Z

2014-04-25

Viperid snakes are widely distributed in the South America and the greater distribution range of the family is found at the Crotalinae subfamily. Despite the abundance of this snakes along their geographic distribution, some ecological aspects remain unknown, principally at subtropical areas. In the present study, we evaluated the activity (daily and seasonal) and the use of the habitat by Bothrops diporus, B. jararaca and B. jararacussu, in an Atlantic Forest area at southern Brazil. We observed higher incidence of viperid snakes during the months with higher temperatures, while no snakes were found during the months with lower temperatures. The data suggest the minimum temperature as environmental variable with the greatest influence on the seasonal activity of this species. Considering the daily activity, we observed a tendency of snakes to avoid the warmest hours. Bothrops jararacussu tend to avoid open areas, being registered only inside and at the edges of the forest. We compared our results with previous studies realized at tropical areas and we suggest the observed seasonal activity as an evolutive response, despite the influence of the different environmental variables, according to the occurence region.

Temperature Observation Time and Type Influence Estimates of Heat-Related Mortality in Seven U.S. Cities

PubMed Central

Davis, Robert E.; Hondula, David M.; Patel, Anjali P.

2015-01-01

Background: Extreme heat is a leading weather-related cause of mortality in the United States, but little guidance is available regarding how temperature variable selection impacts heat–mortality relationships. Objectives: We examined how the strength of the relationship between daily heat-related mortality and temperature varies as a function of temperature observation time, lag, and calculation method. Methods: Long time series of daily mortality counts and hourly temperature for seven U.S. cities with different climates were examined using a generalized additive model. The temperature effect was modeled separately for each hour of the day (with up to 3-day lags) along with different methods of calculating daily maximum, minimum, and mean temperature. We estimated the temperature effect on mortality for each variable by comparing the 99th versus 85th temperature percentiles, as determined from the annual time series. Results: In three northern cities (Boston, MA; Philadelphia, PA; and Seattle, WA) that appeared to have the greatest sensitivity to heat, hourly estimates were consistent with a diurnal pattern in the heat-mortality response, with strongest associations for afternoon or maximum temperature at lag 0 (day of death) or afternoon and evening of lag 1 (day before death). In warmer, southern cities, stronger associations were found with morning temperatures, but overall the relationships were weaker. The strongest temperature–mortality relationships were associated with maximum temperature, although mean temperature results were comparable. Conclusions: There were systematic and substantial differences in the association between temperature and mortality based on the time and type of temperature observation. Because the strongest hourly temperature–mortality relationships were not always found at times typically associated with daily maximum temperatures, temperature variables should be selected independently for each study location. In general, heat-mortality was more closely coupled to afternoon and maximum temperatures in most cities we examined, particularly those typically prone to heat-related mortality. Citation: Davis RE, Hondula DM, Patel AP. 2016. Temperature observation time and type influence estimates of heat-related mortality in seven U.S. cities. Environ Health Perspect 124:795–804; http://dx.doi.org/10.1289/ehp.1509946 PMID:26636734

Influence of air temperature on the first flowering date of Prunus yedoensis Matsum

PubMed Central

Shi, Peijian; Chen, Zhenghong; Yang, Qingpei; Harris, Marvin K; Xiao, Mei

2014-01-01

Climate change is expected to have a significant effect on the first flowering date (FFD) in plants flowering in early spring. Prunus yedoensis Matsum is a good model plant for analyzing this effect. In this study, we used a degree day model to analyze the effect of air temperatures on the FFDs of P. yedoensis at Wuhan University from a long-time series from 1951 to 2012. First, the starting date (=7 February) is determined according to the lowest correlation coefficient between the FFD and the daily average accumulated degree days (ADD). Second, the base temperature (=−1.2°C) is determined according to the lowest root mean square error (RMSE) between the observed and predicted FFDs based on the mean of 62-year ADDs. Finally, based on this combination of starting date and base temperature, the daily average ADD of every year was calculated. Performing a linear fit of the daily average ADD to year, we find that there is an increasing trend that indicates climate warming from a biological climatic indicator. In addition, we find that the minimum annual temperature also has a significant effect on the FFD of P. yedoensis using the generalized additive model. This study provides a method for analyzing the climate change on the FFD in plants' flowering in early spring. PMID:24558585

Dietary Supplementation with n-3 Polyunsaturated Fatty Acids Reduces Torpor Use in a Tropical Daily Heterotherm.

PubMed

Vuarin, Pauline; Henry, Pierre-Yves; Perret, Martine; Pifferi, Fabien

Polyunsaturated fatty acids (PUFAs) are involved in a variety of physiological mechanisms, including heterothermy preparation and expression. However, the effects of the two major classes of PUFAs, n-6 and n-3, can differ substantially. While n-6 PUFAs enhance torpor expression, n-3 PUFAs reduce the ability to decrease body temperature. This negative impact of n-3 PUFAs has been revealed in temperate hibernators only. Yet because tropical heterotherms generally experience higher ambient temperature and exhibit higher minimum body temperature during heterothermy, they may not be affected as much by PUFAs as their temperate counterparts. We tested whether n-3 PUFAs constrain torpor use in a tropical daily heterotherm (Microcebus murinus). We expected dietary n-3 PUFA supplementation to induce a reduction in torpor use and for this effect to appear rapidly given the time required for dietary fatty acids to be assimilated into phospholipids. n-3 PUFA supplementation reduced torpor use, and its effect appeared in the first days of the experiment. Within 2 wk, control animals progressively deepened their torpor bouts, whereas supplemented ones never entered torpor but rather expressed only constant, shallow reductions in body temperature. For the rest of the experiment, the effect of n-3 PUFA supplementation on torpor use remained constant through time. Even though supplemented animals also started to express torpor, they exhibited higher minimum body temperature by 2°-3°C and spent two fewer hours in a torpid state per day than control individuals, on average. Our study supports the view that a higher dietary content in n-3 PUFAs negatively affects torpor use in general, not only in cold-acclimated hibernators.

Effects of reproductive condition, roost microclimate, and weather patterns on summer torpor use by a vespertilionid bat

PubMed Central

Johnson, Joseph S; Lacki, Michael J

2014-01-01

A growing number of mammal species are recognized as heterothermic, capable of maintaining a high-core body temperature or entering a state of metabolic suppression known as torpor. Small mammals can achieve large energetic savings when torpid, but they are also subject to ecological costs. Studying torpor use in an ecological and physiological context can help elucidate relative costs and benefits of torpor to different groups within a population. We measured skin temperatures of 46 adult Rafinesque's big-eared bats (Corynorhinus rafinesquii) to evaluate thermoregulatory strategies of a heterothermic small mammal during the reproductive season. We compared daily average and minimum skin temperatures as well as the frequency, duration, and depth of torpor bouts of sex and reproductive classes of bats inhabiting day-roosts with different thermal characteristics. We evaluated roosts with microclimates colder (caves) and warmer (buildings) than ambient air temperatures, as well as roosts with intermediate conditions (trees and rock crevices). Using Akaike's information criterion (AIC), we found that different statistical models best predicted various characteristics of torpor bouts. While the type of day-roost best predicted the average number of torpor bouts that bats used each day, current weather variables best predicted daily average and minimum skin temperatures of bats, and reproductive condition best predicted average torpor bout depth and the average amount of time spent torpid each day by bats. Finding that different models best explain varying aspects of heterothermy illustrates the importance of torpor to both reproductive and nonreproductive small mammals and emphasizes the multifaceted nature of heterothermy and the need to collect data on numerous heterothermic response variables within an ecophysiological context. PMID:24558571

Climate Change and Simulation of Cardiovascular Disease Mortality: A Case Study of Mashhad, Iran.

PubMed

Baaghideh, Mohammad; Mayvaneh, Fatemeh

2017-03-01

Weather and climate play a significant role in human health. We are accustomed to affects the weather conditions. By increasing or decreasing the environment temperature or change of seasons, some diseases become prevalent or remove. This study investigated the role of temperature in cardiovascular disease mortality of city of Mashhad in the current decade and its simulation in the future decades under conditions of climate change. Cardiovascular disease mortality data and the daily temperatures data were used during (2004-2013) period. First, the correlation between cardiovascular disease mortality and maximum and minimum temperatures were calculated then by using General Circulation Model, Emissions Scenarios, and temperature data were extracted for the next five decades and finally, mortality was simulated. There is a strong positive association between maximum temperature and mortality (r= 0.83, P -value<0.01), also observed a negative and weak but significant association between minimum temperatures and mortality. The results obtained from simulation show increased temperature in the next decades in Mashhad and a 1 °C increase in maximum temperature is associated with a 4.27% (95%CI: 0.91, 7.00) increase in Cardiovascular disease mortality. By increasing temperature and the number of hot days the cardiovascular disease mortality increases and these increases will be intensified in the future decades. Therefore, necessary preventive measures are required to mitigate temperature effects with greater attention to vulnerable group.

Exploring the association between heat and mortality in Switzerland between 1995 and 2013.

PubMed

Ragettli, Martina S; Vicedo-Cabrera, Ana M; Schindler, Christian; Röösli, Martin

2017-10-01

Designing effective public health strategies to prevent adverse health effect of hot weather is crucial in the context of global warming. In Switzerland, the 2003 heat have caused an estimated 7% increase in all-cause mortality. As a consequence, the Swiss Federal Office of Public Health developed an information campaign to raise public awareness on heat threats. For a better understanding on how hot weather affects daily mortality in Switzerland, we assessed the effect of heat on daily mortality in eight Swiss cities and population subgroups from 1995 to 2013 using different temperature metrics (daily mean (Tmean), maximum (Tmax), minimum (Tmin) and maximum apparent temperature (Tappmax)), and aimed to evaluate variations of the heat effect after 2003 (1995-2002 versus 2004-2013). We applied conditional quasi-Poisson regression models with non-linear distributed lag functions to estimate temperature-mortality associations over all cities (1995-2013) and separately for two time periods (1995-2002, 2004-2013). Relative risks (RR) of daily mortality were estimated for increases in temperature from the median to the 98th percentile of the warm season temperature distribution. Over the whole time period, significant temperature-mortality relationships were found for all temperature indicators (RR (95% confidence interval): Tappmax: 1.12 (1.05; 1.18); Tmax: 1.15 (1.08-1.22); Tmean: 1.16 (1.09-1.23); Tmin 1.23 (1.15-1.32)). Mortality risks were higher at the beginning of the summer, especially for Tmin. In the more recent time period, we observed a non-significant reduction in the effect of high temperatures on mortality, with the age group > 74 years remaining the population at highest risk. High temperatures continue to be a considerable risk factor for human health in Switzerland after 2003. More effective public health measures targeting the elderly should be promoted with increased attention to the first heat events in summer and considering both high day-time and night-time temperatures. Copyright © 2017 Elsevier Inc. All rights reserved.

Internet survey of the influence of environmental factors on human health: environmental epidemiologic investigation using the web-based daily questionnaire for health

PubMed Central

Sano, Tomomi; Akahane, Manabu; Sugiura, Hiroaki; Ohkusa, Yasushi; Okabe, Nobuhiko; Imamura, Tomoaki

2012-01-01

With increasing Internet coverage, the use of a web-based survey for epidemiological study is a possibility. We performed an investigation in Japan in winter 2008 using the web-based daily questionnaire for health (WDQH). The WDQH is a web-based questionnaire survey formulated to obtain information about the daily physical condition of the general public on a real-time basis, in order to study correlations between changes in physical health and changes in environmental factors. Respondents were asked whether they felt ill and had specific symptoms including fever. We analysed the environmental factors along with the health conditions obtained from the WDQH. Four factors were found to influence health: minimum temperature, hours of sunlight, median humidity and weekday or holiday. The WDQH allowed a daily health survey in the general population in real time via the Internet. PMID:22946467

Frost injury to bitterbrush in eastern California

Treesearch

R. S. Smith; R. F. Scharpf; E. R. Schneegas

1965-01-01

Widespread dieback of Purshia tridentata, on the Inyo National Forest in eastern California in the spring of 1964, was caused by a severe 3-day frost with daily minimums down to 13°F. An unusually warm 9-day period-with temperatures up to 70°F., which preceded the frost by a week, had induced the bitterbrush to break dormancy and start shoot elongation when the frost...

Observed changes in extremes of daily rainfall and temperature in Jemma Sub-Basin, Upper Blue Nile Basin, Ethiopia

NASA Astrophysics Data System (ADS)

Worku, Gebrekidan; Teferi, Ermias; Bantider, Amare; Dile, Yihun T.

2018-02-01

Climate variability has been a threat to the socio-economic development of Ethiopia. This paper examined the changes in rainfall, minimum, and maximum temperature extremes of Jemma Sub-Basin of the Upper Blue Nile Basin for the period of 1981 to 2014. The nonparametric Mann-Kendall, seasonal Mann-Kendall, and Sen's slope estimator were used to estimate annual trends. Ten rainfall and 12 temperature indices were used to study changes in rainfall and temperature extremes. The results showed an increasing trend of annual and summer rainfall in more than 78% of the stations and a decreasing trend of spring rainfall in most of the stations. An increase in rainfall extreme events was detected in the majority of the stations. Several rainfall extreme indices showed wetting trends in the sub-basin, whereas limited indices indicated dryness in most of the stations. Annual maximum and minimum temperature and extreme temperature indices showed warming trend in the sub-basin. Presence of extreme rainfall and a warming trend of extreme temperature indices may suggest signs of climate change in the Jemma Sub-Basin. This study, therefore, recommended the need for exploring climate induced risks and implementing appropriate climate change adaptation and mitigation strategies.

Regional climate change study requires new temperature datasets

NASA Astrophysics Data System (ADS)

Wang, K.; Zhou, C.

2016-12-01

Analyses of global mean air temperature (Ta), i. e., NCDC GHCN, GISS, and CRUTEM4, are the fundamental datasets for climate change study and provide key evidence for global warming. All of the global temperature analyses over land are primarily based on meteorological observations of the daily maximum and minimum temperatures (Tmax and Tmin) and their averages (T2) because in most weather stations, the measurements of Tmax and Tmin may be the only choice for a homogenous century-long analysis of mean temperature. Our studies show that these datasets are suitable for long-term global warming studies. However, they may introduce substantial bias in quantifying local and regional warming rates, i.e., with a root mean square error of more than 25% at 5°x 5° grids. From 1973 to 1997, the current datasets tend to significantly underestimate the warming rate over the central U.S. and overestimate the warming rate over the northern high latitudes. Similar results revealed during the period 1998-2013, the warming hiatus period, indicate the use of T2 enlarges the spatial contrast of temperature trends. This because T2 over land only sample air temperature twice daily and cannot accurately reflect land-atmosphere and incoming radiation variations in the temperature diurnal cycle. For better regional climate change detection and attribution, we suggest creating new global mean air temperature datasets based on the recently available high spatiotemporal resolution meteorological observations, i.e., daily four observations weather station since 1960s, These datasets will not only help investigate dynamical processes on temperature variances but also help better evaluate the reanalyzed and modeled simulations of temperature and make some substantial improvements for other related climate variables in models, especially over regional and seasonal aspects.

Regional climate change study requires new temperature datasets

NASA Astrophysics Data System (ADS)

Wang, Kaicun; Zhou, Chunlüe

2017-04-01

Analyses of global mean air temperature (Ta), i. e., NCDC GHCN, GISS, and CRUTEM4, are the fundamental datasets for climate change study and provide key evidence for global warming. All of the global temperature analyses over land are primarily based on meteorological observations of the daily maximum and minimum temperatures (Tmax and Tmin) and their averages (T2) because in most weather stations, the measurements of Tmax and Tmin may be the only choice for a homogenous century-long analysis of mean temperature. Our studies show that these datasets are suitable for long-term global warming studies. However, they may have substantial biases in quantifying local and regional warming rates, i.e., with a root mean square error of more than 25% at 5 degree grids. From 1973 to 1997, the current datasets tend to significantly underestimate the warming rate over the central U.S. and overestimate the warming rate over the northern high latitudes. Similar results revealed during the period 1998-2013, the warming hiatus period, indicate the use of T2 enlarges the spatial contrast of temperature trends. This is because T2 over land only samples air temperature twice daily and cannot accurately reflect land-atmosphere and incoming radiation variations in the temperature diurnal cycle. For better regional climate change detection and attribution, we suggest creating new global mean air temperature datasets based on the recently available high spatiotemporal resolution meteorological observations, i.e., daily four observations weather station since 1960s. These datasets will not only help investigate dynamical processes on temperature variances but also help better evaluate the reanalyzed and modeled simulations of temperature and make some substantial improvements for other related climate variables in models, especially over regional and seasonal aspects.

Adjusted monthly temperature and precipitation values for Guinea Conakry (1941-2010) using HOMER.

NASA Astrophysics Data System (ADS)

Aguilar, Enric; Aziz Barry, Abdoul; Mestre, Olivier

2013-04-01

Africa is a data sparse region and there are very few studies presenting homogenized monthly records. In this work, we introduce a dataset consisting of 12 stations spread over Guinea Conakry containing daily values of maximum and minimum temperature and accumulated rainfall for the period 1941-2010. The daily values have been quality controlled using R-Climdex routines, plus other interactive quality control applications, coded by the authors. After applying the different tests, more than 200 daily values were flagged as doubtful and carefully checked against the statistical distribution of the series and the rest of the dataset. Finally, 40 values were modified or set to missing and the rest were validated. The quality controlled daily dataset was used to produce monthly means and homogenized with HOMER, a new R-pacakge which includes the relative methods that performed better in the experiments conducted in the framework of the COST-HOME action. A total number of 38 inhomogeneities were found for temperature. As a total of 788 years of data were analyzed, the average ratio was one break every 20.7 years. The station with a larger number of inhomogeneities was Conakry (5 breaks) and one station, Kissidougou, was identified as homogeneous. The average number of breaks/station was 3.2. The mean value of the monthly factors applied to maximum (minimum) temperature was 0.17 °C (-1.08 °C) . For precipitation, due to the demand of a denser network to correctly homogenize this variable, only two major inhomogeneities in Conakry (1941-1961, -12%) and Kindia (1941-1976, -10%) were corrected. The adjusted dataset was used to compute regional series for the three variables and trends for the 1941-2010 period. The regional mean has been computed by simply averaging anomalies to 1971-2000 of the 12 time series. Two different versions have been obtained: a first one (A) makes use of the missing values interpolation made by HOMER (so all annual values in the regional series are an average of 12 anomalies); the second one (B) removes the missing values, and each value of the regional series is an average of 5 to 12 anomalies. In this case, a variance stabilization factor has been applied. As a last step a trend analysis has been applied over the regional series. This has been done using two different approaches: standard least squares regression (LS) and the implementation by Zhang of the Sen slope estimator (SEN), applied using the zyp R-package. The results for the A & B series and the different trend calculations are very similar, in terms of slopes and signification. All the identified trends are significant at the 95% confidence level or better. Using the A series and the SEN slope, the annual regional mean of maximum temperatures has increased 0.135 °C/decade (95% confidence interval: 0.087 / 0.173) and the annual regional mean of minimum temperatures 0.092 °C/decade (0.050/0.135). Maximum temperatures present high values in the 1940s to 1950s and a large increase in the last decades. In contrast, minimum temperatures were relatively cooler in the 1940s and 1950s and the increase in the last decades is more moderate. Finally, the regional mean of annual accumulated precipitation decreased between 1941 and 2010 by -2.20 mm (-3.82/-0.64). The precipitation series are dominated by the high values before 1970, followed by a well known decrease in rainfall. This homogenized monthly series will improve future analysis over this portion of Western Africa.

A model to forecast short-term snowmelt runoff using synoptic observations of streamflow, temperature, and precipitation

USGS Publications Warehouse

Tangborn, Wendell V.

1980-01-01

Snowmelt runoff is forecast with a statistical model that utilizes daily values of stream discharge, gaged precipitation, and maximum and minimum observations of air temperature. Synoptic observations of these variables are made at existing low- and medium-altitude weather stations, thus eliminating the difficulties and expense of new, high-altitude installations. Four model development steps are used to demonstrate the influence on prediction accuracy of basin storage, a preforecast test season, air temperature (to estimate ablation), and a prediction based on storage. Daily ablation is determined by a technique that employs both mean temperature and a radiative index. Radiation (both long- and short-wave components) is approximated by using the range in daily temperature, which is shown to be closely related to mean cloud cover. A technique based on the relationship between prediction error and prediction season weather utilizes short-term forecasts of precipitation and temperature to improve the final prediction. Verification of the model is accomplished by a split sampling technique for the 1960–1977 period. Short- term (5–15 days) predictions of runoff throughout the main snowmelt season are demonstrated for mountain drainages in western Washington, south-central Arizona, western Montana, and central California. The coefficient of prediction (Cp) based on actual, short-term predictions for 18 years is for Thunder Creek (Washington), 0.69; for South Fork Flathead River (Montana), 0.45; for the Black River (Arizona), 0.80; and for the Kings River (California), 0.80.

Effect of seasonality, weather and holidays on the incidence of proximal hip fracture.

PubMed

Koren, Lior; Barak, Adi; Norman, Doron; Sachs, Ofer; Peled, Eli

2014-05-01

Proximal hip fractures in the elderly are common and place a heavy burden on health resources. Researching the timing of these fractures could contribute to diverting resources towards peaks in incidence and investing in prevention at certain times. To examine the effect of seasonality, weather and Jewish holidays on hip fracture incidence in older adults. The study population comprised 2050 patients aged 65 years or more who sustained a proximal hip fracture. The computerized files of the patients were reviewed for trends in incidence by season, precipitation, minimum and maximum temperatures, day of the week, and certain Jewish festivals. Hip fractures were more likely to occur in the winter than in the summer (P < 0.0001). Factors that significantly correlated with hip fracture were the maximum daily temperature (r = -0.746, P = 0.005) followed by the minimum daily temperature (r = -0.740, P = 0.006) and precipitation (r = 0.329, P = 0.02). There were fewer fractures on Saturdays (the Sabbath) as compared to other days of the week (P = 0.045). Researching the incidence on Jewish holidays, we found an elevated incidence on Passover (P < 0.0001) and a reduced incidence on the Day of Atonement (Yom Kippui) (P = 0.013). In older people there is an elevated incidence of proximal hip fractures during the winter and on the Jewish festivals. On weekends and on the Day of Atonement the incidence of proximal hip fractures was reduced.

Attributing Historical Changes in Probabilities of Record-Breaking Daily Temperature and Precipitation Extreme Events

DOE PAGES

Shiogama, Hideo; Imada, Yukiko; Mori, Masato; ...

2016-08-07

Here, we describe two unprecedented large (100-member), longterm (61-year) ensembles based on MRI-AGCM3.2, which were driven by historical and non-warming climate forcing. These ensembles comprise the "Database for Policy Decision making for Future climate change (d4PDF)". We compare these ensembles to large ensembles based on another climate model, as well as to observed data, to investigate the influence of anthropogenic activities on historical changes in the numbers of record-breaking events, including: the annual coldest daily minimum temperature (TNn), the annual warmest daily maximum temperature (TXx) and the annual most intense daily precipitation event (Rx1day). These two climate model ensembles indicatemore » that human activity has already had statistically significant impacts on the number of record-breaking extreme events worldwide mainly in the Northern Hemisphere land. Specifically, human activities have altered the likelihood that a wider area globally would suffer record-breaking TNn, TXx and Rx1day events than that observed over the 2001- 2010 period by a factor of at least 0.6, 5.4 and 1.3, respectively. However, we also find that the estimated spatial patterns and amplitudes of anthropogenic impacts on the probabilities of record-breaking events are sensitive to the climate model and/or natural-world boundary conditions used in the attribution studies.« less

Methodology and results of calculating central California surface temperature trends: Evidence of human-induced climate change?

USGS Publications Warehouse

Christy, J.R.; Norris, W.B.; Redmond, K.; Gallo, K.P.

2006-01-01

A procedure is described to construct time series of regional surface temperatures and is then applied to interior central California stations to test the hypothesis that century-scale trend differences between irrigated and nonirrigated regions may be identified. The procedure requires documentation of every point in time at which a discontinuity in a station record may have occurred through (a) the examination of metadata forms (e.g., station moves) and (b) simple statistical tests. From this "homogeneous segments" of temperature records for each station are defined. Biases are determined for each segment relative to all others through a method employing mathematical graph theory. The debiased segments are then merged, forming a complete regional time series. Time series of daily maximum and minimum temperatures for stations in the irrigated San Joaquin Valley (Valley) and nearby nonirrigated Sierra Nevada (Sierra) were generated for 1910-2003. Results show that twentieth-century Valley minimum temperatures are warming at a highly significant rate in all seasons, being greatest in summer and fall (> +0.25??C decade-1). The Valley trend of annual mean temperatures is +0.07?? ?? 0.07??C decade-1. Sierra summer and fall minimum temperatures appear to be cooling, but at a less significant rate, while the trend of annual mean Sierra temperatures is an unremarkable -0.02?? ?? 0.10??C decade-1. A working hypothesis is that the relative positive trends in Valley minus Sierra minima (>0.4??C decade-1 for summer and fall) are related to the altered surface environment brought about by the growth of irrigated agriculture, essentially changing a high-albedo desert into a darker, moister, vegetated plain. ?? 2006 American Meteorological Society.

Gamma-radiation monitoring in post-tectonic biotitic granites at Celorico da Beira

NASA Astrophysics Data System (ADS)

Domingos, Filipa; Barbosa, Susana; Pereira, Alcides; Neves, Luís

2017-04-01

Despite its obvious relevance, the effect of meteorological variables such as temperature, pressure, wind, rainfall and particularly humidity on the temporal variability of natural radiation is complex and still not fully understood. Moreover, the nature of their influence with increasing depth is also poorly understood. Thereby, two boreholes were set 3 m apart in the region of Celorico da Beira within post-tectonic biotitic granites of the Beiras Batolith. Continuous measurements were obtained with identical gamma-ray scintillometers deployed at depths of 1 and 6 m during a 6 month period in the years of 2014 and 2015. Temperature, relative humidity, pressure, rainfall, wind speed and direction were measured at the site, as well as temperature and relative humidity inside the boreholes, with the aim of assessing the influence of meteorological parameters on the temporal variability of gamma radiation at two distinct depths. Both time series display a complex temporal structure including multiyear, seasonal and daily variability. At 1 m depth, a daily periodicity on the gamma ray counts time series was noticed with daily maxima occurring most frequently from 8 to 12 p.m. and daily minima between 8 and 12 a.m.. At 6 m depth, maximum and minimum daily means occurred with approximately a 10 h lag from the above. Gamma radiation data exhibited fairly strong correlations with temperature and relative humidity, however, varying with depth. Gamma radiation counts increased with increasing temperature and decreasing relative humidity at 1 m depth, while at a 6 m depth the opposite was recorded, with counts increasing with relative humidity and decreasing with temperature. Wind speed was shown to be inversely related with counts at 6 m depth, while positively correlated at 1 m depth. Pressure and rainfall had minor effects on both short-term and long-term gamma radiation counts.

Effects of climate change on daily minimum and maximum temperatures and cloudiness in the Shikoku region: a statistical downscaling model approach

NASA Astrophysics Data System (ADS)

Tatsumi, Kenichi; Oizumi, Tsutao; Yamashiki, Yosuke

2015-04-01

In this study, we present a detailed analysis of the effect of changes in cloudiness (CLD) between a future period (2071-2099) and the base period (1961-1990) on daily minimum temperature (TMIN) and maximum temperature (TMAX) in the same period for the Shikoku region, Japan. This analysis was performed using climate data obtained with the use of the Statistical DownScaling Model (SDSM). We calibrated the SDSM using the National Center for Environmental Prediction (NCEP) reanalysis dataset for the SDSM input and daily time series of temperature and CLD from 10 surface data points (SDP) in Shikoku. Subsequently, we validated the SDSM outputs, specifically, TMIN, TMAX, and CLD, obtained with the use of the NCEP reanalysis dataset and general circulation model (GCM) data against the SDP. The GCM data used in the validation procedure were those from the Hadley Centre Coupled Model, version 3 (HadCM3) for the Special Report on Emission Scenarios (SRES) A2 and B2 scenarios and from the third generation Coupled Global Climate Model (CGCM3) for the SRES A2 and A1B scenarios. Finally, the validated SDSM was run to study the effect of future changes in CLD on TMIN and TMAX. Our analysis showed that (1) the negative linear fit between changes in TMAX and those in CLD was statistically significant in winter while the relationship between the two changes was not evident in summer, (2) the dependency of future changes in TMAX and TMIN on future changes in CLD were more evident in winter than in other seasons with the present SDSM, (3) the diurnal temperature range (DTR) decreased in the southern part of Shikoku in summer in all the SDSM projections while DTR increased in the northern part of Shikoku in the same season in these projections, (4) the dependencies of changes in DTR on changes in CLD were unclear in summer and winter. Results of the SDSM simulations performed for climate change scenarios such as those from this study contribute to local-scale agricultural and hydrological simulations and development of agricultural and hydrological models.

Age, circadian rhythms, and sleep loss in flight crews

NASA Technical Reports Server (NTRS)

Gander, Philippa H.; Nguyen, DE; Rosekind, Mark R.; Connell, Linda J.

1993-01-01

Age-related changes in trip-induced sleep loss, personality, and the preduty temperature rhythm were analyzed in crews from various flight operations. Eveningness decreased with age. The minimum of the baseline temperature rhythm occurred earlier with age. The amplitude of the baseline temperature rhythm declined with age. Average daily percentage sleep loss during trips increased with age. Among crewmembers flying longhaul flight operations, subjects aged 50-60 averaged 3.5 times more sleep loss per day than subjects aged 20-30. These studies support previous findings that evening types and subjects with later peaking temperature rhythms adapt better to shift work and time zone changes. Age and circadian type may be important considerations for duty schedules and fatigue countermeasures.

Estrus- and steroid-induced changes in circadian rhythms in a diurnal rodent, Octodon degus.

PubMed

Labyak, S E; Lee, T M

1995-09-01

Diurnal Octodon degus exhibited marked alterations in activity and temperature in conjunction with the 3 wk estrous cycle when housed in LD12:12 light cycle. On the day of estrus, mean daily activity increases 109%, mean core temperature rises .4 degree C, activity onset is advanced 2 h, and amplitudes of both rhythms decline compared with the 3 days prior to estrus. On the day following estrus, activity onset was delayed 4.9 h, and mean activity and core temperature fell below that of the preestrus period. Ovariectomy significantly reduced mean temperature (.98 degree C) but did not significantly alter mean activity, and eliminated cyclic effects of estrus. Estrogen replacement led to a nonsignificant elevation in mean activity and core temperature with no change in the phase angle of entrainment. Progesterone replacement significantly reduced mean core temperature and mean activity, while only the phase angle difference between temperature minimum and activity onset was significantly altered. Intact degus maintained in constant darkness displayed only transient fluctuations in activity onset and temperature minimum during and after estrus. Estrogen or progesterone treatment of ovariectomized, free-running degus altered mean temperature and activity levels, but did not influence tau. Changes in phase angle of entrainment during estrus are not the result of hormone effects on the circadian clock but likely reflect increased or decreased levels of activity.

Life cycle and fecundity analysis of Lutzomyia shannoni (Dyar) (Diptera: Psychodidae).

PubMed

Ferro, C; Cárdenas, E; Corredor, D; Morales, A; Munstermann, L E

1998-01-01

The life cycle of Lutzomyia shannoni (Dyar), was described for laboratory conditions with maximum daily temperature of 27-30 degree C, minimum daily temperatures of 22-27 degree C and relative humidity between 87-99%. Life cycle in each stage was as follows: egg 6-12 days (ave, 8.5 days); first stage larva 5-13 days (ave. 9.6 days); second stage larva 4-13 days (ave. 9.2 days); third stage larva 5-19 days (ave. 11.8 days); fourth stage larva 7-37 days (ave. 19.9 days); pupa 7-32 days (ave. 15.2 days). The life expectancy of adults ranged from 4 to 15 days (ave. 8.6 days). The entire egg to adult period ranged from 36 to 74 days (ave. 54.6 days). On average, each female oviposited 22.7 eggs; the average egg retention per female was 24.3 eggs.

Resilience of a High Latitude Red Sea Frining Corals Exposed to Extreme Temperatures

NASA Astrophysics Data System (ADS)

Moustafa, M.; Moustafa, M. S.; Moustafa, S.; Moustafa, Z. D.

2013-05-01

Since 2004, multi-year study set out to establish linkages between fringing coral reefs in the northern Gulf of Suez, Red Sea, and local weather. Insight into local meteorological processes may provide a better understanding of the direct influence weather has on a fringing coral reef. To establish trends, seawater temperature and meteorological record were collected at a small fringing coral reef (Zaki's Reef), located near Ein Sokhna, Egypt (29.5oN & 32.4oE). Monitoring air and water temperature provides evidence of seasonality and interannual variability and may reveal correlations between reef health and climate conditions in this region. Prior to this study, there were no known long-term studies investigating coral reefs in this region. Approximately 35 coral taxa are known to survive the extreme temperature and salinity regime found here, yet only six corals compose 94% of coral cover on Zaki's Reef. Dominant corals include: Acropora humilis, A. microclados, A. hemprichii, Litophyton arboretum, Stylophora pistillata, Porites columna, and P. plantulata. Seawater temperatures were collected at 30 minutes intervals at 5 locations. Seawater temperature data indicate that corals experience 4-6.5oC daily temperature variations and seasonal variations that exceed 29oC. Air temperatures were collected just landward of the reef were compared to Hurghada and Ismailia 400 and 200 km south and north of the study site, respectively. Time series analysis results indicate that air temperature dominant frequencies are half-daily, daily, and yearly cycles, while water temperatures show yearly cycles. A comparison of air temperature with neighboring locations indicates that air temperatures at Ein Sokhna ranged between near 0o C to an excess of 55o C, yet, daily means for Ein Sokhna and Hurghada were very similar (24.2o C and. 25.2o C, respectively). Maximum daily air temperatures at the study site exceeded maximum air temperature at Hurghada (400 km south) by almost 7o C, while minimum daily means at Ein Sokhna were almost equal to those at Ismailia (200 km north). These trends were opposite to what was expected considering each stations geographical locations. The unexpected temperature trends, the daily/half daily dominant frequencies, and the short distance between the mountain range and Zaki's Reef vs. Hurghada (0.5 vs. 35 km), prompted us to hypothesize that a Foehn wind may be responsible for the high air temperatures observed at Ein Sokhna. We applied NOAA's HYSPLIT model to explore local circulation patterns, which suggest that the high mountain range blocks the year-round trade wind and forces it to climb up the western slope, where it loses moisture and reduces its temperature. As this cool, denser air reaches the mountain top, the air parcel starts rolling down the eastern slopes, which causes air temperature to rise and result in an increase in local air temperatures. These warmer than normal air temperatures measured here may aid in securing these northernmost reefs survival. Further scrutiny of the mechanisms by which area reefs are able to thrive extreme environmental conditions continues to be investigated.

Shearing at the end of summer affects body temperature of free-living Angora goats ( Capra aegagrus) more than does shearing at the end of winter.

PubMed

Hetem, R S; de Witt, B A; Fick, L G; Fuller, A; Kerley, G I H; Maloney, S K; Meyer, L C R; Mitchell, D

2009-07-01

Angora goats are known to be vulnerable to cold stress, especially after shearing, but their thermoregulatory responses to shearing have not been measured. We recorded activity, and abdominal and subcutaneous temperatures, for 10 days pre-shearing and post-shearing, in 10 Angora goats inhabiting the succulent thicket of the Eastern Cape, South Africa, in both March (late summer) and September (late winter). Within each season, environmental conditions were similar pre-shearing and post-shearing, but September was an average 5°C colder than March. Shearing resulted in a decreased mean (P < 0.0001), minimum (P < 0.0001) and maximum daily abdominal temperature (P < 0.0001). Paradoxically, the decrease in daily mean (P = 0.03) and maximum (P = 0.01) abdominal temperatures, from pre-shearing to post-shearing, was greater in March than in September. Daily amplitude of body temperature rhythm (P < 0.0001) and the maximum rate of abdominal temperature rise (P < 0.0001) increased from pre-shearing to post-shearing, resulting in an earlier diurnal peak in abdominal temperature (P = 0.001) post-shearing. These changes in amplitude, rate of abdominal temperature rise and time of diurnal peak in abdominal temperature suggest that the goats' thermoregulatory system was more labile after shearing. Mean daily subcutaneous temperatures also decreased post-shearing (P < 0.0001), despite our index goat selecting more stable microclimates after shearing in March (P = 0.03). Following shearing, there was an increased difference between abdominal and subcutaneous temperatures (P < 0.0001) at night, suggesting that the goats used peripheral vasoconstriction to limit heat loss. In addition to these temperature changes, mean daily activity increased nearly two-fold after March shearing, but not September shearing. This increased activity after March shearing was likely the result of an increased foraging time, food intake and metabolic rate, as suggested by the increased water influx (P = 0.0008). Thus, Angora goats entered a heat conservation mode after shearing in both March and September. That the transition from the fleeced to the shorn state had greater thermoregulatory consequences in March than in September may provide a mechanistic explanation for Angora goats' vulnerability to cold in summer.

Climatic indicators over Catalonia during the last century

NASA Astrophysics Data System (ADS)

Busto, M.; Prohom, M.

2010-09-01

The Meteorological Service of Catalonia releases a yearly bulletin whose main objective is to try to detect climate trends over Catalonia during the last decades. Climate indicators are obtained from the analysis of historical daily air temperature, sea temperature and rainfall series. Those series have been first completed, analyzed for quality control and homogenized to ensure its final reliability. Regarding homogenization, monthly air temperature series have been tested and corrected according to the methodology proposed by Caussinus and Mestre (2004). For the two longest air temperature series, the calculated correction factors have been transferred to the daily values following Vincent et al. (2002) recommendations, while no significant inhomogeneities have been detected for precipitation series. The analysis of temperature trends, for the period 1950-2010, of 17 selected climatic series spread across the territory shows a common temperature increase between +0.19 to +0.24 °C/decade. This warming trend is uniform and no specific sub-regional trends are detected. Furthermore, the seasonal approach reveals that mean maximum temperature increases at a higher rate than mean minimum temperature. The summer temperature rise is the most significant, between +0.32 and +0.44 °C/decade, while autumn is the only season showing no significant positive trend. The summer maximum temperature shows the highest increase, exceeding +0.39 °C/decade in all the 17 series. The climatic extremes analysis of the longest Catalan series (Ebre Observatory in Roquetes, Tarragona, since 1905 and Fabra Observatory in Barcelona since 1913) reveals an increase in the number of summer days, tropical nights, minimum of maximum temperature, warm days and warm nights, and a decrease in the number of frost days, cold nights, cold days and cold spell duration indicator. Concerning precipitation, the only significant trend is the reduction of snow days. These trends were calculated according to the Expert Team on Climate Change Detection and Indices (ETCCDI). The sea temperature trend in l'Estartit (NE coast of Catalonia, Costa Brava) since 1974 shows a steady increment in all the measured levels (surface, -20 m, -50 m and -80 m) of +0,33 °C/decade on average. Temperature increment is maximum at -20 m, with +0.36 °C/decade variation. Moreover, there is an increase in the sea level of +3.35 cm/decade. CAUSSINUS, H. and MESTRE, O. (2004): Detection and correction of artificial shifts in climate series. Journal of the Royal Statistical Society Series C - Applied Statistics, 53, 405-425. VINCENT, L.A., ZHANG, X., BONSAL, B.R., HOGG, W.D. (2002): Homogenization of daily temperatures over Canada. Journal of Climate, 15, 1322-1334

Estimating daily minimum, maximum, and mean near surface air temperature using hybrid satellite models across Israel.

PubMed

Rosenfeld, Adar; Dorman, Michael; Schwartz, Joel; Novack, Victor; Just, Allan C; Kloog, Itai

2017-11-01

Meteorological stations measure air temperature (Ta) accurately with high temporal resolution, but usually suffer from limited spatial resolution due to their sparse distribution across rural, undeveloped or less populated areas. Remote sensing satellite-based measurements provide daily surface temperature (Ts) data in high spatial and temporal resolution and can improve the estimation of daily Ta. In this study we developed spatiotemporally resolved models which allow us to predict three daily parameters: Ta Max (day time), 24h mean, and Ta Min (night time) on a fine 1km grid across the state of Israel. We used and compared both the Aqua and Terra MODIS satellites. We used linear mixed effect models, IDW (inverse distance weighted) interpolations and thin plate splines (using a smooth nonparametric function of longitude and latitude) to first calibrate between Ts and Ta in those locations where we have available data for both and used that calibration to fill in neighboring cells without surface monitors or missing Ts. Out-of-sample ten-fold cross validation (CV) was used to quantify the accuracy of our predictions. Our model performance was excellent for both days with and without available Ts observations for both Aqua and Terra (CV Aqua R 2 results for min 0.966, mean 0.986, and max 0.967; CV Terra R 2 results for min 0.965, mean 0.987, and max 0.968). Our research shows that daily min, mean and max Ta can be reliably predicted using daily MODIS Ts data even across Israel, with high accuracy even for days without Ta or Ts data. These predictions can be used as three separate Ta exposures in epidemiology studies for better diurnal exposure assessment. Copyright © 2017 Elsevier Inc. All rights reserved.

The impact of environmental factors on marine turtle stranding rates

PubMed Central

Flint, Mark; Limpus, Colin J.; Mills, Paul C.

2017-01-01

Globally, tropical and subtropical regions have experienced an increased frequency and intensity in extreme weather events, ranging from severe drought to protracted rain depressions and cyclones, these coincided with an increased number of marine turtles subsequently reported stranded. This study investigated the relationship between environmental variables and marine turtle stranding. The environmental variables examined in this study, in descending order of importance, were freshwater discharge, monthly mean maximum and minimum air temperatures, monthly average daily diurnal air temperature difference and rainfall for the latitudinal hotspots (-27°, -25°, -23°, -19°) along the Queensland coast as well as for major embayments within these blocks. This study found that marine turtle strandings can be linked to these environmental variables at different lag times (3–12 months), and that cumulative (months added together for maximum lag) and non-cumulative (single month only) effects cause different responses. Different latitudes also showed different responses of marine turtle strandings, both in response direction and timing.Cumulative effects of freshwater discharge in all latitudes resulted in increased strandings 10–12 months later. For latitudes -27°, -25° and -23° non-cumulative effects for discharge resulted in increased strandings 7–12 months later. Latitude -19° had different results for the non-cumulative bay with strandings reported earlier (3–6 months). Monthly mean maximum and minimum air temperatures, monthly average daily diurnal air temperature difference and rainfall had varying results for each examined latitude. This study will allow first responders and resource managers to be better equipped to deal with increased marine turtle stranding rates following extreme weather events. PMID:28771635

Intense cold and mortality in Castile-La Mancha (Spain): study of mortality trigger thresholds from 1975 to 2003

NASA Astrophysics Data System (ADS)

Miron, Isidro J.; Montero, Juan Carlos; Criado-Alvarez, Juan José; Linares, Cristina; Díaz, Julio

2012-01-01

Studies on temperature-mortality time trends especially address heat, so that any contribution on the subject of cold is necessarily of interest. This study describes the modification of the lagged effects of cold on mortality in Castile-La Mancha from 1975 to 2003, with the novelty of also approaching this aspect in terms of mortality trigger thresholds. Cross-correlation functions (CCFs) were thus established with 15 lags, after application of ARIMA models to the mortality data and minimum daily temperatures (from November to March), and the results for the periods 1975-1984, 1985-1994 and 1995-2003 were then compared. In addition, daily mortality residuals for the periods 1975-1989 and 1990-2003 were related to minimum temperatures grouped in 2°C intervals, with a cold threshold temperature being obtained in cases where such residuals increased significantly ( p < 0.05) with respect to the mean for the study period. A cold-related mortality trigger threshold of -3°C was obtained for Ciudad Real for the period 1990-2003. The significant number of lags ( p < 0.05) in the CCFs declined every 10 years in Toledo (5-2-0), Cuenca (4-2-0), Albacete (4-3-0) and Ciudad Real (3-2-1). This meant that, while the trend in cold-related mortality trigger thresholds in the region could not be ascertained, it was possible to establish a reduction in the lagged effects of cold on mortality, attributable to the improvement in socio-economic conditions over the study period. Evidence was shown of the effects of cold on mortality, a finding that renders the adoption of preventive measures advisable in any case where intense cold is forecast.

Downscaling of RCM outputs for representative catchments in the Mediterranean region, for the 1951-2100 time-frame

NASA Astrophysics Data System (ADS)

Deidda, Roberto; Marrocu, Marino; Pusceddu, Gabriella; Langousis, Andreas; Mascaro, Giuseppe; Caroletti, Giulio

2013-04-01

Within the activities of the EU FP7 CLIMB project (www.climb-fp7.eu), we developed downscaling procedures to reliably assess climate forcing at hydrologically relevant scales, and applied them to six representative hydrological basins located in the Mediterranean region: Riu Mannu and Noce in Italy, Chiba in Tunisia, Kocaeli in Turkey, Thau in France, and Gaza in Palestine. As a first step towards this aim, we used daily precipitation and temperature data from the gridded E-OBS project (www.ecad.eu/dailydata), as reference fields, to rank 14 Regional Climate Model (RCM) outputs from the ENSEMBLES project (http://ensembles-eu.metoffice.com). The four best performing model outputs were selected, with the additional constraint of maintaining 2 outputs obtained from running different RCMs driven by the same GCM, and 2 runs from the same RCM driven by different GCMs. For these four RCM-GCM model combinations, a set of downscaling techniques were developed and applied, for the period 1951-2100, to variables used in hydrological modeling (i.e. precipitation; mean, maximum and minimum daily temperatures; direct solar radiation, relative humidity, magnitude and direction of surface winds). The quality of the final products is discussed, together with the results obtained after applying a bias reduction procedure to daily temperature and precipitation fields.

New developments on the homogenization of Canadian daily temperature data

NASA Astrophysics Data System (ADS)

Vincent, Lucie A.; Wang, Xiaolan L.

2010-05-01

Long-term and homogenized surface air temperature datasets had been prepared for the analysis of climate trends in Canada (Vincent and Gullett 1999). Non-climatic steps due to instruments relocation/changes and changes in observing procedures were identified in the annual mean of the daily maximum and minimum temperatures using a technique based on regression models (Vincent 1998). Monthly adjustments were derived from the regression models and daily adjustments were obtained from an interpolation procedure using the monthly adjustments (Vincent et al. 2002). Recently, new statistical tests have been developed to improve the power of detecting changepoints in climatological data time series. The penalized maximal t (PMT) test (Wang et al. 2007) and the penalized maximal F (PMF) test (Wang 2008b) were developed to take into account the position of each changepoint in order to minimize the effect of unequal and small sample size. A software package RHtestsV3 (Wang and Feng 2009) has also been developed to implement these tests to homogenize climate data series. A recursive procedure was developed to estimate the annual cycle, linear trend, and lag-1 autocorrelation of the base series in tandem, so that the effect of lag-1 autocorrelation is accounted for in the tests. A Quantile Matching (QM) algorithm (Wang 2009) was also developed for adjusting Gaussian daily data so that the empirical distributions of all segments of the detrended series match each other. The RHtestsV3 package was used to prepare a second generation of homogenized temperatures in Canada. Both the PMT test and the PMF test were applied to detect shifts in monthly mean temperature series. Reference series was used in conducting a PMT test. Whenever possible, the main causes of the shifts were retrieved through historical evidence such as the station inspection reports. Finally, the QM algorithm was used to adjust the daily temperature series for the artificial shifts identified from the respective monthly mean series. These procedures were applied to homogenize daily maximum and minimum temperatures recorded at 336 stations across Canada. During the presentation, the procedures will be summarized and their application will be illustrated throughout the provision of selected examples. References Vincent, L.A., X. Zhang, B.R. Bonsal and W.D. Hogg, 2002: Homogenization of daily temperatures over Canada. J. Climate, 15, 1322-1334. Vincent, L.A., and D.W. Gullett, 1999: Canadian historical and homogeneous temperature datasets for climate change analyses. Int. J. Climatol., 19, 1375-1388. Vincent, L.A., 1998: A technique for the identification of inhomogeneities in Canadian temperature series. J. Climate, 11, 1094-1104. Wang, X. L., 2009: A quantile matching adjustment algorithm for Gaussian data series. Climate Research Division, Atmospheric Science and Technology Directorate, Science and Technology Branch, Environment Canada. 5 pp. [Available online at http://cccma.seos.uvic.ca/ETCCDMI/software.shtml]. Wang X. L. and Y. Feng, 2009: RHtestsV3 User Manual. Climate Research Division, Atmospheric Science and Technology Directorate, Science and Technology Branch, Environment Canada. 26 pp. [Available online at http://cccma.seos.uvic.ca/ETCCDMI/software.shtml]. Wang, X. L., 2008a: Accounting for autocorrelation in detecting mean-shifts in climate data series using the penalized maximal t or F test. J. Appl. Meteor. Climatol., 47, 2423-2444. Wang, X. L., 2008b: Penalized maximal F-test for detecting undocumented mean-shifts without trend-change. J. Atmos. Oceanic Tech., 25 (No. 3), 368-384. DOI:10.1175/2007/JTECHA982.1. Wang, X. L., Q. H. Wen, and Y. Wu, 2007: Penalized maximal t test for detecting undocumented mean change in climate data series. J. Appl. Meteor. Climatol., 46 (No. 6), 916-931. DOI:10.1175/JAM2504.1

Estimation of Surface Air Temperature Over Central and Eastern Eurasia from MODIS Land Surface Temperature

NASA Technical Reports Server (NTRS)

Shen, Suhung; Leptoukh, Gregory G.

2011-01-01

Surface air temperature (T(sub a)) is a critical variable in the energy and water cycle of the Earth.atmosphere system and is a key input element for hydrology and land surface models. This is a preliminary study to evaluate estimation of T(sub a) from satellite remotely sensed land surface temperature (T(sub s)) by using MODIS-Terra data over two Eurasia regions: northern China and fUSSR. High correlations are observed in both regions between station-measured T(sub a) and MODIS T(sub s). The relationships between the maximum T(sub a) and daytime T(sub s) depend significantly on land cover types, but the minimum T(sub a) and nighttime T(sub s) have little dependence on the land cover types. The largest difference between maximum T(sub a) and daytime T(sub s) appears over the barren and sparsely vegetated area during the summer time. Using a linear regression method, the daily maximum T(sub a) were estimated from 1 km resolution MODIS T(sub s) under clear-sky conditions with coefficients calculated based on land cover types, while the minimum T(sub a) were estimated without considering land cover types. The uncertainty, mean absolute error (MAE), of the estimated maximum T(sub a) varies from 2.4 C over closed shrublands to 3.2 C over grasslands, and the MAE of the estimated minimum Ta is about 3.0 C.

Oxygen and Temperature Effects on Vertically Migrating Animals in Oxygen Minimum Zones

NASA Astrophysics Data System (ADS)

Seibel, B.

2016-02-01

Large populations of oceanic nekton and zooplankton undergo daily migrations from shallow water at night to depths greater than 200 m during the daytime. In some regions, these migrations cross extreme gradients of temperature, oxygen and carbon dioxide. Oxygen minimum zones (OMZs) are extensive and characterized by deep-water (100-800 m) oxygen partial pressures that would be lethal to most marine organisms, yet are tolerated by vertical migrators. Climate change is predicted to further deplete oxygen, and measurable reductions in oxygen have already been documented in some regions. Increases in shallow water temperature and carbon dioxide are occurring simultaneously. Oxygen levels and temperature are important drivers of biodiversity and distribution, and documented changes in community structure and function are reportedly associated with OMZ expansion and warming. Here I answer fundamental questions concerning zooplankton distributions, adaptations, and functions in oxygen minimum zones. In particular I report that metabolic suppression is a common strategy that facilitates diel occupancy of extreme hypoxia in many oceanic taxa. Anaerobic metabolic pathways play a minimal role in compensating for reduced aerobic ATP production. Numerous epigenetic mechanisms lead to reductions in energetically costly cellular processes, such as transcription and translation. Total metabolism is reduced by 50% or more during exposure to levels of hypoxia that characterize the daytime habitat for most vertically-migrating zooplankton. I further show that many migrators approach their upper thermal maximum in shallow water at night. Thus expanding OMZs and global warming may together compress the habitable depth range for many species.

Diurnal warming in shallow coastal seas: Observations from the Caribbean and Great Barrier Reef regions

NASA Astrophysics Data System (ADS)

Zhu, X.; Minnett, P. J.; Berkelmans, R.; Hendee, J.; Manfrino, C.

2014-07-01

A good understanding of diurnal warming in the upper ocean is important for the validation of satellite-derived sea surface temperature (SST) against in-situ buoy data and for merging satellite SSTs taken at different times of the same day. For shallow coastal regions, better understanding of diurnal heating could also help improve monitoring and prediction of ecosystem health, such as coral reef bleaching. Compared to its open ocean counterpart which has been studied extensively and modeled with good success, coastal diurnal warming has complicating localized characteristics, including coastline geometry, bathymetry, water types, tidal and wave mixing. Our goal is to characterize coastal diurnal warming using two extensive in-situ temperature and weather datasets from the Caribbean and Great Barrier Reef (GBR), Australia. Results showed clear daily warming patterns in most stations from both datasets. For the three Caribbean stations where solar radiation is the main cause of daily warming, the mean diurnal warming amplitudes were about 0.4 K at depths of 4-7 m and 0.6-0.7 K at shallower depths of 1-2 m; the largest warming value was 2.1 K. For coral top temperatures of the GBR, 20% of days had warming amplitudes >1 K, with the largest >4 K. The bottom warming at shallower sites has higher daily maximum temperatures and lower daily minimum temperatures than deeper sites nearby. The averaged daily warming amplitudes were shown to be closely related to daily average wind speed and maximum insolation, as found in the open ocean. Diurnal heating also depends on local features including water depth, location on different sections of the reef (reef flat vs. reef slope), the relative distance from the barrier reef chain (coast vs. lagoon stations vs. inner barrier reef sites vs. outer rim sites); and the proximity to the tidal inlets. In addition, the influence of tides on daily temperature changes and its relative importance compared to solar radiation was quantified by calculating the ratio of power spectrum densities at the principal lunar semidiurnal M2 tide versus 24-hour cycle frequency representing mainly solar radiation forcing, i.e., (PSDM2/PSD24). Despite the fact that GBR stations are generally located at regions with large tidal changes, the tidal effects were modest: 80% of stations showed value of (PSDM2/PSD24) of less than 10%.

Body temperature, thermoregulatory behaviour and pelt characteristics of three colour morphs of springbok (Antidorcas marsupialis).

PubMed

Hetem, Robyn S; de Witt, Brenda A; Fick, Linda G; Fuller, Andrea; Kerley, Graham I H; Meyer, Leith C R; Mitchell, Duncan; Maloney, Shane K

2009-03-01

Using intra-abdominal miniature data loggers, we measured core body temperature in female springbok (Antidorcas marsupialis) of three colour morphs (black, normal and white), free-living in the Karoo, South Africa, for one year. During winter, white springbok displayed lower daily minimum body temperatures (37.4+/-0.5 degrees C), than both black (38.1+/-0.3 degrees C) and normal (38.0+/-0.6 degrees C) springbok. During spring, black springbok displayed higher daily maximum body temperatures (40.7+/-0.1 degrees C) than both white (40.2+/-0.2 degrees C) and normal (40.2+/-0.2 degrees C) springbok. These high maximum body temperatures were associated with larger daily amplitudes of nychthemeral rhythm of body temperature (2.0+/-0.2 degrees C), than that of white (1.6+/-0.1 degrees C) and normal (1.7+/-0.2 degrees C) springbok. Biophysical properties of sample springbok pelts were consistent with these patterns, as the black springbok pelt showed lower reflectance in the visible spectral range, and higher heat load from simulated solar radiation, than did the pelts of the other two springbok. Black springbok had lower diurnal activity in winter, consistent with them having to forage less because their metabolic cost of homeothermy was lower, but were disadvantaged in hot periods. White springbok, by contrast, were more protected from solar heat load, but potentially less able to meet the energy cost of homeothermy in winter. Thus energy considerations may underlie the rarity of the springbok colour morphs.

Minimum daily core body temperature in western grey kangaroos decreases as summer advances: a seasonal pattern, or a direct response to water, heat or energy supply?

PubMed

Maloney, Shane K; Fuller, Andrea; Meyer, Leith C R; Kamerman, Peter R; Mitchell, Graham; Mitchell, Duncan

2011-06-01

Using implanted temperature loggers, we measured core body temperature in nine western grey kangaroos every 5 min for 24 to 98 days in spring and summer. Body temperature was highest at night and decreased rapidly early in the morning, reaching a nadir at 10:00 h, after ambient temperature and solar radiation had begun to increase. On hotter days, the minimum morning body temperature was lower than on cooler days, decreasing from a mean of 36.2°C in the spring to 34.0°C in the summer. This effect correlated better with the time of the year than with proximate thermal stressors, suggesting that either season itself or some factor correlated with season, such as food availability, caused the change. Water saving has been proposed as a selective advantage of heterothermy in other large mammals, but in kangaroos the water savings would have been small and not required in a reserve with permanent standing water. We calculate that the lower core temperature could provide energy savings of nearly 7%. It is likely that the heterothermy that we observed on hot days results either from decreased energy intake during the dry season or from a seasonal pattern entrained in the kangaroos that presumably has been selected for because of decreased energy availability during the dry season.

Reduced diurnal temperature range does not change warming impacts on ecosystem carbon balance of Mediterranean grassland mesocosms

DOE PAGES

Phillips, Claire L.; Gregg, Jillian W.; Wilson, John K.

2011-11-01

Daily minimum temperature (T min) has increased faster than daily maximum temperature (T max) in many parts of the world, leading to decreases in diurnal temperature range (DTR). Projections suggest these trends are likely to continue in many regions, particularly northern latitudes and in arid regions. Despite wide speculation that asymmetric warming has different impacts on plant and ecosystem production than equal-night-and-day warming, there has been little direct comparison of these scenarios. Reduced DTR has also been widely misinterpreted as a result of night-only warming, when in fact T min occurs near dawn, indicating higher morning as well as nightmore » temperatures. We report on the first experiment to examine ecosystem-scale impacts of faster increases in T min than T max, using precise temperature controls to create realistic diurnal temperature profiles with gradual day-night temperature transitions and elevated early morning as well as night temperatures. Studying a constructed grassland ecosystem containing species native to Oregon, USA, we found the ecosystem lost more carbon at elevated than ambient temperatures, but was unaffected by the 3ºC difference in DTR between symmetric warming (constantly ambient +3.5ºC) and asymmetric warming (dawn T min=ambient +5ºC, afternoon T max= ambient +2ºC). Reducing DTR had no apparent effect on photosynthesis, likely because temperatures were most different in the morning and late afternoon when light was low. Respiration was also similar in both warming treatments, because respiration temperature sensitivity was not sufficient to respond to the limited temperature differences between asymmetric and symmetric warming. We concluded that changes in daily mean temperatures, rather than changes in T min/T max, were sufficient for predicting ecosystem carbon fluxes in this reconstructed Mediterranean grassland system.« less

Modeling the contributions of global air temperature, synoptic-scale phenomena and soil moisture to near-surface static energy variability using artificial neural networks

NASA Astrophysics Data System (ADS)

Pryor, Sara C.; Sullivan, Ryan C.; Schoof, Justin T.

2017-12-01

The static energy content of the atmosphere is increasing on a global scale, but exhibits important subglobal and subregional scales of variability and is a useful parameter for integrating the net effect of changes in the partitioning of energy at the surface and for improving understanding of the causes of so-called warming holes (i.e., locations with decreasing daily maximum air temperatures (T) or increasing trends of lower magnitude than the global mean). Further, measures of the static energy content (herein the equivalent potential temperature, θe) are more strongly linked to excess human mortality and morbidity than air temperature alone, and have great relevance in understanding causes of past heat-related excess mortality and making projections of possible future events that are likely to be associated with negative human health and economic consequences. New nonlinear statistical models for summertime daily maximum and minimum θe are developed and used to advance understanding of drivers of historical change and variability over the eastern USA. The predictor variables are an index of the daily global mean temperature, daily indices of the synoptic-scale meteorology derived from T and specific humidity (Q) at 850 and 500 hPa geopotential heights (Z), and spatiotemporally averaged soil moisture (SM). SM is particularly important in determining the magnitude of θe over regions that have previously been identified as exhibiting warming holes, confirming the key importance of SM in dictating the partitioning of net radiation into sensible and latent heat and dictating trends in near-surface T and θe. Consistent with our a priori expectations, models built using artificial neural networks (ANNs) out-perform linear models that do not permit interaction of the predictor variables (global T, synoptic-scale meteorological conditions and SM). This is particularly marked in regions with high variability in minimum and maximum θe, where more complex models built using ANN with multiple hidden layers are better able to capture the day-to-day variability in θe and the occurrence of extreme maximum θe. Over the entire domain, the ANN with three hidden layers exhibits high accuracy in predicting maximum θe > 347 K. The median hit rate for maximum θe > 347 K is > 0.60, while the median false alarm rate is ≈ 0.08.

Downscaling GCM Output with Genetic Programming Model

NASA Astrophysics Data System (ADS)

Shi, X.; Dibike, Y. B.; Coulibaly, P.

2004-05-01

Climate change impact studies on watershed hydrology require reliable data at appropriate spatial and temporal resolution. However, the outputs of the current global climate models (GCMs) cannot be used directly because GCM do not provide hourly or daily precipitation and temperature reliable enough for hydrological modeling. Nevertheless, we can get more reliable data corresponding to future climate scenarios derived from GCM outputs using the so called 'downscaling techniques'. This study applies Genetic Programming (GP) based technique to downscale daily precipitation and temperature values at the Chute-du-Diable basin of the Saguenay watershed in Canada. In applying GP downscaling technique, the objective is to find a relationship between the large-scale predictor variables (NCEP data which provide daily information concerning the observed large-scale state of the atmosphere) and the predictand (meteorological data which describes conditions at the site scale). The selection of the most relevant predictor variables is achieved using the Pearson's coefficient of determination ( R2) (between the large-scale predictor variables and the daily meteorological data). In this case, the period (1961 - 2000) is identified to represent the current climate condition. For the forty years of data, the first 30 years (1961-1990) are considered for calibrating the models while the remaining ten years of data (1991-2000) are used to validate those models. In general, the R2 between the predictor variables and each predictand is very low in case of precipitation compared to that of maximum and minimum temperature. Moreover, the strength of individual predictors varies for every month and for each GP grammar. Therefore, the most appropriate combination of predictors has to be chosen by looking at the output analysis of all the twelve months and the different GP grammars. During the calibration of the GP model for precipitation downscaling, in addition to the mean daily precipitation and daily precipitation variability for each month, monthly average dry and wet-spell lengths are also considered as performance criteria. For the cases of Tmax and Tmin, means and variances of these variables corresponding to each month were considered as performance criteria. The GP downscaling results show satisfactory agreement between the observed daily temperature (Tmax and Tmin) and the simulated temperature. However, the downscaling results for the daily precipitation still require some improvement - suggesting further investigation of other grammars. KEY WORDS: Climate change; GP downscaling; GCM.

Aspects of Hydrological Modelling In The Punjab Himalayan and Karakoram Ranges, Pakistan

NASA Astrophysics Data System (ADS)

Loukas, A.; Khan, M. I.; Quick, M. C.

Various aspects of hydrologic modelling of high mountainous basins in the Punjab Hi- malayan and Karakoram ranges of Northern Pakistan were studied. The runoff from three basins in this region was simulated using the U.B.C. watershed model, which re- quires limited meteorological data of minimum and maximum daily temperature and precipitation. The structure of the model is based on the concept that the hydrolog- ical behavior is a function of elevation and thus, a watershed is conceptualized as a number of elevational zones. A simplified energy budget approach, which is based on daily maximum and minimum temperature and can account for forested and open areas, and aspect and latitude, is used in the U.B.C. model for the estimation of the snowmelt and glacier melt. The studied basins have different hydrological responses and limited data. The runoff from the first basin, the Astore basin, is mainly gener- ated by snowmelt. In the second basin, the Kunhar basin, the runoff is generated by snowmelt but significant redistribution of snow, caused by snow avalanches, affect the runoff generation. The third basin, the Hunza basin, is a highly glacierized basin and its runoff is mainly generated by glacier melt. The application of the U.B.C. watershed model to these three basins showed that the model could estimate reasonably well the runoff generated by the different components.

Effects of weather on survival in populations of boreal toads in Colorado

USGS Publications Warehouse

Scherer, R. D.; Muths, E.; Lambert, B.A.

2008-01-01

Understanding the relationships between animal population demography and the abiotic and biotic elements of the environments in which they live is a central objective in population ecology. For example, correlations between weather variables and the probability of survival in populations of temperate zone amphibians may be broadly applicable to several species if such correlations can be validated for multiple situations. This study focuses on the probability of survival and evaluates hypotheses based on six weather variables in three populations of Boreal Toads (Bufo boreas) from central Colorado over eight years. In addition to suggesting a relationship between some weather variables and survival probability in Boreal Toad populations, this study uses robust methods and highlights the need for demographic estimates that are precise and have minimal bias. Capture-recapture methods were used to collect the data, and the Cormack-Jolly-Seber model in program MARK was used for analysis. The top models included minimum daily winter air temperature, and the sum of the model weights for these models was 0.956. Weaker support was found for the importance of snow depth and the amount of environmental moisture in winter in modeling survival probability. Minimum daily winter air temperature was positively correlated with the probability of survival in Boreal Toads at other sites in Colorado and has been identified as an important covariate in studies in other parts of the world. If air temperatures are an important component of survival for Boreal Toads or other amphibians, changes in climate may have profound impacts on populations. Copyright 2008 Society for the Study of Amphibians and Reptiles.

Geographical and Geomorphological Effects on Air Temperatures in the Columbia Basin's Signature Vineyards

NASA Astrophysics Data System (ADS)

Olson, L.; Pogue, K. R.; Bader, N.

2012-12-01

The Columbia Basin of Washington and Oregon is one of the most productive grape-growing areas in the United States. Wines produced in this region are influenced by their terroir - the amalgamation of physical and cultural elements that influence grapes grown at a particular vineyard site. Of the physical factors, climate, and in particular air temperature, has been recognized as a primary influence on viticulture. Air temperature directly affects ripening in the grapes. Proper fruit ripening, which requires precise and balanced levels of acid and sugar, and the accumulation of pigment in the grape skin, directly correlates with the quality of wine produced. Many features control air temperature within a particular vineyard. Elevation, latitude, slope, and aspect all converge to form complex relationships with air temperatures; however, the relative degree to which these attributes affect temperatures varies between regions and is not well understood. This study examines the influence of geography and geomorphology on air temperatures within the American Viticultural Areas (AVAs) of the Columbia Basin in eastern Washington and Oregon. The premier vineyards within each AVA, which have been recognized for producing high-quality wine, were equipped with air temperature monitoring stations that collected hourly temperature measurements. A variety of temperature statistics were calculated, including daily average, maximum, and minimum temperatures. From these values, average diurnal variation and growing degree-days (10°C) were calculated. A variety of other statistics were computed, including date of first and last frost and time spent below a minimum temperature threshold. These parameters were compared to the vineyard's elevation, latitude, slope, aspect, and local topography using GPS, ArcCatalog, and GIS in an attempt to determine their relative influences on air temperatures. From these statistics, it was possible to delineate two trends of temperature variation controlled by elevation. In some AVAs, such as Walla Walla Valley and Red Mountain, average air temperatures increased with elevation because of the effect of cold air pooling on valley floors. In other AVAs, such as Horse Heaven Hills, Lake Chelan and Columbia Gorge, average temperatures decreased with elevation due to the moderating influences of the Columbia River and Lake Chelan. Other temperature statistics, including average diurnal range and maximum and minimum temperature, were influenced by relative topography, including local topography and slope. Vineyards with flat slopes that had low elevations relative to their surroundings had larger diurnal variations and lower maximum and minimum temperatures than vineyards with steeper slopes that were high relative to their surroundings.

Which metric of ambient ozone to predict daily mortality?

NASA Astrophysics Data System (ADS)

Moshammer, Hanns; Hutter, Hans-Peter; Kundi, Michael

2013-02-01

It is well known that ozone concentration is associated with daily cause specific mortality. But which ozone metric is the best predictor of the daily variability in mortality? We performed a time series analysis on daily deaths (all causes, respiratory and cardiovascular causes as well as death in elderly 65+) in Vienna for the years 1991-2009. We controlled for seasonal and long term trend, day of the week, temperature and humidity using the same basic model for all pollutant metrics. We found model fit was best for same day variability of ozone concentration (calculated as the difference between daily hourly maximum and minimum) and hourly maximum. Of these the variability displayed a more linear dose-response function. Maximum 8 h moving average and daily mean value performed not so well. Nitrogen dioxide (daily mean) in comparison performed better when previous day values were assessed. Same day ozone and previous day nitrogen dioxide effect estimates did not confound each other. Variability in daily ozone levels or peak ozone levels seem to be a better proxy of a complex reactive secondary pollutant mixture than daily average ozone levels in the Middle European setting. If this finding is confirmed this would have implications for the setting of legally binding limit values.

AgRISTARS: Supporting research. Spring small grains planting date distribution model

NASA Technical Reports Server (NTRS)

Hodges, T.; Artley, J. A. (Principal Investigator)

1981-01-01

A model was developed using 996 planting dates at 51 LANDSAT segments for spring wheat and spring barley in Minnesota, Montana, North Dakota, and South Dakota in 1979. Daily maximum and minimum temperatures and precipitation were obtained from the cooperative weather stations nearest to each segment. The model uses a growing degree day summation modified for daily temperature range to estimate the beginning of planting and uses a soil surface wetness variable to estimate how a fixed number of planting days are distributed after planting begins. For 1979, the model predicts first, median, and last planting dates with root mean square errors of 7.91, 6.61, and 7.09 days, respectively. The model also provides three or four dates to represent periods of planting activity within the planting season. Although the full model was not tested on an independent data set, it may be suitable in areas other than the U.S. Great Plains where spring small grains are planted as soon as soil and air temperatures become warm enough in the spring for plant growth.

Evaluation of extreme temperature events in northern Spain based on process control charts

NASA Astrophysics Data System (ADS)

Villeta, M.; Valencia, J. L.; Saá, A.; Tarquis, A. M.

2018-02-01

Extreme climate events have recently attracted the attention of a growing number of researchers because these events impose a large cost on agriculture and associated insurance planning. This study focuses on extreme temperature events and proposes a new method for their evaluation based on statistical process control tools, which are unusual in climate studies. A series of minimum and maximum daily temperatures for 12 geographical areas of a Spanish region between 1931 and 2009 were evaluated by applying statistical process control charts to statistically test whether evidence existed for an increase or a decrease of extreme temperature events. Specification limits were determined for each geographical area and used to define four types of extreme anomalies: lower and upper extremes for the minimum and maximum anomalies. A new binomial Markov extended process that considers the autocorrelation between extreme temperature events was generated for each geographical area and extreme anomaly type to establish the attribute control charts for the annual fraction of extreme days and to monitor the occurrence of annual extreme days. This method was used to assess the significance of changes and trends of extreme temperature events in the analysed region. The results demonstrate the effectiveness of an attribute control chart for evaluating extreme temperature events. For example, the evaluation of extreme maximum temperature events using the proposed statistical process control charts was consistent with the evidence of an increase in maximum temperatures during the last decades of the last century.

Planting data and wheat yield models. [Kansas, South Dakota, and U.S.S.R.

NASA Technical Reports Server (NTRS)

Feyerherm, A. M. (Principal Investigator)

1977-01-01

The author has identified the following significant results. A variable date starter model for spring wheat depending on temperature was more precise than a fixed date model. The same conclusions for fall-planted wheat were not reached. If the largest and smallest of eight temperatures were used to estimate daily maximum and minimum temperatures; respectively, a 1-4 F bias would be introduced into these extremes. For Kansas, a reduction of 0.5 bushels/acre in the root-mean-square-error between model and SRS yields was achieved by a six fold increase (7 to 42) in the density of weather stations. An additional reduction of 0.3 b/A was achieved by incorporating losses due to rusts in the model.

Long-Term Daily and Monthly Climate Records from Stations Across the Contiguous United States (U.S.Historical Climatology Network) (NDP-019)

DOE Data Explorer

Menne, M. J. [National Climatic Data Center, National Oceanic and Atmospheric Administration; Williams, Jr., C. N. [National Climatic Data Center, National Oceanic and Atmospheric Administration; Vose, R. S. [National Climatic Data Center, National Oceanic and Atmospheric Administration

2016-01-01

The United States Historical Climatology Network (USHCN) is a high-quality data set of daily and monthly records of basic meteorological variables from 1218 observing stations across the 48 contiguous United States. Daily data include observations of maximum and minimum temperature, precipitation amount, snowfall amount, and snow depth; monthly data consist of monthly-averaged maximum, minimum, and mean temperature and total monthly precipitation. Most of these stations are U.S. Cooperative Observing Network stations located generally in rural locations, while some are National Weather Service First-Order stations that are often located in more urbanized environments. The USHCN has been developed over the years at the National Oceanic and Atmospheric Administration's (NOAA) National Climatic Data Center (NCDC) to assist in the detection of regional climate change. Furthermore, it has been widely used in analyzing U.S. climte. The period of record varies for each station. USHCN stations were chosen using a number of criteria including length of record, percent of missing data, number of station moves and other station changes that may affect data homogeneity, and resulting network spatial coverage. Collaboration between NCDC and CDIAC on the USHCN project dates to the 1980s (Quinlan et al. 1987). At that time, in response to the need for an accurate, unbiased, modern historical climate record for the United States, the Global Change Research Program of the U.S. Department of Energy and NCDC chose a network of 1219 stations in the contiguous United States that would become a key baseline data set for monitoring U.S. climate. This initial USHCN data set contained monthly data and was made available free of charge from CDIAC. Since then it has been comprehensively updated several times [e.g., Karl et al. (1990) and Easterling et al. (1996)]. The initial USHCN daily data set was made available through CDIAC via Hughes et al. (1992) and contained a 138-station subset of the USHCN. This product was updated by Easterling et al. (1999) and expanded to include 1062 stations. In 2009 the daily USHCN dataset was expanded to include all 1218 stations in the USHCN.

Longer-Term Impact of High and Low Temperature on Mortality: An International Study to Clarify Length of Mortality Displacement

PubMed Central

Bell, Michelle L.; de Sousa Zanotti Stagliorio Coelho, Micheline; Leon Guo, Yue-Liang; Guo, Yuming; Goodman, Patrick; Hashizume, Masahiro; Honda, Yasushi; Kim, Ho; Lavigne, Eric; Michelozzi, Paola; Hilario Nascimento Saldiva, Paulo; Schwartz, Joel; Scortichini, Matteo; Sera, Francesco; Tobias, Aurelio; Tong, Shilu; Wu, Chang-fu; Zanobetti, Antonella; Zeka, Ariana; Gasparrini, Antonio

2017-01-01

Background: In many places, daily mortality has been shown to increase after days with particularly high or low temperatures, but such daily time-series studies cannot identify whether such increases reflect substantial life shortening or short-term displacement of deaths (harvesting). Objectives: To clarify this issue, we estimated the association between annual mortality and annual summaries of heat and cold in 278 locations from 12 countries. Methods: Indices of annual heat and cold were used as predictors in regressions of annual mortality in each location, allowing for trends over time and clustering of annual count anomalies by country and pooling estimates using meta-regression. We used two indices of annual heat and cold based on preliminary standard daily analyses: a) mean annual degrees above/below minimum mortality temperature (MMT), and b) estimated fractions of deaths attributed to heat and cold. The first index was simpler and matched previous related research; the second was added because it allowed the interpretation that coefficients equal to 0 and 1 are consistent with none (0) or all (1) of the deaths attributable in daily analyses being displaced by at least 1 y. Results: On average, regression coefficients of annual mortality on heat and cold mean degrees were 1.7% [95% confidence interval (CI): 0.3, 3.1] and 1.1% (95% CI: 0.6, 1.6) per degree, respectively, and daily attributable fractions were 0.8 (95% CI: 0.2, 1.3) and 1.1 (95% CI: 0.9, 1.4). The proximity of the latter coefficients to 1.0 provides evidence that most deaths found attributable to heat and cold in daily analyses were brought forward by at least 1 y. Estimates were broadly robust to alternative model assumptions. Conclusions: These results provide strong evidence that most deaths associated in daily analyses with heat and cold are displaced by at least 1 y. https://doi.org/10.1289/EHP1756 PMID:29084393

Variability in daily pH scales with coral reef accretion and community structure

NASA Astrophysics Data System (ADS)

Price, N.; Martz, T.; Brainard, R. E.; Smith, J.

2011-12-01

Little is known about natural variability in pH in coastal waters and how resident organisms respond to current nearshore seawater conditions. We used autonomous sensors (SeaFETs) to record temperature and, for the first time, pH with high temporal (hourly observations; 7 months of sampling) resolution on the reef benthos (5-10m depth) at several islands (Kingman, Palmyra and Jarvis) within the newly designated Pacific Remote Island Areas Marine National Monument (PRIMNM) in the northern Line Islands; these islands are uninhabited and lack potentially confounding local impacts (e.g. pollution and overfishing). Recorded benthic pH values were compared with regional means and minimum thresholds based on seasonal amplitude estimated from surrounding open-ocean climatological data, which represent seawater chemistry values in the absence of feedback from the reef. Each SeaFET sensor was co-located with replicate Calcification/Acidification Units (CAUs) designed to quantify species abundances and net community calcification rates so we could determine which, if any, metrics of natural variability in benthic pH and temperature were related to community development and reef accretion rates. The observed range in daily pH encompassed maximums reported from the last century (8.104 in the early evening) to minimums approaching projected levels within the next 100 yrs (7.824 at dawn) for pelagic waters. Net reef calcification rates, measured as calcium carbonate accretion on CAUs, varied within and among islands and were comparable with rates measured from the Pacific and Caribbean using chemistry-based approaches. Benthic species assemblages on the CAUs were differentiated by the presence of calcifying and fleshy taxa (CAP analysis, mean allocation success 80%, δ2 = 0.886, P = <0.001). In general, accretion rates were higher at sites that had a greater number of hours at high pH values each day. Where daily pH failed to exceed climatological seasonal minimum thresholds, net accretion was slower and fleshy, non-calcifying benthic organisms dominated. Natural variation in benthic pH offers a unique opportunity to study ecological consequences of likely future ocean chemistry.

Heat waves in Senegal : detection, characterization and associated processes.

NASA Astrophysics Data System (ADS)

Gnacoussa Sambou, Marie Jeanne; Janicot, Serge; Badiane, Daouda; Pohl, Benjamin; Dieng, Abdou L.; Gaye, Amadou T.

2017-04-01

Atmospheric configuration and synoptic evolution of patterns associated with Senegalese heat wave (HW) are examined on the period 1979-2014 using the Global Surface Summary of the Day (GSOD) observational database and ERA-Interim reanalysis. Since there is no objective and uniform definition of HW events, threshold methods based on atmospheric variables as daily maximum (Tmax) / minimum (Tmin) temperatures and daily mean apparent temperature (AT) are used to define HW threshold detection. Each criterion is related to a specific category of HW events: Tmax (warm day events), Tmin (warm night events) and AT (combining temperature and moisture). These definitions are used in order to characterize as well as possible the warm events over the Senegalese regions (oceanic versus continental region). Statistics on time evolution and spatial distribution of warm events are carried out over the 2 seasons of maximum temperature (March-May and October-November). For each season, a composite of HW events, as well as the most extended event over Senegal (as a case study) are analyzed using usual atmospheric fields (sea level pressure, geopotential height, total column water content, wind components, 2m temperature). This study is part of the project ACASIS (https://acasis.locean-ipsl.upmc.fr/doku.php) on heat waves occurrences over the Sahel and their impact on health. Keywords: heat wave, Senegal, ACASIS.

33 CFR 154.1130 - Requirements for prepositioned response equipment.

Code of Federal Regulations, 2012 CFR

2012-07-01

... Additional Response Plan Requirements for a Trans-Alaska Pipeline Authorization Act (TAPAA) Facility...: (a) On-water recovery equipment with a minimum effective daily recovery rate of 30,000 barrels... of a discharge. (c) On-water recovery equipment with a minimum effective daily recovery rate of 40...

33 CFR 154.1130 - Requirements for prepositioned response equipment.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Additional Response Plan Requirements for a Trans-Alaska Pipeline Authorization Act (TAPAA) Facility...: (a) On-water recovery equipment with a minimum effective daily recovery rate of 30,000 barrels... of a discharge. (c) On-water recovery equipment with a minimum effective daily recovery rate of 40...

33 CFR 154.1130 - Requirements for prepositioned response equipment.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Additional Response Plan Requirements for a Trans-Alaska Pipeline Authorization Act (TAPAA) Facility...: (a) On-water recovery equipment with a minimum effective daily recovery rate of 30,000 barrels... of a discharge. (c) On-water recovery equipment with a minimum effective daily recovery rate of 40...

33 CFR 154.1130 - Requirements for prepositioned response equipment.

Code of Federal Regulations, 2014 CFR

2014-07-01

... Additional Response Plan Requirements for a Trans-Alaska Pipeline Authorization Act (TAPAA) Facility...: (a) On-water recovery equipment with a minimum effective daily recovery rate of 30,000 barrels... of a discharge. (c) On-water recovery equipment with a minimum effective daily recovery rate of 40...

Developing a 1 km resolution daily air temperature dataset for urban and surrounding areas in the conterminous United States

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

Li, Xiaoma; Zhou, Yuyu; Asrar, Ghassem R.

High spatiotemporal resolution air temperature (Ta) datasets are increasingly needed for assessing the impact of temperature change on people, ecosystems, and energy system, especially in the urban domains. However, such datasets are not widely available because of the large spatiotemporal heterogeneity of Ta caused by complex biophysical and socioeconomic factors such as built infrastructure and human activities. In this study, we developed a 1-km gridded dataset of daily minimum Ta (Tmin) and maximum Ta (Tmax), and the associated uncertainties, in urban and surrounding areas in the conterminous U.S. for the 2003–2016 period. Daily geographically weighted regression (GWR) models were developedmore » and used to interpolate Ta using 1 km daily land surface temperature and elevation as explanatory variables. The leave-one-out cross-validation approach indicates that our method performs reasonably well, with root mean square errors of 2.1 °C and 1.9 °C, mean absolute errors of 1.5 °C and 1.3 °C, and R 2 of 0.95 and 0.97, for Tmin and Tmax, respectively. The resulting dataset captures reasonably the spatial heterogeneity of Ta in the urban areas, and also captures effectively the urban heat island (UHI) phenomenon that Ta rises with the increase of urban development (i.e., impervious surface area). The new dataset is valuable for studying environmental impacts of urbanization such as UHI and other related effects (e.g., on building energy consumption and human health). The proposed methodology also shows a potential to build a long-term record of Ta worldwide, to fill the data gap that currently exists for studies of urban systems.« less

Recent increase in maximum temperature at the tropical treeline of North America

NASA Astrophysics Data System (ADS)

Biondi, F.

2009-12-01

There are only a handful of weather stations above 3000 m in the entire American Cordillera, from Alaska to Tierra del Fuego. I present a surface instrumental record of high elevation (treeline) ecoclimatic variables for the tropics of North America. Besides its high elevation (3760 m) and tropical (19.5°N) features, this site is also located in the North American Monsoon System, making the data relevant to a broad suite of environmental issues. Automated half-hour data collected on Nevado de Colima, Mexico, from 2001 to 2009 show an increase in maximum temperature during the dry winter season, while incoming solar radiation remained stationary. Since minimum temperature did not increase as much, the daily range of air temperature has expanded over time. At this elevation, with average daily barometric pressure of 655 ± 1.4 hPa, maximum temperatures reflect the annual and daily energy cycle because of the dominant role of ground heating caused by incoming shortwave radiation. In fact, spring is the warmest season in this area, as it is followed by pronounced cooling during the summer monsoon because of increased cloudiness. The observed warming is associated with reduced wind speed, especially around solar noon, and is therefore most likely driven by reduced atmospheric flow, suggesting that the energy and water balance of high elevation tropical ecosystems are changing in unexpected ways. Further measurements and regional modeling experiments are therefore needed, given the staggering consequences this could have for any resource managers and policy makers concerned with trans-boundary (Mexico-US) terrestrial, coastal, and oceanic issues.

Raised temperatures over the Kericho tea estates: revisiting the climate in the East African highlands malaria debate.

PubMed

Omumbo, Judith A; Lyon, Bradfield; Waweru, Samuel M; Connor, Stephen J; Thomson, Madeleine C

2011-01-17

Whether or not observed increases in malaria incidence in the Kenyan Highlands during the last thirty years are associated with co-varying changes in local temperature, possibly connected to global changes in climate, has been debated for over a decade. Studies, using differing data sets and methodologies, produced conflicting results regarding the occurrence of temperature trends and their likelihood of being responsible, at least in part, for the increases in malaria incidence in the highlands of western Kenya. A time series of quality controlled daily temperature and rainfall data from Kericho, in the Kenyan Highlands, may help resolve the controversy. If significant temperature trends over the last three decades have occurred then climate should be included (along with other factors such as land use change and drug resistance) as a potential driver of the observed increases in malaria in the region. Over 30 years (1 January 1979 to 31 December 2009) of quality controlled daily observations ( > 97% complete) of maximum, minimum and mean temperature were used in the analysis of trends at Kericho meteorological station, sited in a tea growing area of Kenya's western highlands. Inhomogeneities in all the time series were identified and corrected. Linear trends were identified via a least-squares regression analysis with statistical significance assessed using a two-tailed t-test. These 'gold standard' meteorological observations were compared with spatially interpolated temperature datasets that have been developed for regional or global applications. The relationship of local climate processes with larger climate variations, including tropical sea surface temperatures (SST), and El Niño-Southern Oscillation (ENSO) was also assessed. An upward trend of ≈0.2°C/decade was observed in all three temperature variables (P < 0.01). Mean temperature variations in Kericho were associated with large-scale climate variations including tropical SST (r = 0.50; p < 0.01). Local rainfall was found to have inverse effects on minimum and maximum temperature. Three versions of a spatially interpolated temperature data set showed markedly different trends when compared with each other and with the Kericho station observations. This study presents evidence of a warming trend in observed maximum, minimum and mean temperatures at Kericho during the period 1979 to 2009 using gold standard meteorological observations. Although local factors may be contributing to these trends, the findings are consistent with variability and trends that have occurred in correlated global climate processes. Climate should therefore not be dismissed as a potential driver of observed increases in malaria seen in the region during recent decades, however its relative importance compared to other factors needs further elaboration. Climate services, pertinent to the achievement of development targets such as the Millennium Development Goals and the analysis of infectious disease in the context of climate variability and change are being developed and should increase the availability of relevant quality controlled climate data for improving development decisions. The malaria community should seize this opportunity to make their needs heard.

Statistical modeling of daily and subdaily stream temperatures: Application to the Methow River Basin, Washington

NASA Astrophysics Data System (ADS)

Caldwell, R. J.; Gangopadhyay, S.; Bountry, J.; Lai, Y.; Elsner, M. M.

2013-07-01

Management of water temperatures in the Columbia River Basin (Washington) is critical because water projects have substantially altered the habitat of Endangered Species Act listed species, such as salmon, throughout the basin. This is most important in tributaries to the Columbia, such as the Methow River, where the spawning and rearing life stages of these cold water fishes occurs. Climate change projections generally predict increasing air temperatures across the western United States, with less confidence regarding shifts in precipitation. As air temperatures rise, we anticipate a corresponding increase in water temperatures, which may alter the timing and availability of habitat for fish reproduction and growth. To assess the impact of future climate change in the Methow River, we couple historical climate and future climate projections with a statistical modeling framework to predict daily mean stream temperatures. A K-nearest neighbor algorithm is also employed to: (i) adjust the climate projections for biases compared to the observed record and (ii) provide a reference for performing spatiotemporal disaggregation in future hydraulic modeling of stream habitat. The statistical models indicate the primary drivers of stream temperature are maximum and minimum air temperature and stream flow and show reasonable skill in predictability. When compared to the historical reference time period of 1916-2006, we conclude that increases in stream temperature are expected to occur at each subsequent time horizon representative of the year 2020, 2040, and 2080, with an increase of 0.8 ± 1.9°C by the year 2080.

Climate Extreme Events over Northern Eurasia in Changing Climate

NASA Astrophysics Data System (ADS)

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

2014-12-01

During the period of widespread instrumental observations in Northern Eurasia, the annual surface air temperature has increased by 1.5°C. Close to the north in the Arctic Ocean, the late summer sea ice extent has decreased by 40% providing a near-infinite source of water vapor for the dry Arctic atmosphere in the early cold season months. The contemporary sea ice changes are especially visible in the Eastern Hemisphere All these factors affect the change extreme events. Daily and sub-daily data of 940 stations to analyze variations in the space time distribution of extreme temperatures, precipitation, and wind over Russia were used. Changing in number of days with thaw over Russia was described. The total seasonal numbers of days, when daily surface air temperatures (wind, precipitation) were found to be above (below) selected thresholds, were used as indices of climate extremes. Changing in difference between maximum and minimum temperature (DTR) may produce a variety of effects on biological systems. All values falling within the intervals ranged from the lowest percentile to the 5th percentile and from the 95th percentile to the highest percentile for the time period of interest were considered as daily extremes. The number of days, N, when daily temperatures (wind, precipitation, DTR) were within the above mentioned intervals, was determined for the seasons of each year. Linear trends in the number of days were calculated for each station and for quasi-homogeneous climatic regions. Regional analysis of extreme events was carried out using quasi-homogeneous climatic regions. Maps (climatology, trends) are presented mostly for visualization purposes. Differences in regional characteristics of extreme events are accounted for over a large extent of the Russian territory and variety of its physical and geographical conditions. The number of days with maximum temperatures higher than the 95% percentile has increased in most of Russia and decreased in Siberia in spring and autumn. Reducing the number of days with extremely low air temperatures dominated in all seasons. At the same time, the number of days with abnormally low air temperatures has increased in Middle Volga region and south of Western Siberia. In most parts of European Russia observed increase in the number of days with heavy snowfalls.

Effects of environmental conditions on onset of xylem growth in Pinus sylvestris under drought.

PubMed

Swidrak, Irene; Gruber, Andreas; Kofler, Werner; Oberhuber, Walter

2011-05-01

We determined the influence of environmental factors (air and soil temperature, precipitation, photoperiod) on onset of xylem growth in Scots pine (Pinus sylvestris L.) within a dry inner Alpine valley (750 m a.s.l., Tyrol, Austria) by repeatedly sampling micro-cores throughout 2007-10 at two sites (xeric and dry-mesic) at the start of the growing season. Temperature sums were calculated in degree-days (DD) ≥5 °C from 1 January and 20 March, i.e., spring equinox, to account for photoperiodic control of release from winter dormancy. Threshold temperatures at which xylogenesis had a 0.5 probability of being active were calculated by logistic regression. Onset of xylem growth, which was not significantly different between the xeric and dry-mesic sites, ranged from mid-April in 2007 to early May in 2008. Among most study years, statistically significant differences (P<0.05) in onset of xylem growth were detected. Mean air temperature sums calculated from 1 January until onset of xylem growth were 230 ± 44 DD (mean ± standard deviation) at the xeric site and 205 ± 36 DD at the dry-mesic site. Temperature sums calculated from spring equinox until onset of xylem growth showed somewhat less variability during the 4-year study period, amounting to 144 ± 10 and 137 ± 12 DD at the xeric and dry-mesic sites, respectively. At both sites, xylem growth was active when daily minimum, mean and maximum air temperatures were 5.3, 10.1 and 16.2 °C, respectively. Soil temperature thresholds and DD until onset of xylem growth differed significantly between sites, indicating minor importance of root-zone temperature for onset of xylem growth. Although spring precipitation is known to limit radial growth in P. sylvestris exposed to a dry inner Alpine climate, the results of this study revealed that (i) a daily minimum air temperature threshold for onset of xylem growth in the range 5-6 °C exists and (ii) air temperature sum rather than precipitation or soil temperature triggers start of xylem growth. Based on these findings, we suggest that drought stress forces P. sylvestris to draw upon water reserves in the stem for enlargement of first tracheids after cambial resumption in spring. © The Author 2011. Published by Oxford University Press. All rights reserved.

Effects of environmental conditions on onset of xylem growth in Pinus sylvestris under drought

PubMed Central

Swidrak, Irene; Gruber, Andreas; Kofler, Werner; Oberhuber, Walter

2012-01-01

Summary We determined influence of environmental factors (air and soil temperature, precipitation, photoperiod) on onset of xylem growth in Scots pine (Pinus sylvestris L.) within a dry inner Alpine valley (750 m a.s.l., Tyrol, Austria) by repeatedly sampling micro-cores throughout 2007-2010 at two sites (xeric and dry-mesic) at the start of the growing season. Temperature sums were calculated in degree-days (DD) ≥ 5 °C from 1 January and 20 March, i.e. spring equinox, to account for photoperiodic control of release from winter dormancy. Threshold temperatures at which xylogenesis had a 0.5 probability of being active were calculated by logistic regression. Onset of xylem growth, which was not significantly different between the xeric and dry-mesic site, ranged from mid-April in 2007 to early May in 2008. Among most study years statistically significant differences (P < 0.05) in onset of xylem growth were detected. Mean air temperature sums calculated from 1 January until onset of xylem growth were 230 ± 44 DD (mean ± standard deviation) at the xeric and 205 ± 36 DD at the dry-mesic site. Temperature sums calculated from spring equinox until onset of xylem growth showed quite less variability during the four year study period amounting to 144 ± 10 and 137 ± 12 DD at the xeric and dry-mesic site, respectively. At both sites xylem growth was active when daily minimum, mean and maximum air temperatures were 5.3, 10.1 and 16.2 °C, respectively. Soil temperature thresholds and DD until onset of xylem growth differed significantly between sites indicating minor importance of root-zone temperature for onset of xylem growth. Although spring precipitation is known to limit radial growth in P. sylvestris exposed to dry inner Alpine climate, results of this study revealed that (i) a daily minimum air temperature threshold for onset of xylem growth in the range of 5-6 °C exists and (ii) air temperature sum rather than precipitation or soil temperature triggers start of xylem growth. Based on these findings we suggest that drought stress forces P. sylvestris to draw upon water reserves in the stem for enlargement of first tracheids after cambial resumption in spring. PMID:21593011

Evaluation of NLDAS 12-km and downscaled 1-km temperature products in New York State for potential use in health exposure response studies

NASA Astrophysics Data System (ADS)

Estes, M. G., Jr.; Insaf, T.; Crosson, W. L.; Al-Hamdan, M. Z.

2017-12-01

Heat exposure metrics (maximum and minimum daily temperatures,) have a close relationship with human health. While meteorological station data provide a good source of point measurements, temporal and spatially consistent temperature data are needed for health studies. Reanalysis data such as the North American Land Data Assimilation System's (NLDAS) 12-km gridded product are an effort to resolve spatio-temporal environmental data issues; the resolution may be too coarse to accurately capture the effects of elevation, mixed land/water areas, and urbanization. As part of this NASA Applied Sciences Program funded project, the NLDAS 12-km air temperature product has been downscaled to 1-km using MODIS Land Surface Temperature patterns. Limited validation of the native 12-km NLDAS reanalysis data has been undertaken. Our objective is to evaluate the accuracy of both the 12-km and 1-km downscaled products using the US Historical Climatology Network station data geographically dispersed across New York State. Statistical methods including correlation, scatterplots, time series and summary statistics were used to determine the accuracy of the remotely-sensed maximum and minimum temperature products. The specific effects of elevation and slope on remotely-sensed temperature product accuracy were determined with 10-m digital elevation data that were used to calculate percent slope and link with the temperature products at multiple scales. Preliminary results indicate the downscaled temperature product improves accuracy over the native 12-km temperature product with average correlation improvements from 0.81 to 0.85 for minimum and 0.71 to 0.79 for maximum temperatures in 2009. However, the benefits vary temporally and geographically. Our results will inform health studies using remotely-sensed temperature products to determine health risk from excessive heat by providing a more robust assessment of the accuracy of the 12-km NLDAS product and additional accuracy gained from the 1-km downscaled product. Also, the results will be shared with the National Weather Service to determine potential benefits to heat warning systems and evaluated for inclusion in the Centers of Disease Control and Prevention (CDC) Environmental Public Health Tracking Network as a resource for the health community.

Benchmark Data Set for Wheat Growth Models: Field Experiments and AgMIP Multi-Model Simulations.

NASA Technical Reports Server (NTRS)

Asseng, S.; Ewert, F.; Martre, P.; Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P.J.; Rotter, R. P.

2015-01-01

The data set includes a current representative management treatment from detailed, quality-tested sentinel field experiments with wheat from four contrasting environments including Australia, The Netherlands, India and Argentina. Measurements include local daily climate data (solar radiation, maximum and minimum temperature, precipitation, surface wind, dew point temperature, relative humidity, and vapor pressure), soil characteristics, frequent growth, nitrogen in crop and soil, crop and soil water and yield components. Simulations include results from 27 wheat models and a sensitivity analysis with 26 models and 30 years (1981-2010) for each location, for elevated atmospheric CO2 and temperature changes, a heat stress sensitivity analysis at anthesis, and a sensitivity analysis with soil and crop management variations and a Global Climate Model end-century scenario.

Daily estimates of the migrating tide and zonal mean temperature in the mesosphere and lower thermosphere derived from SABER data

NASA Astrophysics Data System (ADS)

Ortland, David A.

2017-04-01

Satellites provide a global view of the structure in the fields that they measure. In the mesosphere and lower thermosphere, the dominant features in these fields at low zonal wave number are contained in the zonal mean, quasi-stationary planetary waves, and tide components. Due to the nature of the satellite sampling pattern, stationary, diurnal, and semidiurnal components are aliased and spectral methods are typically unable to separate the aliased waves over short time periods. This paper presents a data processing scheme that is able to recover the daily structure of these waves and the zonal mean state. The method is validated by using simulated data constructed from a mechanistic model, and then applied to Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) temperature measurements. The migrating diurnal tide extracted from SABER temperatures for 2009 has a seasonal variability with peak amplitude (20 K at 95 km) in February and March and minimum amplitude (less than 5 K at 95 km) in early June and early December. Higher frequency variability includes a change in vertical structure and amplitude during the major stratospheric warming in January. The migrating semidiurnal tide extracted from SABER has variability on a monthly time scale during January through March, minimum amplitude in April, and largest steady amplitudes from May through September. Modeling experiments were performed that show that much of the variability on seasonal time scales in the migrating tides is due to changes in the mean flow structure and the superposition of the tidal responses to water vapor heating in the troposphere and ozone heating in the stratosphere and lower mesosphere.

The impact of sustained hot weather on risk of acute work-related injury in Melbourne, Australia.

PubMed

McInnes, Judith Anne; MacFarlane, Ewan M; Sim, Malcolm R; Smith, Peter

2018-02-01

It has been reported that weather-related high ambient temperature is associated with an increased risk of work-related injury. Understanding this relationship is important because work-related injuries are a major public health problem, and because projected climate changes will potentially expose workers to hot days, including consecutive hot days, more often. The aim of this study was to quantify the impact of exposure to sustained periods of hot weather on work-related injury risk for workers in Melbourne, Australia. A time-stratified case crossover study design was utilised to examine the association between two and three consecutive days and two and three consecutive nights of hot weather and the risk of work-related injury, using definitions of hot weather ranging from the 60th to the 95th percentile of daily maximum and minimum temperatures for the Melbourne metropolitan area, 2002-2012. Workers' compensation claim data was used to identify cases of acute work-related injury. Overall, two and three consecutive days of hot weather were associated with an increased risk of injury, with this effect becoming apparent at a daily maximum temperature of 27.6 °C (70th percentile). Three consecutive days of high but not extreme temperatures were associated with the strongest effect, with a 15% increased risk of injury (odds ratio 1.15, 95% confidence interval 1.01-1.30) observed when daily maximum temperature was ≥33.3 °C (90th percentile) for three consecutive days, compared to when it was not. At a threshold of 35.5 °C (95th percentile), there was no significant association between temperature and injury for either two or three consecutive days of heat. These findings suggest that warnings to minimise harm to workers from hot weather should be given, and prevention protocol initiated, when consecutive warm days of temperatures lower than extreme heat temperatures are forecast, and well before the upper ranges of ambient daytime temperatures are reached.

The impact of sustained hot weather on risk of acute work-related injury in Melbourne, Australia

NASA Astrophysics Data System (ADS)

McInnes, Judith Anne; MacFarlane, Ewan M.; Sim, Malcolm R.; Smith, Peter

2018-02-01

It has been reported that weather-related high ambient temperature is associated with an increased risk of work-related injury. Understanding this relationship is important because work-related injuries are a major public health problem, and because projected climate changes will potentially expose workers to hot days, including consecutive hot days, more often. The aim of this study was to quantify the impact of exposure to sustained periods of hot weather on work-related injury risk for workers in Melbourne, Australia. A time-stratified case crossover study design was utilised to examine the association between two and three consecutive days and two and three consecutive nights of hot weather and the risk of work-related injury, using definitions of hot weather ranging from the 60th to the 95th percentile of daily maximum and minimum temperatures for the Melbourne metropolitan area, 2002-2012. Workers' compensation claim data was used to identify cases of acute work-related injury. Overall, two and three consecutive days of hot weather were associated with an increased risk of injury, with this effect becoming apparent at a daily maximum temperature of 27.6 °C (70th percentile). Three consecutive days of high but not extreme temperatures were associated with the strongest effect, with a 15% increased risk of injury (odds ratio 1.15, 95% confidence interval 1.01-1.30) observed when daily maximum temperature was ≥33.3 °C (90th percentile) for three consecutive days, compared to when it was not. At a threshold of 35.5 °C (95th percentile), there was no significant association between temperature and injury for either two or three consecutive days of heat. These findings suggest that warnings to minimise harm to workers from hot weather should be given, and prevention protocol initiated, when consecutive warm days of temperatures lower than extreme heat temperatures are forecast, and well before the upper ranges of ambient daytime temperatures are reached.

Searching for the best modeling specification for assessing the effects of temperature and humidity on health: a time series analysis in three European cities.

PubMed

Rodopoulou, Sophia; Samoli, Evangelia; Analitis, Antonis; Atkinson, Richard W; de'Donato, Francesca K; Katsouyanni, Klea

2015-11-01

Epidemiological time series studies suggest daily temperature and humidity are associated with adverse health effects including increased mortality and hospital admissions. However, there is no consensus over which metric or lag best describes the relationships. We investigated which temperature and humidity model specification most adequately predicted mortality in three large European cities. Daily counts of all-cause mortality, minimum, maximum and mean temperature and relative humidity and apparent temperature (a composite measure of ambient and dew point temperature) were assembled for Athens, London, and Rome for 6 years between 1999 and 2005. City-specific Poisson regression models were fitted separately for warm (April-September) and cold (October-March) periods adjusting for seasonality, air pollution, and public holidays. We investigated goodness of model fit for each metric for delayed effects up to 13 days using three model fit criteria: sum of the partial autocorrelation function, AIC, and GCV. No uniformly best index for all cities and seasonal periods was observed. The effects of temperature were uniformly shown to be more prolonged during cold periods and the majority of models suggested separate temperature and humidity variables performed better than apparent temperature in predicting mortality. Our study suggests that the nature of the effects of temperature and humidity on mortality vary between cities for unknown reasons which require further investigation but may relate to city-specific population, socioeconomic, and environmental characteristics. This may have consequences on epidemiological studies and local temperature-related warning systems.

Searching for the best modeling specification for assessing the effects of temperature and humidity on health: a time series analysis in three European cities

NASA Astrophysics Data System (ADS)

Rodopoulou, Sophia; Samoli, Evangelia; Analitis, Antonis; Atkinson, Richard W.; de'Donato, Francesca K.; Katsouyanni, Klea

2015-11-01

Epidemiological time series studies suggest daily temperature and humidity are associated with adverse health effects including increased mortality and hospital admissions. However, there is no consensus over which metric or lag best describes the relationships. We investigated which temperature and humidity model specification most adequately predicted mortality in three large European cities. Daily counts of all-cause mortality, minimum, maximum and mean temperature and relative humidity and apparent temperature (a composite measure of ambient and dew point temperature) were assembled for Athens, London, and Rome for 6 years between 1999 and 2005. City-specific Poisson regression models were fitted separately for warm (April-September) and cold (October-March) periods adjusting for seasonality, air pollution, and public holidays. We investigated goodness of model fit for each metric for delayed effects up to 13 days using three model fit criteria: sum of the partial autocorrelation function, AIC, and GCV. No uniformly best index for all cities and seasonal periods was observed. The effects of temperature were uniformly shown to be more prolonged during cold periods and the majority of models suggested separate temperature and humidity variables performed better than apparent temperature in predicting mortality. Our study suggests that the nature of the effects of temperature and humidity on mortality vary between cities for unknown reasons which require further investigation but may relate to city-specific population, socioeconomic, and environmental characteristics. This may have consequences on epidemiological studies and local temperature-related warning systems.

Warming and wetting signals emerging from analysis of changes in climate extreme indices over South America

NASA Astrophysics Data System (ADS)

Skansi, María de los Milagros; Brunet, Manola; Sigró, Javier; Aguilar, Enric; Arevalo Groening, Juan Andrés; Bentancur, Oscar J.; Castellón Geier, Yaruska Rosa; Correa Amaya, Ruth Leonor; Jácome, Homero; Malheiros Ramos, Andrea; Oria Rojas, Clara; Pasten, Alejandro Max; Sallons Mitro, Sukarni; Villaroel Jiménez, Claudia; Martínez, Rodney; Alexander, Lisa V.; Jones, P. D.

2013-01-01

Here we show and discuss the results of an assessment of changes in both area-averaged and station-based climate extreme indices over South America (SA) for the 1950-2010 and 1969-2009 periods using high-quality daily maximum and minimum temperature and precipitation series. A weeklong regional workshop in Guayaquil (Ecuador) provided the opportunity to extend the current picture of changes in climate extreme indices over SA. Our results provide evidence of warming and wetting across the whole SA since the mid-20th century onwards. Nighttime (minimum) temperature indices show the largest rates of warming (e.g. for tropical nights, cold and warm nights), while daytime (maximum) temperature indices also point to warming (e.g. for cold days, summer days, the annual lowest daytime temperature), but at lower rates than for minimums. Both tails of night-time temperatures have warmed by a similar magnitude, with cold days (the annual lowest nighttime and daytime temperatures) seeing reductions (increases). Trends are strong and moderate (moderate to weak) for regional-averaged (local) indices, most of them pointing to a less cold SA during the day and warmer night-time temperatures. Regionally-averaged precipitation indices show clear wetting and a signature of intensified heavy rain events over the eastern part of the continent. The annual amounts of rainfall are rising strongly over south-east SA (26.41 mm/decade) and Amazonia (16.09 mm/decade), but north-east Brazil and the western part of SA have experienced non-significant decreases. Very wet and extremely days, the annual maximum 5-day and 1-day precipitation show the largest upward trends, indicating an intensified rainfall signal for SA, particularly over Amazonia and south-east SA. Local trends for precipitation extreme indices are in general less coherent spatially, but with more general spatially coherent upward trends in extremely wet days over all SA.

Evaluation of different methods to estimate daily reference evapotranspiration in ungauged basins in Southern Brazil

NASA Astrophysics Data System (ADS)

Ribeiro Fontoura, Jessica; Allasia, Daniel; Herbstrith Froemming, Gabriel; Freitas Ferreira, Pedro; Tassi, Rutineia

2016-04-01

Evapotranspiration is a key process of hydrological cycle and a sole term that links land surface water balance and land surface energy balance. Due to the higher information requirements of the Penman-Monteith method and the existing data uncertainty, simplified empirical methods for calculating potential and actual evapotranspiration are widely used in hydrological models. This is especially important in Brazil, where the monitoring of meteorological data is precarious. In this study were compared different methods for estimating evapotranspiration for Rio Grande do Sul, the Southernmost State of Brazil, aiming to suggest alternatives to the recommended method (Penman-Monteith-FAO 56) for estimate daily reference evapotranspiration (ETo) when meteorological data is missing or not available. The input dataset included daily and hourly-observed data from conventional and automatic weather stations respectively maintained by the National Weather Institute of Brazil (INMET) from the period of 1 January 2007 to 31 January 2010. Dataset included maximum temperature (Tmax, °C), minimum temperature (Tmin, °C), mean relative humidity (%), wind speed at 2 m height (u2, m s-1), daily solar radiation (Rs, MJ m- 2) and atmospheric pressure (kPa) that were grouped at daily time-step. Was tested the Food and Agriculture Organization of the United Nations (FAO) Penman-Monteith method (PM) at its full form, against PM assuming missing several variables not normally available in Brazil in order to calculate daily reference ETo. Missing variables were estimated as suggested in FAO56 publication or from climatological means. Furthermore, PM was also compared against the following simplified empirical methods: Hargreaves-Samani, Priestley-Taylor, Mccloud, McGuiness-Bordne, Romanenko, Radiation-Temperature, Tanner-Pelton. The statistical analysis indicates that even if just Tmin and Tmax are available, it is better to use PM estimating missing variables from syntetic data than simplified empirical methods evaluated except for Tanner-Pelton and Priestley-Taylor.

Validation of China-wide interpolated daily climate variables from 1960 to 2011

NASA Astrophysics Data System (ADS)

Yuan, Wenping; Xu, Bing; Chen, Zhuoqi; Xia, Jiangzhou; Xu, Wenfang; Chen, Yang; Wu, Xiaoxu; Fu, Yang

2015-02-01

Temporally and spatially continuous meteorological variables are increasingly in demand to support many different types of applications related to climate studies. Using measurements from 600 climate stations, a thin-plate spline method was applied to generate daily gridded climate datasets for mean air temperature, maximum temperature, minimum temperature, relative humidity, sunshine duration, wind speed, atmospheric pressure, and precipitation over China for the period 1961-2011. A comprehensive evaluation of interpolated climate was conducted at 150 independent validation sites. The results showed superior performance for most of the estimated variables. Except for wind speed, determination coefficients ( R 2) varied from 0.65 to 0.90, and interpolations showed high consistency with observations. Most of the estimated climate variables showed relatively consistent accuracy among all seasons according to the root mean square error, R 2, and relative predictive error. The interpolated data correctly predicted the occurrence of daily precipitation at validation sites with an accuracy of 83 %. Moreover, the interpolation data successfully explained the interannual variability trend for the eight meteorological variables at most validation sites. Consistent interannual variability trends were observed at 66-95 % of the sites for the eight meteorological variables. Accuracy in distinguishing extreme weather events differed substantially among the meteorological variables. The interpolated data identified extreme events for the three temperature variables, relative humidity, and sunshine duration with an accuracy ranging from 63 to 77 %. However, for wind speed, air pressure, and precipitation, the interpolation model correctly identified only 41, 48, and 58 % of extreme events, respectively. The validation indicates that the interpolations can be applied with high confidence for the three temperatures variables, as well as relative humidity and sunshine duration based on the performance of these variables in estimating daily variations, interannual variability, and extreme events. Although longitude, latitude, and elevation data are included in the model, additional information, such as topography and cloud cover, should be integrated into the interpolation algorithm to improve performance in estimating wind speed, atmospheric pressure, and precipitation.

Effects of Recent Minimum Temperature and Water Deficit Increases on Pinus pinaster Radial Growth and Wood Density in Southern Portugal.

PubMed

Kurz-Besson, Cathy B; Lousada, José L; Gaspar, Maria J; Correia, Isabel E; David, Teresa S; Soares, Pedro M M; Cardoso, Rita M; Russo, Ana; Varino, Filipa; Mériaux, Catherine; Trigo, Ricardo M; Gouveia, Célia M

2016-01-01

Western Iberia has recently shown increasing frequency of drought conditions coupled with heatwave events, leading to exacerbated limiting climatic conditions for plant growth. It is not clear to what extent wood growth and density of agroforestry species have suffered from such changes or recent extreme climate events. To address this question, tree-ring width and density chronologies were built for a Pinus pinaster stand in southern Portugal and correlated with climate variables, including the minimum, mean and maximum temperatures and the number of cold days. Monthly and maximum daily precipitations were also analyzed as well as dry spells. The drought effect was assessed using the standardized precipitation-evapotranspiration (SPEI) multi-scalar drought index, between 1 to 24-months. The climate-growth/density relationships were evaluated for the period 1958-2011. We show that both wood radial growth and density highly benefit from the strong decay of cold days and the increase of minimum temperature. Yet the benefits are hindered by long-term water deficit, which results in different levels of impact on wood radial growth and density. Despite of the intensification of long-term water deficit, tree-ring width appears to benefit from the minimum temperature increase, whereas the effects of long-term droughts significantly prevail on tree-ring density. Our results further highlight the dependency of the species on deep water sources after the juvenile stage. The impact of climate changes on long-term droughts and their repercussion on the shallow groundwater table and P. pinaster's vulnerability are also discussed. This work provides relevant information for forest management in the semi-arid area of the Alentejo region of Portugal. It should ease the elaboration of mitigation strategies to assure P. pinaster's production capacity and quality in response to more arid conditions in the near future in the region.

Effects of Recent Minimum Temperature and Water Deficit Increases on Pinus pinaster Radial Growth and Wood Density in Southern Portugal

PubMed Central

Kurz-Besson, Cathy B.; Lousada, José L.; Gaspar, Maria J.; Correia, Isabel E.; David, Teresa S.; Soares, Pedro M. M.; Cardoso, Rita M.; Russo, Ana; Varino, Filipa; Mériaux, Catherine; Trigo, Ricardo M.; Gouveia, Célia M.

2016-01-01

Western Iberia has recently shown increasing frequency of drought conditions coupled with heatwave events, leading to exacerbated limiting climatic conditions for plant growth. It is not clear to what extent wood growth and density of agroforestry species have suffered from such changes or recent extreme climate events. To address this question, tree-ring width and density chronologies were built for a Pinus pinaster stand in southern Portugal and correlated with climate variables, including the minimum, mean and maximum temperatures and the number of cold days. Monthly and maximum daily precipitations were also analyzed as well as dry spells. The drought effect was assessed using the standardized precipitation-evapotranspiration (SPEI) multi-scalar drought index, between 1 to 24-months. The climate-growth/density relationships were evaluated for the period 1958-2011. We show that both wood radial growth and density highly benefit from the strong decay of cold days and the increase of minimum temperature. Yet the benefits are hindered by long-term water deficit, which results in different levels of impact on wood radial growth and density. Despite of the intensification of long-term water deficit, tree-ring width appears to benefit from the minimum temperature increase, whereas the effects of long-term droughts significantly prevail on tree-ring density. Our results further highlight the dependency of the species on deep water sources after the juvenile stage. The impact of climate changes on long-term droughts and their repercussion on the shallow groundwater table and P. pinaster’s vulnerability are also discussed. This work provides relevant information for forest management in the semi-arid area of the Alentejo region of Portugal. It should ease the elaboration of mitigation strategies to assure P. pinaster’s production capacity and quality in response to more arid conditions in the near future in the region. PMID:27570527

Projections of Future Summer Weather in Seoul and Their Impacts on Urban Agriculture

NASA Astrophysics Data System (ADS)

Kim, S. O.; Kim, J. H.; Yun, J. I.

2015-12-01

Climate departure from the past variability was projected to start in 2042 for Seoul. In order to understand the implication of climate departure in Seoul for urban agriculture, we evaluated the daily temperature for the June-September period from 2041 to 2070, which were projected by the RCP8.5 climate scenario. These data were analyzed with respect to climate extremes and their effects on growth of hot pepper (Capsicum annuum), one of the major crops in urban farming. The mean daily maximum and minimum temperatures in 2041-2070 approached to the 90th percentile in the past 30 years (1951- 1980). However, the frequency of extreme events such as heat waves and tropical nights appeared to exceed the past variability. While the departure of mean temperature might begin in or after 2040, the climate departure in the sense of extreme weather events seems already in progress. When the climate scenario data were applied to the growth and development of hot pepper, the departures of both planting date and harvest date are expected to follow those of temperature. However, the maximum duration for hot pepper cultivation, which is the number of days between the first planting and the last harvest, seems to have already deviated from the past variability.

Coherent variability between seasonal temperatures and rainfalls in the Iberian Peninsula, 1951-2016

NASA Astrophysics Data System (ADS)

Rodrigo, F. S.

2018-02-01

In this work trends of seasonal mean of daily minimum (TN), maximum (TX), mean (TM) temperatures, daily range of temperature (DTR), and total seasonal rainfall (R) in 35 Iberian stations since mid-twentieth century are studied. The interest is focused on the relationships between temperature variables and rainfall, taking into account the correlation coefficients between R and the temperature variables. The negative link between rainfall and temperatures is detected in the four seasons of the year, except in western stations in winter for TN and TM, and in autumn for TN (for this variable a certain annual cycle is detected, with predominance of positive correlation in winter, negative in spring and summer, and the autumn as transition season). The role of cloud cover is confirmed in those stations with total cloud cover data. Using an average peninsular series, the relationship between nighttime temperature and rainfall related to long wave radiation is confirmed for the four seasons of the year, although in spring and summer has minor importance than in the cold half year. The relationships between R, TN, and TX are in general terms stable after a moving correlation analysis, although the negative correlation between TX and R seems be weakened in spring and autumn and reinforced in summer. The role of convective precipitation in autumn is discussed. The analysis of combined extreme indices in four representative stations shows an increase of warm and dry days, and a decrease of cold and wet days.

Airborne pollen and spores of León (Spain)

NASA Astrophysics Data System (ADS)

Fernández-González, Delia; Suarez-Cervera, María; Díaz-González, Tomás; Valencia-Barrera, Rosa María

1993-06-01

A qualitative and quantitative analysis of airborne pollen and spores was carried out over 2 years (from September 1987 to August 1989) in the city of León. Slides were prepared daily using a volumetric pollen trap, which was placed on the Faculty of Veterinary Science building (University of León) 12m above ground-level. Fifty-one pollen types were observed; the most important of these were: Cupressaceae during the winter, Pinus and Quercus in spring, and Poaceae, Leguminosae and Chenopodiaceae in the summer. The results also showed the existence of a rich mould spore assemblage in the atmosphere. The group of Amerospores ( Penicillium, Aspergillus and Cladosporium) as well as Dictyospores ( Alternaria) were the most abundant; Puccinia was common in the air in August. Fluctuations in the total pollen and spores m3 of air were compared with meteorological parameters (temperature, relative humidity and rainfall). From the daily sampling of the atmosphere of León, considering the maximum and minimum temperature and duration of rainfall, the start of the pollen grain season was observed generally to coincide with a rise in temperature in the absence of rain.

Spatiotemporal Variability of Drought in Pakistan through High-Resolution Daily Gridded In-Situ Observations

NASA Astrophysics Data System (ADS)

Bashir, F.; Zeng, X.; Gupta, H. V.; Hazenberg, P.

2017-12-01

Drought as an extreme event may have far reaching socio-economic impacts on agriculture based economies like Pakistan. Effective assessment of drought requires high resolution spatiotemporally continuous hydrometeorological information. For this purpose, new in-situ daily observations based gridded analyses of precipitation, maximum, minimum and mean temperature and diurnal temperature range are developed, that covers whole Pakistan on 0.01º latitude-longitude for a 54-year period (1960-2013). The number of participating meteorological observatories used in these gridded analyses is 2 to 6 times greater than any other similar product available. This data set is used to identify extreme wet and dry periods and their spatial patterns across Pakistan using Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI). Periodicity of extreme events is estimated at seasonal to decadal scales. Spatiotemporal signatures of drought incidence indicating its extent and longevity in different areas may help water resource managers and policy makers to mitigate the severity of the drought and its impact on food security through suitable adaptive techniques. Moreover, this high resolution gridded in-situ observations of precipitation and temperature is used to evaluate other coarser-resolution gridded products.

Statistical downscaling of mean temperature, maximum temperature, and minimum temperature on the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Jiang, L.

2017-12-01

Climate change is considered to be one of the greatest environmental threats. Global climate models (GCMs) are the primary tool used for studying climate change. However, GCMs are limited because of their coarse spatial resolution and inability to resolve important sub-grid scale features such as terrain and clouds. Statistical downscaling methods can be used to downscale large-scale variables to local-scale. In this study, we assess the applicability of the Statistical Downscaling Model (SDSM) in downscaling the outputs from Beijing Normal University Earth System Model (BNU-ESM). The study focus on the the Loess Plateau, China, and the variables for downscaling include daily mean temperature (TMEAN), maximum temperature (TMAX) and minimum temperature (TMIN). The results show that SDSM performs well for these three climatic variables on the Loess Plateau. After downscaling, the root mean square errors for TMEAN, TMAX, TMIN for BNU-ESM were reduced by 70.9%, 75.1%, and 67.2%, respectively. All the rates of change in TMEAN, TMAX and TMIN during the 21st century decreased after SDSM downscaling. We also show that SDSM can effectively reduce uncertainty, compared with the raw model outputs. TMEAN uncertainty was reduced by 27.1%, 26.8%, and 16.3% for the future scenarios of RCP 2.6, RCP 4.5 and RCP 8.5, respectively. The corresponding reductions in uncertainty were 23.6%, 30.7%, and 18.7% for TMAX; 37.6%, 31.8%, and 23.2% for TMIN.

Assessment of long-term monthly and seasonal trends of warm (cold), wet (dry) spells in Kansas, USA

NASA Astrophysics Data System (ADS)

Dokoohaki, H.; Anandhi, A.

2013-12-01

A few recent studies have focused on trends in rainfall, temperature, and frost indicators at different temporal scales using centennial weather station data in Kansas; our study supplements this work by assessing the changes in spell indicators in Kansas. These indicators provide the duration between temperature-based (warm and cold) and precipitation-based (wet and dry) spells. For wet (dry) spell calculations, a wet day is defined as a day with precipitation ≥1 mm, and a dry day is defined as one with precipitation ≤1 mm. For warm (cold) spell calculations, a warm day is defined as a day with maximum temperature >90th percentile of daily maximum temperature, and a cold day is defined as a day with minimum temperature <10th percentile of daily minimum temperature. The percentiles are calculated for 1971-2000, and four spell indicators are calculated: Average Wet Spell Length (AWSL), Dry Spell Length (ADSL), Average Warm Spell Days (AWSD) and Average Cold Spell Days (ACSD) are calculated. Data were provided from 23 centennial weather stations across Kansas, and all calculations were done for four time periods (through 1919, 1920-1949, 1950-1979, and 1980-2009). The definitions and software provided by Expert Team on Climate Change Detection and Indices (ETCCDI) were adapted for application to Kansas. The long- and short-term trends in these indices were analyzed at monthly and seasonal timescales. Monthly results indicate that ADSL is decreasing and AWSL is increasing throughout the state. AWSD and ACSD both showed an overall decreasing trend, but AWSD trends were variable during the beginning of the Industrial Revolution. Results of seasonal analysis revealed that the fall season recorded the greatest increasing trend for ACSD and the greatest decreasing trend for AWSD across the whole state and during all time periods. Similarly, the greatest increasing and decreasing trends occurred in winter for AWSL and ADSL, respectively. These variations can be important indicators of climatic change that may not be represented in mean conditions. Detailed geographical and temporal variations of the spell indices also can be beneficial for updating management decisions and providing adaptation recommendations for local and regional agricultural production.

Time-series Analysis of Heat Waves and Emergency Department Visits in Atlanta, 1993 to 2012

PubMed Central

Chen, Tianqi; Sarnat, Stefanie E.; Grundstein, Andrew J.; Winquist, Andrea

2017-01-01

Background: Heat waves are extreme weather events that have been associated with adverse health outcomes. However, there is limited knowledge of heat waves’ impact on population morbidity, such as emergency department (ED) visits. Objectives: We investigated associations between heat waves and ED visits for 17 outcomes in Atlanta over a 20-year period, 1993–2012. Methods: Associations were estimated using Poisson log-linear models controlling for continuous air temperature, dew-point temperature, day of week, holidays, and time trends. We defined heat waves as periods of ≥2 consecutive days with temperatures beyond the 98th percentile of the temperature distribution over the period from 1945–2012. We considered six heat wave definitions using maximum, minimum, and average air temperatures and apparent temperatures. Associations by heat wave characteristics were examined. Results: Among all outcome-heat wave combinations, associations were strongest between ED visits for acute renal failure and heat waves defined by maximum apparent temperature at lag 0 [relative risk (RR) = 1.15; 95% confidence interval (CI): 1.03–1.29], ED visits for ischemic stroke and heat waves defined by minimum temperature at lag 0 (RR = 1.09; 95% CI: 1.02–1.17), and ED visits for intestinal infection and heat waves defined by average temperature at lag 1 (RR = 1.10; 95% CI: 1.00–1.21). ED visits for all internal causes were associated with heat waves defined by maximum temperature at lag 1 (RR = 1.02; 95% CI: 1.00, 1.04). Conclusions: Heat waves can confer additional risks of ED visits beyond those of daily air temperature, even in a region with high air-conditioning prevalence. https://doi.org/10.1289/EHP44 PMID:28599264

Time-series Analysis of Heat Waves and Emergency Department Visits in Atlanta, 1993 to 2012.

PubMed

Chen, Tianqi; Sarnat, Stefanie E; Grundstein, Andrew J; Winquist, Andrea; Chang, Howard H

2017-05-31

Heat waves are extreme weather events that have been associated with adverse health outcomes. However, there is limited knowledge of heat waves' impact on population morbidity, such as emergency department (ED) visits. We investigated associations between heat waves and ED visits for 17 outcomes in Atlanta over a 20-year period, 1993-2012. Associations were estimated using Poisson log-linear models controlling for continuous air temperature, dew-point temperature, day of week, holidays, and time trends. We defined heat waves as periods of consecutive days with temperatures beyond the 98th percentile of the temperature distribution over the period from 1945-2012. We considered six heat wave definitions using maximum, minimum, and average air temperatures and apparent temperatures. Associations by heat wave characteristics were examined. Among all outcome-heat wave combinations, associations were strongest between ED visits for acute renal failure and heat waves defined by maximum apparent temperature at lag 0 [relative risk (RR) = 1.15; 95% confidence interval (CI): 1.03-1.29], ED visits for ischemic stroke and heat waves defined by minimum temperature at lag 0 (RR = 1.09; 95% CI: 1.02-1.17), and ED visits for intestinal infection and heat waves defined by average temperature at lag 1 (RR = 1.10; 95% CI: 1.00-1.21). ED visits for all internal causes were associated with heat waves defined by maximum temperature at lag 1 (RR = 1.02; 95% CI: 1.00, 1.04). Heat waves can confer additional risks of ED visits beyond those of daily air temperature, even in a region with high air-conditioning prevalence. https://doi.org/10.1289/EHP44.

Weekly cycle in the NCAR-NCEP reanalysis of the surface temperature over northern atlantic

NASA Astrophysics Data System (ADS)

Tesouro, M.; Gimeno, L.; Nieto, R.; Añel, J. A.; de La Torre, L.; Ribera, P.; García, R.; Hernández, E.

2003-04-01

Anthropogenic influences on climate has been detected in several climate variables, such as temperature increases and precipitation enhacement. An indicator of the anthropogenic effect is the identification of equivalent weekly cycle in climate parameters. In this case, we analyze the weekly cycle of the daily temperature at 2 metres from the NCAR-NCEP Reanalysis. The region of study is the window from 90ºW to 90ºE and from 88.5ºN to Equator and for the last 44 years. Results don´t show a clear pattern of the weekly cycle although it was possible to identify a minimum on Saturday in most of the grid points. We also analyze the weekly cycle of the temperature channel-2 MSU data that represent the lower troposphere and results don´t show any weekly cycle.

The FORBIO Climate data set for climate analyses

NASA Astrophysics Data System (ADS)

Delvaux, C.; Journée, M.; Bertrand, C.

2015-06-01

In the framework of the interdisciplinary FORBIO Climate research project, the Royal Meteorological Institute of Belgium is in charge of providing high resolution gridded past climate data (i.e. temperature and precipitation). This climate data set will be linked to the measurements on seedlings, saplings and mature trees to assess the effects of climate variation on tree performance. This paper explains how the gridded daily temperature (minimum and maximum) data set was generated from a consistent station network between 1980 and 2013. After station selection, data quality control procedures were developed and applied to the station records to ensure that only valid measurements will be involved in the gridding process. Thereafter, the set of unevenly distributed validated temperature data was interpolated on a 4 km × 4 km regular grid over Belgium. The performance of different interpolation methods has been assessed. The method of kriging with external drift using correlation between temperature and altitude gave the most relevant results.

Strong impacts of daily minimum temperature on the green-up date and summer greenness of the Tibetan Plateau.

PubMed

Shen, Miaogen; Piao, Shilong; Chen, Xiaoqiu; An, Shuai; Fu, Yongshuo H; Wang, Shiping; Cong, Nan; Janssens, Ivan A

2016-09-01

Understanding vegetation responses to climate change on the Tibetan Plateau (TP) helps in elucidating the land-atmosphere energy exchange, which affects air mass movement over and around the TP. Although the TP is one of the world's most sensitive regions in terms of climatic warming, little is known about how the vegetation responds. Here, we focus on how spring phenology and summertime greenness respond to the asymmetric warming, that is, stronger warming during nighttime than during daytime. Using both in situ and satellite observations, we found that vegetation green-up date showed a stronger negative partial correlation with daily minimum temperature (Tmin ) than with maximum temperature (Tmax ) before the growing season ('preseason' henceforth). Summer vegetation greenness was strongly positively correlated with summer Tmin , but negatively with Tmax . A 1-K increase in preseason Tmin advanced green-up date by 4 days (P < 0.05) and in summer enhanced greenness by 3.6% relative to the mean greenness during 2000-2004 (P < 0.01). In contrast, increases in preseason Tmax did not advance green-up date (P > 0.10) and higher summer Tmax even reduced greenness by 2.6% K(-1) (P < 0.05). The stimulating effects of increasing Tmin were likely caused by reduced low temperature constraints, and the apparent negative effects of higher Tmax on greenness were probably due to the accompanying decline in water availability. The dominant enhancing effect of nighttime warming indicates that climatic warming will probably have stronger impact on TP ecosystems than on apparently similar Arctic ecosystems where vegetation is controlled mainly by Tmax . Our results are crucial for future improvements of dynamic vegetation models embedded in the Earth System Models which are being used to describe the behavior of the Asian monsoon. The results are significant because the state of the vegetation on the TP plays an important role in steering the monsoon. © 2016 John Wiley & Sons Ltd.

Highs and lows, ups and downs: Meteorology and mood in bipolar disorder.

PubMed

Bullock, Ben; Murray, Greg; Meyer, Denny

2017-01-01

Seasonal variation of manic and depressive symptoms is a controversial topic in bipolar disorder research. Several studies report seasonal patterns of hospital admissions for depression and mania and variation in symptoms that appear to follow a seasonal pattern, whereas others fail to report such patterns. Differences in research methodologies, data analysis strategies, and temporal resolution of data may partly explain the variation in findings between studies. The current study adds a novel perspective to the literature by investigating specific meteorological factors such as atmospheric pressure, hours of sunshine, relative humidity, and daily maximum and minimum temperatures as more proximal predictors of self-reported daily mood change in people diagnosed with bipolar disorder. The results showed that daily maximum temperature was the only meteorological variable to predict clinically-relevant mood change, with increases in temperature associated with greater odds of a transition into manic mood states. The mediating effects of sleep and activity were also investigated and suggest at least partial influence on the prospective relationship between maximum temperature and mood. Limitations include the small sample size and the fact that the number and valence of social interactions and exposure to natural light were not investigated as potentially important mediators of relationships between meteorological factors and mood. The current data make an important contribution to the literature, serving to clarify the specific meteorological factors that influence mood change in bipolar disorder. From a clinical perspective, greater understanding of seasonal patterns of symptoms in bipolar disorder will help mood episode prophylaxis in vulnerable individuals.

Testing pop-up satellite tags as a tool for identifying critical habitat for Pacific halibut (Hippoglossus stenolepis) in the Gulf of Alaska

USGS Publications Warehouse

Seitz, Andrew C.; Wilson, Derek; Nielsen, Jennifer L.

2002-01-01

To maintain healthy commercial and sport fisheries for Pacific halibut (Hippoglossus stenolepis), critical habitat must be defined by determining life history patterns on a daily and seasonal basis. Pop-up satellite archival transmitting (PSAT) tags provide a fisheries-independent method of collecting environmental preference data (depth and ambient water temperature) as well as daily geolocation estimates based on ambient light conditions. In this study, 14 adult halibut (107-165 cm FL) were tagged and released with PSAT tags in and around Resurrection Bay, Alaska. Commercial fishermen recovered two tags, while five tags transmitted data to ARGOS satellites. Horizontal migration was not consistent among fish as three halibut remained in the vicinity of release while four traveled up to 358 km from the release site. Vertical migration was not consistent among fish and over time, but they spent most their time between 150-350 m. The minimum and maximum depths reached by any of the halibut were 2m and 502m, respectively. The fish preferred water temperatures of roughly 6 °C while experiencing ambient temperatures between 4.3 °C and 12.2 °C. Light attenuation with depth prevented existing geolocation software and light sensing hardware from accurately estimating geoposition, however, information from temperature, depth, ocean bathymetry, and pop-off locations provided inference on fish movement in the study area. PSAT tags were a viable tool for determining daily and seasonal behavior and identifying critical halibut habitat, which will aid fisheries managers in future decisions regarding commercial and sport fishing regulations.

Modeling daily soil temperature over diverse climate conditions in Iran—a comparison of multiple linear regression and support vector regression techniques

NASA Astrophysics Data System (ADS)

Delbari, Masoomeh; Sharifazari, Salman; Mohammadi, Ehsan

2018-02-01

The knowledge of soil temperature at different depths is important for agricultural industry and for understanding climate change. The aim of this study is to evaluate the performance of a support vector regression (SVR)-based model in estimating daily soil temperature at 10, 30 and 100 cm depth at different climate conditions over Iran. The obtained results were compared to those obtained from a more classical multiple linear regression (MLR) model. The correlation sensitivity for the input combinations and periodicity effect were also investigated. Climatic data used as inputs to the models were minimum and maximum air temperature, solar radiation, relative humidity, dew point, and the atmospheric pressure (reduced to see level), collected from five synoptic stations Kerman, Ahvaz, Tabriz, Saghez, and Rasht located respectively in the hyper-arid, arid, semi-arid, Mediterranean, and hyper-humid climate conditions. According to the results, the performance of both MLR and SVR models was quite well at surface layer, i.e., 10-cm depth. However, SVR performed better than MLR in estimating soil temperature at deeper layers especially 100 cm depth. Moreover, both models performed better in humid climate condition than arid and hyper-arid areas. Further, adding a periodicity component into the modeling process considerably improved the models' performance especially in the case of SVR.

Establishing a Water Resources Resilience Baseline for Mexico City

NASA Astrophysics Data System (ADS)

Behzadi, F.; Ray, P. A.

2017-12-01

There is a growing concern for the vulnerability of the Mexico City water system to shocks, and the capacity of the system to accommodate climate and demographic change. This study presents a coarse-resolution, lumped model of the water system of Mexico City as a whole, designed to identify system-wide imbalances, and opportunities for large-scale improvements in city-wide resilience through investments in water imports, exports, and storage. In order to investigate the impact of climate change in Mexico City, the annual and monthly trends of precipitation and temperature at 46 stations near or inside the Mexico City were analyzed. The statistical significance of the trends in rainfall and temperature, both over the entire period of record, and the more recent "climate-change-impacted period" (1970-2015), were determined using the non-parametric Mann-Kendall test. Results show a statistically significant increasing trend in the annual mean precipitation, mean temperature, and annual maximum daily temperature. However, minimum daily temperature does not appear to be increasing, and might be decreasing. Water management in Mexico City faces particular challenges, where the winter dry season is warming more quickly than the wet summer season. A stress test of Mexico City water system is conducted to identify vulnerabilities to changes in exogenous factors (esp., climate, demographics, land use). Following on the stress test, the relative merits of adaptation options that might improve the system's resilience and sustainability will be assessed.

Spatiotemporal Divergence of the Warming Hiatus over Land Based on Different Definitions of Mean Temperature

PubMed Central

Zhou, Chunlüe; Wang, Kaicun

2016-01-01

Existing studies of the recent warming hiatus over land are primarily based on the average of daily minimum and maximum temperatures (T2). This study compared regional warming rates of mean temperature based on T2 and T24 calculated from hourly observations available from 1998 to 2013. Both T2 and T24 show that the warming hiatus over land is apparent in the mid-latitudes of North America and Eurasia, especially in cold seasons, which is closely associated with the negative North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) and cold air propagation by the Arctic-original northerly wind anomaly into mid-latitudes. However, the warming rates of T2 and T24 are significantly different at regional and seasonal scales because T2 only samples air temperature twice daily and cannot accurately reflect land-atmosphere and incoming radiation variations in the temperature diurnal cycle. The trend has a standard deviation of 0.43 °C/decade for T2 and 0.41 °C/decade for T24, and 0.38 °C/decade for their trend difference in 5° × 5° grids. The use of T2 amplifies the regional contrasts of the warming rate, i.e., the trend underestimation in the US and overestimation at high latitudes by T2. PMID:27531421

Variability of temperature properties over Kenya based on observed and reanalyzed datasets

NASA Astrophysics Data System (ADS)

Ongoma, Victor; Chen, Haishan; Gao, Chujie; Sagero, Phillip Obaigwa

2017-08-01

Updated information on trends of climate extremes is central in the assessment of climate change impacts. This work examines the trends in mean, diurnal temperature range (DTR), maximum and minimum temperatures, 1951-2012 and the recent (1981-2010) extreme temperature events over Kenya. The study utilized daily observed and reanalyzed monthly mean, minimum, and maximum temperature datasets. The analysis was carried out based on a set of nine indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI). The trend of the mean and the extreme temperature was determined using Mann-Kendall rank test, linear regression analysis, and Sen's slope estimator. December-February (DJF) season records high temperature while June-August (JJA) experiences the least temperature. The observed rate of warming is + 0.15 °C/decade. However, DTR does not show notable annual trend. Both seasons show an overall warming trend since the early 1970s with abrupt and significant changes happening around the early 1990s. The warming is more significant in the highland regions as compared to their lowland counterparts. There is increase variance in temperature. The percentage of warm days and warm nights is observed to increase, a further affirmation of warming. This work is a synoptic scale study that exemplifies how seasonal and decadal analyses, together with the annual assessments, are important in the understanding of the temperature variability which is vital in vulnerability and adaptation studies at a local/regional scale. However, following the quality of observed data used herein, there remains need for further studies on the subject using longer and more data to avoid generalizations made in this study.

An experimental analysis of electricity conservation procedures1

PubMed Central

Palmer, Michael H.; Lloyd, Margaret E.; Lloyd, Kenneth E.

1977-01-01

Daily electricity consumption of four families was recorded for 106 days. A reversal design, consisting of various experimental conditions interspersed between repeated baseline conditions, was used. During experimental conditions, daily prompts (written conservation slogans attached to front doors) and/or daily feedback (daily kilowatts consumed and daily cost information) were in effect. Maximum consumption occurred during the initial baseline; minimum consumption occurred during different experimental conditions for different families. The mean decrease from the maximum to the minimum for all families was 35%. Reversals in consumption were demonstrated in three families, although successive baselines tended to decrease. No clear differences in effectiveness between prompting and feedback conditions were apparent. The procedures used resulted in considerable dollar savings for the families. PMID:16795572

Raised temperatures over the Kericho tea estates: revisiting the climate in the East African highlands malaria debate

PubMed Central

2011-01-01

Background Whether or not observed increases in malaria incidence in the Kenyan Highlands during the last thirty years are associated with co-varying changes in local temperature, possibly connected to global changes in climate, has been debated for over a decade. Studies, using differing data sets and methodologies, produced conflicting results regarding the occurrence of temperature trends and their likelihood of being responsible, at least in part, for the increases in malaria incidence in the highlands of western Kenya. A time series of quality controlled daily temperature and rainfall data from Kericho, in the Kenyan Highlands, may help resolve the controversy. If significant temperature trends over the last three decades have occurred then climate should be included (along with other factors such as land use change and drug resistance) as a potential driver of the observed increases in malaria in the region. Methods Over 30 years (1 January 1979 to 31 December 2009) of quality controlled daily observations ( > 97% complete) of maximum, minimum and mean temperature were used in the analysis of trends at Kericho meteorological station, sited in a tea growing area of Kenya's western highlands. Inhomogeneities in all the time series were identified and corrected. Linear trends were identified via a least-squares regression analysis with statistical significance assessed using a two-tailed t-test. These 'gold standard' meteorological observations were compared with spatially interpolated temperature datasets that have been developed for regional or global applications. The relationship of local climate processes with larger climate variations, including tropical sea surface temperatures (SST), and El Niño-Southern Oscillation (ENSO) was also assessed. Results An upward trend of ≈0.2°C/decade was observed in all three temperature variables (P < 0.01). Mean temperature variations in Kericho were associated with large-scale climate variations including tropical SST (r = 0.50; p < 0.01). Local rainfall was found to have inverse effects on minimum and maximum temperature. Three versions of a spatially interpolated temperature data set showed markedly different trends when compared with each other and with the Kericho station observations. Conclusion This study presents evidence of a warming trend in observed maximum, minimum and mean temperatures at Kericho during the period 1979 to 2009 using gold standard meteorological observations. Although local factors may be contributing to these trends, the findings are consistent with variability and trends that have occurred in correlated global climate processes. Climate should therefore not be dismissed as a potential driver of observed increases in malaria seen in the region during recent decades, however its relative importance compared to other factors needs further elaboration. Climate services, pertinent to the achievement of development targets such as the Millennium Development Goals and the analysis of infectious disease in the context of climate variability and change are being developed and should increase the availability of relevant quality controlled climate data for improving development decisions. The malaria community should seize this opportunity to make their needs heard. PMID:21241505

Extreme temperature indices analyses: A case study of five meteorological stations in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Hasan, Husna; Salleh, Nur Hanim Mohd

2015-10-01

Extreme temperature events affect many human and natural systems. Changes in extreme temperature events can be detected and monitored by developing the indices based on the extreme temperature data. As an effort to provide the understanding of these changes to the public, a study of extreme temperature indices is conducted at five meteorological stations in Peninsular Malaysia. In this study, changes in the means and extreme events of temperature are assessed and compared using the daily maximum and minimum temperature data for the period of 2004 to 2013. The absolute extreme temperature indices; TXx, TXn, TXn and TNn provided by Expert Team on Climate Change Detection and Indices (ETCCDI) are utilized and linear trends of each index are extracted using least square likelihood method. The results indicate that there exist significant decreasing trend in the TXx index for Kota Bharu station and increasing trend in TNn index for Chuping and Kota Kinabalu stations. The comparison between the trend in mean and extreme temperatures show the same significant tendency for Kota Bharu and Kuala Terengganu stations.

Selected micrometeorological and soil-moisture data at Amargosa Desert Research Site, an arid site near Beatty, Nye County, Nevada, 1998-2000

USGS Publications Warehouse

Johnson, Michael J.; Mayers, Charles J.; Andraski, Brian J.

2002-01-01

Selected micrometeorological and soil-moisture data were collected at the Amargosa Desert Research Site adjacent to a low-level radioactive waste and hazardous chemical waste facility near Beatty, Nev., 1998-2000. Data were collected in support of ongoing research studies to improve the understanding of hydrologic and contaminant-transport processes in arid environments. Micrometeorological data include precipitation, air temperature, solar radiation, net radiation, relative humidity, ambient vapor pressure, wind speed and direction, barometric pressure, soil temperature, and soil-heat flux. All micrometeorological data were collected using a 10-second sampling interval by data loggers that output daily mean, maximum, and minimum values, and hourly mean values. For precipitation, data output consisted of daily, hourly, and 5-minute totals. Soil-moisture data included periodic measurements of soil-water content at nine neutron-probe access tubes with measurable depths ranging from 5.25 to 29.75 meters. The computer data files included in this report contain the complete micrometeorological and soil-moisture data sets. The computer data consists of seven files with about 14 megabytes of information. The seven files are in tabular format: (1) one file lists daily mean, maximum, and minimum micrometeorological data and daily total precipitation; (2) three files list hourly mean micrometeorological data and hourly precipitation for each year (1998-2000); (3) one file lists 5-minute precipitation data; (4) one file lists mean soil-water content by date and depth at four experimental sites; and (5) one file lists soil-water content by date and depth for each neutron-probe access tube. This report highlights selected data contained in the computer data files using figures, tables, and brief discussions. Instrumentation used for data collection also is described. Water-content profiles are shown to demonstrate variability of water content with depth. Time-series data are plotted to illustrate temporal variations in micrometeorological and soil-water content data. Substantial precipitation at the end of an El Ni?o cycle in early 1998 resulted in measurable water penetration to a depth of 1.25 meters at one of the four experimental soil-monitoring sites.

Actual daily evapotranspiration estimated from MERIS and AATSR data over the Chinese Loess Plateau

NASA Astrophysics Data System (ADS)

Liu, R.; Wen, J.; Wang, X.; Wang, L.; Tian, H.; Zhang, T. T.; Shi, X. K.; Zhang, J. H.; Lu, Sh. N.

2009-02-01

The Loess Plateau is located in north of China and has a significant impact on the climate and ecosystem evolvement over the East Asian continent. Based on the land surface energy balance theory, the potential of using Medium Resolution Imaging Spectrometer (onboard sensor of the Environmental Satellite) remote sensing data on 7, 11 and 27 June 2005 is explored. The "split-window" algorithm is used to retrieve surface temperature from the Advanced the Along-Track Scanning Radiometer, another onboard senor of the Environmental Satellite. Then the near surface net radiation, sensible heat flux and soil heat flux are estimated by using the developed algorithm. We introduce a simple algorithm to predict the heat flux partitioning between the soil and vegetation. Combining the sunshine hours, air temperature, sunshine duration and wind speed measured by weather stations, a model for estimating daily ET is proposed. The instantaneous ET is also converted to daily value. Comparison of latent heats flux retrieved by remote sensing data with ground observation from eddy covariance flux system during Loess Plateau land surface process field Experiment, the maximum and minimum error of this approach are 10.96% and 4.80% respectively, the cause of the bias is also explored and discussed.

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

Shiogama, Hideo; Imada, Yukiko; Mori, Masato

Here, we describe two unprecedented large (100-member), longterm (61-year) ensembles based on MRI-AGCM3.2, which were driven by historical and non-warming climate forcing. These ensembles comprise the "Database for Policy Decision making for Future climate change (d4PDF)". We compare these ensembles to large ensembles based on another climate model, as well as to observed data, to investigate the influence of anthropogenic activities on historical changes in the numbers of record-breaking events, including: the annual coldest daily minimum temperature (TNn), the annual warmest daily maximum temperature (TXx) and the annual most intense daily precipitation event (Rx1day). These two climate model ensembles indicatemore » that human activity has already had statistically significant impacts on the number of record-breaking extreme events worldwide mainly in the Northern Hemisphere land. Specifically, human activities have altered the likelihood that a wider area globally would suffer record-breaking TNn, TXx and Rx1day events than that observed over the 2001- 2010 period by a factor of at least 0.6, 5.4 and 1.3, respectively. However, we also find that the estimated spatial patterns and amplitudes of anthropogenic impacts on the probabilities of record-breaking events are sensitive to the climate model and/or natural-world boundary conditions used in the attribution studies.« less

Low-flow characteristics of streams in Ohio through water year 1997

USGS Publications Warehouse

Straub, David E.

2001-01-01

This report presents selected low-flow and flow-duration characteristics for 386 sites throughout Ohio. These sites include 195 long-term continuous-record stations with streamflow data through water year 1997 (October 1 to September 30) and for 191 low-flow partial-record stations with measurements into water year 1999. The characteristics presented for the long-term continuous-record stations are minimum daily streamflow; average daily streamflow; harmonic mean flow; 1-, 7-, 30-, and 90-day minimum average low flow with 2-, 5-, 10-, 20-, and 50-year recurrence intervals; and 98-, 95-, 90-, 85-, 80-, 75-, 70-, 60-, 50-, 40-, 30-, 20-, and 10-percent daily duration flows. The characteristics presented for the low-flow partial-record stations are minimum observed streamflow; estimated 1-, 7-, 30-, and 90-day minimum average low flow with 2-, 10-, and 20-year recurrence intervals; and estimated 98-, 95-, 90-, 85- and 80-percent daily duration flows. The low-flow frequency and duration analyses were done for three seasonal periods (warm weather, May 1 to November 30; winter, December 1 to February 28/29; and autumn, September 1 to November 30), plus the annual period based on the climatic year (April 1 to March 31).

Spatiotemporal extremes of temperature and precipitation during 1960-2015 in the Yangtze River Basin (China) and impacts on vegetation dynamics

NASA Astrophysics Data System (ADS)

Cui, Lifang; Wang, Lunche; Qu, Sai; Singh, Ramesh P.; Lai, Zhongping; Yao, Rui

2018-05-01

Recently, extreme climate variation has been studied in different parts of the world, and the present study aims to study the impacts of climate extremes on vegetation. In this study, we analyzed the spatiotemporal variations of temperature and precipitation extremes during 1960-2015 in the Yangtze River Basin (YRB) using the Mann-Kendall (MK) test with Sen's slope estimator and kriging interpolation method based on daily precipitation (P), maximum temperature (T max), and minimum temperature (T min). We also analyzed the vegetation dynamics in the YRB during 1982-2015 using Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) datasets and investigated the relationship between temperature and precipitation extremes and NDVI using Pearson correlation coefficients. The results showed a pronounced increase in the annual mean maximum temperature (T nav) and mean minimum temperature (T xav) at the rate of 0.23 °C/10 years and 0.15 °C/10 years, respectively, during 1960-2015. In addition, the occurrence of warm days and warm nights shows increasing trends at the rate of 1.36 days/10 years and 1.70 days/10 years, respectively, while cold days and cold nights decreased at the rate of 1.09 days/10 years and 2.69 days/10 years, respectively, during 1960-2015. The precipitation extremes, such as very wet days (R95, the 95th percentile of daily precipitation events), very wet day precipitation (R95p, the number of days with rainfall above R95), rainstorm (R50, the number of days with rainfall above 50 mm), and maximum 1-day precipitation (RX1day), all show pronounced increasing trends during 1960-2015. In general, annual mean NDVI over the whole YRB increased at the rate of 0.01/10 years during 1982-2015, with an increasing transition around 1994. Spatially, annual mean NDVI increased in the northern, eastern, and parts of southwestern YRB, while it decreased in the YRD and parts of southern YRB during 1982-2015. The correlation coefficients showed that annual mean NDVI was closely correlated with temperature extremes during 1982-2015 and 1995-2015, but no significant correlation with precipitation extremes was observed. However, the decrease in NDVI was correlated with increasing R95p and R95 during 1982-1994.

Integrating solar energy and climate research into science education

NASA Astrophysics Data System (ADS)

Betts, Alan K.; Hamilton, James; Ligon, Sam; Mahar, Ann Marie

2016-01-01

This paper analyzes multi-year records of solar flux and climate data from two solar power sites in Vermont. We show the inter-annual differences of temperature, wind, panel solar flux, electrical power production, and cloud cover. Power production has a linear relation to a dimensionless measure of the transmission of sunlight through the cloud field. The difference between panel and air temperatures reaches 24°C with high solar flux and low wind speed. High panel temperatures that occur in summer with low wind speeds and clear skies can reduce power production by as much as 13%. The intercomparison of two sites 63 km apart shows that while temperature is highly correlated on daily (R2=0.98) and hourly (R2=0.94) timescales, the correlation of panel solar flux drops markedly from daily (R2=0.86) to hourly (R2=0.63) timescales. Minimum temperatures change little with cloud cover, but the diurnal temperature range shows a nearly linear increase with falling cloud cover to 16°C under nearly clear skies, similar to results from the Canadian Prairies. The availability of these new solar and climate datasets allows local student groups, a Rutland High School team here, to explore the coupled relationships between climate, clouds, and renewable power production. As our society makes major changes in our energy infrastructure in response to climate change, it is important that we accelerate the technical education of high school students using real-world data.

a Weather Monitoring System for Application to Apple and Corn Production

NASA Astrophysics Data System (ADS)

Stirm, Walter Leroy

Many crop management decisions are based on weather -crop development relationships. Daily weather data is currently used in most crop development research and applied models. Present weather and computer technology now makes possible monitoring of crop development on a realtime basis. This research tests a method of computing crop sensitive temperatures for corn and apple using standard hourly meteorological data. The method also makes use of detailed plant physiological stage measurements to determine timing of vital cultural operations tied to the observed weather conditions. The sensitive temperature method incorporates very short term weather variability accounting for changes in the cloud cover, radiation rates, evaporative cooling and other factors involved in the plant's energy balance. The relationship of plant and weather measurements are also used to determine corn emergence, corn grain drydown rate and fruit harvest duration. The monitoring system also incorporates a crop growth unit forecast technique employing short and medium range temperature forecasts of the National Weather Service. The projections of growth units are made for five and ten days into the future. Predicted growth unit accumulations are compared to historical growth unit accumulations to determine the forecast stage. The sensitive temperature crop monitoring system removes some of the error involved in evaluation of growth units by average daily temperature. Carry over maximum and minimums, extended duration of warm or cool periods within the day and disruption of diurnal temperature curve by passage of fronts are eliminated.

Thermal tolerances of fishes occupying groundwater and surface-water dominated streams

USGS Publications Warehouse

Farless, Nicole; Brewer, Shannon K.

2017-01-01

A thermal tolerance study mimicking different stream environments could improve our ecological understanding of how increasing water temperatures affect stream ectotherms and improve our ability to predict organism responses based on river classification schemes. Our objective was to compare the thermal tolerances of stream fishes of different habitat guilds among 3 exposure periods: critical thermal maximum (CTmax, increase of 2°C/h until loss of equilibrium [LOE] and death [D]), and 2 longer-term treatments (net daily increase of 1°C) that mimicked spring-fed (SF; 4°C daily increase) and non-spring-fed (NSF; 8°C daily increase) conditions. Fishes in the pelagic habitat guild had a 1°C higher average CTmax than benthic fishes. Thermal responses of species depended on exposure period with higher and increased variation in tolerances associated with the SF and NSF exposure periods. Logperch, Orangebelly Darter, Orangethroat Darter, and Southern Redbelly Dace were more sensitive to thermal increases regardless of SF or NSF treatment than were the 3 remaining species (Brook Silverside, Central Stoneroller, and Redspot Chub), which represented average thermal responses among the species tested. The 3 species that had a higher thermal response to CTmax-D (lethal endpoint of death) also were able to increase their tolerances more than other species in both SF and NSF treatments. Our data indicate finer guild designations may be useful for predicting thermal-response patterns. A diel thermal refuge increases the thermal responses of ectotherms to daily maxima, but the patterns across our SF and NSF treatments were similar suggesting minimum refuge temperatures may be more important than maximums. Nonetheless, stream temperature cooling over a 24-h period is important to ectotherm thermal tolerances, a result suggesting that sources of cooler water to streams might benefit from protection.

Uncertainty Assessment of the NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP) Dataset

NASA Technical Reports Server (NTRS)

Wang, Weile; Nemani, Ramakrishna R.; Michaelis, Andrew; Hashimoto, Hirofumi; Dungan, Jennifer L.; Thrasher, Bridget L.; Dixon, Keith W.

2016-01-01

The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of downscaled climate projections that are derived from 21 General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and across two of the four greenhouse gas emissions scenarios (RCP4.5 and RCP8.5). Each of the climate projections includes daily maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2100 and the spatial resolution is 0.25 degrees (approximately 25 km x 25 km). The GDDP dataset has received warm welcome from the science community in conducting studies of climate change impacts at local to regional scales, but a comprehensive evaluation of its uncertainties is still missing. In this study, we apply the Perfect Model Experiment framework (Dixon et al. 2016) to quantify the key sources of uncertainties from the observational baseline dataset, the downscaling algorithm, and some intrinsic assumptions (e.g., the stationary assumption) inherent to the statistical downscaling techniques. We developed a set of metrics to evaluate downscaling errors resulted from bias-correction ("quantile-mapping"), spatial disaggregation, as well as the temporal-spatial non-stationarity of climate variability. Our results highlight the spatial disaggregation (or interpolation) errors, which dominate the overall uncertainties of the GDDP dataset, especially over heterogeneous and complex terrains (e.g., mountains and coastal area). In comparison, the temporal errors in the GDDP dataset tend to be more constrained. Our results also indicate that the downscaled daily precipitation also has relatively larger uncertainties than the temperature fields, reflecting the rather stochastic nature of precipitation in space. Therefore, our results provide insights in improving statistical downscaling algorithms and products in the future.

Variability in Temperature-Related Mortality Projections under Climate Change

PubMed Central

Benmarhnia, Tarik; Sottile, Marie-France; Plante, Céline; Brand, Allan; Casati, Barbara; Fournier, Michel

2014-01-01

Background: Most studies that have assessed impacts on mortality of future temperature increases have relied on a small number of simulations and have not addressed the variability and sources of uncertainty in their mortality projections. Objectives: We assessed the variability of temperature projections and dependent future mortality distributions, using a large panel of temperature simulations based on different climate models and emission scenarios. Methods: We used historical data from 1990 through 2007 for Montreal, Quebec, Canada, and Poisson regression models to estimate relative risks (RR) for daily nonaccidental mortality in association with three different daily temperature metrics (mean, minimum, and maximum temperature) during June through August. To estimate future numbers of deaths attributable to ambient temperatures and the uncertainty of the estimates, we used 32 different simulations of daily temperatures for June–August 2020–2037 derived from three global climate models (GCMs) and a Canadian regional climate model with three sets of RRs (one based on the observed historical data, and two on bootstrap samples that generated the 95% CI of the attributable number (AN) of deaths). We then used analysis of covariance to evaluate the influence of the simulation, the projected year, and the sets of RRs used to derive the attributable numbers of deaths. Results: We found that < 1% of the variability in the distributions of simulated temperature for June–August of 2020–2037 was explained by differences among the simulations. Estimated ANs for 2020–2037 ranged from 34 to 174 per summer (i.e., June–August). Most of the variability in mortality projections (38%) was related to the temperature–mortality RR used to estimate the ANs. Conclusions: The choice of the RR estimate for the association between temperature and mortality may be important to reduce uncertainty in mortality projections. Citation: Benmarhnia T, Sottile MF, Plante C, Brand A, Casati B, Fournier M, Smargiassi A. 2014. Variability in temperature-related mortality projections under climate change. Environ Health Perspect 122:1293–1298; http://dx.doi.org/10.1289/ehp.1306954 PMID:25036003

Soil temperature investigations using satellite acquired thermal-infrared data in semi-arid regions. Thesis. Final Report; [Utah

NASA Technical Reports Server (NTRS)

Day, R. L.; Petersen, G. W.

1983-01-01

Thermal-infrared data from the Heat Capacity Mapping Mission satellite were used to map the spatial distribution of diurnal surface temperatures and to estimate mean annual soil temperatures (MAST) and annual surface temperature amplitudes (AMP) in semi-arid east central Utah. Diurnal data with minimal snow and cloud cover were selected for five dates throughout a yearly period and geometrically co-registered. Rubber-sheet stretching was aided by the WARP program which allowed preview of image transformations. Daytime maximum and nighttime minimum temperatures were averaged to generation average daily temperature (ADT) data set for each of the five dates. Five ADT values for each pixel were used to fit a sine curve describing the theoretical annual surface temperature response as defined by a solution of a one-dimensinal heat flow equation. Linearization of the equation produced estimates of MAST and AMP plus associated confidence statistics. MAST values were grouped into classes and displayed on a color video screen. Diurnal surface temperatures and MAST were primarily correlated with elevation.

Climate Data Bases of the People's Republic of China 1841-1988 (TR-055)

DOE Data Explorer

Kaiser, Dale. [Oak Ridge National Lab, Oak Ridge, TN (USA); Carbon Dioxide Analysis Center (CDIAC); Tao, Shiyan [Chinese Academy of Sciences, Beijing, China; Fu, Congbin [Chinese Academy of Sciences, Beijing, China; Zeng, Zhaomei [Chinese Academy of Sciences (CAS), Beijing, China; Zhang, Qingyun [Chinese Academy of Sciences (CAS), Beijing (China); Wang, Wei-Chyung [University at Albany, State University of New York, Albany, New York (USA); Atmospheric Science Research Center; Karl, Thomas [National Oceanic and Atmospheric Administration, Asheville, North Carolina (USA); Global Climate Laboratory, National Climatic Data Center

1993-01-01

A data base containing meteorological observations from the People's Republic of China (PRC) is described. These data 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's Institute of Atmospheric Physics (Beijing, PRC) has provided records from 296 stations, organized into five data sets: (1) a 60-station data set containing monthly measurements of barometric pressure, surface air temperature, precipitation amount, relative humidity, sunshine duration, cloud amount, wind direction and speed, and number of days with snow cover; (2) a 205-station data set containing monthly mean temperatures and monthly precipitation totals; (3) a 40-station subset of the 205-station data set containing monthly mean maximum and minimum temperatures and monthly extreme maximum and minimum temperatures; (4) a 180-station data set containing daily precipitation totals; and (5) a 147-station data set containing 10-day precipitation totals. Sixteen stations from these data sets (13 from the 60-station set and 3 from the 205-station set) have temperature and/or precipitation records that begin prior to 1900, whereas the remaining stations began observing in the early to mid-1900s. Records from most stations extend through 1988. (Note: Users interested in the TR055 60-station data set should acquire expanded and updated data from CDIAC's NDP-039, Two Long-Term Instrumental Climatic Data Bases of the People's Republic of China)

[Impacts of climate warming on growth period and yield of rice in Northeast China during recent two decades].

PubMed

Hou, Wen-jia; Geng, Ting; Chen, Qun; Chen, Chang-qing

2015-01-01

By using rice growth period, yield and climate observation data during the recent two decades, the impact of climate warming on rice in Northeast China was investigated by mathematical statistics methods. The results indicated that in the three provinces of Northeast China, the average, maximum and minimum temperatures in rice growing season were on the. rise, and the rainfall presented a downward trend during 1989-2009. Compared to 1990s, the rice whole growth periods of Heilongjiang, Jilin and Liaoning provinces in 2000s were prolonged 14 d, 4.5 d and 5.1 d, respectively. The increase of temperature in May, June and September could extend the rice growth period, while that in July would shorten the growth duration. The rice growth duration of registered varieties and experiment sites had a similar increasing trend in Northeast China except for the Heilongjiang Province, and the extension of registered varieties growth period was the main factor causing the prolonged growth period of rice at experiment sites. The change in daily average, minimum and maximum temperatures all could affect the rice yield in Northeast China. The increasing temperature significantly increased the rice yield in Heilongjiang Province, especially in the west region of Sanjiang Plain. Except for the south of Liaoning Province, rice yields in other regions of Northeast China were promoted by increasing temperature. Proper measures for breeding, cultivation and farming, could be adopted to fully improve the adaptation of rice to climate warming in Northeast China.

Brief Report: Investigating Uncertainty in the Minimum Mortality Temperature: Methods and Application to 52 Spanish Cities.

PubMed

Tobías, Aurelio; Armstrong, Ben; Gasparrini, Antonio

2017-01-01

The minimum mortality temperature from J- or U-shaped curves varies across cities with different climates. This variation conveys information on adaptation, but ability to characterize is limited by the absence of a method to describe uncertainty in estimated minimum mortality temperatures. We propose an approximate parametric bootstrap estimator of confidence interval (CI) and standard error (SE) for the minimum mortality temperature from a temperature-mortality shape estimated by splines. The coverage of the estimated CIs was close to nominal value (95%) in the datasets simulated, although SEs were slightly high. Applying the method to 52 Spanish provincial capital cities showed larger minimum mortality temperatures in hotter cities, rising almost exactly at the same rate as annual mean temperature. The method proposed for computing CIs and SEs for minimums from spline curves allows comparing minimum mortality temperatures in different cities and investigating their associations with climate properly, allowing for estimation uncertainty.

Downscaling RCP8.5 daily temperatures and precipitation in Ontario using localized ensemble optimal interpolation (EnOI) and bias correction

NASA Astrophysics Data System (ADS)

Deng, Ziwang; Liu, Jinliang; Qiu, Xin; Zhou, Xiaolan; Zhu, Huaiping

2017-10-01

A novel method for daily temperature and precipitation downscaling is proposed in this study which combines the Ensemble Optimal Interpolation (EnOI) and bias correction techniques. For downscaling temperature, the day to day seasonal cycle of high resolution temperature of the NCEP climate forecast system reanalysis (CFSR) is used as background state. An enlarged ensemble of daily temperature anomaly relative to this seasonal cycle and information from global climate models (GCMs) are used to construct a gain matrix for each calendar day. Consequently, the relationship between large and local-scale processes represented by the gain matrix will change accordingly. The gain matrix contains information of realistic spatial correlation of temperature between different CFSR grid points, between CFSR grid points and GCM grid points, and between different GCM grid points. Therefore, this downscaling method keeps spatial consistency and reflects the interaction between local geographic and atmospheric conditions. Maximum and minimum temperatures are downscaled using the same method. For precipitation, because of the non-Gaussianity issue, a logarithmic transformation is used to daily total precipitation prior to conducting downscaling. Cross validation and independent data validation are used to evaluate this algorithm. Finally, data from a 29-member ensemble of phase 5 of the Coupled Model Intercomparison Project (CMIP5) GCMs are downscaled to CFSR grid points in Ontario for the period from 1981 to 2100. The results show that this method is capable of generating high resolution details without changing large scale characteristics. It results in much lower absolute errors in local scale details at most grid points than simple spatial downscaling methods. Biases in the downscaled data inherited from GCMs are corrected with a linear method for temperatures and distribution mapping for precipitation. The downscaled ensemble projects significant warming with amplitudes of 3.9 and 6.5 °C for 2050s and 2080s relative to 1990s in Ontario, respectively; Cooling degree days and hot days will significantly increase over southern Ontario and heating degree days and cold days will significantly decrease in northern Ontario. Annual total precipitation will increase over Ontario and heavy precipitation events will increase as well. These results are consistent with conclusions in many other studies in the literature.

[Impact of low temperature in young ear formation stage on rice seed setting.

PubMed

Ma, Shu Qing; Liu, Xiao Hang; Deng, Kui Cai; Quan, Hu Jie; Tong, Li Yuan; Xi, Zhu Xiang; Chai, Qing Rong; Yang, Jun

2018-01-01

A low temperature treatment in rice booting key period was executed on the north slope of Changbai Mountains to construct the impact model of low temperature on rice shell rate, and to reveal the effects of low temperature at different stages of rice young panicle on seed setting. The results showed that effects of low temperature in the young ear formation stage on rice shell rate generally followed the logarithmic function, the lower the temperature was, the greater the temperature influence coefficient was, and the longer the low temperature duration was, the higher rice shell rate was. The seed setting rate was most sensitive to low temperature in the middle time of booting stage (the period from formation to meiosis of the pollen mother cell), followed by the early and later stages. During the booting stage, with 1 ℃ decrease of daily temperature under 2-, 3- and 5-day low temperature treatments, the shell rate increased by 0.5, 1.7 and 4.3 percentage, respectively, and with 1 ℃ decrease of daily minimum temperature, the shell rate increased by 0.4,1.8 and 4.5 percentage, respectively. The impact of 2-day low temperature was smaller than that of 3 days or more. The impact of accumulative cold-temperature on the shell rate followed exponential function. In the range of harmful low temperature, rice shell rate increased about 8.5 percentage with the accumulative cold-temperature increasing 10 ℃·d. When the 3 days average temperature dropped to 21.6, 18.0 and 15.0 ℃, or the 5 days average temperature dropped to 22.0, 20.4 and 18.5 ℃, or the accumulative cold-temperature was more than 8, 19, 26 ℃·d, the light, moderate and severe booting stage chilling injury would occur, respectively. In Northeast China, low temperature within 2 d in rice booting stage might not cause moderate and severe chilling injury.

Fundamental statistical relationships between monthly and daily meteorological variables: Temporal downscaling of weather based on a global observational dataset

NASA Astrophysics Data System (ADS)

Sommer, Philipp; Kaplan, Jed

2016-04-01

Accurate modelling of large-scale vegetation dynamics, hydrology, and other environmental processes requires meteorological forcing on daily timescales. While meteorological data with high temporal resolution is becoming increasingly available, simulations for the future or distant past are limited by lack of data and poor performance of climate models, e.g., in simulating daily precipitation. To overcome these limitations, we may temporally downscale monthly summary data to a daily time step using a weather generator. Parameterization of such statistical models has traditionally been based on a limited number of observations. Recent developments in the archiving, distribution, and analysis of "big data" datasets provide new opportunities for the parameterization of a temporal downscaling model that is applicable over a wide range of climates. Here we parameterize a WGEN-type weather generator using more than 50 million individual daily meteorological observations, from over 10'000 stations covering all continents, based on the Global Historical Climatology Network (GHCN) and Synoptic Cloud Reports (EECRA) databases. Using the resulting "universal" parameterization and driven by monthly summaries, we downscale mean temperature (minimum and maximum), cloud cover, and total precipitation, to daily estimates. We apply a hybrid gamma-generalized Pareto distribution to calculate daily precipitation amounts, which overcomes much of the inability of earlier weather generators to simulate high amounts of daily precipitation. Our globally parameterized weather generator has numerous applications, including vegetation and crop modelling for paleoenvironmental studies.

Comparison of artificial intelligence methods and empirical equations to estimate daily solar radiation

NASA Astrophysics Data System (ADS)

Mehdizadeh, Saeid; Behmanesh, Javad; Khalili, Keivan

2016-08-01

In the present research, three artificial intelligence methods including Gene Expression Programming (GEP), Artificial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) as well as, 48 empirical equations (10, 12 and 26 equations were temperature-based, sunshine-based and meteorological parameters-based, respectively) were used to estimate daily solar radiation in Kerman, Iran in the period of 1992-2009. To develop the GEP, ANN and ANFIS models, depending on the used empirical equations, various combinations of minimum air temperature, maximum air temperature, mean air temperature, extraterrestrial radiation, actual sunshine duration, maximum possible sunshine duration, sunshine duration ratio, relative humidity and precipitation were considered as inputs in the mentioned intelligent methods. To compare the accuracy of empirical equations and intelligent models, root mean square error (RMSE), mean absolute error (MAE), mean absolute relative error (MARE) and determination coefficient (R2) indices were used. The results showed that in general, sunshine-based and meteorological parameters-based scenarios in ANN and ANFIS models presented high accuracy than mentioned empirical equations. Moreover, the most accurate method in the studied region was ANN11 scenario with five inputs. The values of RMSE, MAE, MARE and R2 indices for the mentioned model were 1.850 MJ m-2 day-1, 1.184 MJ m-2 day-1, 9.58% and 0.935, respectively.

Statistical physics when the minimum temperature is not absolute zero

NASA Astrophysics Data System (ADS)

Chung, Won Sang; Hassanabadi, Hassan

2018-04-01

In this paper, the nonzero minimum temperature is considered based on the third law of thermodynamics and existence of the minimal momentum. From the assumption of nonzero positive minimum temperature in nature, we deform the definitions of some thermodynamical quantities and investigate nonzero minimum temperature correction to the well-known thermodynamical problems.

Recent climate trends and implications for water resources in the Catskill Mountain region, New York, USA

USGS Publications Warehouse

Burns, Douglas A.; Klaus, Julian; McHale, Michael R.

2007-01-01

Climate scientists have concluded that the earth’s surface air temperature warmed by 0.6 °C during the 20th century, and that warming induced by increasing concentrations of greenhouse gases is likely to continue in the 21st century, accompanied by changes in the hydrologic cycle. Climate change has important implications in the Catskill region of southeastern New York State, because the region is a source of water supply for New York City. We used the non-parametric Mann–Kendall test to evaluate annual, monthly, and multi-month trends in air temperature, precipitation amount, stream runoff, and potential evapotranspiration (PET) in the region during 1952–2005 based on data from 9 temperature sites, 12 precipitation sites, and 8 stream gages. A general pattern of warming temperatures and increased precipitation, runoff, and PET is evident in the region. Regional annual mean air temperature increased significantly by 0.6 °C per 50 years during the period; the greatest increases and largest number of significant upward trends were in daily minimum air temperature. Daily maximum air temperature showed the greatest increase during February through April, whereas minimum air temperature showed the greatest increase during May through September. Regional mean precipitation increased significantly by 136 mm per 50 years, nearly double that of the regional mean increase in runoff, which was not significant. Regional mean PET increased significantly by 19 mm per 50 years, about one-seventh that of the increase in precipitation amount, and broadly consistent with increased runoff during 1952–2005, despite the lack of significance in the mean regional runoff trend. Peak snowmelt as approximated by the winter–spring center of volume of stream runoff generally shifted from early April at the beginning of the record to late March at the end of the record, consistent with a decreasing trend in April runoff and an increasing trend in maximum March air temperature. This change indicates an increased supply of water to reservoirs earlier in the year. Additionally, the supply of water to reservoirs at the beginning of winter is greater as indicated by the timing of the greatest increases in precipitation and runoff—both occurred during summer and fall. The future balance between changes in air temperature and changes in the timing and amount of precipitation in the region will have important implications for the available water supply in the region.

Dissolved oxygen fluctuations in karst spring flow and implications for endemic species: Barton Springs, Edwards aquifer, Texas, USA

USGS Publications Warehouse

Mahler, Barbara J.; Bourgeais, Renan

2013-01-01

Karst aquifers and springs provide the dissolved oxygen critical for survival of endemic stygophiles worldwide, but little is known about fluctuations of dissolved oxygen concentrations (DO) and factors that control those concentrations. We investigated temporal variation in DO at Barton Springs, Austin, Texas, USA. During 2006–2012, DO fluctuated by as much as a factor of 2, and at some periods decreased to concentrations that adversely affect the Barton Springs salamander (Eurycea sorosum) (≤4.4 mg/L), a federally listed endangered species endemic to Barton Springs. DO was lowest (≤4.4 mg/L) when discharge was low (≤1 m3/s) and spring water temperature was >21 °C, although not at a maximum; the minimum DO recorded was 4.0 mg/L. Relatively low DO (3/s) and maximum T (22.2 °C). A four-segment linear regression model with daily data for discharge and spring water temperature as explanatory variables provided an excellent fit for mean daily DO (Nash–Sutcliffe coefficient for the validation period of 0.90). DO also fluctuated at short-term timescales in response to storms, and DO measured at 15-min intervals could be simulated with a combination of discharge, spring temperature, and specific conductance as explanatory variables. On the basis of the daily-data regression model, we hypothesize that more frequent low DO corresponding to salamander mortality could result from (i) lower discharge from Barton Springs resulting from increased groundwater withdrawals or decreased recharge as a result of climate change, and (or) (ii) higher groundwater temperature as a result of climate change.

Daily air temperature interpolated at high spatial resolution over a large mountainous region

USGS Publications Warehouse

Dodson, R.; Marks, D.

1997-01-01

Two methods are investigated for interpolating daily minimum and maximum air temperatures (Tmin and Tmax) at a 1 km spatial resolution over a large mountainous region (830 000 km2) in the U.S. Pacific Northwest. The methods were selected because of their ability to (1) account for the effect of elevation on temperature and (2) efficiently handle large volumes of data. The first method, the neutral stability algorithm (NSA), used the hydrostatic and potential temperature equations to convert measured temperatures and elevations to sea-level potential temperatures. The potential temperatures were spatially interpolated using an inverse-squared-distance algorithm and then mapped to the elevation surface of a digital elevation model (DEM). The second method, linear lapse rate adjustment (LLRA), involved the same basic procedure as the NSA, but used a constant linear lapse rate instead of the potential temperature equation. Cross-validation analyses were performed using the NSA and LLRA methods to interpolate Tmin and Tmax each day for the 1990 water year, and the methods were evaluated based on mean annual interpolation error (IE). The NSA method showed considerable bias for sites associated with vertical extrapolation. A correction based on climate station/grid cell elevation differences was developed and found to successfully remove the bias. The LLRA method was tested using 3 lapse rates, none of which produced a serious extrapolation bias. The bias-adjusted NSA and the 3 LLRA methods produced almost identical levels of accuracy (mean absolute errors between 1.2 and 1.3??C), and produced very similar temperature surfaces based on image difference statistics. In terms of accuracy, speed, and ease of implementation, LLRA was chosen as the best of the methods tested.

A new approach to predict soil temperature under vegetated surfaces.

PubMed

Dolschak, Klaus; Gartner, Karl; Berger, Torsten W

2015-12-01

In this article, the setup and the application of an empirical model, based on Newton's law of cooling, capable to predict daily mean soil temperature ( T soil ) under vegetated surfaces, is described. The only input variable, necessary to run the model, is a time series of daily mean air temperature. The simulator employs 9 empirical parameters, which were estimated by inverse modeling. The model, which primarily addresses forested sites, incorporates the effect of snow cover and soil freezing on soil temperature. The model was applied to several temperate forest sites, managing the split between Central Europe (Austria) and the United States (Harvard Forest, Massachusetts; Hubbard Brook, New Hampshire), aiming to cover a broad range of site characteristics. Investigated stands differ fundamentally in stand composition, elevation, exposition, annual mean temperature, precipitation regime, as well as in the duration of winter snow cover. At last, to explore the limits of the formulation, the simulator was applied to non-forest sites (Illinois), where soil temperature was recorded under short cut grass. The model was parameterized, specifically to site and measurement depth. After calibration of the model, an evaluation was performed, using ~50 % of the available data. In each case, the simulator was capable to deliver a feasible prediction of soil temperature in the validation time interval. To evaluate the practical suitability of the simulator, the minimum amount of soil temperature point measurements, necessary to yield expedient model performance was determined. In the investigated case 13-20 point observations, uniformly distributed within an 11-year timeframe, have been proven sufficient to yield sound model performance (root mean square error <0.9 °C, Nash-Sutcliffe efficiency >0.97). This makes the model suitable for the application on sites, where the information on soil temperature is discontinuous or scarce.

Decentralized and cost-effective solar water purification system for remote communities

NASA Astrophysics Data System (ADS)

Abd-ur-Rehman, Hafiz M.; Shakir, Sehar; Atta-ur-Razaq; Saqib, Hamza; Tahir, Saad

2018-05-01

In this study, a modified stepped solar still is proposed for water desalination. The overall objective of this work is to develop and test the proposed still design to identify the productivity enhancement as compared to conventional basin type solar still. The proposed design takes the advantage of its stepped configuration that allows the water stream to maintain a minimum desirable water column height and the water flow through the stages under the force of gravity. A minimum water depth in the still results in a higher rate of evaporation. The still is also incorporated with Fresnel lens to increase the water temperature that eventually increases the rate of water evaporation. Another important aspect of this design is the incorporation of phase-change-material (PCM) to increase the operational hours of the solar still. Consequently, daily productivity of fresh water is increased.

Use of a Weather Generator for analysis of projections of future daily temperature and its validation with climate change indices

NASA Astrophysics Data System (ADS)

Di Piazza, A.; Cordano, E.; Eccel, E.

2012-04-01

The issue of climate change detection is considered a major challenge. In particular, high temporal resolution climate change scenarios are required in the evaluation of the effects of climate change on agricultural management (crop suitability, yields, risk assessment, etc.) energy production and water management. In this work, a "Weather Generator" technique was used for downscaling climate change scenarios for temperature. An R package (RMAWGEN, Cordano and Eccel, 2011 - available on http://cran.r-project.org) was developed aiming to generate synthetic daily weather conditions by using the theory of vectorial auto-regressive models (VAR). The VAR model was chosen for its ability in maintaining the temporal and spatial correlations among variables. In particular, observed time series of daily maximum and minimum temperature are transformed into "new" normally-distributed variable time series which are used to calibrate the parameters of a VAR model by using ordinary least square methods. Therefore the implemented algorithm, applied to monthly mean climatic values downscaled by Global Climate Model predictions, can generate several stochastic daily scenarios where the statistical consistency among series is saved. Further details are present in RMAWGEN documentation. An application is presented here by using a dataset with daily temperature time series recorded in 41 different sites of Trentino region for the period 1958-2010. Temperature time series were pre-processed to fill missing values (by a site-specific calibrated Inverse Distance Weighting algorithm, corrected with elevation) and to remove inhomogeneities. Several climatic indices were taken into account, useful for several impact assessment applications, and their time trends within the time series were analyzed. The indices go from the more classical ones, as annual mean temperatures, seasonal mean temperatures and their anomalies (from the reference period 1961-1990) to the climate change indices selected from the list recommended by the World Meteorological Organization Commission for Climatology (WMO-CCL) and the Research Programme on Climate Variability and Predictability (CLIVAR) project's Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI). Each index was applied to both observed (and processed) data and to synthetic time series produced by the Weather Generator, over the thirty year reference period 1981-2010, in order to validate the procedure. Climate projections were statistically downscaled for a selection of sites for the two 30-year periods 2021-2050 and 2071-2099 of the European project "Ensembles" multi-model output (scenario A1B). The use of several climatic indices strengthens the trend analysis of both the generated synthetic series and future climate projections.

Evaluation and trends of land cover, streamflow, and water quality in the North Canadian River Basin near Oklahoma City, Oklahoma, 1968–2009

USGS Publications Warehouse

Esralew, Rachel A.; Andrews, William J.; Smith, S. Jerrod

2011-01-01

The U.S. Geological Survey, in cooperation with the city of Oklahoma City, collected water-quality samples from the North Canadian River at the streamflow-gaging station near Harrah, Oklahoma (Harrah station), since 1968, and at an upstream streamflow-gaging station at Britton Road at Oklahoma City, Oklahoma (Britton Road station), since 1988. Statistical summaries and frequencies of detection of water-quality constituent data from water samples, and summaries of water-quality constituent data from continuous water-quality monitors are described from the start of monitoring at those stations through 2009. Differences in concentrations between stations and time trends for selected constituents were evaluated to determine the effects of: (1) wastewater effluent discharges, (2) changes in land-cover, (3) changes in streamflow, (4) increases in urban development, and (5) other anthropogenic sources of contamination on water quality in the North Canadian River downstream from Oklahoma City. Land-cover changes between 1992 and 2001 in the basin between the Harrah station and Lake Overholser upstream included an increase in developed/barren land-cover and a decrease in pasture/hay land cover. There were no significant trends in median and greater streamflows at either streamflow-gaging station, but there were significant downward trends in lesser streamflows, especially after 1999, which may have been associated with decreases in precipitation between 1999 and 2009 or construction of low-water dams on the river upstream from Oklahoma City in 1999. Concentrations of dissolved chloride, lead, cadmium, and chlordane most frequently exceeded the Criterion Continuous Concentration (a water-quality standard for protection of aquatic life) in water-quality samples collected at both streamflow-gaging stations. Visual trends in annual frequencies of detection were investigated for selected pesticides with frequencies of detection greater than 10 percent in all water samples collected at both streamflow-gaging stations. Annual frequencies of detection of 2,4-dichlorophenoxyacetic acid and bromacil increased with time. Annual frequencies of detection of atrazine, chlorpyrifos, diazinon, dichlorprop, and lindane decreased with time. Dissolved nitrogen and phosphorus concentrations were significantly greater in water samples collected at the Harrah station than at the Britton Road station, whereas specific conductance was greater at the Britton Road station. Concentrations of dissolved oxygen, biochemical oxygen demand, and fecal coliform bacteria were not significantly different between stations. Daily minimum, mean, and maximum specific conductance collected from continuous water-quality monitors were significantly greater at the Britton Road station than in water samples collected at the Harrah station. Daily minimum, maximum, and diurnal fluctuations of water temperature collected from continuous water-quality monitors were significantly greater at the Harrah station than at the Britton Road station. The daily maximums and diurnal range of dissolved oxygen concentrations were significantly greater in water samples collected at the Britton Road station than at the Harrah station, but daily mean dissolved oxygen concentrations in water at those streamflow-gaging stations were not significantly different. Daily mean and diurnal water temperature ranges increased with time at the Britton Road and Harrah streamflow-gaging stations, whereas daily mean and diurnal specific conductance ranges decreased with time at both streamflow-gaging stations from 1988–2009. Daily minimum dissolved oxygen concentrations collected from continuous water-quality monitors more frequently indicated hypoxic conditions at the Harrah station than at the Britton Road station after 1999. Fecal coliform bacteria counts in water decreased slightly from 1988–2009 at the Britton Road station. The Seasonal Kendall's tau test indicated significant downward trends in

Statistical downscaling and future scenario generation of temperatures for Pakistan Region

NASA Astrophysics Data System (ADS)

Kazmi, Dildar Hussain; Li, Jianping; Rasul, Ghulam; Tong, Jiang; Ali, Gohar; Cheema, Sohail Babar; Liu, Luliu; Gemmer, Marco; Fischer, Thomas

2015-04-01

Finer climate change information on spatial scale is required for impact studies than that presently provided by global or regional climate models. It is especially true for regions like South Asia with complex topography, coastal or island locations, and the areas of highly heterogeneous land-cover. To deal with the situation, an inexpensive method (statistical downscaling) has been adopted. Statistical DownScaling Model (SDSM) employed for downscaling of daily minimum and maximum temperature data of 44 national stations for base time (1961-1990) and then the future scenarios generated up to 2099. Observed as well as Predictors (product of National Oceanic and Atmospheric Administration) data were calibrated and tested on individual/multiple basis through linear regression. Future scenario was generated based on HadCM3 daily data for A2 and B2 story lines. The downscaled data has been tested, and it has shown a relatively strong relationship with the observed in comparison to ECHAM5 data. Generally, the southern half of the country is considered vulnerable in terms of increasing temperatures, but the results of this study projects that in future, the northern belt in particular would have a possible threat of increasing tendency in air temperature. Especially, the northern areas (hosting the third largest ice reserves after the Polar Regions), an important feeding source for Indus River, are projected to be vulnerable in terms of increasing temperatures. Consequently, not only the hydro-agricultural sector but also the environmental conditions in the area may be at risk, in future.

Development of a large-sample catchment-scale hydro-meteorological, land cover and physical dataset for Chile

NASA Astrophysics Data System (ADS)

Alvarez-Garreton, C. D.; Mendoza, P. A.; Zambrano-Bigiarini, M.; Galleguillos, M. H.; Boisier, J. P.; Lara, A.; Cortés, G.; Garreaud, R.; McPhee, J. P.; Addor, N.; Puelma, C.

2017-12-01

We provide the first catchment-based hydrometeorological, vegetation and physical data set over 531 catchments in Chile (17.8 S - 55.0 S). We compiled publicly available streamflow records at daily time steps for the period 1980-2015, and generated basin-averaged time series of the following hydrometeorological variables: 1) daily precipitation coming from three different gridded sources (re-analysis and satellite-based); 2) daily maximum and minimum temperature; 3) 8-days potential evapotranspiration (PET) based on MODIS imagery and daily PET based on Hargreaves formula; and 4) daily snow water equivalent. Additionally, catchments are characterized by their main physical (area, mean elevation, mean slope) and land cover characteristics. We synthetized these datasets with several indices characterizing the spatial distribution of climatic, hydrological, topographic and vegetation attributes. The new catchment-based dataset is unprecedented in the region and provides information that can be used in a myriad of applications, including catchment classification and regionalization studies, impacts of different land cover types on catchment response, characterization of drought history and projections, climate change impacts on hydrological processes, etc. Derived practical applications include water management and allocation strategies, decision making and adaptation planning to climate change. This data set will be publicly available and we encourage the community to use it.

Air quality and acute deaths in California, 2000-2012.

PubMed

Young, S Stanley; Smith, Richard L; Lopiano, Keneth K

2017-08-01

Many studies have shown an association between air quality and acute deaths, and such associations are widely interpreted as causal. Several factors call causation and even association into question, for example multiple testing and multiple modeling, publication bias and confirmation bias. Many published studies are difficult or impossible to reproduce because of lack of access to confidential data sources. Here we make publically available a dataset containing daily air quality levels, PM 2.5 and ozone, daily temperature levels, minimum and maximum and daily maximum relative humidity levels for the eight most populous California air basins, thirteen years, >2M deaths, over 37,000 exposure days. The data are analyzed using standard time series analysis, and a sensitivity analysis is computed varying model parameters, locations and years. Our analysis finds little evidence for association between air quality and acute deaths. These results are consistent with those for the widely cited NMMAPS dataset when the latter are restricted to California. The daily death variability was mostly explained by time of year or weather variables; Neither PM 2.5 nor ozone added appreciably to the prediction of daily deaths. These results call into question the widespread belief that association between air quality and acute deaths is causal/near-universal. Copyright © 2017 Elsevier Inc. All rights reserved.

Inflight fuel tank temperature survey data

NASA Technical Reports Server (NTRS)

Pasion, A. J.

1979-01-01

Statistical summaries of the fuel and air temperature data for twelve different routes and for different aircraft models (B747, B707, DC-10 and DC-8), are given. The minimum fuel, total air and static air temperature expected for a 0.3% probability were summarized in table form. Minimum fuel temperature extremes agreed with calculated predictions and the minimum fuel temperature did not necessarily equal the minimum total air temperature even for extreme weather, long range flights.

Role of Temperature, Humidity and Rainfall on Influenza Transmission in Guatemala, El Salvador and Panama

NASA Technical Reports Server (NTRS)

Soebiyanto, Radina P.; Bonilla, Luis; Jara, Jorge; McCracken, John; Azziz?-Baumgartner, Eduardo; Widdowson, Marc-Alain; Kiang, Richard

2012-01-01

Worldwide, seasonal influenza causes about 500,000 deaths and 5 million severe illnesses per year. The environmental drivers of influenza transmission are poorly understood especially in the tropics. We aimed to identify meteorological factors for influenza transmission in tropical Central America. We gathered laboratory-confirmed influenza case-counts by week from Guatemala City, San Salvador Department (El Salvador) and Panama Province from 2006 to 2010. The average total cases per year were: 390 (Guatemala), 99 (San Salvador) and 129 (Panama). Meteorological factors including daily air temperature, rainfall, relative and absolute humidity (RH, AH) were obtained from ground stations, NASA satellites and land models. For these factors, we computed weekly averages and their deviation from the 5-yr means. We assessed the relationship between the number of influenza case-counts and the meteorological factors, including effects lagged by 1 to 4 weeks, using Poisson regression for each site. Our results showed influenza in San Salvador would increase by 1 case within a week of every 1 day with RH>75% (Relative Risk (RR)= 1.32, p=.001) and every 1C increase in minimum temperature (RR=1.29, p=.007) but it would decrease by 1 case for every 1mm-above mean weekly rainfall (RR=0.93,p<.001) (model pseudo-R2=0.55). Within 2 weeks, influenza in Panama was increased by 1 case for every 1% increase in RH (RR=1.04, p=.003), and it was increased by 2 cases for every 1C increase of minimum temperature (RR=2.01, p<.001) (model pseudo-R2=0.4). Influenza counts in Guatemala had 1 case increase for every 1C increase in minimum temperature in the previous week (RR=1.21, p<.001), and for every 1mm/day-above normal increase of rainfall rate (RR=1.03, p=.03) (model pseudo-R2=0.54). Our findings that cases increase with temperature and humidity differ from some temperate-zone studies. But they indicate that climate parameters such as humidity and temperature could be predictive of influenza activity and should be incorporated into country-specific influenza transmission models

Modeling Streamflow and Water Temperature in the North Santiam and Santiam Rivers, Oregon, 2001-02

USGS Publications Warehouse

Sullivan, Annett B.; Roundsk, Stewart A.

2004-01-01

To support the development of a total maximum daily load (TMDL) for water temperature in the Willamette Basin, the laterally averaged, two-dimensional model CE-QUAL-W2 was used to construct a water temperature and streamflow model of the Santiam and North Santiam Rivers. The rivers were simulated from downstream of Detroit and Big Cliff dams to the confluence with the Willamette River. Inputs to the model included bathymetric data, flow and temperature from dam releases, tributary flow and temperature, and meteorologic data. The model was calibrated for the period July 1 through November 21, 2001, and confirmed with data from April 1 through October 31, 2002. Flow calibration made use of data from two streamflow gages and travel-time and river-width data. Temperature calibration used data from 16 temperature monitoring locations in 2001 and 5 locations in 2002. A sensitivity analysis was completed by independently varying input parameters, including point-source flow, air temperature, flow and water temperature from dam releases, and riparian shading. Scenario analyses considered hypothetical river conditions without anthropogenic heat inputs, with restored riparian vegetation, with minimum streamflow from the dams, and with a more-natural seasonal water temperature regime from dam releases.

Characteristics of sub-daily precipitation extremes in observed data and regional climate model simulations

NASA Astrophysics Data System (ADS)

Beranová, Romana; Kyselý, Jan; Hanel, Martin

2018-04-01

The study compares characteristics of observed sub-daily precipitation extremes in the Czech Republic with those simulated by Hadley Centre Regional Model version 3 (HadRM3) and Rossby Centre Regional Atmospheric Model version 4 (RCA4) regional climate models (RCMs) driven by reanalyses and examines diurnal cycles of hourly precipitation and their dependence on intensity and surface temperature. The observed warm-season (May-September) maxima of short-duration (1, 2 and 3 h) amounts show one diurnal peak in the afternoon, which is simulated reasonably well by RCA4, although the peak occurs too early in the model. HadRM3 provides an unrealistic diurnal cycle with a nighttime peak and an afternoon minimum coinciding with the observed maximum for all three ensemble members, which suggests that convection is not captured realistically. Distorted relationships of the diurnal cycles of hourly precipitation to daily maximum temperature in HadRM3 further evidence that underlying physical mechanisms are misrepresented in this RCM. Goodness-of-fit tests indicate that generalised extreme value distribution is an applicable model for both observed and RCM-simulated precipitation maxima. However, the RCMs are not able to capture the range of the shape parameter estimates of distributions of short-duration precipitation maxima realistically, leading to either too many (nearly all for HadRM3) or too few (RCA4) grid boxes in which the shape parameter corresponds to a heavy tail. This means that the distributions of maxima of sub-daily amounts are distorted in the RCM-simulated data and do not match reality well. Therefore, projected changes of sub-daily precipitation extremes in climate change scenarios based on RCMs not resolving convection need to be interpreted with caution.

An extended linear scaling method for downscaling temperature and its implication in the Jhelum River basin, Pakistan, and India, using CMIP5 GCMs

NASA Astrophysics Data System (ADS)

Mahmood, Rashid; JIA, Shaofeng

2017-11-01

In this study, the linear scaling method used for the downscaling of temperature was extended from monthly scaling factors to daily scaling factors (SFs) to improve the daily variations in the corrected temperature. In the original linear scaling (OLS), mean monthly SFs are used to correct the future data, but mean daily SFs are used to correct the future data in the extended linear scaling (ELS) method. The proposed method was evaluated in the Jhelum River basin for the period 1986-2000, using the observed maximum temperature (Tmax) and minimum temperature (Tmin) of 18 climate stations and the simulated Tmax and Tmin of five global climate models (GCMs) (GFDL-ESM2G, NorESM1-ME, HadGEM2-ES, MIROC5, and CanESM2), and the method was also compared with OLS to observe the improvement. Before the evaluation of ELS, these GCMs were also evaluated using their raw data against the observed data for the same period (1986-2000). Four statistical indicators, i.e., error in mean, error in standard deviation, root mean square error, and correlation coefficient, were used for the evaluation process. The evaluation results with GCMs' raw data showed that GFDL-ESM2G and MIROC5 performed better than other GCMs according to all the indicators but with unsatisfactory results that confine their direct application in the basin. Nevertheless, after the correction with ELS, a noticeable improvement was observed in all the indicators except correlation coefficient because this method only adjusts (corrects) the magnitude. It was also noticed that the daily variations of the observed data were better captured by the corrected data with ELS than OLS. Finally, the ELS method was applied for the downscaling of five GCMs' Tmax and Tmin for the period of 2041-2070 under RCP8.5 in the Jhelum basin. The results showed that the basin would face hotter climate in the future relative to the present climate, which may result in increasing water requirements in public, industrial, and agriculture sectors; change in the hydrological cycle and monsoon pattern; and lack of glaciers in the basin.

Solar Minimum

NASA Astrophysics Data System (ADS)

Lopresto, James C.; Mathews, John; Manross, Kevin

1995-12-01

Calcium K plage, H alpha plage and sunspot area have been monitored daily on the INTERNET since November of 1992. The plage and sunspot area have been measured by image processing. The purpose of the project is to investigate the degree of correlation between plage area and solar irradiance. The plage variation shows the expected variation produced by solar rotation and the longer secular changes produced by the solar cycle. The H alpha and sunspot plage area reached a minimum in about late 1994 or early 1995. This is in agreement with the K2 spectral index obtained daily from Sacramento Peak Observatory. The Calcium K plage area minimum seems delayed with respect to the others mentioned above. The minimum of the K line plage area is projected to come within the last few months of 1995.

The association between diurnal temperature range and childhood bacillary dysentery

NASA Astrophysics Data System (ADS)

Wen, Li-ying; Zhao, Ke-fu; Cheng, Jian; Wang, Xu; Yang, Hui-hui; Li, Ke-sheng; Xu, Zhi-wei; Su, Hong

2016-02-01

Previous studies have found that mean, maximum, and minimum temperatures were associated with bacillary dysentery (BD). However, little is known about whether the within-day variation of temperature has any impact on bacillary dysentery. The current study aimed to identify the relationship between diurnal temperature range (DTR) and BD in Hefei, China. Daily data on BD counts among children aged 0-14 years from 1 January 2006 to 31 December 2012 were retrieved from Hefei Center for Disease Control and Prevention. Daily data on ambient temperature and relative humidity covering the same period were collected from the Hefei Bureau of Meteorology. A Poisson generalized linear regression model combined with a distributed lag non-linear model (DLNM) was used in the analysis after controlling the effects of season, long-term trends, mean temperature, and relative humidity. The results showed that there existed a statistically significant relationship between DTR and childhood BD. The DTR effect on childhood bacillary dysentery increased when DTR was over 8 °C. And it was greatest at 1-day lag, with an 8 % (95 % CI = 2.9-13.4 %) increase of BD cases per 5 °C increment of DTR. Male children and children aged 0-5 years appeared to be more vulnerable to the DTR effect. The data indicate that large DTR may increase the incidence of childhood BD. Caregivers and health practitioners should be made aware of the potential threat posed by large DTR. Therefore, DTR should be taken into consideration when making targeted health policies and programs to protect children from being harmed by climate impacts.

The association between diurnal temperature range and childhood bacillary dysentery.

PubMed

Wen, Li-ying; Zhao, Ke-fu; Cheng, Jian; Wang, Xu; Yang, Hui-hui; Li, Ke-sheng; Xu, Zhi-wei; Su, Hong

2016-02-01

Previous studies have found that mean, maximum, and minimum temperatures were associated with bacillary dysentery (BD). However, little is known about whether the within-day variation of temperature has any impact on bacillary dysentery. The current study aimed to identify the relationship between diurnal temperature range (DTR) and BD in Hefei, China. Daily data on BD counts among children aged 0-14 years from 1 January 2006 to 31 December 2012 were retrieved from Hefei Center for Disease Control and Prevention. Daily data on ambient temperature and relative humidity covering the same period were collected from the Hefei Bureau of Meteorology. A Poisson generalized linear regression model combined with a distributed lag non-linear model (DLNM) was used in the analysis after controlling the effects of season, long-term trends, mean temperature, and relative humidity. The results showed that there existed a statistically significant relationship between DTR and childhood BD. The DTR effect on childhood bacillary dysentery increased when DTR was over 8 °C. And it was greatest at 1-day lag, with an 8% (95% CI = 2.9-13.4%) increase of BD cases per 5 °C increment of DTR. Male children and children aged 0-5 years appeared to be more vulnerable to the DTR effect. The data indicate that large DTR may increase the incidence of childhood BD. Caregivers and health practitioners should be made aware of the potential threat posed by large DTR. Therefore, DTR should be taken into consideration when making targeted health policies and programs to protect children from being harmed by climate impacts.

Contribution of urbanization to the increase of extreme heat events in an urban agglomeration in east China: Urbanization and the Increase of EHEs

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

Yang, Xuchao; Ruby Leung, L.; Zhao, Naizhuo

The urban agglomeration of Yangtze River Delta (YRD) is emblematic of China’s rapid urbanization during the past decades. Based on homogenized daily maximum and minimum temperature data, the contributions of urbanization to trends of extreme temperature indices (ETIs) during summer in YRD are evaluated. Dynamically classifying the observational stations into urban and rural areas, this study presents unexplored changes in temperature extremes during the past four decades in the YRD region and quantifies the amplification of the positive trends in ETIs by the urban heat island effect. Overall, urbanization contributes to more than one third in the increase of intensitymore » of extreme heat events in the region, which is comparable to the contribution of greenhouse gases. Compared to rural stations, more notable shifts to the right in the probability distribution of temperature and ETIs were observed in urban stations.« less

Airborne monitoring of crop canopy temperatures for irrigation scheduling and yield prediction

NASA Technical Reports Server (NTRS)

Millard, J. P.; Jackson, R. D.; Goettelman, R. C.; Reginato, R. J.; Idso, S. B.; Lapado, R. L.

1977-01-01

Airborne and ground measurements were made on April 1 and 29, 1976, over a USDA test site consisting mostly of wheat in various stages of water stress, but also including alfalfa and bare soil. These measurements were made to evaluate the feasibility of measuring crop temperatures from aircraft so that a parameter termed stress degree day, SDD, could be computed. Ground studies have shown that SDD is a valuable indicator of a crop's water needs, and that it can be related to irrigation scheduling and yield. The aircraft measurement program required predawn and afternoon flights coincident with minimum and maximum crop temperatures. Airborne measurements were made with an infrared line scanner and with color IR photography. The scanner data were registered, subtracted, and color-coded to yield pseudo-colored temperature-difference images. Pseudo-colored images reading directly in daily SDD increments were also produced. These maps enable a user to assess plant water status and thus determine irrigation needs and crop yield potentials.

Hydrothermal extremes at the South-West Pribaikalie during the current climate changes

NASA Astrophysics Data System (ADS)

Voropay, Nadezhda

2017-04-01

Climatic extremes of air temperature and precipitation were analyzed for the Tunka Intermountain Depression (South-West Pribaikalie, Buryatia, Russian Federation). Intermountain depressions occupy a quarter of the territory of the Baikal region. The specific climatic conditions in the depressions are formed due to the geographic location and the influence of latitudinal zonation and altitudinal gradients. Air temperature and precipitation data records from at weather stations for the period 1940-2015 were analyzed. Long-term average annual temperature is negative and varies from -0.8 °C to -2.4 °C. Air temperature absolute minimum is -48 °C, absolute maximum is +36 °C. The long-term average annual precipitation is 370-480 mm, but in some years annual precipitation reach 760 mm. The summer months have about 70% of the total annual precipitation, in July and August the sum may reach 340 mm. Maximum daily sum of rainfalls is 80 mm. The contribution of the global and regional circulation characteristics into the variability of regional climatic characteristics was estimated.

Regional model simulations of New Zealand climate

NASA Astrophysics Data System (ADS)

Renwick, James A.; Katzfey, Jack J.; Nguyen, Kim C.; McGregor, John L.

1998-03-01

Simulation of New Zealand climate is examined through the use of a regional climate model nested within the output of the Commonwealth Scientific and Industrial Research Organisation nine-level general circulation model (GCM). R21 resolution GCM output is used to drive a regional model run at 125 km grid spacing over the Australasian region. The 125 km run is used in turn to drive a simulation at 50 km resolution over New Zealand. Simulations with a full seasonal cycle are performed for 10 model years. The focus is on the quality of the simulation of present-day climate, but results of a doubled-CO2 run are discussed briefly. Spatial patterns of mean simulated precipitation and surface temperatures improve markedly as horizontal resolution is increased, through the better resolution of the country's orography. However, increased horizontal resolution leads to a positive bias in precipitation. At 50 km resolution, simulated frequency distributions of daily maximum/minimum temperatures are statistically similar to those of observations at many stations, while frequency distributions of daily precipitation appear to be statistically different to those of observations at most stations. Modeled daily precipitation variability at 125 km resolution is considerably less than observed, but is comparable to, or exceeds, observed variability at 50 km resolution. The sensitivity of the simulated climate to changes in the specification of the land surface is discussed briefly. Spatial patterns of the frequency of extreme temperatures and precipitation are generally well modeled. Under a doubling of CO2, the frequency of precipitation extremes changes only slightly at most locations, while air frosts become virtually unknown except at high-elevation sites.

Analysis of a long drought in Piedmont, Italy - Autumn 2001

NASA Astrophysics Data System (ADS)

Gandini, D.; Marchisio, C.; Paesano, G.; Pelosini, P.

2003-04-01

A long period of drought and cold temperatures has characterised the seasons of Autumn 2001 and Winter 2001-2002 on the regions of the southern Alpine chain. The analysis of precipitation's data, collected by the Regional Monitoring network of Piedmont Region (on the south-west side of Alps), shows that they are far below the mean values and very close to the historical minimum of the last century. The six months accumulated precipitation in Turin (Piedmont chief town), from June to December 2001, has reached the historical minimum value of 206 mm in comparison with a mean value of 540 mm. The drought has been remarkable also in the mountain areas with the lack of snowfalls and critical consequences for water reservoirs. At the same time, the number of days with daily averaged temperature below or close to 0°C in December 2001 has been the greatest value of the last 50 years, much higher than the 50 years average, for the whole Piedmont region. This study contains a detailed analysis of observed data to characterise the drought episode, associated with a climatological analysis of meteorological parameters in order to detect the typical large scale pattern of the drought periods and their persistency's features.

Diurnal and Seasonal Variations in the Net Ecosystem CO2 Exchange of a Pasture in the Three-River Source Region of the Qinghai−Tibetan Plateau

PubMed Central

Wang, Bin; Jin, Haiyan; Li, Qi; Chen, Dongdong; Zhao, Liang; Tang, Yanhong; Kato, Tomomichi; Gu, Song

2017-01-01

Carbon dioxide (CO2) exchange between the atmosphere and grassland ecosystems is very important for the global carbon balance. To assess the CO2 flux and its relationship to environmental factors, the eddy covariance method was used to evaluate the diurnal cycle and seasonal pattern of the net ecosystem CO2 exchange (NEE) of a cultivated pasture in the Three-River Source Region (TRSR) on the Qinghai−Tibetan Plateau from January 1 to December 31, 2008. The diurnal variations in the NEE and ecosystem respiration (Re) during the growing season exhibited single-peak patterns, the maximum and minimum CO2 uptake observed during the noon hours and night; and the maximum and minimum Re took place in the afternoon and early morning, respectively. The minimum hourly NEE rate and the maximum hourly Re rate were −7.89 and 5.03 μmol CO2 m−2 s−1, respectively. The NEE and Re showed clear seasonal variations, with lower values in winter and higher values in the peak growth period. The highest daily values for C uptake and Re were observed on August 12 (−2.91 g C m−2 d−1) and July 28 (5.04 g C m−2 day−1), respectively. The annual total NEE and Re were −140.01 and 403.57 g C m−2 year−1, respectively. The apparent quantum yield (α) was −0.0275 μmol μmol−1 for the entire growing period, and the α values for the pasture’s light response curve varied with the leaf area index (LAI), air temperature (Ta), soil water content (SWC) and vapor pressure deficit (VPD). Piecewise regression results indicated that the optimum Ta and VPD for the daytime NEE were 14.1°C and 0.65 kPa, respectively. The daytime NEE decreased with increasing SWC, and the temperature sensitivity of respiration (Q10) was 3.0 during the growing season, which was controlled by the SWC conditions. Path analysis suggested that the soil temperature at a depth of 5 cm (Tsoil) was the most important environmental factor affecting daily variations in NEE during the growing season, and the photosynthetic photon flux density (PPFD) was the major limiting factor for this cultivated pasture. PMID:28129406

Gravitational biology and the mammalian circadian timing system

NASA Astrophysics Data System (ADS)

Fuller, Charles A.; Murakami, Dean M.; Sulzman, Frank M.

Mammals have evolved under the influence of many selective pressures. Two of these pressures have been the static force of gravity and the daily variations in the environment due to the rotation of the earth. It is now clear that each of these pressures has led to specific adaptations which influence how organisms respond to changes in either gravity or daily time cues. However, several unpredicted responses to altered gravitational environments occur within the homeostatic and circadian control systems. These results may be particularly relevant to biological and medical issues related to spaceflight. This paper demonstrates that the homeostatic regulation of rat body temperature, heart rate, and activity become depressed following exposure to a 2 G hyperdynamic field, and recovers within 5-6 days. In addition, the circadian rhythms of these same variables exhibit a depression of rhythm amplitude; however, recovery required a minimum of 7 days.

Weather types and the regime of wildfires in Portugal

NASA Astrophysics Data System (ADS)

Pereira, M. G.; Trigo, R. M.; Dacamara, C. C.

2009-04-01

An objective classification scheme, as developed by Trigo and DaCamara (2000), was applied to classify the daily atmospheric circulation affecting Portugal between 1980 and 2007 into a set of 10 basic weather types (WTs). The classification scheme relies on a set of atmospheric circulation indices, namely southerly flow (SF), westerly flow (WF), total flow (F), southerly shear vorticity (ZS), westerly shear vorticity (ZW) and total vorticity (Z). The weather-typing approach, together with surfacemeteorological variables (e.g. intensity and direction of geostrophic wind, maximum and minimum temperature and precipitation) were then associated to wildfire events as recorded in the official Portuguese fire database consisting of information on each fire occurred in the 18 districts of Continental Portugal within the same period (>450.000 events). The objective of this study is to explore the dependence of wildfire activity on weather and climate and then evaluate the potential of WTs to discriminate among recorded wildfires on what respects to their occurrence and development. Results show that days characterised by surface flow with an eastern component (i.e. NE, E and SE) account for a high percentage of daily burnt area, as opposed to surface westerly flow (NW, W and SW), which represents about a quarter of the total number of days but only accounts for a very low percentage of active fires and of burnt area. Meteorological variables such as minimum and maximum temperatures, that are closely associated to surface wind intensity and direction, also present a good ability to discriminate between the different types of fire events.. Trigo R.M., DaCamara C. (2000) "Circulation Weather Types and their impact on the precipitation regime in Portugal". Int J of Climatology, 20, 1559-1581.

Susceptibility to Heat-Related Fluid and Electrolyte Imbalance Emergency Department Visits in Atlanta, Georgia, USA.

PubMed

Heidari, Leila; Winquist, Andrea; Klein, Mitchel; O'Lenick, Cassandra; Grundstein, Andrew; Ebelt Sarnat, Stefanie

2016-10-02

Identification of populations susceptible to heat effects is critical for targeted prevention and more accurate risk assessment. Fluid and electrolyte imbalance (FEI) may provide an objective indicator of heat morbidity. Data on daily ambient temperature and FEI emergency department (ED) visits were collected in Atlanta, Georgia, USA during 1993-2012. Associations of warm-season same-day temperatures and FEI ED visits were estimated using Poisson generalized linear models. Analyses explored associations between FEI ED visits and various temperature metrics (maximum, minimum, average, and diurnal change in ambient temperature, apparent temperature, and heat index) modeled using linear, quadratic, and cubic terms to allow for non-linear associations. Effect modification by potential determinants of heat susceptibility (sex; race; comorbid congestive heart failure, kidney disease, and diabetes; and neighborhood poverty and education levels) was assessed via stratification. Higher warm-season ambient temperature was significantly associated with FEI ED visits, regardless of temperature metric used. Stratified analyses suggested heat-related risks for all populations, but particularly for males. This work highlights the utility of FEI as an indicator of heat morbidity, the health threat posed by warm-season temperatures, and the importance of considering susceptible populations in heat-health research.

Susceptibility to Heat-Related Fluid and Electrolyte Imbalance Emergency Department Visits in Atlanta, Georgia, USA

PubMed Central

Heidari, Leila; Winquist, Andrea; Klein, Mitchel; O’Lenick, Cassandra; Grundstein, Andrew; Ebelt Sarnat, Stefanie

2016-01-01

Identification of populations susceptible to heat effects is critical for targeted prevention and more accurate risk assessment. Fluid and electrolyte imbalance (FEI) may provide an objective indicator of heat morbidity. Data on daily ambient temperature and FEI emergency department (ED) visits were collected in Atlanta, Georgia, USA during 1993–2012. Associations of warm-season same-day temperatures and FEI ED visits were estimated using Poisson generalized linear models. Analyses explored associations between FEI ED visits and various temperature metrics (maximum, minimum, average, and diurnal change in ambient temperature, apparent temperature, and heat index) modeled using linear, quadratic, and cubic terms to allow for non-linear associations. Effect modification by potential determinants of heat susceptibility (sex; race; comorbid congestive heart failure, kidney disease, and diabetes; and neighborhood poverty and education levels) was assessed via stratification. Higher warm-season ambient temperature was significantly associated with FEI ED visits, regardless of temperature metric used. Stratified analyses suggested heat-related risks for all populations, but particularly for males. This work highlights the utility of FEI as an indicator of heat morbidity, the health threat posed by warm-season temperatures, and the importance of considering susceptible populations in heat-health research. PMID:27706089

Comparison of MODIS Land Surface Temperature and Air Temperature over the Continental USA Meteorological Stations

NASA Technical Reports Server (NTRS)

Zhang, Ping; Bounoua, Lahouari; Imhoff, Marc L.; Wolfe, Robert E.; Thome, Kurtis

2014-01-01

The National Land Cover Database (NLCD) Impervious Surface Area (ISA) and MODIS Land Surface Temperature (LST) are used in a spatial analysis to assess the surface-temperature-based urban heat island's (UHIS) signature on LST amplitude over the continental USA and to make comparisons to local air temperatures. Air-temperature-based UHIs (UHIA), calculated using the Global Historical Climatology Network (GHCN) daily air temperatures, are compared with UHIS for urban areas in different biomes during different seasons. NLCD ISA is used to define urban and rural temperatures and to stratify the sampling for LST and air temperatures. We find that the MODIS LST agrees well with observed air temperature during the nighttime, but tends to overestimate it during the daytime, especially during summer and in nonforested areas. The minimum air temperature analyses show that UHIs in forests have an average UHIA of 1 C during the summer. The UHIS, calculated from nighttime LST, has similar magnitude of 1-2 C. By contrast, the LSTs show a midday summer UHIS of 3-4 C for cities in forests, whereas the average summer UHIA calculated from maximum air temperature is close to 0 C. In addition, the LSTs and air temperatures difference between 2006 and 2011 are in agreement, albeit with different magnitude.

A globally calibrated scheme for generating daily meteorology from monthly statistics: Global-WGEN (GWGEN) v1.0

NASA Astrophysics Data System (ADS)

Sommer, Philipp S.; Kaplan, Jed O.

2017-10-01

While a wide range of Earth system processes occur at daily and even subdaily timescales, many global vegetation and other terrestrial dynamics models historically used monthly meteorological forcing both to reduce computational demand and because global datasets were lacking. Recently, dynamic land surface modeling has moved towards resolving daily and subdaily processes, and global datasets containing daily and subdaily meteorology have become available. These meteorological datasets, however, cover only the instrumental era of the last approximately 120 years at best, are subject to considerable uncertainty, and represent extremely large data files with associated computational costs of data input/output and file transfer. For periods before the recent past or in the future, global meteorological forcing can be provided by climate model output, but the quality of these data at high temporal resolution is low, particularly for daily precipitation frequency and amount. Here, we present GWGEN, a globally applicable statistical weather generator for the temporal downscaling of monthly climatology to daily meteorology. Our weather generator is parameterized using a global meteorological database and simulates daily values of five common variables: minimum and maximum temperature, precipitation, cloud cover, and wind speed. GWGEN is lightweight, modular, and requires a minimal set of monthly mean variables as input. The weather generator may be used in a range of applications, for example, in global vegetation, crop, soil erosion, or hydrological models. While GWGEN does not currently perform spatially autocorrelated multi-point downscaling of daily weather, this additional functionality could be implemented in future versions.

Cross-correlation map analyses show weather variation influences on mosquito abundance patterns in Saginaw County, Michigan, 1989-2005.

PubMed

Chuang, Ting-Wu; Ionides, Edward L; Knepper, Randall G; Stanuszek, William W; Walker, Edward D; Wilson, Mark L

2012-07-01

Weather is important determinant of mosquito abundance that, in turn, influences vectorborne disease dynamics. In temperate regions, transmission generally is seasonal as mosquito abundance and behavior varies with temperature, precipitation, and other meteorological factors. We investigated how such factors affected species-specific mosquito abundance patterns in Saginaw County, MI, during a 17-yr period. Systematic sampling was undertaken at 22 trapping sites from May to September, during 1989-2005, for 19,228 trap-nights and 300,770 mosquitoes in total. Aedes vexans (Meigen), Culex pipiens L. and Culex restuans Theobald, the most abundant species, were analyzed. Weather data included local daily maximum temperature, minimum temperature, total precipitation, and average relative humidity. In addition to standard statistical methods, cross-correlation mapping was used to evaluate temporal associations with various lag periods between weather variables and species-specific mosquito abundances. Overall, the average number of mosquitoes was 4.90 per trap-night for Ae. vexans, 2.12 for Cx. pipiens, and 1.23 for Cx. restuans. Statistical analysis of the considerable temporal variability in species-specific abundances indicated that precipitation and relative humidity 1 wk prior were significantly positively associated with Ae. vexans, whereas elevated maximum temperature had a negative effect during summer. Cx. pipiens abundance was positively influenced by the preceding minimum temperature in the early season but negatively associated with precipitation during summer and with maximum temperature in July and August. Cx. restuans showed the least weather association, with only relative humidity 2-24 d prior being linked positively during late spring-early summer. The recently developed analytical method applied in this study could enhance our understanding of the influences of weather variability on mosquito population dynamics.

An outbreak of cardiovascular syndromes requiring urgent medical treatment and its association with environmental factors: an ecological study

PubMed Central

Turner, Robin M; Muscatello, David J; Zheng, Wei; Willmore, Alan; Arendts, Glenn

2007-01-01

Background In April 2005, syndromic surveillance based on statistical control chart methods in Sydney, Australia, signalled increasing incidence of urgent emergency department visits for cardiovascular and chest pain syndromes compared to the preceding twelve months. This paper aimed to determine whether environmental factors could have been responsible for this 'outbreak'. Methods The outcome studied was daily counts of emergency department visits for cardiovascular or chest pain syndromes that were considered immediately or imminently life threatening on arrival at hospital. The outbreak had a mean daily count of 5.7 visits sustained for eight weeks, compared with 4.0 in the same months in previous years. Poisson regression was used to systematically assess the emergency department visits in relation to available daily weather and pollution variables by first finding the best model that explained short-term variation in the outcome over the period 25 January 2002 to 31 May 2005, and then assessing interactions of all available variables with the 'outbreak' period, April-May 2005. Rate ratios were estimated for an interquartile increase in each variable meaning that the ratio measures the relative increase (or decrease) in the emergency department visits for an interquartile increase in the weather or pollution variable. The rate ratios for the outbreak period measure the relative increase (or decrease) in the emergency department visits for an interquartile increase in the weather or pollution variable during the outbreak period only. Results The best fitting model over the whole study period included minimum temperature with a rate ratio (RR) of 0.86 (95% confidence interval (CI), 0.77–0.96), maximum relative humidity of 1.09 (95% CI 1.05–1.14) and minimum daily particulate matter less than 10 microns (PM10) of 1.05 (95% CI, 1.01–1.09). During the outbreak period, maximum temperature (RR 1.27, 95% CI 1.03–1.57), solar radiation (RR 1.44, 95% CI, 1.00–2.07) and ozone (RR 1.13, 95% CI 1.01–1.26) were associated with the outcome. Conclusion The increase may have been associated with photochemical pollution. Syndromic surveillance can identify outbreaks of non-communicable diseases associated with environmental factors. PMID:18036253

Assessing climate change over the Marche Region (central Italy) from 1961 to 2100: projected changes in mean temperature and future heat waves characterization (with a statistical evaluation of RCMs local performance)

NASA Astrophysics Data System (ADS)

Sangelantoni, Lorenzo; Coluccelli, Alessandro; Russo, Aniello

2014-05-01

Marche region (central Italy, facing the Adriatic Sea) climate dynamics are connected to the Mediterranean basin, identified as one of the most sensitive areas to ongoing climate change. Taken into account difficulties to carry out an overarching assessment over the heterogeneous Mediterranean climate-change issues frame, we opted toward a consistent regional bordered study. Projected changes in mean seasonal temperature, with an introductory multi-statistical model performance evaluation and a future heat waves intensity and duration characterization, are here presented. Multi-model projections over Marche Region, on daily mean, minimum and maximum temperature, have been extracted from the outputs of a set of 7 Regional Climate Models (RCMs) over Europe run by several research Institutes participating to the EU ENSEMBLE project. These climate simulations from 1961 to 2100 refer to the boundary conditions of the IPCC A1B emission scenario, and have a horizontal resolution of 25km × 25km. Furthermore, two RCMs outputs from Med-CORDEX project, with a higher horizontal resolution (12km x 12km) and boundary conditions provided by the new Representative Concentration Pathway (RCP) 4.5 and 8.5, are considered. Observed daily mean, minimum and maximum temperature over Marche region domain have been extracted from E-OBS gridded data set (Version 9.0) referring to the period 1970-2004. This twofold work firstly provides a concise statistical summary of how well employed RCMs reproduce observed (1970-2004) mean temperature over Marche region in term of correlation, root-mean-square difference, and ratio of their variances, graphically displayed on a 2D-Taylor diagram. This multi-statistical model performance evaluation easily allows: - to compare the agreement with observation of the 9 individual RCMs - to compare RCMs with different horizontal resolution (12 km and 25 km) - to evaluate the improvement provided by the RCMs ensemble. Results indicate that the 9 RCMs ensemble provides the statistically best reproduction of the observed interannual mean temperature distribution. Secondly, we assessed projected seasonal ensemble average change in mean temperature referring to the ending 21st century obtained by comparison between 2071-2100 and 1961-1990 time slice modeled mean value over Marche region. Results emphasize summer as the season most affected by projected temperature increase (+4.5°C / +5.0°C), followed by spring season temperature increase (+3.5°C / +4.0°C). Finally, considering that some of the most severe health hazards arise from multi-day heat-waves, associated with both hot day-time and warm night-time temperatures, we assessed modeled trend (1961-2100) of the heat waves intensity and duration: intensity through the temporal evolution of the summer (J J A months) maximum and minimum temperature 90th percentile, heat waves length by temporal evolution of two detected threshold-based indices (annual maximum number of consecutive days characterized by Tmin >= 24°C and annual maximum number of consecutive days characterized by Tmax > = 32°C). Same analysis for both coastal and mountainous areas has been conducted. Future research plans aim to involve ensemble RCMs simulation, processed with bias correction methods, in forcing climate change impacts models, to provide a detailed regional heat waves impacts scenario, mainly over agriculture and health sectors.

Climate Data Homogenization and its Impact on Heatwave Changes in the Eastern Mediterranean

NASA Astrophysics Data System (ADS)

Kuglitsch, F. G.; Toreti, A.; Xoplaki, E.; Della-Marta, P. M.; Zerefos, C. S.; Turkes, M.; Luterbacher, J.

2010-12-01

Heatwaves have discernible impacts on mortality and morbidity, infrastructure, agricultural resources, the retail industry, ecosystem and tourism and consequently affect human societies. A new definition of socially relevant heatwaves is presented and applied to new data sets of high-quality homogenized daily maximum and minimum summer air temperature series from 246 stations in the eastern Mediterranean region (including Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Cyprus, Greece, Israel, Romania, Serbia, Slovenia, Turkey). Changes in heatwave number, length and intensity between 1960 and 2006 are quantified before and after data homogenization. Daily temperature homogeneity analyses suggest that many instrumental measurements in the 1960s are warm-biased, correcting for these biases regionally averaged heatwave trends are up to 8% higher. We find significant changes across the western Balkans, southwestern and western Turkey, and along the southern Black Sea coastline. Since the 1960s, the mean heatwave intensity, heatwave length and heatwave number across the eastern Mediterranean region have increased by a factor of 7.6 ± 1.3, 7.5 ± 1.3 and 6.2 ± 1.1, respectively. These findings suggest that the heatwave increase in this region is higher than previously reported.

Heat Wave Changes in the Eastern Mediterranean since 1960

NASA Astrophysics Data System (ADS)

Kuglitsch, Franz G.; Toreti, Andrea; Xoplaki, Elena; Della-Marta, Paul M.; Zerefos, Christos S.; Türkes, Murat; Luterbacher, Jürg

2010-05-01

Heat waves have discernible impacts on mortality and morbidity, infrastructure, agricultural resources, the retail industry, ecosystem and tourism and consequently affect human societies. A new definition of socially relevant heat waves is presented and applied to new data sets of high-quality homogenized daily maximum and minimum summer air temperature series from 246 stations in the eastern Mediterranean region (including Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Cyprus, Greece, Israel, Romania, Serbia, Slovenia, Turkey). Changes in heat wave number, length and intensity between 1960 and 2006 are quantified. Daily temperature homogeneity analysis suggest that many instrumental measurements in the 1960s are warm-biased, correcting for these biases regionally averaged heat wave trends are up to 8% higher. We find significant changes across the western Balkans, southwestern and western Turkey, and along the southern Black Sea coastline. Since the 1960s, the mean heat wave intensity, heat wave length and heat wave number across the eastern Mediterranean region have increased by a factor 7.6 ±1.3, 7.5 ±1.3 and 6.2 ±1.1, respectively. These findings suggest that the heat wave increase in this region is higher than previously reported.

Actual and future trends of extreme values of temperature for the NW Iberian Peninsula

NASA Astrophysics Data System (ADS)

Taboada, J.; Brands, S.; Lorenzo, N.

2009-09-01

It is now very well established that yearly averaged temperatures are increasing due to anthropogenic climate change. In the area of Galicia (NW Spain) this trend has also been determined. The main objective of this work is to assess actual and future trends of different extreme indices of temperature, which are of curcial importance for many impact studies. Station data for the study was provided by the CLIMA database of the regional government of Galicia (NW Spain). As direct GCM-output significantly underestimates the variance of daily surface temperature variables in NW Spain, these variables are obtained by applying a statistical downscaling technique (analog method), using 850hPa temperature and mean sea level pressure as combined predictors. The predictor fields have been extracted from three GCMs participating in the IPCC AR4 under A1, A1B and A2 scenarios. The definitions of the extreme indices have been taken from the joint CCl/CLIVAR/JCOMM Expert Team (ET) on Climate Change Detection and Indices (ETCCDI) This group has defined a set of standard extreme values to simplify intercomparisons of data from different regions of the world. For the temperatures in the period 1960-2006, results show a significant increase of the number of days with maximum temperatures above the 90th percentile. Furthermore, a significant decrease of the days with maximum temperatures below the 10th percentile has been found. The tendencies of minimum temperatures are reverse: less nights with minimum temperatures below 10th percentile, and more with minimum temperatures above 90th percentile. Those tendencies can be observed all over the year, but are more pronounced in summer. We have also calculated the relationship between the above mentioned extreme values and different teleconnection patterns appearing in the North Atlantic area. Results show that local tendencies are associated with trends of EA (Eastern Atlantic) and SCA (Scandinavian) patterns. NAO (North Atlantic Oscillation) has also some relationship with these tendencies, but only related with cold days and nights in winter. The results of the applied statistical downscaling technique indicate that observed trends in maximum and minimum temperatures in NW Spain are expected to continue in the next decades because of anthropogenic climate change. The common tendency is that hot days increase while cold nights diminish all over the year. As expected, these tendencies change between different scenarios: they are more marked for A2 and A1B scenarios than for the for the B1 scenario. Moreover, the three models behave different under the same scenario, leaving a great uncertainty for the future. Nevertheless, we conclude that more frequent hot days, as well as an increasing probability of summertime heat waves are to be expected in the next decades. Cold days tend to diminish, decreasing the probability of wintertime cold waves and leaving a greater part of the area under study without frost days throughout the year.

Seasonally frozen layer in natural and drained peatlands at the South of West Siberia, Russia

NASA Astrophysics Data System (ADS)

Dyukarev, Egor; Kiselev, Maxim; Voropay, Nadezhda; Preis, Yulia

2017-04-01

The temperature regime of soils in natural and drained peatlands at Bakchar bog located in the South Taiga zone of West Siberia is studied. Soil temperature for depths up to 320 cm was registered using autonomous temperature profile recorder during the period from August 2010 to September 2016. Maximal and minimal temperatures were registered at surface in July and February, consequently. Extreme soil temperatures at 320 cm depth shifts to December (maximum) and July (minimum) reducing absolute values. Annual peat soil temperature amplitude decrease with depth from 21,8 °C on surface to 1,1 °C at 320 cm. The analysis of daily, month and annual mean data of temperature in peat soil has shown that seasonally frozen layer was registered up to 20-60 cm depth. The duration of seasonally freeze layer existence varies from 130 to 180 days. Drained peatlands with the lowest water table have highest freeze depth. Soil at water-logged sedge-sphagnum fen in winter is warmer than soil in ryam ecosystem and mineral soil at upland. Maximal freezing depth in peatlands is up to 3 times lower than at drain areas.

Dissolved oxygen, stream temperature, and fish habitat response to environmental water purchases.

PubMed

Null, Sarah E; Mouzon, Nathaniel R; Elmore, Logan R

2017-07-15

Environmental water purchases are increasingly used for ecological protection. In Nevada's Walker Basin (western USA), environmental water purchases augment streamflow in the Walker River and increase lake elevation of terminal Walker Lake. However, water quality impairments like elevated stream temperatures and low dissolved oxygen concentrations also limit ecosystems and species, including federally-threatened Lahontan cutthroat trout. In this paper, we prioritize water volumes and locations that most enhance water quality for riverine habitat from potential environmental water rights purchases. We monitored and modeled streamflows, stream temperatures, and dissolved oxygen concentrations using River Modeling System, an hourly, physically-based hydrodynamic and water quality model. Modeled environmental water purchases ranged from average daily increases of 0.11-1.41 cubic meters per second (m 3 /s) during 2014 and 2015, two critically dry years. Results suggest that water purchases consistently cooled maximum daily stream temperatures and warmed nightly minimum temperatures. This prevented extremely low dissolved oxygen concentrations below 5.0 mg/L, but increased the duration of moderate conditions between 5.5 and 6.0 mg/L. Small water purchases less than approximately 0.71 m 3 /s per day had little benefit for Walker River habitat. Dissolved oxygen concentrations were affected by upstream environmental conditions, where suitable upstream water quality improved downstream conditions and vice versa. Overall, this study showed that critically dry water years degrade environmental water quality and habitat, but environmental water purchases of at least 0.71 m 3 /s were promising for river restoration. Published by Elsevier Ltd.

Impacts of Initial Soil Moisture and Vegetation on the Diurnal Temperature Range in Arid and Semiarid Regions in China

NASA Astrophysics Data System (ADS)

Yuan, Guanghui; Zhang, Lei; Liang, Jiening; Cao, Xianjie; Guo, Qi; Yang, Zhaohong

2017-11-01

To assess the impacts of initial soil moisture (SMOIS) and the vegetation fraction (Fg) on the diurnal temperature range (DTR) in arid and semiarid regions in China, three simulations using the weather research and forecasting (WRF) model are conducted by modifying the SMOIS, surface emissivity and Fg. SMOIS affects the daily maximum temperature (Tmax) and daily minimum temperature (Tmin) by altering the distribution of available energy between sensible and latent heat fluxes during the day and by altering the surface emissivity at night. Reduced soil wetness can increase both the Tmax and Tmin, but the effect on the DTR is determined by the relative strength of the effects on Tmax and Tmin. Observational data from the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) and the Shapotou Desert Research and Experimental Station (SPD) suggest that the magnitude of the SMOIS effect on the distribution of available energy during the day is larger than that on surface emissivity at night. In other words, SMOIS has a negative effect on the DTR. Changes in Fg modify the surface radiation and the energy budget. Due to the depth of the daytime convective boundary layer, the temperature in daytime is affected less than in nighttime by the radiation and energy budget. Increases in surface emissivity and decreases in soil heating resulting from increased Fg mainly decrease Tmin, thereby increasing the DTR. The effects of SMOIS and Fg on both Tmax and Tmin are the same, but the effects on DTR are the opposite.

Mars climatology from viking 1 after 20 sols.

PubMed

Hess, S L; Henry, R M; Leovy, C B; Ryan, J A; Tillman, J E; Chamberlain, T E; Cole, H L; Dutton, R G; Greene, G C; Simon, W E; Mitchell, J L

1976-10-01

The results from the meteorology instruments on the Viking 1 lander are presented for the first 20 sols of operation. The daily patterns of temperature, wind, and pressure have been highly consistent during the period. Hence, these have been assembled into 20-sol composites and analyzed harmonically. Maximum temperature was 241.8 degrees K and minimum 187.2 degrees K. The composite wind vector has a mean diurnal magnitude of 2.4 meters per second with prevailing wind from the south and counterclockwise diurnal rotation. Pressure exhibits diurnal and semidiurnal oscillations. The diurnal is ascribed to a combination of effects, and the semidiurnal appears to be the solar semidiurnal tide. Similarities to Earth are discussed. A major finding is a continual secular decrease in diurnal mean pressure. This is ascribed to carbon dioxide deposition at the south polar cap.

Shams 1 - Design and operational experiences of the 100MW - 540°C CSP plant in Abu Dhabi

NASA Astrophysics Data System (ADS)

Alobaidli, Abdulaziz; Sanz, Borja; Behnke, Klaus; Witt, Thomas; Viereck, Detlef; Schwarz, Mark André

2017-06-01

SHAMS 1 ("Shams" means "Sun" in Arabic) Concentrated Solar Power plant is a very successful example of a modern plant, which combines the known configuration of a parabolic trough technology with the well-established power generation technologies operated at 540°C live steam temperature while respecting the specific requirement of the daily starts and shutdowns. In addition to the high live steam temperature challenge and being located in the middle of the desert approx. 120 km south west of the city of Abu Dhabi, the plant has to face, the plant has to fact several atmospheric challenges like the high dust concentration, wind storms, and high ambient temperature. This paper, written jointly by Shams Power Company - the project and operating company and MAN Diesel & Turbo - the steam turbine original manufacturer, describes the challenges in optimizing the design of the steam turbine to fulfill the requirement of fast start up while operating the plant on daily transient pattern for minimum 30 years. It also addresses the several atmospheric challenges and how the project and operating company has overcame them. Finally, the paper gives a snap shot on the operational experience and record of the plant showing that despite the very challenging environment, the budgeted target has been exceeded in the first two years of operation.

Selected micrometeorological, soil-moisture, and evapotranspiration data at Amargosa Desert Research Site in Nye County near Beatty, Nevada, 2001-05

USGS Publications Warehouse

Johnson, Michael J.; Mayers, C. Justin; Garcia, C. Amanda; Andraski, Brian J.

2007-01-01

Selected micrometeorological and soil-moisture data were collected at the Amargosa Desert Research Site adjacent to a low-level radio-active waste and hazardous chemical waste facility near Beatty, Nevada, 2001-05. Evapotranspiration data were collected from February 2002 through the end of December 2005. Data were col-lected in support of ongoing research to improve the understanding of hydrologic and contaminant-transport processes in arid environments. Micrometeorological data include solar radiation, net radiation, air temperature, relative humidity, saturated and ambient vapor pressure, wind speed and direction, barometric pressure, precipitation, near-surface soil temperature, soil-heat flux and soil-water content. All micrometeorological data were collected using a 10-second sampling interval by data loggers that output daily and hourly mean values. Daily maximum and minimum values are based on hourly mean values. Precipitation data output includes daily and hourly totals. Selected soil-moisture profiles at depth include periodic measurements of soil volumetric water-content measurements at nine neutron-probe access tubes to depths ranging from 5.25 to 29.25 meters. Evapotranspiration data include measurement of daily evapotranspiration and 15-minute fluxes of the four principal energy budget components of latent-heat flux, sensible-heat flux, soil-heat flux, and net radiation. Other data collected and used in equations to determine evapotranspiration include temperature and water content of soil, temperature and vapor pressure of air, and covariance values. Evapotranspiration and flux estimates during 15-minute intervals were calculated at a 0.1-second execution interval using the eddy covariance method. Data files included in this report contain the complete micrometeorological, soil-moisture, and evapotranspiration field data sets. These data files are presented in tabular Excel spreadsheet format. This report highlights selected data contained in the computer generated data files using figures, tables, and brief discussions. Instrumentation used for data collection also is described. Water-content profiles are shown to demonstrate variability of water content with depth. Time-series data are plotted to illustrate temporal variations in micrometeorological, soil-water content, and evapotranspiration data.

The Effects of Temperature and Precipitation on the Yield of Zea Mays L. I the Southeastern United States

NASA Astrophysics Data System (ADS)

Stooksbury, David Emory

Three families of straightforward maize (Zea mays L.) yield/climate models using monthly temperature and precipitation terms are produced. One family of models uses USDA's Crop Reporting Districts (CRD) as its scale of aggregation. The other two families of models use three different district aggregates based on climate or yield patterns. The climate and yield districts are determined by using a two-stage cluster analysis. The CRD-based family of models perform as well as the climate and yield based models. All models explain between 80% and 90% of the variance in maize yield. The most important climate term affecting maize yield in the South is the daily maximum temperature at pollination time. The higher the maximum temperature, the lower the yield. Above normal minimum temperature during pollination increases yield in the Middle South. Weather that favors early planting and rapid vegetative growth increases yield. Ideal maize yield weather includes a dry period during planting followed by a warm period during vegetative growth. Moisture variables are important only during the planting and harvest periods when above normal precipitation delays field work and thereby reduces yield. The model results indicate that the dire predictions about the fate of Southern agriculture in a trace gas warmed world may not be true. This is due to the overwhelming influence of the daily maximum temperature on yield. An optimum aggregate for climate impact studies was not found. I postulate that this is due to the dynamic nature of the American maize production system. For most climate impact studies on a dynamic agricultural system, there does not need to be a concern about the model aggregation.

High-resolution projections of 21st century climate over the Athabasca River Basin through an integrated evaluation-classification-downscaling-based climate projection framework

NASA Astrophysics Data System (ADS)

Cheng, Guanhui; Huang, Guohe; Dong, Cong; Zhu, Jinxin; Zhou, Xiong; Yao, Y.

2017-03-01

An evaluation-classification-downscaling-based climate projection (ECDoCP) framework is developed to fill a methodological gap of general circulation models (GCMs)-driven statistical-downscaling-based climate projections. ECDoCP includes four interconnected modules: GCM evaluation, climate classification, statistical downscaling, and climate projection. Monthly averages of daily minimum (Tmin) and maximum (Tmax) temperature and daily cumulative precipitation (Prec) over the Athabasca River Basin (ARB) at a 10 km resolution in the 21st century under four Representative Concentration Pathways (RCPs) are projected through ECDoCP. At the octodecadal scale, temperature and precipitation would increase; after bias correction, temperature would increase with a decreased increment, while precipitation would increase only under RCP 8.5. Interannual variability of climate anomalies would increase from RCPs 4.5, 2.6, 6.0 to 8.5 for temperature and from RCPs 2.6, 4.5, 6.0 to 8.5 for precipitation. Bidecadal averaged climate anomalies would decrease from December-January-February (DJF), March-April-May (MAM), September-October-November (SON) to June-July-August (JJA) for Tmin, from DJF, SON, MAM to JJA for Tmax, and from JJA, MAM, SON to DJF for Prec. Climate projection uncertainties would decrease in May to September for temperature and in November to April for precipitation. Spatial climatic variability would not obviously change with RCPs; climatic anomalies are highly correlated with climate-variable magnitudes. Climate anomalies would decrease from upstream to downstream for temperature, and precipitation would follow an opposite pattern. The north end and the other zones would have colder and warmer days, respectively; precipitation would decrease in the upstream and increase in the remaining region. Climate changes might lead to issues, e.g., accelerated glacier/snow melting, deserving attentions of researchers and the public.

Comparison of short-term associations with meteorological variables between COPD and pneumonia hospitalization among the elderly in Hong Kong—a time-series study

NASA Astrophysics Data System (ADS)

Lam, Holly Ching-yu; Chan, Emily Ying-yang; Goggins, William Bernard

2018-05-01

Pneumonia and chronic obstructive pulmonary diseases (COPD) are the commonest causes of respiratory hospitalization among older adults. Both diseases have been reported to be associated with ambient temperature, but the associations have not been compared between the diseases. Their associations with other meteorological variables have also not been well studied. This study aimed to evaluate the associations between meteorological variables, pneumonia, and COPD hospitalization among adults over 60 and to compare these associations between the diseases. Daily cause-specific hospitalization counts in Hong Kong during 2004-2011 were regressed on daily meteorological variables using distributed lag nonlinear models. Associations were compared between diseases by ratio of relative risks. Analyses were stratified by season and age group (60-74 vs. ≥ 75). In hot season, high temperature (> 28 °C) and high relative humidity (> 82%) were statistically significantly associated with more pneumonia in lagged 0-2 and lagged 0-10 days, respectively. Pneumonia hospitalizations among the elderly (≥ 75) also increased with high solar radiation and high wind speed. During the cold season, consistent hockey-stick associations with temperature and relative humidity were found for both admissions and both age groups. The minimum morbidity temperature and relative humidity were at about 21-22 °C and 82%. The lagged effects of low temperature were comparable for both diseases (lagged 0-20 days). The low-temperature-admissions associations with COPD were stronger and were strongest among the elderly. This study found elevated pneumonia and COPD admissions risks among adults ≥ 60 during periods of extreme weather conditions, and the associations varied by season and age group. Vulnerable groups should be advised to avoid exposures, such as staying indoor and maintaining satisfactory indoor conditions, to minimize risks.

Use of statistically and dynamically downscaled atmospheric model output for hydrologic simulations in three mountainous basins in the western United States

USGS Publications Warehouse

Hay, L.E.; Clark, M.P.

2003-01-01

This paper examines the hydrologic model performance in three snowmelt-dominated basins in the western United States to dynamically- and statistically downscaled output from the National Centers for Environmental Prediction/National Center for Atmospheric Research Reanalysis (NCEP). Runoff produced using a distributed hydrologic model is compared using daily precipitation and maximum and minimum temperature timeseries derived from the following sources: (1) NCEP output (horizontal grid spacing of approximately 210 km); (2) dynamically downscaled (DDS) NCEP output using a Regional Climate Model (RegCM2, horizontal grid spacing of approximately 52 km); (3) statistically downscaled (SDS) NCEP output; (4) spatially averaged measured data used to calibrate the hydrologic model (Best-Sta) and (5) spatially averaged measured data derived from stations located within the area of the RegCM2 model output used for each basin, but excluding Best-Sta set (All-Sta). In all three basins the SDS-based simulations of daily runoff were as good as runoff produced using the Best-Sta timeseries. The NCEP, DDS, and All-Sta timeseries were able to capture the gross aspects of the seasonal cycles of precipitation and temperature. However, in all three basins, the NCEP-, DDS-, and All-Sta-based simulations of runoff showed little skill on a daily basis. When the precipitation and temperature biases were corrected in the NCEP, DDS, and All-Sta timeseries, the accuracy of the daily runoff simulations improved dramatically, but, with the exception of the bias-corrected All-Sta data set, these simulations were never as accurate as the SDS-based simulations. This need for a bias correction may be somewhat troubling, but in the case of the large station-timeseries (All-Sta), the bias correction did indeed 'correct' for the change in scale. It is unknown if bias corrections to model output will be valid in a future climate. Future work is warranted to identify the causes for (and removal of) systematic biases in DDS simulations, and improve DDS simulations of daily variability in local climate. Until then, SDS based simulations of runoff appear to be the safer downscaling choice.

Effects of Cold-Dry (Harmattan) and Hot-Dry Seasons on Daily Rhythms of Rectal and Body Surface Temperatures in Sheep and Goats in a Natural Tropical Environment

PubMed Central

Ayo, Joseph O.

2016-01-01

Studies on daily rhythmicity in livestock under natural conditions are limited, and there is mounting evidence that rhythm patterns differ between chronobiological studies conducted in the laboratory and studies conducted under pronounced natural seasonality. Here, we investigated the influence of cold-dry (harmattan) and hot-dry seasons on daily rhythmicity of rectal (RT) and body surface temperatures (BST) in indigenous sheep and goats under natural light-dark cycles. The RT and BST of the animals, and the ambient temperature (AT) and relative humidity (RH) inside the pen, were measured every three hours for a period of two days, twice on separate days during the hot-dry and the harmattan seasons, respectively. The AT and RH had minimum values of 16°C and 15% recorded during the harmattan and maximum values of 32°C and 46% recorded during the hot-dry season, respectively. A trigonometric statistical model was applied to characterize the main rhythmic parameters according to the single cosinor procedure. The result showed that RT and BST exhibited different degrees of daily rhythmicity, and their oscillatory patterns differed with the seasons (larger amplitude during the harmattan season than during the hot-dry season). The goats displayed greater (p < 0.05) amplitude of BST than the sheep in all seasons. The acrophases were restricted to the light phase of the light-dark cycle. The mesor of RT in goats was not affected by the season, but mesors of BST in both species were significantly higher (p < 0.05) during the hot-dry than the harmattan season. The goats had a more robust RT rhythm (70%) as compared to the sheep (56%). Overall, the results demonstrated that seasonal changes influenced considerably the daily rhythmicity of RT and BST in sheep and goats under natural light-dark cycle. Awareness of these changes may be useful in the improvement of diagnosis, treatment and prevention of diseases, and welfare and productivity of sheep and goats under cold-dry and hot-dry conditions.

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.

Air pollution and child mortality: a time-series study in São Paulo, Brazil.

PubMed Central

Conceição, G M; Miraglia, S G; Kishi, H S; Saldiva, P H; Singer, J M

2001-01-01

Although most available evidence relating air pollution and mortality was obtained for adults, pollution has been also associated with increased mortality in children, but in a significantly smaller number of studies. This study was designed to evaluate the association between child mortality and air pollution in the city of São Paulo, Brazil, from 1994 to 1997. Daily records of mortality due to respiratory diseases for children under 5 years of age were obtained from the municipal mortality information improvement program. Daily concentrations of sulfur dioxide (SO(2)), carbon monoxide (CO), inhalable particulate matter less than 10 microm in diameter (PM(10)), and ozone were obtained from the state air pollution controlling agency. Information on minimum daily temperature and on relative humidity were obtained from the Institute of Astronomy and Geophysics of the University of São Paulo. Statistical analysis was performed through generalized additive models considering a Poisson response distribution and a log link. Explanatory variables were time, temperature, humidity, and pollutant concentrations. The loess smoother was applied to time (in order to model seasonality) and temperature. Significant associations between mortality and concentrations of CO, SO(2), and PM(10) were detected. The coefficients (and standard errors) of these three pollutants were 0.0306 (0.0076), 0.0055 (0.0016), and 0.0014 (0.0006), respectively. The observed associations were dose dependent and quite evident after a short period of exposure (2 days). According to the proposed model and considering the mean of the pollutant concentration during the period of the study, the estimated proportions of respiratory deaths attributed to CO, SO(2), and PM(10), when considered individually, are around 15, 13, and 7%, respectively. PMID:11427383

Investigation and Modeling of Cranberry Weather Stress.

NASA Astrophysics Data System (ADS)

Croft, Paul Joseph

Cranberry bog weather conditions and weather-related stress were investigated for development of crop yield prediction models and models to predict daily weather conditions in the bog. Field investigations and data gathering were completed at the Rutgers University Blueberry/Cranberry Research Center experimental bogs in Chatsworth, New Jersey. Study indicated that although cranberries generally exhibit little or no stomatal response to changing atmospheric conditions, the evaluation of weather-related stress could be accomplished via use of micrometeorological data. Definition of weather -related stress was made by establishing critical thresholds of the frequencies of occurrence, and magnitudes of, temperature and precipitation in the bog based on values determined by a review of the literature and a grower questionnaire. Stress frequencies were correlated with cranberry yield to develop predictive models based on the previous season's yield, prior season data, prior and current season data, current season data; and prior and current season data through July 31 of the current season. The predictive ability of the prior season models was best and could be used in crop planning and production. Further examination of bog micrometeorological data permitted the isolation of those weather conditions conducive to cranberry scald and allowed for the institution of a pilot scald advisory program during the 1991 season. The micrometeorological data from the bog was also used to develop models to predict daily canopy temperature and precipitation, based on upper air data, for grower use. Models were developed for each month for maximum and minimum temperatures and for precipitation and generally performed well. The modeling of bog weather conditions is an important first step toward daily prediction of cranberry weather-related stress.

Simulation of corn yields and parameters uncertainties analysis in Hebei and Sichuang, China

NASA Astrophysics Data System (ADS)

Fu, A.; Xue, Y.; Hartman, M. D.; Chandran, A.; Qiu, B.; Liu, Y.

2016-12-01

Corn is one of most important agricultural production in China. Research on the impacts of climate change and human activities on corn yields is important in understanding and mitigating the negative effects of environmental factors on corn yields and maintaining the stable corn production. Using climatic data, including daily temperature, precipitation, and solar radiation from 1948 to 2010, soil properties, observed corn yields, and farmland management information, corn yields in Sichuang and Hebei Provinces of China in the past 63 years were simulated using the Daycent model, and the results was evaluated using Root mean square errors, bias, simulation efficiency, and standard deviation. The primary climatic factors influencing corn yields were examined, the uncertainties of climatic factors was analyzed, and the uncertainties of human activity parameters were also studied by changing fertilization levels and cultivated ways. The results showed that: (1) Daycent model is capable to simulate corn yields in Sichuang and Hebei provinces of China. Observed and simulated corn yields have the similar increasing trend with time. (2) The minimum daily temperature is the primary factor influencing corn yields in Sichuang. In Hebei Province, daily temperature, precipitation and wind speed significantly affect corn yields.(3) When the global warming trend of original data was removed, simulated corn yields were lower than before, decreased by about 687 kg/hm2 from 1992 to 2010; When the fertilization levels, cultivated ways were increased and decreased by 50% and 75%, respectively in the Schedule file in Daycent model, the simulated corn yields increased by 1206 kg/hm2 and 776 kg/hm2, respectively, with the enhancement of fertilization level and the improvement of cultivated way. This study provides a scientific base for selecting a suitable fertilization level and cultivated way in corn fields in China.

Incubation behavior of king eiders on the coastal plain of Northern Alaska

USGS Publications Warehouse

Bentzen, R.L.; Powell, A.N.; Phillips, Laura M.; Suydam, R.S.

2010-01-01

Incubating birds balance their energetic demands during incubation with the needs of the developing embryos. Incubation behavior is correlated with body size; larger birds can accumulate more endogenous reserves and maintain higher incubation constancy. King eiders (Somateria spectabilis) contend with variable and cold spring weather, little nesting cover, and low food availability, and thus are likely to rely heavily on endogenous reserves to maintain high incubation constancy. We examined the patterns of nest attendance of king eiders at Teshekpuk and Kuparuk, Alaska (2002-2005) in relation to clutch size, daily temperature, and endogenous reserves to explore factors controlling incubation behavior. Females at Kuparuk had higher constancy (98.5 ?? 0.2%, n = 30) than at Teshekpuk (96.9 ?? 0.8%, n = 26), largely due to length of recesses. Mean recess length ranged from 21.5 to 23.7 min at Kuparuk, and from 28.5 to 51.2 min at Teshekpuk. Mean body mass on arrival at breeding grounds (range; Teshekpuk 1,541-1,805, Kuparuk 1,616-1,760), and at the end of incubation (Teshekpuk 1,113-1,174, Kuparuk 1,173-1,183), did not vary between sites or among years (F < 1.1, P > 0.3). Daily constancy increased 1% with every 5??C increase in minimum daily temperature (??min = 0.005, 95% CI 0.002, 0.009). Higher constancy combined with similar mass loss at Kuparuk implies that females there met foraging requirements with shorter recesses. Additionally, females took more recesses at low temperatures, suggesting increased maintenance needs which were potentially ameliorated by feeding during these recesses, indicating that metabolic costs and local foraging conditions drove incubation behavior. ?? 2010 US Government.

Anthropogenically-induced changes in temperatures and implications for water resources in the western United States.

NASA Astrophysics Data System (ADS)

Bonfils, C.; Santer, B.; Pierce, D.; Hidalgo, H.; Bala, G.; Dash, T.; Barnett, T.; Cayan, D.; Doutriaux, C.; Wood, A.; Mirin, A.; Nosawa, T.

2008-12-01

Large changes in the hydrology of the western United States have been observed since the mid-20th century. These include a reduction in the amount of precipitation arriving as snow, a decline in snowpack at low and mid-elevations, and a shift towards earlier arrival of both snowmelt and the center of mass of streamflows. In order to project future water supply reliability, it is crucial to obtain a better understanding of the underlying cause or causes for these long-term changes. A regional warming is often posited as the cause of these changes, without formal testing of different competitive explanations for the warming. In this study, we perform a rigorous detection and attribution analysis to determine the causes of the late winter/early spring changes in hydrologically-relevant temperature variables over mountain ranges of the western U.S. Natural internal climate variability, as estimated from two long control climate model simulations, is insufficient to explain the rapid increase in daily minimum and maximum temperatures, the sharp decline in frost days, and the rise in degree-days above 0°C (a simple proxy for temperature-driven snowmelt). The observations are however consistent with climate simulations that include the combined effects of anthropogenic greenhouse gases and aerosols. We also address the benefits of conducting multivariate versus univariate detection and attribution analysis, with, for instance, a focus on changes in snowmelt, streamflow peaks and minimum temperature. With models of climate change unanimously projecting an acceleration of warming in the western United States, serious implications for water infrastructures and water supply sustainability can be expected, increasing already the necessity of developing adaptation measures in water resources management.

Demonstrating the limitations of line ratio temperature diagnostic using Fe X and Fe XIV spectral line intensity observations

NASA Technical Reports Server (NTRS)

Brickhouse, Nancy; Esser, Ruth; Habbal, Shadia R.

1995-01-01

The electron temperature in the inner corona can be derived from spectral line intensity measurements by comparing the ratio of the measured intensities of two spectral lines to the ratio calculated from theoretical models. In a homogeneous plasma the line ratio technique can be used for any two lines if the ratio of the intensities is independent of the density. The corona, however, is far from homogeneous. Even large coronal holes present at the solar poles at solar minimum can be partly or completely obscured by emission from hotter and denser surrounding regions. In this paper we investigate the effect of these surrounding regions on coronal hole temperatures. using daily intensity measurements at 1.15 Rs of the Fe XIV 5303 A and Fe X 6374 A spectral lines carried out at the National Solar Observatory at Sacramento Peak. We show that the temperatures derived using the line ratio technique for these two spectral lines can vary by more than 0.8 x 10(exp 6) K due to the contribution from surrounding regions. This example demonstrates the inadequacy of spectral lines with widely separate peak temperatures for temperature diagnostic.

The influence of climatic factors on the development of hemorrhagic fever with renal syndrome and leptospirosis during the peak season in Korea: an ecologic study.

PubMed

Joshi, Yadav Prasad; Kim, Eun-Hye; Cheong, Hae-Kwan

2017-06-07

Hemorrhagic fever with renal syndrome (HFRS) and leptospirosis are seasonal rodent-borne infections in the Republic of Korea (Korea). The occurrences of HFRS and leptospirosis are influenced by climatic variability. However, few studies have examined the effects of local climatic variables on the development of these infections. The purpose of this study was to estimate the effect of climatic factors on the occurrence of HFRS and leptospirosis in Korea. Daily records on human cases of HFRS and leptospirosis between January 2001 to December 2009 were analyzed. The associations of climatic factors with these cases in high incidence provinces were estimated using the time-series method and multivariate generalized linear Poisson models with a maximal lag of 12 weeks. From 2001 to 2009, a total of 2912 HFRS and 889 leptospirosis cases were reported, with overall incidences of 0.67 and 0.21 cases per 100,000, respectively, in the study areas. The increase in minimum temperature (1 °C) at a lag of 11 weeks was associated with 17.8% [95% confidence interval (CI): 15.1, 20.6%] and 22.7% (95% CI: 16.5, 29.3%) increases in HFRS and leptospirosis cases, respectively. A 1-h increase in the daily sunshine was related to a 27.5% (95% CI: 18.2, 37.6%) increase in HFRS at a lag of 0 week. A 1% increase in daily minimum relative humidity and a 1 mm increase in daily rainfall were associated with 4.0% (95% CI:1.8, 6.1) and 2.0% (95% CI: 1.2, 2.8%) increases in weekly leptospirosis cases at 11 and 6 weeks later, respectively. A 1 mJ/m 2 increase in daily solar radiation was associated with a 13.7% (95% CI: 4.9, 23.2%) increase in leptospirosis cases, maximized at a 2-week lag. During the peak season in Korea, climatic factors play a significant role in the development of HFRS and leptospirosis. The findings of this study may be applicable to the forecasting and prediction of disease outbreaks.

Session A-14: Variability of Storm Tracks Storm Tracks and Unseasonable Temperatures in Europe in December 2001

NASA Technical Reports Server (NTRS)

Przybylak, R.; Ardizzone, J.; Atlas, R.; Koslowsky, D.; Otterman, J.; Rogers, J.; Starr, D.; Atlas, Robert (Technical Monitor)

2002-01-01

In December 2001, a series of cyclonic centers progressed rapidly into Europe from the west and north. The cyclones moved in generally similar directions, along paths separated by few hundreds of kilometers. The advancing cyclones brought the usual sequence of changing wind directions and produced some high speed wind events. We investigate the wind patterns for this month based on analyses derived the Special Sensor Microwave/Imager observations and NCEP analyses. Whereas southwesterlies from the North Atlantic produced moderate temperatures early in the month, strong northerlies and northwesterlies (up to 15 m/s on 20-22 December) produced a drop in daily minimum and maximum temperatures of 18.8 C and 9.9 C, respectively, over a 4 day period (to -18.8 C and -6.8 C, respectively, on December 23 in Torun, Poland). Such low values in December are unprecedented in recent decades, though not for January or February.

Daytime warming has stronger negative effects on soil nematodes than night-time warming.

PubMed

Yan, Xiumin; Wang, Kehong; Song, Lihong; Wang, Xuefeng; Wu, Donghui

2017-03-07

Warming of the climate system is unequivocal, that is, stronger warming during night-time than during daytime. Here we focus on how soil nematodes respond to the current asymmetric warming. A field infrared heating experiment was performed in the western of the Songnen Plain, Northeast China. Three warming modes, i.e. daytime warming, night-time warming and diurnal warming, were taken to perform the asymmetric warming condition. Our results showed that the daytime and diurnal warming treatment significantly decreased soil nematodes density, and night-time warming treatment marginally affected the density. The response of bacterivorous nematode and fungivorous nematode to experimental warming showed the same trend with the total density. Redundancy analysis revealed an opposite effect of soil moisture and soil temperature, and the most important of soil moisture and temperature in night-time among the measured environment factors, affecting soil nematode community. Our findings suggested that daily minimum temperature and warming induced drying are most important factors affecting soil nematode community under the current global asymmetric warming.

Daytime warming has stronger negative effects on soil nematodes than night-time warming.

PubMed

Yan, Xiumin; Wang, Kehong; Song, Lihong; Wang, Xuefeng; Wu, Donghui

2017-03-20

Warming of the climate system is unequivocal, that is, stronger warming during night-time than during daytime. Here we focus on how soil nematodes respond to the current asymmetric warming. A field infrared heating experiment was performed in the western of the Songnen Plain, Northeast China. Three warming modes, i.e. daytime warming, night-time warming and diurnal warming, were taken to perform the asymmetric warming condition. Our results showed that the daytime and diurnal warming treatment significantly decreased soil nematodes density, and night-time warming treatment marginally affected the density. The response of bacterivorous nematode and fungivorous nematode to experimental warming showed the same trend with the total density. Redundancy analysis revealed an opposite effect of soil moisture and soil temperature, and the most important of soil moisture and temperature in night-time among the measured environment factors, affecting soil nematode community. Our findings suggested that daily minimum temperature and warming induced drying are most important factors affecting soil nematode community under the current global asymmetric warming.

How much have California winters warmed over the last century?

NASA Astrophysics Data System (ADS)

Wang, K. J.; Williams, A. P.; Lettenmaier, D. P.

2017-09-01

Extraordinarily warm 2013-2014 and 2014-2015 winter temperatures in California accompanied by drought conditions contributed to low snow accumulations and stressed water resources, giving rise to the question: how much has California's climate warmed over the last century? We examine long-term trends in maximum (Tmax) and minimum (Tmin) daily temperatures in winter estimated from five gridded data sets. Resulting trends show some consistent features, such as higher trends in Tmin than Tmax; however, substantial differences exist in the trend magnitudes and spatial patterns due mostly to the nature of spatial interpolation employed in the different data sets. Averaged across California over 1920-2015, Tmax trends vary from -0.30 to 1.2°C/century, while Tmin trends range from 1.2 to 1.9°C/century. The differences in temperature strongly impact modeled changes in snow water equivalent over the last century (from -5.0 to -7.6 km3/century).

Trends in extremes of temperature, dew point, and precipitation from long instrumental series from central Europe

NASA Astrophysics Data System (ADS)

Kürbis, K.; Mudelsee, M.; Tetzlaff, G.; Brázdil, R.

2009-09-01

For the analysis of trends in weather extremes, we introduce a diagnostic index variable, the exceedance product, which combines intensity and frequency of extremes. We separate trends in higher moments from trends in mean or standard deviation and use bootstrap resampling to evaluate statistical significances. The application of the concept of the exceedance product to daily meteorological time series from Potsdam (1893 to 2005) and Prague-Klementinum (1775 to 2004) reveals that extremely cold winters occurred only until the mid-20th century, whereas warm winters show upward trends. These changes were significant in higher moments of the temperature distribution. In contrast, trends in summer temperature extremes (e.g., the 2003 European heatwave) can be explained by linear changes in mean or standard deviation. While precipitation at Potsdam does not show pronounced trends, dew point does exhibit a change from maximum extremes during the 1960s to minimum extremes during the 1970s.

Daytime warming has stronger negative effects on soil nematodes than night-time warming

PubMed Central

Yan, Xiumin; Wang, Kehong; Song, Lihong; Wang, Xuefeng; Wu, Donghui

2017-01-01

Warming of the climate system is unequivocal, that is, stronger warming during night-time than during daytime. Here we focus on how soil nematodes respond to the current asymmetric warming. A field infrared heating experiment was performed in the western of the Songnen Plain, Northeast China. Three warming modes, i.e. daytime warming, night-time warming and diurnal warming, were taken to perform the asymmetric warming condition. Our results showed that the daytime and diurnal warming treatment significantly decreased soil nematodes density, and night-time warming treatment marginally affected the density. The response of bacterivorous nematode and fungivorous nematode to experimental warming showed the same trend with the total density. Redundancy analysis revealed an opposite effect of soil moisture and soil temperature, and the most important of soil moisture and temperature in night-time among the measured environment factors, affecting soil nematode community. Our findings suggested that daily minimum temperature and warming induced drying are most important factors affecting soil nematode community under the current global asymmetric warming. PMID:28317914

Daytime warming has stronger negative effects on soil nematodes than night-time warming

NASA Astrophysics Data System (ADS)

Yan, Xiumin; Wang, Kehong; Song, Lihong; Wang, Xuefeng; Wu, Donghui

2017-03-01

Warming of the climate system is unequivocal, that is, stronger warming during night-time than during daytime. Here we focus on how soil nematodes respond to the current asymmetric warming. A field infrared heating experiment was performed in the western of the Songnen Plain, Northeast China. Three warming modes, i.e. daytime warming, night-time warming and diurnal warming, were taken to perform the asymmetric warming condition. Our results showed that the daytime and diurnal warming treatment significantly decreased soil nematodes density, and night-time warming treatment marginally affected the density. The response of bacterivorous nematode and fungivorous nematode to experimental warming showed the same trend with the total density. Redundancy analysis revealed an opposite effect of soil moisture and soil temperature, and the most important of soil moisture and temperature in night-time among the measured environment factors, affecting soil nematode community. Our findings suggested that daily minimum temperature and warming induced drying are most important factors affecting soil nematode community under the current global asymmetric warming.

Severe European winters in a secular perspective

NASA Astrophysics Data System (ADS)

Hoy, Andreas; Hänsel, Stephanie

2017-04-01

Temperature conditions during the winter time are substantially shaped by a strong year-to-year variability. European winters since the late 1980s - compared to previous decades and centuries - were mainly characterised by a high temperature level, including recent record-warm winters. Yet, comparably cold winters and severe cold spells still occur nowadays, like recently observed from 2009 to 2013 and in early 2017. Central England experienced its second coldest December since start of observations more than 350 years ago in 2010, and some of the lowest temperatures ever measured in northern Europe (below -50 °C in Lapland) were recorded in January 1999. Analysing thermal characteristics and spatial distribution of severe (historical) winters - using early instrumental data - helps expanding and consolidating our knowledge of past weather extremes. This contribution presents efforts towards this direction. We focus on a) compiling and assessing a very long-term instrumental, spatially widespread and well-distributed, high-quality meteorological data set to b) investigate very cold winter temperatures in Europe from early measurements until today. In a first step, we analyse the longest available time series of monthly temperature averages within Europe. Our dataset extends from the Nordic countries up to the Mediterranean and from the British Isles up to Russia. We utilise as much as possible homogenised times series in order to ensure reliable results. Homogenised data derive from the NORDHOM (Scandinavia) and HISTALP (greater alpine region) datasets or were obtained from national weather services and universities. Other (not specifically homogenised) data were derived from the ECA&D dataset or national institutions. The employed time series often start already during the 18th century, with Paris & Central England being the longest datasets (from 1659). In a second step, daily temperature averages are involved. Only some of those series are homogenised, but those available are sufficiently distributed throughout Europe to ensure reliable results. Furthermore, the comparably dense network of long-term observations allows an appropriate quality checking within the network. Additionally, the large collective of homogenised monthly data enables assessing the quality of many daily series. Daily data are used to sum up negative values for the respective winter periods to create times series of "cold summations", which are a good indicator for the severeness of winters in most parts of Europe. Additionally, days below certain thresholds may be counted or summed up. Future work will include daily minimum and maximum temperatures, allowing calculating and applying an extensive set of climate indices, refining the work presented here.

40 CFR 60.37e - Compliance, performance testing, and monitoring guidelines.

Code of Federal Regulations, 2010 CFR

2010-07-01

... requirements: (1) Establish maximum charge rate and minimum secondary chamber temperature as site-specific... above the maximum charge rate or below the minimum secondary chamber temperature measured as 3-hour... below the minimum secondary chamber temperature shall constitute a violation of the established...

Design of landfill daily cells.

PubMed

Panagiotakopoulos, D; Dokas, I

2001-08-01

The objective of this paper is to study the behaviour of the landfill soil-to-refuse (S/R) ratio when size, geometry and operating parameters of the daily cell vary over realistic ranges. A simple procedure is presented (1) for calculating the cell parameters values which minimise the S/R ratio and (2) for studying the sensitivity of this minimum S/R ratio to variations in cell size, final refuse density, working face length, lift height and cover thickness. In countries where daily soil cover is required, savings in landfill space could be realised following this procedure. The sensitivity of minimum S/R to variations in cell dimensions decreases with cell size. Working face length and lift height affect the S/R ratio significantly. This procedure also offers the engineer an additional tool for comparing one large daily cell with two or more smaller ones, at two different working faces within the same landfill.

Temperature fine-tunes Mediterranean Arabidopsis thaliana life-cycle phenology geographically.

PubMed

Marcer, A; Vidigal, D S; James, P M A; Fortin, M-J; Méndez-Vigo, B; Hilhorst, H W M; Bentsink, L; Alonso-Blanco, C; Picó, F X

2018-01-01

To understand how adaptive evolution in life-cycle phenology operates in plants, we need to unravel the effects of geographic variation in putative agents of natural selection on life-cycle phenology by considering all key developmental transitions and their co-variation patterns. We address this goal by quantifying the temperature-driven and geographically varying relationship between seed dormancy and flowering time in the annual Arabidopsis thaliana across the Iberian Peninsula. We used data on genetic variation in two major life-cycle traits, seed dormancy (DSDS50) and flowering time (FT), in a collection of 300 A. thaliana accessions from the Iberian Peninsula. The geographically varying relationship between life-cycle traits and minimum temperature, a major driver of variation in DSDS50 and FT, was explored with geographically weighted regressions (GWR). The environmentally varying correlation between DSDS50 and FT was analysed by means of sliding window analysis across a minimum temperature gradient. Maximum local adjustments between minimum temperature and life-cycle traits were obtained in the southwest Iberian Peninsula, an area with the highest minimum temperatures. In contrast, in off-southwest locations, the effects of minimum temperature on DSDS50 were rather constant across the region, whereas those of minimum temperature on FT were more variable, with peaks of strong local adjustments of GWR models in central and northwest Spain. Sliding window analysis identified a minimum temperature turning point in the relationship between DSDS50 and FT around a minimum temperature of 7.2 °C. Above this minimum temperature turning point, the variation in the FT/DSDS50 ratio became rapidly constrained and the negative correlation between FT and DSDS50 did not increase any further with increasing minimum temperatures. The southwest Iberian Peninsula emerges as an area where variation in life-cycle phenology appears to be restricted by the duration and severity of the hot summer drought. The temperature-driven varying relationship between DSDS50 and FT detected environmental boundaries for the co-evolution between FT and DSDS50 in A. thaliana. In the context of global warming, we conclude that A. thaliana phenology from the southwest Iberian Peninsula, determined by early flowering and deep seed dormancy, might become the most common life-cycle phenotype for this annual plant in the region. © 2017 German Botanical Society and The Royal Botanical Society of the Netherlands.

Simulation of hydrodynamics, temperature, and dissolved oxygen in Beaver Lake, Arkansas, 1994-1995

USGS Publications Warehouse

Haggard, Brian; Green, W. Reed

2002-01-01

The tailwaters of Beaver Lake and other White River reservoirs support a cold-water trout fishery of significant economic yield in northwestern Arkansas. The Arkansas Game and Fish Commission has requested an increase in existing minimum flows through the Beaver Lake dam to increase the amount of fishable waters downstream. Information is needed to assess the impact of additional minimum flows on temperature and dissolved-oxygen qualities of reservoir water above the dam and the release water. A two-dimensional, laterally averaged hydrodynamic, thermal and dissolved-oxygen model was developed and calibrated for Beaver Lake, Arkansas. The model simulates surface-water elevation, currents, heat transport and dissolved-oxygen dynamics. The model was developed to assess the impacts of proposed increases in minimum flows from 1.76 cubic meters per second (the existing minimum flow) to 3.85 cubic meters per second (the additional minimum flow). Simulations included assessing (1) the impact of additional minimum flows on tailwater temperature and dissolved-oxygen quality and (2) increasing initial water-surface elevation 0.5 meter and assessing the impact of additional minimum flow on tailwater temperatures and dissolved-oxygen concentrations. The additional minimum flow simulation (without increasing initial pool elevation) appeared to increase the water temperature (<0.9 degrees Celsius) and decrease dissolved oxygen concentration (<2.2 milligrams per liter) in the outflow discharge. Conversely, the additional minimum flow plus initial increase in pool elevation (0.5 meter) simulation appeared to decrease outflow water temperature (0.5 degrees Celsius) and increase dissolved oxygen concentration (<1.2 milligrams per liter) through time. However, results from both minimum flow scenarios for both water temperature and dissolved oxygen concentration were within the boundaries or similar to the error between measured and simulated water column profile values.

Frost risk for overwintering crops in a changing climate

NASA Astrophysics Data System (ADS)

Vico, Giulia; Weih, Martin

2013-04-01

Climate change scenarios predict a general increase in daily temperatures and a decline in snow cover duration. On the one hand, higher temperature in fall and spring may facilitate the development of overwintering crops and allow the expansion of winter cropping in locations where the growing season is currently too short. On the other hand, higher temperatures prior to winter crop dormancy slow down frost hardening, enhancing crop vulnerability to temperature fluctuation. Such vulnerability may be exacerbated by reduced snow cover, with potential further negative impacts on yields in extremely low temperatures. We propose a parsimonious probabilistic model to quantify the winter frost damage risk for overwintering crops, based on a coupled model of air temperature, snow cover, and crop minimum tolerable temperature. The latter is determined by crop features, previous history of temperature, and snow cover. The temperature-snow cover model is tested against meteorological data collected over 50 years in Sweden and applied to winter wheat varieties differing in their ability to acquire frost resistance. Hence, exploiting experimental results assessing crop frost damage under limited temperature and snow cover realizations, this probabilistic framework allows the quantification of frost risk for different crop varieties, including in full temperature and precipitation unpredictability. Climate change scenarios are explored to quantify the effects of changes in temperature mean and variance and precipitation regime over crops differing in winter frost resistance and response to temperature.

Effect modification of the association between temperature variability and daily cardiovascular mortality by air pollutants in three Chinese cities.

PubMed

Luo, Kai; Li, Runkui; Wang, Zongshuang; Zhang, Ruiming; Xu, Qun

2017-11-01

There is limited evidence showing the mortality effects of temperature variability (TV) on cardiovascular diseases. The joint effects between TV and air pollutants are also less well-established. This study aims to assess the effect modification of TV-cardiovascular mortality by air pollutants in three Chinese cities (Beijing, Nanjing and Chengdu). Data of daily mortality, air pollutants and meteorological factors from 2008 to 2011 was collected from each city. TV was calculated as the standard deviation of daily maximum and minimum temperatures over exposure days. The city-specific effect estimates of TV on cardiovascular mortality were calculated using a quasi-Poisson regression model, adjusting for potential confounders (e.g., seasonality and temperature). An interaction term of TV and a three-level air pollutants stratum indicator was included in the models. Effect modifications by air pollutants were assessed by comparing the estimates of TV's effect between pollutant stratums and calculating the corresponding 95% confidential interval of the differences. Multivariate meta-analysis was conducted to obtain the pooled estimates. The data showed that TV was associated with increased risk of cardiovascular mortality, especially for longer TV exposure days (0-8 days, TV08). This association was still observed after adjusting for air pollutants on current day or the previous two days. Stronger estimates were observed in females, but no significant difference between males and females was detected, indicating the absence of evidence of effect modification by gender. Estimates of TV-cardiovascular mortality varied across two season periods (warm and cool season) and age groups, but the evidence of effect modification by age and seasons was absent. Regarding the effect modification of TV-cardiovascular mortality association by air pollutants, a significant effect modification was identified for PM 10, but not for NO 2 and SO 2 in the whole population for all TV exposure days. This finding also persisted in subgroups, specifically in females and the elderly. Copyright © 2017 Elsevier Ltd. All rights reserved.

Stochastic modelling of the monthly average maximum and minimum temperature patterns in India 1981-2015

NASA Astrophysics Data System (ADS)

Narasimha Murthy, K. V.; Saravana, R.; Vijaya Kumar, K.

2018-04-01

The paper investigates the stochastic modelling and forecasting of monthly average maximum and minimum temperature patterns through suitable seasonal auto regressive integrated moving average (SARIMA) model for the period 1981-2015 in India. The variations and distributions of monthly maximum and minimum temperatures are analyzed through Box plots and cumulative distribution functions. The time series plot indicates that the maximum temperature series contain sharp peaks in almost all the years, while it is not true for the minimum temperature series, so both the series are modelled separately. The possible SARIMA model has been chosen based on observing autocorrelation function (ACF), partial autocorrelation function (PACF), and inverse autocorrelation function (IACF) of the logarithmic transformed temperature series. The SARIMA (1, 0, 0) × (0, 1, 1)12 model is selected for monthly average maximum and minimum temperature series based on minimum Bayesian information criteria. The model parameters are obtained using maximum-likelihood method with the help of standard error of residuals. The adequacy of the selected model is determined using correlation diagnostic checking through ACF, PACF, IACF, and p values of Ljung-Box test statistic of residuals and using normal diagnostic checking through the kernel and normal density curves of histogram and Q-Q plot. Finally, the forecasting of monthly maximum and minimum temperature patterns of India for the next 3 years has been noticed with the help of selected model.

Extremely cold events and sudden air temperature drops during winter season in the Czech Republic

NASA Astrophysics Data System (ADS)

Crhová, Lenka; Valeriánová, Anna; Holtanová, Eva; Müller, Miloslav; Kašpar, Marek; Stříž, Martin

2014-05-01

Today a great attention is turned to analysis of extreme weather events and frequency of their occurrence under changing climate. In most cases, these studies are focused on extremely warm events in summer season. However, extremely low values of air temperature during winter can have serious impacts on many sectors as well (e.g. power engineering, transportation, industry, agriculture, human health). Therefore, in present contribution we focus on extremely and abnormally cold air temperature events in winter season in the Czech Republic. Besides the seasonal extremes of minimum air temperature determined from station data, the standardized data with removed annual cycle are used as well. Distribution of extremely cold events over the season and the temporal evolution of frequency of occurrence during the period 1961-2010 are analyzed. Furthermore, the connection of cold events with extreme sudden temperature drops is studied. The extreme air temperature events and events of extreme sudden temperature drop are assessed using the Weather Extremity Index, which evaluates the extremity (based on return periods) and spatial extent of the meteorological extreme event of interest. The generalized extreme value distribution parameters are used to estimate return periods of daily temperature values. The work has been supported by the grant P209/11/1990 funded by the Czech Science Foundation.

Climate and its change over the Tibetan Plateau and its Surroundings in 1963-2015

NASA Astrophysics Data System (ADS)

Ding, J.; Cuo, L.

2017-12-01

Tibetan Plateau and its surroundings (TPS, 23°-43°N, 73°-106°E) lies in the southwest of China and includes Tibet Autonomous Region, Qinghai Province, southern Xinjiang Uygur Autonomous Region, part of Gansu Province, western Sichuan Province, and northern Yunnan Province. The region is of strategic importance in water resources because it is the headwater of ten large rivers that support more than 16 billion population. In this study, we use daily temperature maximum and minimum, precipitation and wind speed in 1963-2015 obtained from Climate Data Center of China Meteorological Administration and Qinghai Meteorological Bureau to investigate extreme climate conditions and their changes over the TPS. The extreme events are selected based on annual extreme values and percentiles. Annual extreme value approach produces one value each year for all variables, which enables us to examine the magnitude of extreme events; whereas percentile approach selects extreme values by setting 95th percentile as thresholds for maximum temperature, precipitation and wind speed, and 5th percentile for minimum temperature. Percentile approach not only enables us to investigate the magnitude but also frequency of the extreme events. Also, Mann-Kendall trend and mutation analysis were applied to analyze the changes in mean and extreme conditions. The results will help us understand more about the extreme events during the past five decades on the TPS and will provide valuable information for the upcoming IPCC reports on climate change.

40 CFR Table 2 to Subpart Mmmmm of... - Operating Limits for New or Reconstructed Flame Lamination Affected Sources

Code of Federal Regulations, 2010 CFR

2010-07-01

... scrubber, maintain the daily average pressure drop across the venturi within the operating range value... . . . You must . . . 1. Scrubber a. Maintain the daily average scrubber inlet liquid flow rate above the minimum value established during the performance test. b. Maintain the daily average scrubber effluent pH...

40 CFR Table 2 to Subpart Mmmmm of... - Operating Limits for New or Reconstructed Flame Lamination Affected Sources

Code of Federal Regulations, 2011 CFR

2011-07-01

... . . . You must . . . 1. Scrubber a. Maintain the daily average scrubber inlet liquid flow rate above the minimum value established during the performance test. b. Maintain the daily average scrubber effluent pH... scrubber, maintain the daily average pressure drop across the venturi within the operating range value...

Elephant (Loxodonta africana) home ranges in Sabi Sand Reserve and Kruger National Park: a five-year satellite tracking study.

PubMed

Thomas, Bindi; Holland, John D; Minot, Edward O

2008-01-01

During a five-year GPS satellite tracking study in Sabi Sand Reserve (SSR) and Kruger National Park (KNP) we monitored the daily movements of an elephant cow (Loxodonta africana) from September 2003 to August 2008. The study animal was confirmed to be part of a group of seven elephants therefore her position is representative of the matriarchal group. We found that the study animal did not use habitat randomly and confirmed strong seasonal fidelity to its summer and winter five-year home ranges. The cow's summer home range was in KNP in an area more than four times that of her SSR winter home range. She exhibited clear park habitation with up to three visits per year travelling via a well-defined northern or southern corridor. There was a positive correlation between the daily distance the elephant walked and minimum daily temperature and the elephant was significantly closer to rivers and artificial waterholes than would be expected if it were moving randomly in KNP and SSR. Transect lines established through the home ranges were surveyed to further understand the fine scale of the landscape and vegetation representative of the home ranges.

Supporting Climatic Trends of Corn and Soybean Production in the USA

NASA Astrophysics Data System (ADS)

Mishra, V.; Cherkauer, K. A.; Verdin, J. P.

2010-12-01

The United States of America (USA) is a major source of corn and soybeans, producing about 39 percent of the world’s corn and 50 percent of world’s soybean supply. The north central states, including parts of the Midwestern US and the Great Plains form what is commonly described as the “Corn Belt” and consist of the most productive grain growing region in the United States. Changes in climate, including precipitation and temperature, are being observed throughout the world, and the Corn Belt region of the US is not immune posing a potential threat to global food security. We conducted a retrospective analysis of observed climate variables and crop production statistics to evaluate if observed climatic trends are having a positive or negative effect on corn and soybean production in the US. We selected climate indices based on gridded daily precipitation, maximum and minimum air temperature data from the National Climatic Data Center (NCDC) for the period of 1920-2009 and for 13 states in the Corn Belt region. We used the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) for different periods overlapping the important seasons for crop growths, such as the planting (April-May), grain-filling (June-August), and harvesting (September -October) seasons. We estimated the seasonal average of maximum and minimum daily temperatures to identify the historic trends and variability in air temperature during the key crop-growth seasons. Extreme warm temperatures can affect crop growth and yields adversely; therefore, cumulative maximum air temperature above the 90th percentiles (e.g. Cumulative Heat Index) was estimated for each growing period. We evaluated historic trends and variability of areal extents of severe or extreme droughts along with the areal extents facing the high cumulative heat stress. Our results showed that climatic extremes (e.g. droughts and heat stress) that occurred during the period of June - August (JJA), affected the yields of corn and soybeans most severely. High moisture and low heat stress during the JJA period favored crop yields, while low moisture and high heat conditions during the planting season (April-May) increased yields. Results also indicated that this part of the US is trending towards lower heat stress and drought extents, and higher moisture conditions during the JJA period. Therefore, in future, if the present trends persist, we expect the climate will more supportive of increased corn and soybean yields.

41 CFR 302-4.704 - Must we require a minimum driving distance per day?

Code of Federal Regulations, 2010 CFR

2010-07-01

... Federal Travel Regulation System RELOCATION ALLOWANCES PERMANENT CHANGE OF STATION (PCS) ALLOWANCES FOR... driving distance not less than an average of 300 miles per day. However, an exception to the daily minimum... reasons acceptable to you. ...

Application of thermal model for pan evaporation to the hydrology of a defined medium, the sponge

NASA Technical Reports Server (NTRS)

Trenchard, M. H.; Artley, J. A. (Principal Investigator)

1981-01-01

A technique is presented which estimates pan evaporation from the commonly observed values of daily maximum and minimum air temperatures. These two variables are transformed to saturation vapor pressure equivalents which are used in a simple linear regression model. The model provides reasonably accurate estimates of pan evaporation rates over a large geographic area. The derived evaporation algorithm is combined with precipitation to obtain a simple moisture variable. A hypothetical medium with a capacity of 8 inches of water is initialized at 4 inches. The medium behaves like a sponge: it absorbs all incident precipitation, with runoff or drainage occurring only after it is saturated. Water is lost from this simple system through evaporation just as from a Class A pan, but at a rate proportional to its degree of saturation. The contents of the sponge is a moisture index calculated from only the maximum and minium temperatures and precipitation.

Minimization of Food Cost on 2000-Calorie Diabetic Diet

NASA Astrophysics Data System (ADS)

Urrutia, J. D.; Mercado, J.; Tampis, R. L.

2017-03-01

This study focuses on minimization of food cost that satisfies the daily nutrients required based on 2000-calorie diet for a diabetic person. This paper attempts to provide a food combination that satisfies the daily nutrient requirements of a diabetic person and its lowest possible dietary food cost. A linear programming diet model is used to determine the cheapest combination of food items that satisfy the recommended daily nutritional requirements of the diabetic persons. According to the findings, a 50 year old and above diabetic male need to spend a minimum of 72.22 pesos for foods that satisfy the daily nutrients they need. In order to attain the minimum spending, the foods must consist of 60.49 grams of anchovy, 91.24 grams of carrot, 121.92 grams of durian, 121.41 grams of chicken egg, 70.82 grams of pork (lean), and 369.70 grams of rice (well-milled). For a 50 year old and above diabetic female, the minimum spending is 64.65 pesos per day and the food must consist of 75.87 grams of anchovy, 43.38 grams of carrot, 160.46 grams of durian, 69.66 grams of chicken egg, 23.16 grams of pork (lean) and 416.19 grams of rice (well-milled).

Continuity vs. the Crowd-Tradeoffs Between Continuous and Intermittent Citizen Hydrology Streamflow Observations.

PubMed

Davids, Jeffrey C; van de Giesen, Nick; Rutten, Martine

2017-07-01

Hydrologic data has traditionally been collected with permanent installations of sophisticated and accurate but expensive monitoring equipment at limited numbers of sites. Consequently, observation frequency and costs are high, but spatial coverage of the data is limited. Citizen Hydrology can possibly overcome these challenges by leveraging easily scaled mobile technology and local residents to collect hydrologic data at many sites. However, understanding of how decreased observational frequency impacts the accuracy of key streamflow statistics such as minimum flow, maximum flow, and runoff is limited. To evaluate this impact, we randomly selected 50 active United States Geological Survey streamflow gauges in California. We used 7 years of historical 15-min flow data from 2008 to 2014 to develop minimum flow, maximum flow, and runoff values for each gauge. To mimic lower frequency Citizen Hydrology observations, we developed a bootstrap randomized subsampling with replacement procedure. We calculated the same statistics, and their respective distributions, from 50 subsample iterations with four different subsampling frequencies ranging from daily to monthly. Minimum flows were estimated within 10% for half of the subsample iterations at 39 (daily) and 23 (monthly) of the 50 sites. However, maximum flows were estimated within 10% at only 7 (daily) and 0 (monthly) sites. Runoff volumes were estimated within 10% for half of the iterations at 44 (daily) and 12 (monthly) sites. Watershed flashiness most strongly impacted accuracy of minimum flow, maximum flow, and runoff estimates from subsampled data. Depending on the questions being asked, lower frequency Citizen Hydrology observations can provide useful hydrologic information.

Temperature dataloggers as stove use monitors (SUMs): Field methods and signal analysis

PubMed Central

Ruiz-Mercado, Ilse; Canuz, Eduardo; Smith, Kirk R.

2013-01-01

We report the field methodology of a 32-month monitoring study with temperature dataloggers as Stove Use Monitors (SUMs) to quantify usage of biomass cookstoves in 80 households of rural Guatemala. The SUMs were deployed in two stoves types: a well-operating chimney cookstove and the traditional open-cookfire. We recorded a total of 31,112 days from all chimney cookstoves, with a 10% data loss rate. To count meals and determine daily use of the stoves we implemented a peak selection algorithm based on the instantaneous derivatives and the statistical long-term behavior of the stove and ambient temperature signals. Positive peaks with onset and decay slopes exceeding predefined thresholds were identified as “fueling events”, the minimum unit of stove use. Adjacent fueling events detected within a fixed-time window were clustered in single “cooking events” or “meals”. The observed means of the population usage were: 89.4% days in use from all cookstoves and days monitored, 2.44 meals per day and 2.98 fueling events. We found that at this study site a single temperature threshold from the annual distribution of daily ambient temperatures was sufficient to differentiate days of use with 0.97 sensitivity and 0.95 specificity compared to the peak selection algorithm. With adequate placement, standardized data collection protocols and careful data management the SUMs can provide objective stove-use data with resolution, accuracy and level of detail not possible before. The SUMs enable unobtrusive monitoring of stove-use behavior and its systematic evaluation with stove performance parameters of air pollution, fuel consumption and climate-altering emissions. PMID:25225456

Daily reference crop evapotranspiration with reduced data sets in the humid environments of Azores islands using estimates of actual vapor pressure, solar radiation, and wind speed

NASA Astrophysics Data System (ADS)

Paredes, P.; Fontes, J. C.; Azevedo, E. B.; Pereira, L. S.

2017-11-01

Reference crop evapotranspiration (ETo) estimations using the FAO Penman-Monteith equation (PM-ETo) require a set of weather data including maximum and minimum air temperatures (T max, T min), actual vapor pressure (e a), solar radiation (R s), and wind speed (u 2). However, those data are often not available, or data sets are incomplete due to missing values. A set of procedures were proposed in FAO56 (Allen et al. 1998) to overcome these limitations, and which accuracy for estimating daily ETo in the humid climate of Azores islands is assessed in this study. Results show that after locally and seasonally calibrating the temperature adjustment factor a d used for dew point temperature (T dew) computation from mean temperature, ETo estimations shown small bias and small RMSE ranging from 0.15 to 0.53 mm day-1. When R s data are missing, their estimation from the temperature difference (T max-T min), using a locally and seasonal calibrated radiation adjustment coefficient (k Rs), yielded highly accurate ETo estimates, with RMSE averaging 0.41 mm day-1 and ranging from 0.33 to 0.58 mm day-1. If wind speed observations are missing, the use of the default u 2 = 2 m s-1, or 3 m s-1 in case of weather measurements over clipped grass in airports, revealed appropriated even for the windy locations (u 2 > 4 m s-1), with RMSE < 0.36 mm day-1. The appropriateness of procedure to estimating the missing values of e a, R s, and u 2 was confirmed.

Revisiting the extended spring indices using gridded weather data and machine learning

NASA Astrophysics Data System (ADS)

Mehdipoor, Hamed; Izquierdo-Verdiguier, Emma; Zurita-Milla, Raul

2016-04-01

The extended spring indices or SI-x [1] have been successfully used to predict the timing of spring onset at continental scales. The SI-x models were created by combining lilac and honeysuckle volunteered phenological observations, temperature data (from weather stations) and latitudinal information. More precisely, these models use a linear regression to predict the day of year of first leaf and first bloom for these two indicator species. In this contribution we revisit both the data and the method used to calibrate the SI-x models to check whether the addition of new input data or the use of non-linear regression methods could lead to improments in the model outputs. In particular, we use a recently published dataset [2] of volunteered observations on cloned and common lilac over longer period of time (1980-2014) and we replace the weather station data by 54 features derived from Daymet [3], which provides 1 by 1 km gridded estimates of daily weather parameters (maximum and minimum temperatures, precipitation, water vapor pressure, solar radiation, day length, snow water equivalent) for North America. These features consist of both daily weather values and their long- and short-term accumulations and elevation. we also replace the original linear regression by a non-linear method. Specifically, we use random forests to both identify the most important features and to predict the day of year of the first leaf of cloned and common lilacs. Preliminary results confirm the importance of the SI-x features (maximum and minimum temperatures and day length). However, our results show that snow water equivalent and water vapor pressure are also necessary to properly model leaf onset. Regarding the predictions, our results indicate that Random Forests yield comparable results to those produced by the SI-x models (in terms of root mean square error -RMSE). For cloned and common lilac, the models predict the day of year of leafing with 16 and 15 days of accuracy respectively. Further research should focus on extensively comparing the features used by both modelling approaches and on analyzing spring onset patterns over continental United States. References 1. Schwartz, M.D., T.R. Ault, and J.L. Betancourt, Spring onset variations and trends in the continental United States: past and regional assessment using temperature-based indices. International Journal of Climatology, 2013. 33(13): p. 2917-2922. 2. Rosemartin, A.H., et al., Lilac and honeysuckle phenology data 1956-2014. Scientific Data, 2015. 2: p. 150038. 3. Thornton, P.E., et al. Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 2. 2014.

Sampling biases in datasets of historical mean air temperature over land.

PubMed

Wang, Kaicun

2014-04-10

Global mean surface air temperature (Ta) has been reported to have risen by 0.74°C over the last 100 years. However, the definition of mean Ta is still a subject of debate. The most defensible definition might be the integral of the continuous temperature measurements over a day (Td0). However, for technological and historical reasons, mean Ta over land have been taken to be the average of the daily maximum and minimum temperature measurements (Td1). All existing principal global temperature analyses over land rely heavily on Td1. Here, I make a first quantitative assessment of the bias in the use of Td1 to estimate trends of mean Ta using hourly Ta observations at 5600 globally distributed weather stations from the 1970s to 2013. I find that the use of Td1 has a negligible impact on the global mean warming rate. However, the trend of Td1 has a substantial bias at regional and local scales, with a root mean square error of over 25% at 5° × 5° grids. Therefore, caution should be taken when using mean Ta datasets based on Td1 to examine high resolution details of warming trends.

Climatic and social risk factors for Aedes infestation in rural Thailand.

PubMed

Nagao, Yoshiro; Thavara, Usavadee; Chitnumsup, Pensri; Tawatsin, Apiwat; Chansang, Chitti; Campbell-Lendrum, Diarmid

2003-07-01

An intense epidemic of dengue haemorrhagic fever in 1998 prompted the Thai government to investigate the feasibility of focalized vector (Aedes aegypti) control programmes. We tested for correlations of three indices of Aedes larval abundance (housing index, container index and Breteau index) against 38 socio-economic and four climatic variables. Availability of public water wells, existence of transport services and proportion of tin houses were positively associated with larval indices. Private water wells, health education, health insurance coverage, thatched houses and use of firewood for cooking were negatively associated. These probably represent both direct effects on breeding sites (private vs. public wells decrease necessity to store water, and health education may encourage breeding site removal), and more general effects of health-related attitudes, housing quality and remoteness from urban areas. Indices were positively associated with daily minimum temperature, an increase in precipitation from the previous month (reflecting the onset of the rainy season) and daily maximum temperatures of approximately 33-34 degrees C. The associations were used to derive statistical models to predict the rank order of larval indices within the study area (Spearman's correlation coefficients = 0.525-0.554). The study provides a rational basis for identifying possible social interventions, and for prioritizing previously unsurveyed villages for further monitoring and focalized vector control.

Climate Prediction Center - Monitoring and Data - Regional Climate Maps:

Science.gov Websites

; Precipitation & Temperature > Regional Climate Maps: USA Menu Weekly 1-Month 3-Month 12-Month Weekly Total Precipitation Average Temperature Extreme Maximum Temperature Extreme Minimum Temperature Departure of Average Temperature from Normal Extreme Apparent Temperature Minimum Wind Chill Temperature

On the Trend of the Annual Mean, Maximum, and Minimum Temperature and the Diurnal Temperature Range in the Armagh Observatory, Northern Ireland, Dataset, 1844 -2012

NASA Technical Reports Server (NTRS)

Wilson, Robert M.

2013-01-01

Examined are the annual averages, 10-year moving averages, decadal averages, and sunspot cycle (SC) length averages of the mean, maximum, and minimum surface air temperatures and the diurnal temperature range (DTR) for the Armagh Observatory, Northern Ireland, during the interval 1844-2012. Strong upward trends are apparent in the Armagh surface-air temperatures (ASAT), while a strong downward trend is apparent in the DTR, especially when the ASAT data are averaged by decade or over individual SC lengths. The long-term decrease in the decadaland SC-averaged annual DTR occurs because the annual minimum temperatures have risen more quickly than the annual maximum temperatures. Estimates are given for the Armagh annual mean, maximum, and minimum temperatures and the DTR for the current decade (2010-2019) and SC24.

40 CFR 63.1257 - Test methods and compliance procedures.

Code of Federal Regulations, 2012 CFR

2012-07-01

...)(2), or 63.1256(h)(2)(i)(C) with a minimum residence time of 0.5 seconds and a minimum temperature of... temperature of the organic HAP, must consider the vent stream flow rate, and must establish the design minimum and average temperature in the combustion zone and the combustion zone residence time. (B) For a...

40 CFR 63.1257 - Test methods and compliance procedures.

Code of Federal Regulations, 2011 CFR

2011-07-01

...)(2), or 63.1256(h)(2)(i)(C) with a minimum residence time of 0.5 seconds and a minimum temperature of... temperature of the organic HAP, must consider the vent stream flow rate, and must establish the design minimum and average temperature in the combustion zone and the combustion zone residence time. (B) For a...

40 CFR 63.1257 - Test methods and compliance procedures.

Code of Federal Regulations, 2010 CFR

2010-07-01

...)(2), or 63.1256(h)(2)(i)(C) with a minimum residence time of 0.5 seconds and a minimum temperature of... temperature of the organic HAP, must consider the vent stream flow rate, and must establish the design minimum and average temperature in the combustion zone and the combustion zone residence time. (B) For a...

Changes in temperature and precipitation extremes observed in Modena, Italy

NASA Astrophysics Data System (ADS)

Boccolari, M.; Malmusi, S.

2013-03-01

Climate changes has become one of the most analysed subjects from researchers community, mainly because of the numerous extreme events that hit the globe. To have a better view of climate changes and trends, long observations time series are needed. During last decade a lot of Italian time series, concerning several surface meteorological variables, have been analysed and published. No one of them includes one of the longest record in Italy, the time series of the Geophysical Observatory of the University of Modena and Reggio Emilia. Measurements, collected since early 19th century, always in the same position, except for some months during the second world war, embrace daily temperature, precipitation amount, relative humidity, pressure, cloudiness and other variables. In this work we concentrated on the analysis of yearly and seasonal trends and climate extremes of temperature, both minimum and maximum, and precipitation time series, for the periods 1861-2010 and 1831-2010 respectively, in which continuous measurements are available. In general, our results confirm quite well those reported by IPCC and in many other studies over Mediterranean area. In particular, we found that minimum temperature has a non significant positive trend of + 0.1 °C per decade considering all the period, the value increases to 0.9 °C per decade for 1981-2010. For maximum temperature we observed a non significant + 0.1 °C trend for all the period, while + 0.8 °C for the last thirty years. On the other hand precipitation is decreasing, -6.3 mm per decade, considering all the analysed period, while the last thirty years are characterised by a great increment of 74.8 mm per decade. For both variables several climate indices have been analysed and they confirm what has been found for minimum and maximum temperatures and precipitation. In particular, during last 30 years frost days and ice days are decreasing, whereas summer days are increasing. During the last 30-year tropical nights and warm spell duration indices are characterised by a particular strong increment, if compared to the ones of the entire period. Finally, a cursory comparison between winter precipitation and NAO index was done, showing a high anti-correlation, especially since the second half of 20th century.

Exploring the spatio-temporal relationship between two key aeroallergens and meteorological variables in the United Kingdom

NASA Astrophysics Data System (ADS)

Khwarahm, Nabaz; Dash, Jadunandan; Atkinson, Peter M.; Newnham, R. M.; Skjøth, C. A.; Adams-Groom, B.; Caulton, Eric; Head, K.

2014-05-01

Constructing accurate predictive models for grass and birch pollen in the air, the two most important aeroallergens, for areas with variable climate conditions such as the United Kingdom, require better understanding of the relationships between pollen count in the air and meteorological variables. Variations in daily birch and grass pollen counts and their relationship with daily meteorological variables were investigated for nine pollen monitoring sites for the period 2000-2010 in the United Kingdom. An active pollen count sampling method was employed at each of the monitoring stations to sample pollen from the atmosphere. The mechanism of this method is based on the volumetric spore traps of Hirst design (Hirst in Ann Appl Biol 39(2):257-265, 1952). The pollen season (start date, finish date) for grass and birch were determined using a first derivative method. Meteorological variables such as daily rainfall; maximum, minimum and average temperatures; cumulative sum of Sunshine duration; wind speed; and relative humidity were related to the grass and birch pollen counts for the pre-peak, post peak and the entire pollen season. The meteorological variables were correlated with the pollen count data for the following temporal supports: same-day, 1-day prior, 1-day mean prior, 3-day mean prior, 7-day mean prior. The direction of influence (positive/negative) of meteorological variables on pollen count varied for birch and grass, and also varied when the pollen season was treated as a whole season, or was segmented into the pre-peak and post-peak seasons. Maximum temperature, sunshine duration and rainfall were the most important variables influencing the count of grass pollen in the atmosphere. Both maximum temperature (pre-peak) and sunshine produced a strong positive correlation, and rain produced a strong negative correlation with grass pollen count in the air. Similarly, average temperature, wind speed and rainfall were the most important variables influencing the count of birch pollen in the air. Both wind speed and rain produced a negative correlation with birch pollen count in the air and average temperature produced a positive correlation.

People as sensors: mass media and local temperature influence climate change discussion on Twitter

NASA Astrophysics Data System (ADS)

Kirilenko, A.; Molodtsova, T.; Stepchenkova, S.

2014-12-01

We examined whether people living under significant temperature anomalies connect their sensory experiences to climate change and the role that media plays in this process. We used Twitter messages containing words "climate change" and "global warming" as the indicator of attention that public pays to the issue. Specifically, the goals were: (1) to investigate whether people immediately notice significant local weather anomalies and connect them to climate change and (2) to examine the role of mass media in this process. Over 2 million tweets were collected for a two-year period (2012 - 2013) and were assigned to 157 urban areas in the continental USA (Figure 1). Geographical locations of the tweets were identified with a geolocation resolving algorithm based the profile of the users. Daily number of tweets (tweeting rate) was computed for 157 conterminous USA urban areas and adjusted for data acquisition errors. The USHCN daily minimum and maximum temperatures were obtained for the station locations closest to the centers of the urban areas and the 1981-2010 30-year temperature mean and standard deviation were used as the climate normals. For the analysis, we computed the following indices for each day of 2012 - 2013 period: standardized temperature anomaly, absolute standardized temperature anomaly, and extreme cold and hot temperature anomalies for each urban zone. The extreme cold and hot temperature anomalies were then transformed into country-level values that represent the number of people living in extreme temperature conditions. The rate of tweeting on climate change was regressed on the time variables, number of climate change publications in the mass media, and temperature. In the majority of regression models, the mass media and temperature variables were significant at the p<0.001 level. Additionally, we did not find convincing evidence that the media acts as a mediator in the relationship between local weather and climate change discourse intensity. Our analysis of Twitter data confirmed that the public is able to recognize extreme temperature anomalies and connects these anomalies to climate change. Finally, we demonstrated the utility of social network data for research on public climate change perception.

Spatial downscaling and correction of precipitation and temperature time series to high resolution hydrological response units in the Canadian Rocky Mountains

NASA Astrophysics Data System (ADS)

Kienzle, Stefan

2015-04-01

Precipitation is the central driving force of most hydrological processes, and is also the most variable element of the hydrological cycle. As the precipitation to runoff ratio is non-linear, errors in precipitation estimations are amplified in streamflow simulations. Therefore, the accurate estimate of areal precipitation is essential for watershed models and relevant impacts studies. A procedure is presented to demonstrate the spatial distribution of daily precipitation and temperature estimates across the Rocky Mountains within the framework of the ACRU agro-hydrological modelling system (ACRU). ACRU (Schulze, 1995) is a physical-conceptual, semi-distributed hydrological modelling system designed to be responsive to changes in land use and climate. The model has been updated to include specific high-mountain and cold climate routines and is applied to simulate impacts of land cover and climate change on the hydrological behaviour of numerous Rocky Mountain watersheds in Alberta, Canada. Both air temperature and precipitation time series need to be downscaled to hydrological response units (HRUs), as they are the spatial modelling units for the model. The estimation of accurate daily air temperatures is critical for the separation of rain and snow. The precipitation estimation procedure integrates a spatially distributed daily precipitation database for the period 1950 to 2010 at a scale of 10 by 10 km with a 1971-2000 climate normal database available at 2 by 2 km (PRISM). Resulting daily precipitation time series are further downscaled to the spatial resolution of hydrological response units, defined by 100 m elevation bands, land cover, and solar radiation, which have an average size of about 15 km2. As snow measurements are known to have a potential under-catch of up to 40%, further adjustment of snowfall may need to be increased using a procedure by Richter (1995). Finally, precipitation input to HRUs with slopes steeper than 10% need to be further corrected, because the true, sloped area, has a larger area than the planimetric area derived from a GIS. The omission of correcting for sloped areas would result in incorrect calculations of interception volumes, soil moisture storages, groundwater recharge rates, actual evapotranspiration volumes, and runoff coefficients. Daily minimum and maximum air temperatures are estimated for each HRU by downscaling the 10km time series to the HRUs by (a) applying monthly mean lapse rates, estimated either from surrounding climate stations or from the PRISM climate normal dataset in combination with a digital elevation model, (b) adjusting further for aspect of the HRU based on monthly mean incoming solar radiation, and (c) adjusting for canopy cover using the monthly mean leaf area indices. Precipitation estimates can be verified using independent snow water equivalent measurements derived from snow pillow or snow course observations, while temperature estimates are verified against either independent temperature measurements from climate stations, or from fire observation towers.

Estimation of minimum ventilation requirement of dairy cattle barns for different outdoor temperature and its affects on indoor temperature: Bursa case.

PubMed

Yaslioglu, Erkan; Simsek, Ercan; Kilic, Ilker

2007-04-15

In the study, 10 different dairy cattle barns with natural ventilation system were investigated in terms of structural aspects. VENTGRAPH software package was used to estimate minimum ventilation requirements for three different outdoor design temperatures (-3, 0 and 1.7 degrees C). Variation in indoor temperatures was also determined according to the above-mentioned conditions. In the investigated dairy cattle barns, on condition that minimum ventilation requirement to be achieved for -3, 0 and 1.7 degrees C outdoor design temperature and 70, 80% Indoor Relative Humidity (IRH), estimated indoor temperature were ranged from 2.2 to 12.2 degrees C for 70% IRH, 4.3 to 15.0 degrees C for 80% IRH. Barn type, outdoor design temperature and indoor relative humidity significantly (p < 0.01) affect the indoor temperature. The highest ventilation requirement was calculated for straw yard (13879 m3 h(-1)) while the lowest was estimated for tie-stall (6169.20 m3 h(-1)). Estimated minimum ventilation requirements per animal were significantly (p < 0.01) different according to the barn types. Effect of outdoor esign temperatures on minimum ventilation requirements and minimum ventilation requirements per animal was found to be significant (p < 0.05, p < 0.01). Estimated indoor temperatures were in thermoneutral zone (-2 to 20 degrees C). Therefore, one can be said that use of naturally ventilated cold dairy barns in the region will not lead to problems associated with animal comfort in winter.

Influence of meteorological conditions on RSV infection in Portugal

NASA Astrophysics Data System (ADS)

Oliveira-Santos, M.; Santos, J. A.; Soares, J.; Dias, A.; Quaresma, M.

2016-12-01

Acute viral bronchiolitis is a common cause for infant hospital admissions. Of all etiological agents, respiratory syncytial virus (RSV) is commonly the most frequent. The present study assesses relationships between atmospheric factors and RSV infections in under 3-year-old patients admitted to the Inpatient Paediatric Service of Vila Real (North of Portugal). For this purpose, (1) clinical files of children admitted with a diagnosis of acute bronchiolitis from September 2005 to December 2015 (>10 years) were scrutinised and (2) local daily temperature/precipitation series, as well as six weather types controlling meteorological conditions in Portugal, were used. Fifty-five percent of all 770 admitted children were effectively infected with a given virus, whilst 48 % (367) were RSV+, i.e. 87 % of virus-infected children were RSV+. The bulk of incidence is verified in the first year of age (82 %, 302), slightly higher in males. RSV outbreaks are typically from December to March, but important inter-annual variability is found in both magnitude and shape. Although no clear connections were found between monthly temperatures/precipitation and RSV outbreaks apart from seasonality, a linkage to wintertime cold spells is apparent on a daily basis. Anomalously low minimum temperatures from the day of admittance back to 10 days before are observed. This relationship is supported by anomalously high occurrences of the E and AA weather types over the same period, which usually trigger dry and cold weather. These findings highlight some predictability in the RSV occurrences, revealing potential for modelling and risk assessments.

The control of short-term feed intake by metabolic oxidation in late-pregnant and early lactating dairy cows exposed to high ambient temperatures.

PubMed

Eslamizad, Mehdi; Lamp, Ole; Derno, Michael; Kuhla, Björn

2015-06-01

The objective of the present study was to integrate the dynamics of feed intake and metabolic oxidation in late pregnant and early lactating Holstein cows under heat stress conditions. On day 21 before parturition and again on day 20 after parturition, seven Holstein cows were kept for 7days at thermoneutral (TN) conditions (15°C; temperature-humidity-index (THI)=60) followed by a 7day heat stress (HS) period at 28°C (THI=76). On the last day of each temperature condition, gas exchange, feed intake and water intake were recorded every 6min in a respiration chamber. Pre- and post-partum cows responded to HS by decreasing feed intake. The reduction in feed intake in pre-partum cows was achieved through decreased meal size, meal duration, eating rate and daily eating time with no change in meal frequency, while post-partum cows kept under HS conditions showed variable responses in feeding behavior. In both pre- and post-partum cows exposed to heat stress, daily and resting metabolic heat production decreased while the periprandial respiratory quotient (RQ) increased. The prolonged time between meal and the postprandial minimum in fat oxidation and the postprandial RQ maximum, respectively, revealed that HS as compared to TN early-lactating cows have slower postprandial fat oxidation, longer feed digestion, and thereby showing a shift from fat to glucose utilization. Copyright © 2015 Elsevier Inc. All rights reserved.

Cold episodes in the Peruvian Central Andes: Composites, Types, and their Impacts over South America (1958-2014)

NASA Astrophysics Data System (ADS)

Sulca, J. C.; Vuille, M. F.; Roundy, P. E.; Trasmonte, G.; Silva, Y.; Takahashi, K.

2015-12-01

The Mantaro basin (MB) is located in the central Peruvian Andes. Occasionally, cold episodes are observed during austral summer (January-March), that strongly damage crops. However, little is known about the causes and impacts of such cold episodes. The main goal of this study is thus to characterize cold episodes in the MB and assess their large-scale circulation and teleconnections over South America (SA) during austral summer. To identify cold events in the MB daily minimum temperature (Tmin) for the period 1958-2014 from Huayao station, located within the MB was used. A cold episode is defined when daily minimum temperature drops below its 10-percentile for at least one day. Additionally, to study the sensitivity between physical mechanisms associated with cold episodes and temperature, cold episodes are classified in three groups: Weak cold episodes (7.5 ≤ Tmin ≤ 10 percentile), strong cold episodes (Tmin ≤ 2.5 percentile), but excluding the 9 coldest events (Tmin ≤ 0 ͦ C), henceforth referred to as extraordinary cold episodes. Several gridded reanalysis were used to characterize the large-scale circulation, cloud cover and rainfall over SA associated with these events. Weak and strong cold episodes in the MB are mainly associated with a weakening of the Bolivian High-Nordeste Low system by tropical-extratropical interactions. Both types of cold episodes are associated with westerly wind anomalies at mid- and upper-tropospheric levels aloft the Peruvian Central Andes, which inhibit the influx of humid air masses from the lowlands to the east and hence limit the development of cloud cover (e.g., positive OLR anomalies over MB). The resulting clear sky conditions cause nighttime temperatures to drop, leading to cold extremes below 10-percentile. Simultaneously, northeastern Brazil (NEB) registers negative OLR anomalies, strong convection and enhanced cloud cover because displacement of the South Atlantic Convergence Zone (SACZ) toward the northeast of its climatologic position. By contrast, extraordinary cold episodes in the MB are associated with cold and dry polar air advection at all tropospheric levels toward the central Peruvian Andes. On interannual timescales, El Niño may limit the occurrence of all types of cold episodes in the MB through enhanced tropical tropospheric background warming.

How much complexity is warranted in a rainfall-runoff model? Findings obtained from symbolic regression, using Eureqa

NASA Astrophysics Data System (ADS)

Abrahart, R. J.; Beriro, D. J.

2012-04-01

The information content in a rainfall-runoff record is sufficient to support models of only very limited complexity (Jakeman and Hornberger, 1993). This begs the question of what limits should observed data place on the allowable complexity of rainfall-runoff models? Eureqa1 (Schmidt and Lipson, 2009) - pronounced "eureka" - is a software tool for finding equations and detecting mathematical relationships in a dataset. The challenge, for both software and modeller, is to identify, by means of symbolic regression, the simplest mathematical formulas which describe the underlying mechanisms that produced the data. It actually delivers, however, a series of preferred modelling solutions comprising one champion for each specific level of complexity i.e. related to solution enlargement involving the progressive incorporation of additional permitted factors (internal operators/ external drivers). The potential benefit of increased complexity can as a result be assessed in a rational manner. Eureqa is free to download and use; and, in the current study, has been employed to construct a set of rainfall-runoff transfer function models for the Annapolis River at Wilmot, in north-western Nova Scotia, Canada. The climatic conditions in this catchment present an interesting set of modelling challenges; daily variations and seasonal changes in temperature, snowfall and retention result in great difficulty for runoff prediction by means of a data-driven approach. Data from 10 years of daily observations are used in the present study (01/01/2000-31/12/2009): comprising [i] discharge, [ii] total rainfall (excluding snowfall), [iii] total snowfall, [iv] thickness of snow cover, and [v] maximum and [vi] minimum temperature. Precipitation occurs throughout the whole year being slightly lower during summer. Snowfall is common from November until April and rare hurricane weather may occur in autumn. The average maximum temperature is below 0 0C in January and February, but significant variation may result, producing milder weather and snowmelt throughout the winter. The average minimum temperature is below 0 0C during half of the year, such that freezing and melting occur frequently. The principal rainfall-runoff drivers are found to be lagged discharge and lagged precipitation, as expected. The complexity-accuracy trade-off, is nevertheless found to exhibit threshold behaviour, in which snow cover is eventually included at higher levels of complexity to account for multifaceted cold season processes.

Frost damage in citric and olive production as the result of climate degradation

NASA Astrophysics Data System (ADS)

Saa Requejo, A.; Díaz Alvarez, M. C.; Tarquis, A. M.; Burgaz Moreno, F.; Garcia Moreno, R.

2009-04-01

Low temperature is one of the chief limiting factors in plant distribution. Freezing temperature shortens the growing season and may lower the yield and quality of any number of fruit crops. Minimum temperatures records for the Spanish region of Murcia were studied as limiting factor in fruit production. An analysis of temperature series since 1935 showed that the range of the absolute minimum temperatures (Tmin) on frost days in the target year, namely -0.5 °C to -4.0°C, was statistically similar to the range recorded in 1993, while the mean minimum temperatures (tmin) were found to have risen. The historical series also showed the mean minimum temperatures (tmin) to have increased, however. Through 1985, tmin ranged from 4.0 to -2.0 °C, depending on the area, while these limits shifted in more recent years to 7.0 - 0.5 °C. This increase in mean temperature produced that the frost episodes in March 2004 was considered by lemon, mandarin and olive producers as the worst in many years for frost damage since the minimum temperature was reached in a more sensitive phenological stage, despite the statistical evidence that similar freezing temperatures had been reached on similar dates in other years.

Urbanisation induces early flowering: evidence from Platanus acerifolia and Prunus cerasus

NASA Astrophysics Data System (ADS)

Mimet, A.; Pellissier, V.; Quénol, H.; Aguejdad, R.; Dubreuil, V.; Rozé, F.

2009-05-01

The effect of towns on plant phenology, i.e. advancement of spring development compared with a rural environment, via the urban heat island (UHI) phenomenon, has been shown for many towns in many countries. This work combines experimental and observational methodology to provide a better and deeper view of climatic habitat in an urban context with a view to understanding the relationship between plant development and urban climate on the intra-urban scale (by taking into account town structure). A dense network of 17 meteorological stations was set up in Rennes, France, enabling us to identify and quantify climatic changes associated with the UHI. Meanwhile, phenological observations were made during early spring (March and April) in 2005 on Platanus acerifolia and Prunus cerasus to study the relationship between climatic and phenological data. The results show that there is both a climatic gradient and a developmental gradient corresponding to the type of urbanisation in the town of Rennes. The town influences plant phenology by reducing the diurnal temperature range and by increasing the minimum temperature as one approaches the town centre. The influence of ground cover type (plants or buildings) on development is also shown. The developmental phases of preflowering and flowering are influenced to differing extents by climatic variables. The period during which climatic variables are effective before a given developmental phase varies considerably. The preflowering phases are best correlated with the mean of the minimum air temperature for the 15-day period before the observation, whereas flowering appears to be more dependent on the mean of the daily diurnal temperature range for the 8 days preceding the observation.

Developing a phenological model for grapevine to assess future frost risk in Luxembourg

NASA Astrophysics Data System (ADS)

Caffarra, A.; Molitor, D.; Pertot, I.; Sinigoy, P.; Junk, J.

2012-04-01

Late frost damage represents a significant hazard to grape production in cool climate viticulture regions such as Luxembourg. The main aim of our study is to analyze the frequency of these events for the Luxembourg's winegrowing region in the future. Spring frost injuries on grape may occur when young green parts are exposed to air temperature below 0°C. The potential risk is determined by: (i) minimum air temperature conditions and the (ii) the timing of bud burst. Therefore, we developed and validated a model for budburst of the grapevine (*Vitis vinifera)* cultivar Rivaner, the most grown local variety, based on multi-annual data from 7 different sites across Europe and the US. An advantage of this approach is, that it could be applied to a wide range of climate conditions. Higher spring temperatures were projected for the future and could lead to earlier dates of budburst as well as earlier dates of last frost events in the season. However, so far it is unknown if this will increase or decrease the risk of severe late frost damages for Luxembourg's winegrowing region. To address this question results of 10 regional climate change projections from the FP6 ENSEMBLES project (spatial resolution = 25km; A1B emission scenario) were combined with the new bud burst model. The use of a multi model ensemble of climate change projections allows for a better quantification of the uncertainties. A bias corrections scheme, based on local observations, was applied to the model output. Projected daily minimum air temperatures, up to 2098, were compared to the projected date of bud burst in order to quantify the future frost risk for Luxembourg.

Urbanisation induces early flowering: evidence from Platanus acerifolia and Prunus cerasus.

PubMed

Mimet, A; Pellissier, V; Quénol, H; Aguejdad, R; Dubreuil, V; Rozé, F

2009-05-01

The effect of towns on plant phenology, i.e. advancement of spring development compared with a rural environment, via the urban heat island (UHI) phenomenon, has been shown for many towns in many countries. This work combines experimental and observational methodology to provide a better and deeper view of climatic habitat in an urban context with a view to understanding the relationship between plant development and urban climate on the intra-urban scale (by taking into account town structure). A dense network of 17 meteorological stations was set up in Rennes, France, enabling us to identify and quantify climatic changes associated with the UHI. Meanwhile, phenological observations were made during early spring (March and April) in 2005 on Platanus acerifolia and Prunus cerasus to study the relationship between climatic and phenological data. The results show that there is both a climatic gradient and a developmental gradient corresponding to the type of urbanisation in the town of Rennes. The town influences plant phenology by reducing the diurnal temperature range and by increasing the minimum temperature as one approaches the town centre. The influence of ground cover type (plants or buildings) on development is also shown. The developmental phases of preflowering and flowering are influenced to differing extents by climatic variables. The period during which climatic variables are effective before a given developmental phase varies considerably. The preflowering phases are best correlated with the mean of the minimum air temperature for the 15-day period before the observation, whereas flowering appears to be more dependent on the mean of the daily diurnal temperature range for the 8 days preceding the observation.

Assessing the accuracy of ANFIS, EEMD-GRNN, PCR, and MLR models in predicting PM2.5

NASA Astrophysics Data System (ADS)

Ausati, Shadi; Amanollahi, Jamil

2016-10-01

Since Sanandaj is considered one of polluted cities of Iran, prediction of any type of pollution especially prediction of suspended particles of PM2.5, which are the cause of many diseases, could contribute to health of society by timely announcements and prior to increase of PM2.5. In order to predict PM2.5 concentration in the Sanandaj air the hybrid models consisting of an ensemble empirical mode decomposition and general regression neural network (EEMD-GRNN), Adaptive Neuro-Fuzzy Inference System (ANFIS), principal component regression (PCR), and linear model such as multiple liner regression (MLR) model were used. In these models the data of suspended particles of PM2.5 were the dependent variable and the data related to air quality including PM2.5, PM10, SO2, NO2, CO, O3 and meteorological data including average minimum temperature (Min T), average maximum temperature (Max T), average atmospheric pressure (AP), daily total precipitation (TP), daily relative humidity level of the air (RH) and daily wind speed (WS) for the year 2014 in Sanandaj were the independent variables. Among the used models, EEMD-GRNN model with values of R2 = 0.90, root mean square error (RMSE) = 4.9218 and mean absolute error (MAE) = 3.4644 in the training phase and with values of R2 = 0.79, RMSE = 5.0324 and MAE = 3.2565 in the testing phase, exhibited the best function in predicting this phenomenon. It can be concluded that hybrid models have accurate results to predict PM2.5 concentration compared with linear model.

A generalized conditional heteroscedastic model for temperature downscaling

NASA Astrophysics Data System (ADS)

Modarres, R.; Ouarda, T. B. M. J.

2014-11-01

This study describes a method for deriving the time varying second order moment, or heteroscedasticity, of local daily temperature and its association to large Coupled Canadian General Circulation Models predictors. This is carried out by applying a multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) approach to construct the conditional variance-covariance structure between General Circulation Models (GCMs) predictors and maximum and minimum temperature time series during 1980-2000. Two MGARCH specifications namely diagonal VECH and dynamic conditional correlation (DCC) are applied and 25 GCM predictors were selected for a bivariate temperature heteroscedastic modeling. It is observed that the conditional covariance between predictors and temperature is not very strong and mostly depends on the interaction between the random process governing temporal variation of predictors and predictants. The DCC model reveals a time varying conditional correlation between GCM predictors and temperature time series. No remarkable increasing or decreasing change is observed for correlation coefficients between GCM predictors and observed temperature during 1980-2000 while weak winter-summer seasonality is clear for both conditional covariance and correlation. Furthermore, the stationarity and nonlinearity Kwiatkowski-Phillips-Schmidt-Shin (KPSS) and Brock-Dechert-Scheinkman (BDS) tests showed that GCM predictors, temperature and their conditional correlation time series are nonlinear but stationary during 1980-2000 according to BDS and KPSS test results. However, the degree of nonlinearity of temperature time series is higher than most of the GCM predictors.

40 CFR 90.508 - Test procedures.

Code of Federal Regulations, 2010 CFR

2010-07-01

... service or target is less than the minimum rate specified (12 hours per day), then the minimum daily accumulation rate shall be equal to the manufacturer's service target. (3) Service accumulation shall be... nonroad engine sales for the United States market for the applicable year of 7,500 or greater shall...

The Short-Term Effect of Ambient Temperature on Mortality in Wuhan, China: A Time-Series Study Using a Distributed Lag Non-Linear Model

PubMed Central

Zhang, Yunquan; Li, Cunlu; Feng, Renjie; Zhu, Yaohui; Wu, Kai; Tan, Xiaodong; Ma, Lu

2016-01-01

Less evidence concerning the association between ambient temperature and mortality is available in developing countries/regions, especially inland areas of China, and few previous studies have compared the predictive ability of different temperature indictors (minimum, mean, and maximum temperature) on mortality. We assessed the effects of temperature on daily mortality from 2003 to 2010 in Jiang’an District of Wuhan, the largest city in central China. Quasi-Poisson generalized linear models combined with both non-threshold and double-threshold distributed lag non-linear models (DLNM) were used to examine the associations between different temperature indictors and cause-specific mortality. We found a U-shaped relationship between temperature and mortality in Wuhan. Double-threshold DLNM with mean temperature performed best in predicting temperature-mortality relationship. Cold effect was delayed, whereas hot effect was acute, both of which lasted for several days. For cold effects over lag 0–21 days, a 1 °C decrease in mean temperature below the cold thresholds was associated with a 2.39% (95% CI: 1.71, 3.08) increase in non-accidental mortality, 3.65% (95% CI: 2.62, 4.69) increase in cardiovascular mortality, 3.87% (95% CI: 1.57, 6.22) increase in respiratory mortality, 3.13% (95% CI: 1.88, 4.38) increase in stroke mortality, and 21.57% (95% CI: 12.59, 31.26) increase in ischemic heart disease (IHD) mortality. For hot effects over lag 0–7 days, a 1 °C increase in mean temperature above the hot thresholds was associated with a 25.18% (95% CI: 18.74, 31.96) increase in non-accidental mortality, 34.10% (95% CI: 25.63, 43.16) increase in cardiovascular mortality, 24.27% (95% CI: 7.55, 43.59) increase in respiratory mortality, 59.1% (95% CI: 41.81, 78.5) increase in stroke mortality, and 17.00% (95% CI: 7.91, 26.87) increase in IHD mortality. This study suggested that both low and high temperature were associated with increased mortality in Wuhan, and that mean temperature had better predictive ability than minimum and maximum temperature in the association between temperature and mortality. PMID:27438847

Some Advances in Downscaling Probabilistic Climate Forecasts for Agricultural Decision Support

NASA Astrophysics Data System (ADS)

Han, E.; Ines, A.

2015-12-01

Seasonal climate forecasts, commonly provided in tercile-probabilities format (below-, near- and above-normal), need to be translated into more meaningful information for decision support of practitioners in agriculture. In this paper, we will present two new novel approaches to temporally downscale probabilistic seasonal climate forecasts: one non-parametric and another parametric method. First, the non-parametric downscaling approach called FResampler1 uses the concept of 'conditional block sampling' of weather data to create daily weather realizations of a tercile-based seasonal climate forecasts. FResampler1 randomly draws time series of daily weather parameters (e.g., rainfall, maximum and minimum temperature and solar radiation) from historical records, for the season of interest from years that belong to a certain rainfall tercile category (e.g., being below-, near- and above-normal). In this way, FResampler1 preserves the covariance between rainfall and other weather parameters as if conditionally sampling maximum and minimum temperature and solar radiation if that day is wet or dry. The second approach called predictWTD is a parametric method based on a conditional stochastic weather generator. The tercile-based seasonal climate forecast is converted into a theoretical forecast cumulative probability curve. Then the deviates for each percentile is converted into rainfall amount or frequency or intensity to downscale the 'full' distribution of probabilistic seasonal climate forecasts. Those seasonal deviates are then disaggregated on a monthly basis and used to constrain the downscaling of forecast realizations at different percentile values of the theoretical forecast curve. As well as the theoretical basis of the approaches we will discuss sensitivity analysis (length of data and size of samples) of them. In addition their potential applications for managing climate-related risks in agriculture will be shown through a couple of case studies based on actual seasonal climate forecasts for: rice cropping in the Philippines and maize cropping in India and Kenya.

Soil and air temperatures for different habitats in Mount Rainier National Park.

Treesearch

Sarah E. Greene; Mark Klopsch

1985-01-01

This paper reports air and soil temperature data from 10 sites in Mount Rainier National Park in Washington State for 2- to 5-year periods. Data provided are monthly summaries for day and night mean air temperatures, mean minimum and maximum air temperatures, absolute minimum and maximum air temperatures, range of air temperatures, mean soil temperature, and absolute...

Simulation of hydrodynamics, temperature, and dissolved oxygen in Table Rock Lake, Missouri, 1996-1997

USGS Publications Warehouse

Green, W. Reed; Galloway, Joel M.; Richards, Joseph M.; Wesolowski, Edwin A.

2003-01-01

Outflow from Table Rock Lake and other White River reservoirs support a cold-water trout fishery of substantial economic yield in south-central Missouri and north-central Arkansas. The Missouri Department of Conservation has requested an increase in existing minimum flows through the Table Rock Lake Dam from the U.S. Army Corps of Engineers to increase the quality of fishable waters downstream in Lake Taneycomo. Information is needed to assess the effect of increased minimum flows on temperature and dissolved- oxygen concentrations of reservoir water and the outflow. A two-dimensional, laterally averaged, hydrodynamic, temperature, and dissolved-oxygen model, CE-QUAL-W2, was developed and calibrated for Table Rock Lake, located in Missouri, north of the Arkansas-Missouri State line. The model simulates water-surface elevation, heat transport, and dissolved-oxygen dynamics. The model was developed to assess the effects of proposed increases in minimum flow from about 4.4 cubic meters per second (the existing minimum flow) to 11.3 cubic meters per second (the increased minimum flow). Simulations included assessing the effect of (1) increased minimum flows and (2) increased minimum flows with increased water-surface elevations in Table Rock Lake, on outflow temperatures and dissolved-oxygen concentrations. In both minimum flow scenarios, water temperature appeared to stay the same or increase slightly (less than 0.37 ?C) and dissolved oxygen appeared to decrease slightly (less than 0.78 mg/L) in the outflow during the thermal stratification season. However, differences between the minimum flow scenarios for water temperature and dissolved- oxygen concentration and the calibrated model were similar to the differences between measured and simulated water-column profile values.

On pressure measurement and seasonal pressure variations during the Phoenix mission

NASA Astrophysics Data System (ADS)

Taylor, Peter A.; Kahanpää, Henrik; Weng, Wensong; Akingunola, Ayodeji; Cook, Clive; Daly, Mike; Dickinson, Cameron; Harri, Ari-Matti; Hill, Darren; Hipkin, Victoria; Polkko, Jouni; Whiteway, Jim

2010-03-01

In situ surface pressures measured at 2 s intervals during the 150 sol Phoenix mission are presented and seasonal variations discussed. The lightweight Barocap®/Thermocap® pressure sensor system performed moderately well. However, the original data processing routine had problems because the thermal environment of the sensor was subject to more rapid variations than had been expected. Hence, the data processing routine was updated after Phoenix landed. Further evaluation and the development of a correction are needed since the temperature dependences of the Barocap sensor heads have drifted after the calibration of the sensor. The inaccuracy caused by this appears when the temperature of the unit rises above 0°C. This frequently affects data in the afternoons and precludes a full study of diurnal pressure variations at this time. Short-term fluctuations, on time scales of order 20 s are unaffected and are reported in a separate paper in this issue. Seasonal variations are not significantly affected by this problem and show general agreement with previous measurements from Mars. During the 151 sol mission the surface pressure dropped from around 860 Pa to a minimum (daily average) of 724 Pa on sol 140 (Ls 143). This local minimum occurred several sols earlier than expected based on GCM studies and Viking data. Since battery power was lost on sol 151 we are not sure if the timing of the minimum that we saw could have been advanced by a low-pressure meteorological event. On sol 95 (Ls 122), we also saw a relatively low-pressure feature. This was accompanied by a large number of vertical vortex events, characterized by short, localized (in time), low-pressure perturbations.

Assessing the vulnerability of the transportation industry of Ukraine to future climate change

NASA Astrophysics Data System (ADS)

Khomenko, Inna

2017-04-01

Climate change will affect transportation primarily through increases in several types of weather and climate extremes. The impacts will vary by mode of transportation and region of the country, but they will be widespread and costly in both human and economic terms and will require significant changes in the planning, design, construction, operation, and maintenance of transportation systems. In the study impact of climate change on operation of road transport are analysed on the basis of RCP 4.5 and RCP 8.5 scenarios. Data contains series of daily mean, maximum and minimum temperature, daily liquid (or mixed) and solid precipitation, daily mean relative humidity and daily mean and maximum wind speed, obtained for the period of 2011 to 2050 for 28 cities distributed evenly across Ukraine. Spatial and temporal distributions of meteorological variables are obtained. The statistic characteristics obtained were compared with the correspondent climate normals and highway-related temporal changeability is determined. Frequency of freezing rain, wet snow, very hot days, droughts, fogs, ice-covered ground, slippery wet ground, ice and snow slippery coat are investigated. Climate and economic risks to the road transport network are assessed. Maps of spatial distribution of risk assessment are obtained. The results obtained show typical weather pattern is changed and climate and weather extreme influencing on operation of road transport are more frequent for the both scenarios, but for the RCP 8.5 scenario hazard weather occurs more often. During the period of 2011-2050 significant climate warming (by 2-3°C) is registered. Extreme temperatures are observed more frequently. High temperatures bring on growth in frequency of wildfires and heat waves. Annual precipitation amount decreases, except the western mountain and northern regions, where precipitation amount increase on 35%. Increase in temperature and decrease in precipitation can produce droughts in southern, eastern and central regions. But growth in precipitation in mountain region can cause flooding and landslides. Strong increase in mixed precipitation and significant reduction in ice and liquid precipitation take place for all territory of Ukraine. In the southern region ice precipitation is virtually vanished and observed only 2-3 days per year. Growth of mixed precipitation causes increase in severe weather events such as freezing precipitation, ice-covered ground and snow slippery coat.

Adverse Climatic Conditions and Impact on Construction Scheduling and Cost

DTIC Science & Technology

1988-01-01

ABBREVIATIONS ABS MAX MAX TEMP ...... Absolute maximum maximum temperature ABS MIN MIN TEMP ...... Absolute minimum minimum temperature BTU...o Degrees Farenheit MEAN MAX TEMP o.................... Mean maximum temperature MEAN MIN TEMP...temperatures available, a determination had to be made as to whether forecasts were based on absolute , mean, or statistically derived temperatures

Dynamic temperature fields under Mars landing sites and implications for supporting microbial life.

PubMed

Ulrich, Richard; Kral, Tim; Chevrier, Vincent; Pilgrim, Robert; Roe, Larry

2010-01-01

While average temperatures on Mars may be too low to support terrestrial life-forms or aqueous liquids, diurnal peak temperatures over most of the planet can be high enough to provide for both, down to a few centimeters beneath the surface for some fraction of the time. A thermal model was applied to the Viking 1, Viking 2, Pathfinder, Spirit, and Opportunity landing sites to demonstrate the dynamic temperature fields under the surface at these well-characterized locations. A benchmark temperature of 253 K was used as a lower limit for possible metabolic activity, which corresponds to the minimum found for specific terrestrial microorganisms. Aqueous solutions of salts known to exist on Mars can provide liquid solutions well below this temperature. Thermal modeling has shown that 253 K is reached beneath the surface at diurnal peak heating for at least some parts of the year at each of these landing sites. Within 40 degrees of the equator, 253 K beneath the surface should occur for at least some fraction of the year; and, within 20 degrees , it will be seen for most of the year. However, any life-form that requires this temperature to thrive must also endure daily excursions to far colder temperatures as well as periods of the year where 253 K is never reached at all.

Effect of clothing weight on body weight.

PubMed

Whigham, L D; Schoeller, D A; Johnson, L K; Atkinson, R L

2013-01-01

In clinical settings, it is common to measure weight of clothed patients and estimate a correction for the weight of clothing, but we can find no papers in the medical literature regarding the variability in clothing weight of adults with weather, season and gender. Fifty adults (35 women) were weighed four times during a 12-month period with and without clothing. Clothing weights were determined and regressed against minimum, maximum and average daily outdoor temperature. The average clothing weight (±s.d.) throughout the year was significantly greater in men than in women (1.2±0.3 vs 0.8±0.3 kg, P<0.0001). The average within-person minimum and the average within-person maximum clothing weights across the year were 0.9±0.2 and 1.5±0.4 kg for men, and 0.5±0.2 and 1.1±0.4 kg for women, respectively. The within-person s.d. in clothing weight was 0.3 kg for both men and women. Over the 55 °C range in the lowest to the highest outdoor temperatures, the regressions predicted a maximal change in clothing weight of only 0.4 kg in women and 0.6 kg in men. The clothing weight of men is significantly greater than that of women, but there is little variability throughout the year. Therefore, a clothing adjustment of approximately 0.8 kg for women and 1.2 kg for men is appropriate regardless of outdoor temperature.

Sahelian springtime heat waves and their evolution over the past 60 years

NASA Astrophysics Data System (ADS)

Barbier, Jessica; Guichard, Françoise; Bouniol, Dominique; Couvreux, Fleur; Roehrig, Romain

2017-04-01

The Sahel is a semi-arid region which experiences very high temperature both during day- and night-times: monthly-mean temperatures in Spring typically oscillate between 30 and 40°C. At the same time a strong climatic warming has been observed over the past 60 years in this region: it reaches +1,5°C over April-May. Thus heat waves in this region have severe impacts on health, ecosystem, agriculture and more broadly economical activities, which will probably worsen in the context of climate change. However, heat waves in the Sahel remain poorly studied. The present work documents Sahelian heat waves and assesses their evolution across the last 60 years. Properties of heat waves are sensitive to the way they are detected. Here, we use a methodology based on anomalies that allows to filter the seasonal, inter-annual and climatic evolutions, using a percentile-type threshold. It is applied separately to daily maximum and minimum temperatures and leads to two types of heat waves: day- and night-time ones. This separation matters because physical processes linked to minimum and maximum temperatures can be quite distinct. The changes in both types of heat wave were studied over the period 1950-2012 using the Berkeley Earth Surface Temperature gridded product: several heat wave characteristics were investigated, including morphological ones such as the length and the spatial extent of the event, the heat wave intensity and the associated warming trends. We found no significant trends in the frequency, duration and spatial extent of both types of heat waves, while on the other hand their maximum and minimum temperatures displayed significant positive trends. They were mainly explained by the regional warming. By contrast, with a standard climatic heat index using percentile-threshold on raw temperatures, both day- and night-time heat wave frequencies were increasing, and while the day-time heat waves were getting longer and larger, the night-time heat waves were getting hotter. The explanations for the differences between the heat indexes will be discussed. The ability of the three reanalyses ERA-Interim, NCEP2 and MERRA to reproduce Sahelian heat wave properties and their associated trends was further assessed on the period 1979-2010. At this shorter scale, we did not find any significant heat wave trend. Furthermore, reanalyses strongly differed in the representation of the heat wave inter-annual variability. These results raise concern about the utilization of meteorological reanalyses for the study of heat wave trends in West Africa.

Artificial neural network model of the relationship between Betula pollen and meteorological factors in Szczecin (Poland)

NASA Astrophysics Data System (ADS)

Puc, Małgorzata

2012-03-01

Birch pollen is one of the main causes of allergy during spring and early summer in northern and central Europe. The aim of this study was to create a forecast model that can accurately predict daily average concentrations of Betula sp. pollen grains in the atmosphere of Szczecin, Poland. In order to achieve this, a novel data analysis technique—artificial neural networks (ANN)—was used. Sampling was carried out using a volumetric spore trap of the Hirst design in Szczecin during 2003-2009. Spearman's rank correlation analysis revealed that humidity had a strong negative correlation with Betula pollen concentrations. Significant positive correlations were observed for maximum temperature, average temperature, minimum temperature and precipitation. The ANN resulted in multilayer perceptrons 366 8: 2928-7-1:1, time series prediction was of quite high accuracy (SD Ratio between 0.3 and 0.5, R > 0.85). Direct comparison of the observed and calculated values confirmed good performance of the model and its ability to recreate most of the variation.

Predictive modeling of mosquito abundance and dengue transmission in Kenya

NASA Astrophysics Data System (ADS)

Caldwell, J.; Krystosik, A.; Mutuku, F.; Ndenga, B.; LaBeaud, D.; Mordecai, E.

2017-12-01

Approximately 390 million people are exposed to dengue virus every year, and with no widely available treatments or vaccines, predictive models of disease risk are valuable tools for vector control and disease prevention. The aim of this study was to modify and improve climate-driven predictive models of dengue vector abundance (Aedes spp. mosquitoes) and viral transmission to people in Kenya. We simulated disease transmission using a temperature-driven mechanistic model and compared model predictions with vector trap data for larvae, pupae, and adult mosquitoes collected between 2014 and 2017 at four sites across urban and rural villages in Kenya. We tested predictive capacity of our models using four temperature measurements (minimum, maximum, range, and anomalies) across daily, weekly, and monthly time scales. Our results indicate seasonal temperature variation is a key driving factor of Aedes mosquito abundance and disease transmission. These models can help vector control programs target specific locations and times when vectors are likely to be present, and can be modified for other Aedes-transmitted diseases and arboviral endemic regions around the world.

Evaluation of corrective measures implemented for the preventive conservation of fresco paintings in Ariadne’s house (Pompeii, Italy)

PubMed Central

2013-01-01

Background A microclimate monitoring study was conducted in 2008 aimed at assessing the conservation risks affecting the valuable wall paintings decorating Ariadne’s House (Pompeii, Italy). It was found that thermohygrometric conditions were very unfavorable for the conservation of frescoes. As a result, it was decided to implement corrective measures, and the transparent polycarbonate sheets covering three rooms (one of them delimited by four walls and the others composed of three walls) were replaced by opaque roofs. In order to examine the effectiveness of this measure, the same monitoring system comprised by 26 thermohygrometric probes was installed again in summer 2010. Data recorded in 2008 and 2010 were compared. Results Microclimate conditions were also monitored in a control room with the same roof in both years. The average temperature in this room was lower in 2010, and it was decided to consider a time frame of 18 summer days with the same mean temperature in both years. In the rooms with three walls, the statistical analysis revealed that the diurnal maximum temperature decreased about 3.5°C due to the roof change, and the minimum temperature increased 0.5°C. As a result, the daily thermohygrometric variations resulted less pronounced in 2010, with a reduction of approximately 4°C, which is favorable for the preservation of mural paintings. In the room with four walls, the daily fluctuations also decreased about 4°C. Based on the results, other alternative actions are discussed aimed at improving the conservation conditions of wall paintings. Conclusions The roof change has reduced the most unfavorable thermohygrometric conditions affecting the mural paintings, but additional actions should be adopted for a long term preservation of Pompeian frescoes. PMID:23683173

Evaluation of corrective measures implemented for the preventive conservation of fresco paintings in Ariadne's house (Pompeii, Italy).

PubMed

Merello, Paloma; García-Diego, Fernando-Juan; Zarzo, Manuel

2013-05-17

A microclimate monitoring study was conducted in 2008 aimed at assessing the conservation risks affecting the valuable wall paintings decorating Ariadne's House (Pompeii, Italy). It was found that thermohygrometric conditions were very unfavorable for the conservation of frescoes. As a result, it was decided to implement corrective measures, and the transparent polycarbonate sheets covering three rooms (one of them delimited by four walls and the others composed of three walls) were replaced by opaque roofs. In order to examine the effectiveness of this measure, the same monitoring system comprised by 26 thermohygrometric probes was installed again in summer 2010. Data recorded in 2008 and 2010 were compared. Microclimate conditions were also monitored in a control room with the same roof in both years. The average temperature in this room was lower in 2010, and it was decided to consider a time frame of 18 summer days with the same mean temperature in both years. In the rooms with three walls, the statistical analysis revealed that the diurnal maximum temperature decreased about 3.5°C due to the roof change, and the minimum temperature increased 0.5°C. As a result, the daily thermohygrometric variations resulted less pronounced in 2010, with a reduction of approximately 4°C, which is favorable for the preservation of mural paintings. In the room with four walls, the daily fluctuations also decreased about 4°C. Based on the results, other alternative actions are discussed aimed at improving the conservation conditions of wall paintings. The roof change has reduced the most unfavorable thermohygrometric conditions affecting the mural paintings, but additional actions should be adopted for a long term preservation of Pompeian frescoes.

Potential Impacts of Future Warming and Land Use Changes on Intra-Urban Heat Exposure in Houston, Texas

PubMed Central

Conlon, Kathryn; Monaghan, Andrew; Hayden, Mary; Wilhelmi, Olga

2016-01-01

Extreme heat events in the United States are projected to become more frequent and intense as a result of climate change. We investigated the individual and combined effects of land use and warming on the spatial and temporal distribution of daily minimum temperature (Tmin) and daily maximum heat index (HImax) during summer in Houston, Texas. Present-day (2010) and near-future (2040) parcel-level land use scenarios were embedded within 1-km resolution land surface model (LSM) simulations. For each land use scenario, LSM simulations were conducted for climatic scenarios representative of both the present-day and near-future periods. LSM simulations assuming present-day climate but 2040 land use patterns led to spatially heterogeneous temperature changes characterized by warmer conditions over most areas, with summer average increases of up to 1.5°C (Tmin) and 7.3°C (HImax) in some newly developed suburban areas compared to simulations using 2010 land use patterns. LSM simulations assuming present-day land use but a 1°C temperature increase above the urban canopy (consistent with warming projections for 2040) yielded more spatially homogeneous metropolitan-wide average increases of about 1°C (Tmin) and 2.5°C (HImax), respectively. LSM simulations assuming both land use and warming for 2040 led to summer average increases of up to 2.5°C (Tmin) and 8.3°C (HImax), with the largest increases in areas projected to be converted to residential, industrial and mixed-use types. Our results suggest that urbanization and climate change may significantly increase the average number of summer days that exceed current threshold temperatures for initiating a heat advisory for metropolitan Houston, potentially increasing population exposure to extreme heat. PMID:26863298

Meteorological influence on the occurrence of gastric dilatation-volvulus in military working dogs in Texas.

PubMed

Moore, George E; Levine, Michael; Anderson, Johnna D; Trapp, Robert J

2008-01-01

Gastric dilatation-volvulus (GDV) is a life-threatening condition in dogs and other species in which the stomach dilates and rotates on itself. The etiology of the disease is multi-factorial, but explicit precipitating causes are unknown. This study sought to determine if there was a significant association between changes in hourly-measured temperature and/or atmospheric pressure and the occurrence of GDV in the population of high-risk working dogs in Texas. The odds of a day being a GDV day, given certain temperature and atmospheric pressure conditions for that day or the day before, was estimated using logistic regression models. There were 57 days in which GDV(s) occurred, representing 2.60% of the days in the 6-year study period. The months of November, December, and January collectively accounted for almost half (47%) of all cases. Disease risk was negatively associated with daily maximum temperature. An increased risk of GDV was weakly associated with the occurrence of large hourly drops in temperature that day and of higher minimum barometric pressure that day and the day before GDV occurrence, but extreme changes were not predictive of the disease.

Meteorological influence on the occurrence of gastric dilatation-volvulus in military working dogs in Texas

NASA Astrophysics Data System (ADS)

Moore, George E.; Levine, Michael; Anderson, Johnna D.; Trapp, Robert J.

2008-01-01

Gastric dilatation-volvulus (GDV) is a life-threatening condition in dogs and other species in which the stomach dilates and rotates on itself. The etiology of the disease is multi-factorial, but explicit precipitating causes are unknown. This study sought to determine if there was a significant association between changes in hourly-measured temperature and/or atmospheric pressure and the occurrence of GDV in the population of high-risk working dogs in Texas. The odds of a day being a GDV day, given certain temperature and atmospheric pressure conditions for that day or the day before, was estimated using logistic regression models. There were 57 days in which GDV(s) occurred, representing 2.60% of the days in the 6-year study period. The months of November, December, and January collectively accounted for almost half (47%) of all cases. Disease risk was negatively associated with daily maximum temperature. An increased risk of GDV was weakly associated with the occurrence of large hourly drops in temperature that day and of higher minimum barometric pressure that day and the day before GDV occurrence, but extreme changes were not predictive of the disease.

Comparison of short-term associations with meteorological variables between COPD and pneumonia hospitalization among the elderly in Hong Kong-a time-series study.

PubMed

Lam, Holly Ching-Yu; Chan, Emily Ying-Yang; Goggins, William Bernard

2018-05-05

Pneumonia and chronic obstructive pulmonary diseases (COPD) are the commonest causes of respiratory hospitalization among older adults. Both diseases have been reported to be associated with ambient temperature, but the associations have not been compared between the diseases. Their associations with other meteorological variables have also not been well studied. This study aimed to evaluate the associations between meteorological variables, pneumonia, and COPD hospitalization among adults over 60 and to compare these associations between the diseases. Daily cause-specific hospitalization counts in Hong Kong during 2004-2011 were regressed on daily meteorological variables using distributed lag nonlinear models. Associations were compared between diseases by ratio of relative risks. Analyses were stratified by season and age group (60-74 vs. ≥ 75). In hot season, high temperature (> 28 °C) and high relative humidity (> 82%) were statistically significantly associated with more pneumonia in lagged 0-2 and lagged 0-10 days, respectively. Pneumonia hospitalizations among the elderly (≥ 75) also increased with high solar radiation and high wind speed. During the cold season, consistent hockey-stick associations with temperature and relative humidity were found for both admissions and both age groups. The minimum morbidity temperature and relative humidity were at about 21-22 °C and 82%. The lagged effects of low temperature were comparable for both diseases (lagged 0-20 days). The low-temperature-admissions associations with COPD were stronger and were strongest among the elderly. This study found elevated pneumonia and COPD admissions risks among adults ≥ 60 during periods of extreme weather conditions, and the associations varied by season and age group. Vulnerable groups should be advised to avoid exposures, such as staying indoor and maintaining satisfactory indoor conditions, to minimize risks.

Climate change, heat, and mortality in the tropical urban area of San Juan, Puerto Rico.

PubMed

Méndez-Lázaro, Pablo A; Pérez-Cardona, Cynthia M; Rodríguez, Ernesto; Martínez, Odalys; Taboas, Mariela; Bocanegra, Arelis; Méndez-Tejeda, Rafael

2018-05-01

Extreme heat episodes are becoming more common worldwide, including in tropical areas of Australia, India, and Puerto Rico. Higher frequency, duration, and intensity of extreme heat episodes are triggering public health issues in most mid-latitude and continental cities. With urbanization, land use and land cover have affected local climate directly and indirectly encouraging the Urban Heat Island effect with potential impacts on heat-related morbidity and mortality among urban populations. However, this association is not completely understood in tropical islands such as Puerto Rico. The present study examines the effects of heat in two municipalities (San Juan and Bayamón) within the San Juan metropolitan area on overall and cause-specific mortality among the population between 2009 and 2013. The number of daily deaths attributed to selected causes (cardiovascular disease, hypertension, diabetes, stroke, chronic lower respiratory disease, pneumonia, and kidney disease) coded and classified according to the Tenth Revision of the International Classification of Diseases was analyzed. The relations between elevated air surface temperatures on cause-specific mortality were modeled. Separate Poisson regression models were fitted to explain the total number of deaths as a function of daily maximum and minimum temperatures, while adjusting for seasonal patterns. Results show a significant increase in the effect of high temperatures on mortality, during the summers of 2012 and 2013. Stroke (relative risk = 16.80, 95% CI 6.81-41.4) and cardiovascular diseases (relative risk = 16.63, 95% CI 10.47-26.42) were the primary causes of death most associated with elevated summer temperatures. Better understanding of how these heat events affect the health of the population will provide a useful tool for decision makers to address and mitigate the effects of the increasing temperatures on public health. The enhanced temperature forecast may be a crucial component in decision making during the National Weather Service Heat Watches, Advisories, and Warning process.

Climate change, heat, and mortality in the tropical urban area of San Juan, Puerto Rico

NASA Astrophysics Data System (ADS)

Méndez-Lázaro, Pablo A.; Pérez-Cardona, Cynthia M.; Rodríguez, Ernesto; Martínez, Odalys; Taboas, Mariela; Bocanegra, Arelis; Méndez-Tejeda, Rafael

2018-05-01

Extreme heat episodes are becoming more common worldwide, including in tropical areas of Australia, India, and Puerto Rico. Higher frequency, duration, and intensity of extreme heat episodes are triggering public health issues in most mid-latitude and continental cities. With urbanization, land use and land cover have affected local climate directly and indirectly encouraging the Urban Heat Island effect with potential impacts on heat-related morbidity and mortality among urban populations. However, this association is not completely understood in tropical islands such as Puerto Rico. The present study examines the effects of heat in two municipalities (San Juan and Bayamón) within the San Juan metropolitan area on overall and cause-specific mortality among the population between 2009 and 2013. The number of daily deaths attributed to selected causes (cardiovascular disease, hypertension, diabetes, stroke, chronic lower respiratory disease, pneumonia, and kidney disease) coded and classified according to the Tenth Revision of the International Classification of Diseases was analyzed. The relations between elevated air surface temperatures on cause-specific mortality were modeled. Separate Poisson regression models were fitted to explain the total number of deaths as a function of daily maximum and minimum temperatures, while adjusting for seasonal patterns. Results show a significant increase in the effect of high temperatures on mortality, during the summers of 2012 and 2013. Stroke (relative risk = 16.80, 95% CI 6.81-41.4) and cardiovascular diseases (relative risk = 16.63, 95% CI 10.47-26.42) were the primary causes of death most associated with elevated summer temperatures. Better understanding of how these heat events affect the health of the population will provide a useful tool for decision makers to address and mitigate the effects of the increasing temperatures on public health. The enhanced temperature forecast may be a crucial component in decision making during the National Weather Service Heat Watches, Advisories, and Warning process.

Climate change, heat, and mortality in the tropical urban area of San Juan, Puerto Rico

NASA Astrophysics Data System (ADS)

Méndez-Lázaro, Pablo A.; Pérez-Cardona, Cynthia M.; Rodríguez, Ernesto; Martínez, Odalys; Taboas, Mariela; Bocanegra, Arelis; Méndez-Tejeda, Rafael

2016-12-01

Extreme heat episodes are becoming more common worldwide, including in tropical areas of Australia, India, and Puerto Rico. Higher frequency, duration, and intensity of extreme heat episodes are triggering public health issues in most mid-latitude and continental cities. With urbanization, land use and land cover have affected local climate directly and indirectly encouraging the Urban Heat Island effect with potential impacts on heat-related morbidity and mortality among urban populations. However, this association is not completely understood in tropical islands such as Puerto Rico. The present study examines the effects of heat in two municipalities (San Juan and Bayamón) within the San Juan metropolitan area on overall and cause-specific mortality among the population between 2009 and 2013. The number of daily deaths attributed to selected causes (cardiovascular disease, hypertension, diabetes, stroke, chronic lower respiratory disease, pneumonia, and kidney disease) coded and classified according to the Tenth Revision of the International Classification of Diseases was analyzed. The relations between elevated air surface temperatures on cause-specific mortality were modeled. Separate Poisson regression models were fitted to explain the total number of deaths as a function of daily maximum and minimum temperatures, while adjusting for seasonal patterns. Results show a significant increase in the effect of high temperatures on mortality, during the summers of 2012 and 2013. Stroke (relative risk = 16.80, 95% CI 6.81-41.4) and cardiovascular diseases (relative risk = 16.63, 95% CI 10.47-26.42) were the primary causes of death most associated with elevated summer temperatures. Better understanding of how these heat events affect the health of the population will provide a useful tool for decision makers to address and mitigate the effects of the increasing temperatures on public health. The enhanced temperature forecast may be a crucial component in decision making during the National Weather Service Heat Watches, Advisories, and Warning process.

Solar radiation and out-of-hospital cardiac arrest in Japan.

PubMed

Onozuka, Daisuke; Hagihara, Akihito

2017-11-01

Although several studies have estimated the effects of temperature on mortality and morbidity, little is known regarding the burden of out-of-hospital cardiac arrest (OHCA) attributable to solar radiation. We obtained data for all cases of OHCA and meteorological data reported between 2011 and 2014 in 3 Japanese prefectures: Hokkaido, Ibaraki, and Fukuoka. We first examined the relationship between daily solar radiation and OHCA risk for each prefecture using time-varying distributed lag non-linear models and then pooled the results in a multivariate random-effects meta-analysis. The attributable fractions of OHCA were calculated for low and high solar radiation, defined as solar radiation below and above the minimum morbidity solar radiation, respectively. The minimum morbidity solar radiation was defined as the specific solar radiation associated with the lowest morbidity risk. A total of 49,892 cases of OHCA occurred during the study period. The minimum morbidity solar radiation for each prefecture was the 100th percentile (72.5 MJ/m 2 ) in Hokkaido, the 83rd percentile (59.7 MJ/m 2 ) in Ibaraki, and the 70th percentile (53.8 MJ/m 2 ) in Fukuoka. Overall, 20.00% (95% empirical confidence interval [eCI]: 10.97-27.04) of the OHCA cases were attributable to daily solar radiation. The attributable fraction for low solar radiation was 19.50% (95% eCI: 10.00-26.92), whereas that for high solar radiation was 0.50% (95% eCI: -0.07-1.01). Low solar radiation was associated with a substantial attributable risk for OHCA. Our findings suggest that public health efforts to reduce OHCA burden should consider the solar radiation level. Large prospective studies with longitudinal collection of individual data is required to more conclusively assess the impact of solar radiation on OHCA. Copyright © 2017 Elsevier Ltd. All rights reserved.

Climate Variability and Impact at NASA's Marshal Space Flight Center

NASA Technical Reports Server (NTRS)

Smoot, James L.; Jedlovec, Gary; Williams, Brett

2013-01-01

Climate analysis for the Southeast U. S. has indicated that inland regions have experienced an average temperature increase of 2F since 1970. This trend is generally characterized by warmer winters with an indication of increased precipitation in the Fall season. Extended periods of limited rainfall in the Spring and Summer periods have had greater areal coverage and, at other times the number of precipitation events has been increasing. Climate model projections for the next 10-70 years indicate warmer temperatures for the Southeast U.S., particularly in the Spring and Summer, with some indication of more extremes in temperature and precipitation as shown in the table below. The realization of these types of regional climate changes in the form of extended heat waves and droughts and their subsequent stress on facilities, infrastructure, and workforce could have substantial impact on the activities and functions of NASA's Marshall Space Flight Center (MSFC) in Huntsville, Alabama. This presentation will present the results of an examination of the 100 year temperature and precipitation record for MSFC. Local warming has cause an increase in daily maximum and minimum temperatures by nearly 3F, with a substantial increase in the number of maximum temperatures exceeding 90F and a decrease in the number of days with minimum temperatures below freezing. These trends have substantial impact of the number of heating / cooling degree days for the area. Yearly precipitation totals are inversely correlated with the change in mean temperature and the frequency of heavy rain events has remain consistent with the changes in yearly totals. An extended heat wave index was developed which shows an increase in frequency of heat waves over the last 35 years and a subsequent reduction in precipitation during the heat waves. This trend will contribute to more intense drought conditions over the northern Alabama region, increasing the potential of destructive wildfires in and around the Center. MSFC has begun using this climate change information to adapt short-term and long-term plans for Center operations.

Statistical summaries of streamflow data for selected gaging stations on and near the Idaho National Engineering Laboratory, Idaho, through September 1990

USGS Publications Warehouse

Stone, M.A.J.; Mann, Larry J.; Kjelstrom, L.C.

1993-01-01

Statistical summaries and graphs of streamflow data were prepared for 13 gaging stations with 5 or more years of continuous record on and near the Idaho National Engineering Laboratory. Statistical summaries of streamflow data for the Big and Little Lost Rivers and Birch Creek were analyzed as a requisite for a comprehensive evaluation of the potential for flooding of facilities at the Idaho National Engineering Laboratory. The type of statistical analyses performed depended on the length of streamflow record for a gaging station. Streamflow statistics generated for stations with 5 to 9 years of record were: (1) magnitudes of monthly and annual flows; (2) duration of daily mean flows; and (3) maximum, median, and minimum daily mean flows. Streamflow statistics generated for stations with 10 or more years of record were: (1) magnitudes of monthly and annual flows; (2) magnitudes and frequencies of daily low, high, instantaneous peak (flood frequency), and annual mean flows; (3) duration of daily mean flows; (4) exceedance probabilities of annual low, high, instantaneous peak, and mean annual flows; (5) maximum, median, and minimum daily mean flows; and (6) annual mean and mean annual flows.

The potential of different artificial neural network (ANN) techniques in daily global solar radiation modeling based on meteorological data

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

Behrang, M.A.; Assareh, E.; Ghanbarzadeh, A.

2010-08-15

The main objective of present study is to predict daily global solar radiation (GSR) on a horizontal surface, based on meteorological variables, using different artificial neural network (ANN) techniques. Daily mean air temperature, relative humidity, sunshine hours, evaporation, and wind speed values between 2002 and 2006 for Dezful city in Iran (32 16'N, 48 25'E), are used in this study. In order to consider the effect of each meteorological variable on daily GSR prediction, six following combinations of input variables are considered: (I)Day of the year, daily mean air temperature and relative humidity as inputs and daily GSR as output.more » (II)Day of the year, daily mean air temperature and sunshine hours as inputs and daily GSR as output. (III)Day of the year, daily mean air temperature, relative humidity and sunshine hours as inputs and daily GSR as output. (IV)Day of the year, daily mean air temperature, relative humidity, sunshine hours and evaporation as inputs and daily GSR as output. (V)Day of the year, daily mean air temperature, relative humidity, sunshine hours and wind speed as inputs and daily GSR as output. (VI)Day of the year, daily mean air temperature, relative humidity, sunshine hours, evaporation and wind speed as inputs and daily GSR as output. Multi-layer perceptron (MLP) and radial basis function (RBF) neural networks are applied for daily GSR modeling based on six proposed combinations. The measured data between 2002 and 2005 are used to train the neural networks while the data for 214 days from 2006 are used as testing data. The comparison of obtained results from ANNs and different conventional GSR prediction (CGSRP) models shows very good improvements (i.e. the predicted values of best ANN model (MLP-V) has a mean absolute percentage error (MAPE) about 5.21% versus 10.02% for best CGSRP model (CGSRP 5)). (author)« less

Evaluating the applicability of using daily forecasts from seasonal prediction systems (SPSs) for agriculture: a case study of Nepal's Terai with the NCEP CFSv2

NASA Astrophysics Data System (ADS)

Jha, Prakash K.; Athanasiadis, Panos; Gualdi, Silvio; Trabucco, Antonio; Mereu, Valentina; Shelia, Vakhtang; Hoogenboom, Gerrit

2018-03-01

Ensemble forecasts from dynamic seasonal prediction systems (SPSs) have the potential to improve decision-making for crop management to help cope with interannual weather variability. Because the reliability of crop yield predictions based on seasonal weather forecasts depends on the quality of the forecasts, it is essential to evaluate forecasts prior to agricultural applications. This study analyses the potential of Climate Forecast System version 2 (CFSv2) in predicting the Indian summer monsoon (ISM) for producing meteorological variables relevant to crop modeling. The focus area was Nepal's Terai region, and the local hindcasts were compared with weather station and reanalysis data. The results showed that the CFSv2 model accurately predicts monthly anomalies of daily maximum and minimum air temperature (Tmax and Tmin) as well as incoming total surface solar radiation (Srad). However, the daily climatologies of the respective CFSv2 hindcasts exhibit significant systematic biases compared to weather station data. The CFSv2 is less capable of predicting monthly precipitation anomalies and simulating the respective intra-seasonal variability over the growing season. Nevertheless, the observed daily climatologies of precipitation fall within the ensemble spread of the respective daily climatologies of CFSv2 hindcasts. These limitations in the CFSv2 seasonal forecasts, primarily in precipitation, restrict the potential application for predicting the interannual variability of crop yield associated with weather variability. Despite these limitations, ensemble averaging of the simulated yield using all CFSv2 members after applying bias correction may lead to satisfactory yield predictions.

Experimental investigations of the minimum ignition energy and the minimum ignition temperature of inert and combustible dust cloud mixtures.

PubMed

Addai, Emmanuel Kwasi; Gabel, Dieter; Krause, Ulrich

2016-04-15

The risks associated with dust explosions still exist in industries that either process or handle combustible dust. This explosion risk could be prevented or mitigated by applying the principle of inherent safety (moderation). This is achieved by adding an inert material to a highly combustible material in order to decrease the ignition sensitivity of the combustible dust. The presented paper deals with the experimental investigation of the influence of adding an inert dust on the minimum ignition energy and the minimum ignition temperature of the combustible/inert dust mixtures. The experimental investigation was done in two laboratory scale equipment: the Hartmann apparatus and the Godbert-Greenwald furnace for the minimum ignition energy and the minimum ignition temperature test respectively. This was achieved by mixing various amounts of three inert materials (magnesium oxide, ammonium sulphate and sand) and six combustible dusts (brown coal, lycopodium, toner, niacin, corn starch and high density polyethylene). Generally, increasing the inert materials concentration increases the minimum ignition energy as well as the minimum ignition temperatures until a threshold is reached where no ignition was obtained. The permissible range for the inert mixture to minimize the ignition risk lies between 60 to 80%. Copyright © 2016 Elsevier B.V. All rights reserved.

Future Extreme Event Vulnerability in the Rural Northeastern United States

NASA Astrophysics Data System (ADS)

Winter, J.; Bowen, F. L.; Partridge, T.; Chipman, J. W.

2017-12-01

Future climate change impacts on humans will be determined by the convergence of evolving physical climate and socioeconomic systems. Of particular concern is the intersection of extreme events and vulnerable populations. Rural areas of the Northeastern United States have experienced increased temperature and precipitation extremes, especially over the past three decades, and face unique challenges due to their physical isolation, natural resources dependent economies, and high poverty rates. To explore the impacts of future extreme events on vulnerable, rural populations in the Northeast, we project extreme events and vulnerability indicators to identify where changes in extreme events and vulnerable populations coincide. Specifically, we analyze future (2046-2075) maximum annual daily temperature, minimum annual daily temperature, maximum annual daily precipitation, and maximum consecutive dry day length for Representative Concentration Pathways (RCP) 4.5 and 8.5 using four global climate models (GCM) and a gridded observational dataset. We then overlay those projections with estimates of county-level population and relative income for 2060 to calculate changes in person-events from historical (1976-2005), with a focus on Northeast counties that have less than 250,000 people and are in the bottom income quartile. We find that across the rural Northeast for RCP4.5, heat person-events per year increase tenfold, far exceeding decreases in cold person-events and relatively small changes in precipitation and drought person-events. Counties in the bottom income quartile have historically (1976-2005) experienced a disproportionate number of heat events, and counties in the bottom two income quartiles are projected to experience a greater heat event increase by 2046-2075 than counties in the top two income quartiles. We further explore the relative contributions of event frequency, population, and income changes to the total and geographic distribution of climate change impacts on rural, vulnerable areas of the Northeast.

Climate change and malaria risk in Russia in 21st century

NASA Astrophysics Data System (ADS)

Malkhazova, S.; Shartova, N.

2010-09-01

The purpose of this research is development of prognostic model of malaria risk for Russia in the 21st century according to climate scenario IPCC "А2". The following issues have been formulated to reach the goal of the research: - define the basic epidemiological parameters describing malaria situation and methods of data processing; - creating of maps of malaria risk; - analysis of changes in malaria distribution for predictable future climate conditions in comparison with conditions of a modern climate. A lot of reasons (biological, social and economic) impact on malaria distribution. Nevertheless, incubation period of the parasite first of all depends on temperature. This is a primary factor that defines a potential area of infection, ability and specificity to transmit malaria. According to this, the model is based on the relationship between climate (average daily temperature) and the intensity of malaria transmission. The object of research is malaria parasite Plasmodium vivax, which has for Russia the greatest importance because it has the lowest minimal temperature threshold for development. Climate data is presented by daily average temperatures of air for three analyzed periods. 1961 -1989 describes a modern climate and corresponds to the minimum 30-year period that is necessary for an assessment of climate and changes connected with biotic components. Prognostic malaria model is based on predicted daily average temperatures for 2046-2065 (the middle of century) and 2089-2100 (the end of century). All data sets are presented in the grid 2х20. The conclusion on possible changes in malaria distribution and transmission in the middle and the end of the 21st century: There is going to be the increase of duration of effective temperatures period (period when parasite development is possible), period of effective susceptibility to infection of mosquitoes (period when malaria transmission cycle is possible); shift of the beginning of malaria transmission period to earlier time as well as the end of this period's shift to later time is connected to increase of effective temperatures annual sum. Northern bounds of the territory where temperature conditions allow parasite's development and disease transmission are going to move significantly to the north. Accordingly there will be an expansion of potential disease distribution area. Annual development of parasite and malaria transmission will probably be possible on nearly whole European part of Russia. The probability of malaria transmission and its intensity will increase. The results of the research indicate growth of malaria risk in Russia in 21st century.

Investigation of alternative layouts for the supercritical carbon dioxide Brayton cycle for a sodium-cooled fast reactor.

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

Moisseytsev, A.; Sienicki, J. J.

2009-07-01

Analyses of supercritical carbon dioxide (S-CO{sub 2}) Brayton cycle performance have largely settled on the recompression supercritical cycle (or Feher cycle) incorporating a flow split between the main compressor downstream of heat rejection, a recompressing compressor providing direct compression without heat rejection, and high and low temperature recuperators to raise the effectiveness of recuperation and the cycle efficiency. Alternative cycle layouts have been previously examined by Angelino (Politecnico, Milan), by MIT (Dostal, Hejzlar, and Driscoll), and possibly others but not for sodium-cooled fast reactors (SFRs) operating at relatively low core outlet temperature. Thus, the present authors could not be suremore » that the recompression cycle is an optimal arrangement for application to the SFR. To ensure that an advantageous alternative layout has not been overlooked, several alternative cycle layouts have been investigated for a S-CO{sub 2} Brayton cycle coupled to the Advanced Burner Test Reactor (ABTR) SFR preconceptual design having a 510 C core outlet temperature and a 470 C turbine inlet temperature to determine if they provide any benefit in cycle performance (e.g., enhanced cycle efficiency). No such benefits were identified, consistent with the previous examinations, such that attention was devoted to optimizing the recompression supercritical cycle. The effects of optimizing the cycle minimum temperature and pressure are investigated including minimum temperatures and/or pressures below the critical values. It is found that improvements in the cycle efficiency of 1% or greater relative to previous analyses which arbitrarily fixed the minimum temperature and pressure can be realized through an optimal choice of the combination of the minimum cycle temperature and pressure (e.g., for a fixed minimum temperature there is an optimal minimum pressure). However, this leads to a requirement for a larger cooler for heat rejection which may impact the tradeoff between efficiency and capital cost. In addition, for minimum temperatures below the critical temperature, a lower heat sink temperature is required the availability of which is dependent upon the climate at the specific plant site.« less

Annual minimum temperature variations in early 21st century in Punjab, Pakistan

NASA Astrophysics Data System (ADS)

Jahangir, Misbah; Maria Ali, Syeda; Khalid, Bushra

2016-01-01

Climate change is a key emerging threat to the global environment. It imposes long lasting impacts both at regional and national level. In the recent era, global warming and extreme temperatures have drawn great interest to the scientific community. As in a past century considerable increase in global surface temperatures have been observed and predictions revealed that it will continue in the future. In this regard, current study mainly focused on analysis of regional climatic change (annual minimum temperature trends and its correlation with land surface temperatures in the early 21st century in Punjab) for a period of 1979-2013. The projected model data European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-Interim) has been used for eight Tehsils of Punjab i.e., annual minimum temperatures and annual seasonal temperatures. Trend analysis of annual minimum and annual seasonal temperature in (Khushab, Noorpur, Sargodha, Bhalwal, Sahiwal, Shahpur, Sillanwali and Chinoit) tehsils of Punjab was carried out by Regression analysis and Mann-Kendall test. Landsat 5 Thematic Mapper (TM) data was used in comparison with Model data for the month of May from the years 2000, 2009 and 2010. Results showed that no significant trends were observed in annual minimum temperature. A significant change was observed in Noorpur, Bhalwal, Shahpur, Sillanwali, Sahiwal, Chinoit and Sargodha tehsils during spring season, which indicated that this particular season was a transient period of time.

Assessing the combined effects of climatic factors on spring wheat phenophase and grain yield in Inner Mongolia, China

PubMed Central

Pu, Feiyu; Li, Yunpeng; Xu, Jingwen; Li, Ning; Zhang, Yi; Guo, Jianping; Pan, Zhihua

2017-01-01

Understanding the regional relationships between climate change and crop production will benefit strategic decisions for future agricultural adaptation in China. In this study, the combined effects of climatic factors on spring wheat phenophase and grain yield over the past three decades in Inner Mongolia, China, were explored based on the daily climate variables from 1981–2014 and detailed observed data of spring wheat from 1981–2014. Inner Mongolia was divided into three different climate type regions, the eastern, central and western regions. The data were gathered from 10 representative agricultural meteorological experimental stations in Inner Mongolia and analysed with the Agricultural Production Systems Simulator (APSIM) model. First, the performance of the APSIM model in the spring wheat planting areas of Inner Mongolia was tested. Then, the key climatic factors limiting the phenophases and yield of spring wheat were identified. Finally, the responses of spring wheat phenophases and yield to climate change were further explored regionally. Our results revealed a general yield reduction of spring wheat in response to the pronounced climate warming from 1981 to 2014, with an average of 3564 kg·ha-1. The regional differences in yields were significant. The maximum potential yield of spring wheat was found in the western region. However, the minimum potential yield was found in the middle region. The air temperature and soil surface temperature were the optimum climatic factors that affected the key phenophases of spring wheat in Inner Mongolia. The influence of the average maximum temperature on the key phenophases of spring wheat was greater than the average minimum temperature, followed by the relative humidity and solar radiation. The most insensitive climatic factors were precipitation, wind speed and reference crop evapotranspiration. As for the yield of spring wheat, temperature, solar radiation and air relative humidity were major meteorological factors that affected in the eastern and western Inner Mongolia. Furthermore, the effect of the average minimum temperature on yield was greater than that of the average maximum temperature. The increase of temperature in the western and middle regions would reduce the spring wheat yield, while in the eastern region due to the rising temperature, the spring wheat yield increased. The increase of solar radiation in the eastern and central regions would increase the yield of spring wheat. The increased air relative humidity would make the western spring wheat yield increased and the eastern spring wheat yield decreased. Finally, the models describing combined effects of these dominant climatic factors on the maturity and yield in different regions of Inner Mongolia were used to establish geographical differences. Our findings have important implications for improving climate change impact studies and for local agricultural production to cope with ongoing climate change. PMID:29099842

Assessing the combined effects of climatic factors on spring wheat phenophase and grain yield in Inner Mongolia, China.

PubMed

Zhao, Junfang; Pu, Feiyu; Li, Yunpeng; Xu, Jingwen; Li, Ning; Zhang, Yi; Guo, Jianping; Pan, Zhihua

2017-01-01

Understanding the regional relationships between climate change and crop production will benefit strategic decisions for future agricultural adaptation in China. In this study, the combined effects of climatic factors on spring wheat phenophase and grain yield over the past three decades in Inner Mongolia, China, were explored based on the daily climate variables from 1981-2014 and detailed observed data of spring wheat from 1981-2014. Inner Mongolia was divided into three different climate type regions, the eastern, central and western regions. The data were gathered from 10 representative agricultural meteorological experimental stations in Inner Mongolia and analysed with the Agricultural Production Systems Simulator (APSIM) model. First, the performance of the APSIM model in the spring wheat planting areas of Inner Mongolia was tested. Then, the key climatic factors limiting the phenophases and yield of spring wheat were identified. Finally, the responses of spring wheat phenophases and yield to climate change were further explored regionally. Our results revealed a general yield reduction of spring wheat in response to the pronounced climate warming from 1981 to 2014, with an average of 3564 kg·ha-1. The regional differences in yields were significant. The maximum potential yield of spring wheat was found in the western region. However, the minimum potential yield was found in the middle region. The air temperature and soil surface temperature were the optimum climatic factors that affected the key phenophases of spring wheat in Inner Mongolia. The influence of the average maximum temperature on the key phenophases of spring wheat was greater than the average minimum temperature, followed by the relative humidity and solar radiation. The most insensitive climatic factors were precipitation, wind speed and reference crop evapotranspiration. As for the yield of spring wheat, temperature, solar radiation and air relative humidity were major meteorological factors that affected in the eastern and western Inner Mongolia. Furthermore, the effect of the average minimum temperature on yield was greater than that of the average maximum temperature. The increase of temperature in the western and middle regions would reduce the spring wheat yield, while in the eastern region due to the rising temperature, the spring wheat yield increased. The increase of solar radiation in the eastern and central regions would increase the yield of spring wheat. The increased air relative humidity would make the western spring wheat yield increased and the eastern spring wheat yield decreased. Finally, the models describing combined effects of these dominant climatic factors on the maturity and yield in different regions of Inner Mongolia were used to establish geographical differences. Our findings have important implications for improving climate change impact studies and for local agricultural production to cope with ongoing climate change.

An assessment of precipitation and surface air temperature over China by regional climate models

NASA Astrophysics Data System (ADS)

Wang, Xueyuan; Tang, Jianping; Niu, Xiaorui; Wang, Shuyu

2016-12-01

An analysis of a 20-year summer time simulation of present-day climate (1989-2008) over China using four regional climate models coupled with different land surface models is carried out. The climatic means, interannual variability, linear trends, and extremes are examined, with focus on precipitation and near surface air temperature. The models are able to reproduce the basic features of the observed summer mean precipitation and temperature over China and the regional detail due to topographic forcing. Overall, the model performance is better for temperature than that of precipitation. The models reasonably grasp the major anomalies and standard deviations over China and the five subregions studied. The models generally reproduce the spatial pattern of high interannual variability over wet regions, and low variability over the dry regions. The models also capture well the variable temperature gradient increase to the north by latitude. Both the observed and simulated linear trend of precipitation shows a drying tendency over the Yangtze River Basin and wetting over South China. The models capture well the relatively small temperature trends in large areas of China. The models reasonably simulate the characteristics of extreme precipitation indices of heavy rain days and heavy precipitation fraction. Most of the models also performed well in capturing both the sign and magnitude of the daily maximum and minimum temperatures over China.

Seasonal cues of Arctic grayling movement in a small Arctic stream: the importance of surface water connectivity

USGS Publications Warehouse

Heim, Kurt C.; Wipfli, Mark S.; Whitman, Matthew S.; Arp, Christopher D.; Adams, Jeff; Falke, Jeffrey A.

2015-01-01

In Arctic ecosystems, freshwater fish migrate seasonally between productive shallow water habitats that freeze in winter and deep overwinter refuge in rivers and lakes. How these movements relate to seasonal hydrology is not well understood. We used passive integrated transponder tags and stream wide antennae to track 1035 Arctic grayling in Crea Creek, a seasonally flowing beaded stream on the Arctic Coastal Plain, Alaska. Migration of juvenile and adult fish into Crea Creek peaked in June immediately after ice break-up in the stream. Fish that entered the stream during periods of high flow and cold stream temperature traveled farther upstream than those entering during periods of lower flow and warmer temperature. We used generalized linear models to relate migration of adult and juvenile fish out of Crea Creek to hydrology. Most adults migrated in late June – early July, and there was best support (Akaike weight = 0.46; w i ) for a model indicating that the rate of migration increased with decreasing discharge. Juvenile migration occurred in two peaks; the early peak consisted of larger juveniles and coincided with adult migration, while the later peak occurred shortly before freeze-up in September and included smaller juveniles. A model that included discharge, minimum stream temperature, year, season, and mean size of potential migrants was most strongly supported (w i  = 0.86). Juvenile migration rate increased sharply as daily minimum stream temperature decreased, suggesting fish respond to impending freeze-up. We found fish movements to be intimately tied to the strong seasonality of discharge and temperature, and demonstrate the importance of small stream connectivity for migratory Arctic grayling during the entire open-water period. The ongoing and anticipated effects of climate change and petroleum development on Arctic hydrology (e.g. reduced stream connectivity, earlier peak flows, increased evapotranspiration) have important implications for Arctic freshwater ecosystems.

Evaluation of an eddy resolving global model at the Bermuda Atlantic Time-series Study site

NASA Astrophysics Data System (ADS)

Hiron, L.; Goncalves Neto, A.; Bates, N. R.; Johnson, R. J.

2016-02-01

The Bermuda Atlantic Time-series Study (BATS) commenced monthly sampling in 1988 and thus provides an invaluable 27 years of ocean temperature and salinity profiles for inferring climate relevant processes. However, the passage of mesoscale eddies through this site complicates the local heat and salinity budgets due to inadequate spatial and temporal sampling of these eddy systems. Thus, application of high resolution operational numerical models potentially offers a framework for estimating the horizontal transport due to mesoscale processes. The goal of this research was to analyze the accuracy of the MERCATOR operational 1/12° global ocean model at the BATS site by comparing temperature, salinity and heat budgets for years 2008 - 2015. Overall agreement in the upper 540m for temperature and salinity is found to be very encouraging with significant (P< 0.01) correlations at all depths for both fields. The highest value of correlation coefficient for the temperature field is 0.98 at the surface which decreases to 0.66 at 150m and then reaches a minimum of 0.50 at 320 to 540m. Similarly, the highest correlation coefficient for salinity is found at the surface, with a value of 0.83 and then decreases to a minimum of 0.25 in the subtropical mode water though then increases to 0.5 at 540m. Mixing in the MERCATOR model is also very well captured with a mixed layer depth (MLD) correlation coefficient of 0.92 for the seven year period. Finally, the total heat budget (0-540m) from MERCATOR varies coherently with the BATS observations as shown by a high correlation coefficient of 0.84 (P < 0.01). According to these analyses, daily output from the MERCATOR model represents accurately the temperature, salinity, heat budget and MLD at the BATS site. We propose this model can be used in future research at the BATS site by providing information about mesoscale structure and importantly, advective fluxes at this site.

Trends in rainfall and temperature extremes in Morocco

NASA Astrophysics Data System (ADS)

Khomsi, K.; Mahe, G.; Tramblay, Y.; Sinan, M.; Snoussi, M.

2015-02-01

In Morocco, socioeconomic fields are vulnerable to weather extreme events. This work aims to analyze the frequency and the trends of temperature and rainfall extreme events in two contrasted Moroccan regions (the Tensift in the semi-arid South, and the Bouregreg in the sub-humid North), during the second half of the 20th century. This study considers long time series of daily extreme temperatures and rainfall, recorded in the stations of Marrakech and Safi for the Tensift region, and Kasba-Tadla and Rabat-Sale for the Bouregreg region, data from four other stations (Tanger, Fes, Agadir and Ouarzazate) from outside the regions were added. Extremes are defined by using as thresholds the 1st, 5th, 90th, 95th, and 99th percentiles. Results show upward trends in maximum and minimum temperatures of both regions and no generalized trends in rainfall amounts. Changes in cold events are larger than those for warm events, and the number of very cold events decrease significantly in the whole studied area. The southern region is the most affected with the changes of the temperature regime. Most of the trends found in rainfall heavy events are positive with weak magnitudes even though no statistically significant generalized trends could be identified during both seasons.

Development of rabbit embryos during a 96-h period of in vitro culture after superovulatory treatment under conditions of elevated ambient temperature.

PubMed

Cheng, H; Dooley, M P; Hopkins, S M; Anderson, L L; Yibchok-anun, S; Hsu, W H

1999-08-16

The effects of elevated ambient temperature on the response to exogenous gonadotropins were evaluated in female New Zealand White rabbits exposed to 33+/-1 degrees C (mean +/- SE) and 10-30% relative humidity (8 h/day) during a 5-day period. Does were treated with pFSH (0.3 mg/0.3 ml Standard Armour) twice daily during three consecutive days with a minimum interval of 8 h between injections. Six hours after the last FSH injection all does were removed from the experimental chamber, given hCG (25 IU/kg) and paired overnight. Nineteen hours after pairing, embryos were flushed from the reproductive tracts, evaluated, and subjected to in vitro culture during a 96-h period. The ovulatory responses to exogenous gonadotropins and fertilization rates did not differ significantly under conditions of elevated ambient temperature, whereas fewer blastocysts and increased number of degenerate embryos were observed after culture. We conclude that although hyperthermia was induced during exposure to elevated ambient temperature, it did not alter the ovulatory responses to gonadotropin treatment and plasma concentrations of FSH and LH compared with does in a thermoneutral environment. Exposure of donor rabbits to elevated ambient temperature before mating, however, increased embryonic degeneration.

Climate change impact assessment on food security in Indonesia

NASA Astrophysics Data System (ADS)

Ettema, Janneke; Aldrian, Edvin; de Bie, Kees; Jetten, Victor; Mannaerts, Chris

2013-04-01

As Indonesia is the world's fourth most populous country, food security is a persistent challenge. The potential impact of future climate change on the agricultural sector needs to be addressed in order to allow early implementation of mitigation strategies. The complex island topography and local sea-land-air interactions cannot adequately be represented in large scale General Climate Models (GCMs) nor visualized by TRMM. Downscaling is needed. Using meteorological observations and a simple statistical downscaling tool, local future projections are derived from state-of-the-art, large-scale GCM scenarios, provided by the CMIP5 project. To support the agriculture sector, providing information on especially rainfall and temperature variability is essential. Agricultural production forecast is influenced by several rain and temperature factors, such as rainy and dry season onset, offset and length, but also by daily and monthly minimum and maximum temperatures and its rainfall amount. A simple and advanced crop model will be used to address the sensitivity of different crops to temperature and rainfall variability, present-day and future. As case study area, Java Island is chosen as it is fourth largest island in Indonesia but contains more than half of the nation's population and dominates it politically and economically. The objective is to identify regions at agricultural risk due to changing patterns in precipitation and temperature.

Effect of electromagnetic radiation on the coils used in aneurysm embolization.

PubMed

Lv, Xianli; Wu, Zhongxue; Li, Youxiang

2014-06-01

This study evaluated the effects of electromagnetic radiation in our daily lives on the coils used in aneurysm embolization. Faraday's electromagnetic induction principle was applied to analyze the effects of electromagnetic radiation on the coils used in aneurysm embolization. To induce a current of 0.5mA in less than 5 mm platinum coils required to stimulate peripheral nerves, the minimum magnetic field will be 0.86 μT. To induce a current of 0.5 mA in platinum coils by a hair dryer, the minimum aneurysm radius is 2.5 mm (5 mm aneurysm). To induce a current of 0.5 mA in platinum coils by a computer or TV, the minimum aneurysm radius is 8.6 mm (approximate 17 mm aneurysm). The minimum magnetic field is much larger than the flux densities produced by computer and TV, while the minimum aneurysm radius is much larger than most aneurysm sizes to levels produced by computer and TV. At present, the effects of electromagnetic radiation in our daily lives on intracranial coils do not produce a harmful reaction. Patients with coiled aneurysm are advised to avoid using hair dryers. This theory needs to be proved by further detailed complex investigations. Doctors should give patients additional instructions before the procedure, depending on this study.

Effect of Electromagnetic Radiation on the Coils Used in Aneurysm Embolization

PubMed Central

Lv, Xianli; Wu, Zhongxue; Li, Youxiang

2014-01-01

Summary This study evaluated the effects of electromagnetic radiation in our daily lives on the coils used in aneurysm embolization. Faraday’s electromagnetic induction principle was applied to analyze the effects of electromagnetic radiation on the coils used in aneurysm embolization. To induce a current of 0.5mA in less than 5 mm platinum coils required to stimulate peripheral nerves, the minimum magnetic field will be 0.86 μT. To induce a current of 0.5 mA in platinum coils by a hair dryer, the minimum aneurysm radius is 2.5 mm (5 mm aneurysm). To induce a current of 0.5 mA in platinum coils by a computer or TV, the minimum aneurysm radius is 8.6 mm (approximate 17 mm aneurysm). The minimum magnetic field is much larger than the flux densities produced by computer and TV, while the minimum aneurysm radius is much larger than most aneurysm sizes to levels produced by computer and TV. At present, the effects of electromagnetic radiation in our daily lives on intracranial coils do not produce a harmful reaction. Patients with coiled aneurysm are advised to avoid using hair dryers. This theory needs to be proved by further detailed complex investigations. Doctors should give patients additional instructions before the procedure, depending on this study. PMID:24976203

Simple process-led algorithms for simulating habitats (SPLASH v.1.0): robust indices of radiation, evapotranspiration and plant-available moisture

NASA Astrophysics Data System (ADS)

Davis, Tyler W.; Prentice, I. Colin; Stocker, Benjamin D.; Thomas, Rebecca T.; Whitley, Rhys J.; Wang, Han; Evans, Bradley J.; Gallego-Sala, Angela V.; Sykes, Martin T.; Cramer, Wolfgang

2017-02-01

Bioclimatic indices for use in studies of ecosystem function, species distribution, and vegetation dynamics under changing climate scenarios depend on estimates of surface fluxes and other quantities, such as radiation, evapotranspiration and soil moisture, for which direct observations are sparse. These quantities can be derived indirectly from meteorological variables, such as near-surface air temperature, precipitation and cloudiness. Here we present a consolidated set of simple process-led algorithms for simulating habitats (SPLASH) allowing robust approximations of key quantities at ecologically relevant timescales. We specify equations, derivations, simplifications, and assumptions for the estimation of daily and monthly quantities of top-of-the-atmosphere solar radiation, net surface radiation, photosynthetic photon flux density, evapotranspiration (potential, equilibrium, and actual), condensation, soil moisture, and runoff, based on analysis of their relationship to fundamental climatic drivers. The climatic drivers include a minimum of three meteorological inputs: precipitation, air temperature, and fraction of bright sunshine hours. Indices, such as the moisture index, the climatic water deficit, and the Priestley-Taylor coefficient, are also defined. The SPLASH code is transcribed in C++, FORTRAN, Python, and R. A total of 1 year of results are presented at the local and global scales to exemplify the spatiotemporal patterns of daily and monthly model outputs along with comparisons to other model results.

Climate sensitivity of DSSAT under different agriculture practice scenarios in China

NASA Astrophysics Data System (ADS)

Xia, L.; Robock, A.

2014-12-01

Crop yields are sensitive to both agricultural practice and climate changes. Under different agricultural practice scenarios, crop yield may have different climate sensitivities. Since it is important to understand how future climate changes affect agriculture productivity and what the potential adaptation strategies would be to compensate for possible negative impacts on crop production, we performed experiments to study climate sensitivity under different agricultural practice scenarios for rice, maize and wheat in the top four production provinces in China using the Decision Support System for Agrotechnology Transfer (DSSAT) crop model. The agricultural practice scenarios include four categories: different amounts of nitrogen fertilizer or no nitrogen stress; irrigation turned on or off, or no water stress; all possible seeds in the DSSAT cultivar data base; and different planting dates. For the climate sensitivity test, the control climate is from 1998 to 2007, and we individually modify four climate variables: daily maximum and minimum temperature by +2 °C and -2 °C, daily precipitation by +20% and -20%, and daily solar radiation by + 20% and -20%. With more nitrogen fertilizer applied, crops are more sensitive to temperature changes as well as precipitation changes because of their release from nitrogen limitation. With irrigation turned on, crop yield sensitivity to temperature decreases in most of the regions depending on the amount of the local precipitation, since more water is available and soil temperature varies less with higher soil moisture. Those results indicate that there could be possible agriculture adaptation strategies under certain future climate scenarios. For example, increasing nitrogen fertilizer usage by a certain amount might compensate for the negative impact on crop yield from climate changes. However, since crops are more sensitive to climate changes when there is more nitrogen fertilizer applied, if the climate changes are unfavorable to crop yields, increasing nitrogen fertilizer usage at certain levels might enhance the negative climate change impact. Enhanced nitrogen fertilizer use might have additional negative impacts on climate because of nitrogen emissions to the atmosphere, but those effects were not studied here.

Modelling short-term variability in carbon and water exchange in a temperate Scots pine forest

NASA Astrophysics Data System (ADS)

Vermeulen, M. H.; Kruijt, B. J.; Hickler, T.; Kabat, P.

2015-02-01

Vegetation - atmosphere carbon and water exchange at one particular site can strongly vary from year to year, and understanding this interannual variability in carbon and water exchange (IAVcw) is a critical factor in projecting future ecosystem changes. However, the mechanisms driving this IAVcw are not well understood. We used data on carbon and water fluxes from a multi-year Eddy Covariance study (1997-2009) in a Dutch Scots pine forest and forced a process-based ecosystem model (LPJ-GUESS) with local data to, firstly, test whether the model can explain IAVcw and seasonal carbon and water exchange from direct environmental factors only. Initial model runs showed low correlations with estimated annual gross primary productivity (GPP) and annual actual evapotranspiration (AET), while monthly and daily fluxes showed high correlations. The model underestimated GPP and AET during winter and drought events. Secondly, we adapted the temperature inhibition function of photosynthesis to account for the observation that at this particular site, trees continue to assimilate at very low atmospheric temperatures (up to daily averages of -10 °C), resulting in a net carbon sink in winter. While we were able to improve daily and monthly simulations during winter by lowering the modelled minimum temperature threshold for photosynthesis, this did not increase explained IAVcw at the site. Thirdly, we implemented three alternative hypotheses concerning water uptake by plants in order to test which one best corresponds with the data. In particular, we analyse the effects during the 2003 heatwave. These simulations revealed a strong sensitivity of the modelled fluxes during dry and warm conditions, but no single formulation was consistently superior in reproducing the data for all time scales and the overall model-data match for IAVcw could not be improved. Most probably access to deep soil water leads to higher AET and GPP simulated during the heat wave of 2003. We conclude that photosynthesis at lower temperatures than assumed in most models can be important for winter carbon and water fluxes in pine forests. Furthermore, details of the model representations of water uptake, which are often overlooked, need further attention, and deep water access should be treated explicitly.

Modelling short-term variability in carbon and water exchange in a temperate Scots pine forest

NASA Astrophysics Data System (ADS)

Vermeulen, M. H.; Kruijt, B. J.; Hickler, T.; Kabat, P.

2015-07-01

The vegetation-atmosphere carbon and water exchange at one particular site can strongly vary from year to year, and understanding this interannual variability in carbon and water exchange (IAVcw) is a critical factor in projecting future ecosystem changes. However, the mechanisms driving this IAVcw are not well understood. We used data on carbon and water fluxes from a multi-year eddy covariance study (1997-2009) in a Dutch Scots pine forest and forced a process-based ecosystem model (Lund-Potsdam-Jena General Ecosystem Simulator; LPJ-GUESS) with local data to, firstly, test whether the model can explain IAVcw and seasonal carbon and water exchange from direct environmental factors only. Initial model runs showed low correlations with estimated annual gross primary productivity (GPP) and annual actual evapotranspiration (AET), while monthly and daily fluxes showed high correlations. The model underestimated GPP and AET during winter and drought events. Secondly, we adapted the temperature inhibition function of photosynthesis to account for the observation that at this particular site, trees continue to assimilate at very low atmospheric temperatures (up to daily averages of -10 °C), resulting in a net carbon sink in winter. While we were able to improve daily and monthly simulations during winter by lowering the modelled minimum temperature threshold for photosynthesis, this did not increase explained IAVcw at the site. Thirdly, we implemented three alternative hypotheses concerning water uptake by plants in order to test which one best corresponds with the data. In particular, we analyse the effects during the 2003 heatwave. These simulations revealed a strong sensitivity of the modelled fluxes during dry and warm conditions, but no single formulation was consistently superior in reproducing the data for all timescales and the overall model-data match for IAVcw could not be improved. Most probably access to deep soil water leads to higher AET and GPP simulated during the heatwave of 2003. We conclude that photosynthesis at lower temperatures than assumed in most models can be important for winter carbon and water fluxes in pine forests. Furthermore, details of the model representations of water uptake, which are often overlooked, need further attention, and deep water access should be treated explicitly.

Cold-related mortality vs heat-related mortality in a changing climate: A case study in Vilnius (Lithuania).

PubMed

Martinez, Gerardo Sanchez; Diaz, Julio; Hooyberghs, Hans; Lauwaet, Dirk; De Ridder, Koen; Linares, Cristina; Carmona, Rocio; Ortiz, Cristina; Kendrovski, Vladimir; Adamonyte, Dovile

2018-06-21

Direct health effects of extreme temperatures are a significant environmental health problem in Lithuania, and could worsen further under climate change. This paper attempts to describe the change in environmental temperature conditions that the urban population of Vilnius could experience under climate change, and the effects such change could have on excess heat-related and cold-related mortality in two future periods within the 21st century. We modelled the urban climate of Vilnius for the summer and winter seasons during a sample period (2009-2015) and projected summertime and wintertime daily temperatures for two prospective periods, one in the near (2030-2045) and one in the far future (2085-2100), under the Representative Concentration Pathway (RCP) 8.5. We then analysed the historical relationship between temperature and mortality for the period 2009-2015, and estimated the projected mortality in the near future and far future periods under a changing climate and population, assuming alternatively no acclimatisation and acclimatisation to heat and cold based on a constant-percentile threshold temperature. During the sample period 2009-2015 in summertime we observed an increase in daily mortality from a maximum daily temperature of 30 °C (the 96th percentile of the series), with an average of around 7 deaths per year. Under a no acclimatisation scenario, annual average heat-related mortality would rise to 24 deaths/year (95% CI: 8.4-38.4) in the near future and to 46 deaths/year (95% CI: 16.4-74.4) in the far future. Under a heat acclimatisation scenario, mortality would not increase significantly in the near or in the far future. Regarding wintertime cold-related mortality in the sample period 2009-2015, we observed increased mortality on days on which the minimum daily temperature fell below - 12 °C (the 7th percentile of the series), with an average of around 10 deaths a year. Keeping the threshold temperature constant, annual average cold-related mortality would decrease markedly in the near future, to 5 deaths/year (95% CI: 0.8-7.9) and even more in the far future, down to 0.44 deaths/year (95% C: 0.1-0.8). Assuming a "middle ground" between the acclimatisation and non-acclimatisation scenarios, the decrease in cold-related mortality will not compensate the increase in heat-related mortality. Thermal extremes, both heat and cold, constitute a serious public health threat in Vilnius, and in a changing climate the decrease in mortality attributable to cold will not compensate for the increase in mortality attributable to heat. Study results reinforce the notion that public health prevention against thermal extremes should be designed as a dynamic, adaptive process from the inception. Copyright © 2018 Elsevier Inc. All rights reserved.

Development and validation of a 5-day-ahead hay fever forecast for patients with grass-pollen-induced allergic rhinitis

NASA Astrophysics Data System (ADS)

de Weger, Letty A.; Beerthuizen, Thijs; Hiemstra, Pieter S.; Sont, Jacob K.

2014-08-01

One-third of the Dutch population suffers from allergic rhinitis, including hay fever. In this study, a 5-day-ahead hay fever forecast was developed and validated for grass pollen allergic patients in the Netherlands. Using multiple regression analysis, a two-step pollen and hay fever symptom prediction model was developed using actual and forecasted weather parameters, grass pollen data and patient symptom diaries. Therefore, 80 patients with a grass pollen allergy rated the severity of their hay fever symptoms during the grass pollen season in 2007 and 2008. First, a grass pollen forecast model was developed using the following predictors: (1) daily means of grass pollen counts of the previous 10 years; (2) grass pollen counts of the previous 2-week period of the current year; and (3) maximum, minimum and mean temperature ( R 2 = 0.76). The second modeling step concerned the forecasting of hay fever symptom severity and included the following predictors: (1) forecasted grass pollen counts; (2) day number of the year; (3) moving average of the grass pollen counts of the previous 2 week-periods; and (4) maximum and mean temperatures ( R 2 = 0.81). Since the daily hay fever forecast is reported in three categories (low-, medium- and high symptom risk), we assessed the agreement between the observed and the 1- to 5-day-ahead predicted risk categories by kappa, which ranged from 65 % to 77 %. These results indicate that a model based on forecasted temperature and grass pollen counts performs well in predicting symptoms of hay fever up to 5 days ahead.

A comparative climate analysis of heat-related emergency 911 dispatches: Chicago, Illinois and Phoenix, Arizona USA 2003 to 2006.

PubMed

Hartz, Donna A; Brazel, Anthony J; Golden, Jay S

2013-09-01

Research into the health impacts of heat has proliferated since 2000. Temperature increases could exacerbate the increased heat already experienced by urban populations due to urbanization. Heat-related mortality studies have found that hot southern cities in North America have not experienced the summer increases in mortality found in their more northern counterparts. Heat-related morbidity studies have not assessed this possible regional difference. This comparison study uses data from emergency 911 dispatches [referred to as heat-related dispatches (HRD)] identified by responders as heat-related for two United States cities located in different regions with very different climates: Chicago, Illinois in the upper midwest and Phoenix, Arizona in the southwest. Phoenix's climate is hot and arid. Chicago's climate is more temperate, but can also experience days with unusually high temperatures combined with high humidity. This study examines the relationships between rising HRD and daily temperatures: maximum (Tmax); apparent (ATmax): minimum (Tmin) and two energy balance indices (PET and UTCI). Phoenix had more HRD cumulatively, over a longer warm weather season, but did not experience the large spikes in HRD that occurred in Chicago, even though it was routinely subjected to much hotter weather conditions. Statistical analyses showed the strongest relationships to daily ATmax for both cities. Phoenix's lack of HRD spikes, similar to the summer mortality patterns for southern cities, suggests an avenue for future research to better understand the dynamics of possible physiological or behavioral adaption that seems to reduce residents' vulnerability to heat.

Development and validation of a 5-day-ahead hay fever forecast for patients with grass-pollen-induced allergic rhinitis.

PubMed

de Weger, Letty A; Beerthuizen, Thijs; Hiemstra, Pieter S; Sont, Jacob K

2014-08-01

One-third of the Dutch population suffers from allergic rhinitis, including hay fever. In this study, a 5-day-ahead hay fever forecast was developed and validated for grass pollen allergic patients in the Netherlands. Using multiple regression analysis, a two-step pollen and hay fever symptom prediction model was developed using actual and forecasted weather parameters, grass pollen data and patient symptom diaries. Therefore, 80 patients with a grass pollen allergy rated the severity of their hay fever symptoms during the grass pollen season in 2007 and 2008. First, a grass pollen forecast model was developed using the following predictors: (1) daily means of grass pollen counts of the previous 10 years; (2) grass pollen counts of the previous 2-week period of the current year; and (3) maximum, minimum and mean temperature (R (2)=0.76). The second modeling step concerned the forecasting of hay fever symptom severity and included the following predictors: (1) forecasted grass pollen counts; (2) day number of the year; (3) moving average of the grass pollen counts of the previous 2 week-periods; and (4) maximum and mean temperatures (R (2)=0.81). Since the daily hay fever forecast is reported in three categories (low-, medium- and high symptom risk), we assessed the agreement between the observed and the 1- to 5-day-ahead predicted risk categories by kappa, which ranged from 65 % to 77 %. These results indicate that a model based on forecasted temperature and grass pollen counts performs well in predicting symptoms of hay fever up to 5 days ahead.

A comparative climate analysis of heat-related emergency 911 dispatches: Chicago, Illinois and Phoenix, Arizona USA 2003 to 2006

NASA Astrophysics Data System (ADS)

Hartz, Donna A.; Brazel, Anthony J.; Golden, Jay S.

2013-09-01

Research into the health impacts of heat has proliferated since 2000. Temperature increases could exacerbate the increased heat already experienced by urban populations due to urbanization. Heat-related mortality studies have found that hot southern cities in North America have not experienced the summer increases in mortality found in their more northern counterparts. Heat-related morbidity studies have not assessed this possible regional difference. This comparison study uses data from emergency 911 dispatches [referred to as heat-related dispatches (HRD)] identified by responders as heat-related for two United States cities located in different regions with very different climates: Chicago, Illinois in the upper midwest and Phoenix, Arizona in the southwest. Phoenix's climate is hot and arid. Chicago's climate is more temperate, but can also experience days with unusually high temperatures combined with high humidity. This study examines the relationships between rising HRD and daily temperatures: maximum (Tmax); apparent (ATmax): minimum (Tmin) and two energy balance indices (PET and UTCI). Phoenix had more HRD cumulatively, over a longer warm weather season, but did not experience the large spikes in HRD that occurred in Chicago, even though it was routinely subjected to much hotter weather conditions. Statistical analyses showed the strongest relationships to daily ATmax for both cities. Phoenix's lack of HRD spikes, similar to the summer mortality patterns for southern cities, suggests an avenue for future research to better understand the dynamics of possible physiological or behavioral adaption that seems to reduce residents' vulnerability to heat.

Estimation of the daily global solar radiation based on the Gaussian process regression methodology in the Saharan climate

NASA Astrophysics Data System (ADS)

Guermoui, Mawloud; Gairaa, Kacem; Rabehi, Abdelaziz; Djafer, Djelloul; Benkaciali, Said

2018-06-01

Accurate estimation of solar radiation is the major concern in renewable energy applications. Over the past few years, a lot of machine learning paradigms have been proposed in order to improve the estimation performances, mostly based on artificial neural networks, fuzzy logic, support vector machine and adaptive neuro-fuzzy inference system. The aim of this work is the prediction of the daily global solar radiation, received on a horizontal surface through the Gaussian process regression (GPR) methodology. A case study of Ghardaïa region (Algeria) has been used in order to validate the above methodology. In fact, several combinations have been tested; it was found that, GPR-model based on sunshine duration, minimum air temperature and relative humidity gives the best results in term of mean absolute bias error (MBE), root mean square error (RMSE), relative mean square error (rRMSE), and correlation coefficient ( r) . The obtained values of these indicators are 0.67 MJ/m2, 1.15 MJ/m2, 5.2%, and 98.42%, respectively.

RESPONSIVENESS OF THE ACTIVITIES OF DAILY LIVING SCALE OF THE KNEE OUTCOME SURVEY AND NUMERIC PAIN RATING SCALE IN PATIENTS WITH PATELLOFEMORAL PAIN

PubMed Central

Piva, Sara R.; Gil, Alexandra B.; Moore, Charity G.; Fitzgerald, G. Kelley

2016-01-01

Objective To assess internal and external responsiveness of the Activity of Daily Living Scale of the Knee Outcome Survey and Numeric Pain Rating Scale on patients with patellofemoral pain. Design One group pre-post design. Subjects A total of 60 individuals with patellofemoral pain (33 women; mean age 29.9 (standard deviation 9.6) years). Methods The Activity of Daily Living Scale and the Numeric Pain Rating Scale were assessed before and after 8 weeks of physical therapy program. Patients completed a global rating of change scale at the end of therapy. The standardized effect size, Guyatt responsiveness index, and the minimum clinical important difference were calculated. Results Standardized effect size of the Activity of Daily Living Scale was 0.63, Guyatt responsiveness index was 1.4, area under the curve was 0.83 (95% confidence interval: 0.72, 0.94), and the minimum clinical important difference corresponded to an increase of 7.1 percentile points. Standardized effect size of the Numeric Pain Rating Scale was 0.72, Guyatt responsiveness index was 2.2, area under the curve was 0.80 (95% confidence interval: 0.70, 0.92), and the minimum clinical important difference corresponded to a decrease of 1.16 points. Conclusion Information from this study may be helpful to therapists when evaluating the effectiveness of rehabilitation intervention on physical function and pain, and to power future clinical trials on patients with patellofemoral pain. PMID:19229444

Responsiveness of the activities of daily living scale of the knee outcome survey and numeric pain rating scale in patients with patellofemoral pain.

PubMed

Piva, Sara R; Gil, Alexandra B; Moore, Charity G; Fitzgerald, G Kelley

2009-02-01

To assess internal and external responsiveness of the Activity of Daily Living Scale of the Knee Outcome Survey and Numeric Pain Rating Scale on patients with patellofemoral pain. One group pre-post design. A total of 60 individuals with patellofemoral pain (33 women; mean age 29.9 (standard deviation 9.6) years). The Activity of Daily Living Scale and the Numeric Pain Rating Scale were assessed before and after 8 weeks of physical therapy program. Patients completed a global rating of change scale at the end of therapy. The standardized effect size, Guyatt responsiveness index, and the minimum clinical important difference were calculated. Standardized effect size of the Activity of Daily Living Scale was 0.63, Guyatt responsiveness index was 1.4, area under the curve was 0.83 (95% confidence interval: 0.72, 0.94), and the minimum clinical important difference corresponded to an increase of 7.1 percentile points. Standardized effect size of the Numeric Pain Rating Scale was 0.72, Guyatt responsiveness index was 2.2, area under the curve was 0.80 (95% confidence interval: 0.70, 0.92), and the minimum clinical important difference corresponded to a decrease of 1.16 points. Information from this study may be helpful to therapists when evaluating the effectiveness of rehabilitation intervention on physical function and pain, and to power future clinical trials on patients with patellofemoral pain.

40 CFR Table 5 to Subpart Mmmmm of... - Continuous Compliance With Emission Limits and Operating Limits

Code of Federal Regulations, 2010 CFR

2010-07-01

... performance test. v. If you use a venturi scrubber, maintaining the daily average pressure drop across the.... Each new or reconstructed flame lamination affected source using a scrubber a. Maintain the daily average scrubber inlet liquid flow rate above the minimum value established during the performanceb...

Special features of the dayCent modeling package and additional procedures for parameterization, calibration, validation, and applications

USDA-ARS?s Scientific Manuscript database

DayCent (Daily Century) is a biogeochemical model of intermediate complexity used to simulate flows of carbon and nutrients for crop, grassland, forest, and savanna ecosystems. Required model inputs are: soil texture, current and historical land use, vegetation cover, and daily maximum/minimum tempe...

40 CFR Table 5 to Subpart Mmmmm of... - Continuous Compliance With Emission Limits and Operating Limits

Code of Federal Regulations, 2011 CFR

2011-07-01

.... Each new or reconstructed flame lamination affected source using a scrubber a. Maintain the daily average scrubber inlet liquid flow rate above the minimum value established during the performanceb. Maintain the daily average scrubber effluent pH within the operating range established during the...

Long-term changes (1980-2003) in total ozone time series over Northern Hemisphere midlatitudes

NASA Astrophysics Data System (ADS)

Białek, Małgorzata

2006-03-01

Long-term changes in total ozone time series for Arosa, Belsk, Boulder and Sapporo stations are examined. For each station we analyze time series of the following statistical characteristics of the distribution of daily ozone data: seasonal mean, standard deviation, maximum and minimum of total daily ozone values for all seasons. The iterative statistical model is proposed to estimate trends and long-term changes in the statistical distribution of the daily total ozone data. The trends are calculated for the period 1980-2003. We observe lessening of negative trends in the seasonal means as compared to those calculated by WMO for 1980-2000. We discuss a possibility of a change of the distribution shape of ozone daily data using the Kolmogorov-Smirnov test and comparing trend values in the seasonal mean, standard deviation, maximum and minimum time series for the selected stations and seasons. The distribution shift toward lower values without a change in the distribution shape is suggested with the following exceptions: the spreading of the distribution toward lower values for Belsk during winter and no decisive result for Sapporo and Boulder in summer.

Comparative production of channel catfish and channel x blue hybrid catfish subjected to two minimum dissolved oxygen concentrations

USDA-ARS?s Scientific Manuscript database

The effect of daily minimum dissolved oxygen concentration on growth and yield (kg/ha) of the channel catfish (Ictalurus punctatus) and the channel x blue hybrid catfish (I. punctatus female x I. furcatus male), which shared the Jubilee strain of channel catfish as the maternal parent, was evaluated...

Performance measures for lower gastrointestinal endoscopy: a European Society of Gastrointestinal Endoscopy (ESGE) quality improvement initiative

PubMed Central

Thomas-Gibson, Siwan; Bugajski, Marek; Bretthauer, Michael; Rees, Colin J; Dekker, Evelien; Hoff, Geir; Jover, Rodrigo; Suchanek, Stepan; Ferlitsch, Monika; Anderson, John; Roesch, Thomas; Hultcranz, Rolf; Racz, Istvan; Kuipers, Ernst J; Garborg, Kjetil; East, James E; Rupinski, Maciej; Seip, Birgitte; Bennett, Cathy; Senore, Carlo; Minozzi, Silvia; Bisschops, Raf; Domagk, Dirk; Valori, Roland; Spada, Cristiano; Hassan, Cesare; Dinis-Ribeiro, Mario; Rutter, Matthew D

2017-01-01

The European Society of Gastrointestinal Endoscopy and United European Gastroenterology present a short list of key performance measures for lower gastrointestinal endoscopy. We recommend that endoscopy services across Europe adopt the following seven key performance measures for lower gastrointestinal endoscopy for measurement and evaluation in daily practice at a center and endoscopist level: 1 rate of adequate bowel preparation (minimum standard 90%); 2 cecal intubation rate (minimum standard 90%); 3 adenoma detection rate (minimum standard 25%); 4 appropriate polypectomy technique (minimum standard 80%); 5 complication rate (minimum standard not set); 6 patient experience (minimum standard not set); 7 appropriate post-polypectomy surveillance recommendations (minimum standard not set). Other identified performance measures have been listed as less relevant based on an assessment of their importance, scientific acceptability, feasibility, usability, and comparison to competing measures. PMID:28507745

Climatic change on the Gulf of Fonseca (Central America) using two-step statistical downscaling of CMIP5 model outputs

NASA Astrophysics Data System (ADS)

Ribalaygua, Jaime; Gaitán, Emma; Pórtoles, Javier; Monjo, Robert

2018-05-01

A two-step statistical downscaling method has been reviewed and adapted to simulate twenty-first-century climate projections for the Gulf of Fonseca (Central America, Pacific Coast) using Coupled Model Intercomparison Project (CMIP5) climate models. The downscaling methodology is adjusted after looking for good predictor fields for this area (where the geostrophic approximation fails and the real wind fields are the most applicable). The method's performance for daily precipitation and maximum and minimum temperature is analysed and revealed suitable results for all variables. For instance, the method is able to simulate the characteristic cycle of the wet season for this area, which includes a mid-summer drought between two peaks. Future projections show a gradual temperature increase throughout the twenty-first century and a change in the features of the wet season (the first peak and mid-summer rainfall being reduced relative to the second peak, earlier onset of the wet season and a broader second peak).

Response of winter and spring wheat grain yields to meteorological variation

NASA Technical Reports Server (NTRS)

Feyerherm, A. M.; Kanemasu, E. T.; Paulsen, G. M.

1977-01-01

Mathematical models which quantify the relation of wheat yield to selected weather-related variables are presented. Other sources of variation (amount of applied nitrogen, improved varieties, cultural practices) have been incorporated in the models to explain yield variation both singly and in combination with weather-related variables. Separate models were developed for fall-planted (winter) and spring-planted (spring) wheats. Meteorological variation is observed, basically, by daily measurements of minimum and maximum temperatures, precipitation, and tabled values of solar radiation at the edge of the atmosphere and daylength. Two different soil moisture budgets are suggested to compute simulated values of evapotranspiration; one uses the above-mentioned inputs, the other uses the measured temperatures and precipitation but replaces the tabled values (solar radiation and daylength) by measured solar radiation and satellite-derived multispectral scanner data to estimate leaf area index. Weather-related variables are defined by phenological stages, rather than calendar periods, to make the models more universally applicable.

The Slowly Varying Corona. I. Daily Differential Emission Measure Distributions Derived from EVE Spectra

NASA Astrophysics Data System (ADS)

Schonfeld, S. J.; White, S. M.; Hock-Mysliwiec, R. A.; McAteer, R. T. J.

2017-08-01

Daily differential emission measure (DEM) distributions of the solar corona are derived from spectra obtained by the Extreme-ultraviolet Variability Experiment (EVE) over a 4 yr period starting in 2010 near solar minimum and continuing through the maximum of solar cycle 24. The DEMs are calculated using six strong emission features dominated by Fe lines of charge states viii, ix, xi, xii, xiv, and xvi that sample the nonflaring coronal temperature range 0.3-5 MK. A proxy for the non-Fe xviii emission in the wavelength band around the 93.9 Å line is demonstrated. There is little variability in the cool component of the corona (T < 1.3 MK) over the 4 yr, suggesting that the quiet-Sun corona does not respond strongly to the solar cycle, whereas the hotter component (T > 2.0 MK) varies by more than an order of magnitude. A discontinuity in the behavior of coronal diagnostics in 2011 February-March, around the time of the first X-class flare of cycle 24, suggests fundamentally different behavior in the corona under solar minimum and maximum conditions. This global state transition occurs over a period of several months. The DEMs are used to estimate the thermal energy of the visible solar corona (of order 1031 erg), its radiative energy loss rate ((2.5-8) × {10}27 erg s-1), and the corresponding energy turnover timescale (about an hour). The uncertainties associated with the DEMs and these derived values are mostly due to the coronal Fe abundance and density and the CHIANTI atomic line database.

Water quality in Rhode River at Smithsonian Institution Pier near Annapolis, Maryland, January 1976 through December 1978

USGS Publications Warehouse

Cory, Robert L.; Dresler, P.V.

1980-01-01

Water temperature, salinity, turbidity, dissolved oxygen, pH, and water level data were continuously monitored and recorded from the Smithsonian Institution pier near Annapolis, Md., from January 1976 through December 1978. Daily maximum and minimum values are tabulated and summarized, and monthly averages and extremes are presented. Water temperature ranged from 0.0 to 33.9 Celsius. Both high and low extreme values exceeded those recorded during the previous 6 years. Salinity patterns showed normal seasonal variations and were related to the Susquehanna River inflow, which controls the upper bay salinity. Salinity between 13 and 15 parts per thousand in November and December 1978 were the highest recorded over a 9-year period. Turbidity varied seasonally, with lowest values in winter and highest in spring. Dissolved oxygen ranged from 2.0 to 18.7 milligrams per liter. Large variations between summertime daily minima and maxima indicated the high state of eutrophication of the water being monitored. Hydrogen-ion activity (pH) ranged from 7.0 to 10.2 over the 3-year period. The pH changes reflect daily variation in partial pressure of carbon dioxide, which varies inversely with the dissolved oxygen. Water level variation at the monitoring site for the 3-year period was 1.89 meters, with highest water 0.59 meter above mean high water and lowest 0.83 meter below mean low water. An apparent decline of 0.07 meter below previously recorded mean high and mean low water was associated with stronger winds and a prevalance of westerly winds in February during the winter of 1976-1977. (USGS)

Morphology, surface temperatures, and northern limits of columnar cacti in the Sonoran Desert

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

Nobel, P.S.

1980-02-01

Interspecific morphological differences and intraspecific morphological changes with latitude were evaluated to help examine the distributional ranges of Carnegiea gigantea, Lemaireocereus thurberi, Lophocereus schottii, Pachycereus pecten-aboriginum, and P. pringlei in the Sonoran Desert (US and Mexico). A computer model, which predicted the average surface temperature of the stem within 1/sup 0/C of that measured hourly throughout a 24-h period, was particularly useful in studying the thermal relations of the stem apex, where the lowest surface temperature occurred. Simulated increases in stem diameter raised the minimum apical temperature for C. gigantea and may help account for the extension of its rangemore » to higher latitudes than the other species studied. However, diameter increases led to a slight decrease in minimum apical temperatures for Lophocereus schottii. The immature stems of L. schottii are morphologically distinct from the mature stems, which caused minimum apical temperatures to be 1.6/sup 0/C lower for the immature stems under given environmental conditions; thus, freezing damage to the immature stems could limit the northward extension of the range of this species. As the apical pubescence in the simulations was increased up to the normal amount (10 mm), the minimum apical temperature for the stem of C. gigantea increased 2.4/sup 0/C. Simulated increases in spine shading of the apexalso raised the minimum apical temperatures, again indicating the influence of morphological features on the temperature of the meristematic region.« less

40 CFR 63.1365 - Test methods and initial compliance procedures.

Code of Federal Regulations, 2013 CFR

2013-07-01

... design minimum and average temperature in the combustion zone and the combustion zone residence time. (B... establish the design minimum and average flame zone temperatures and combustion zone residence time, and... carbon bed temperature after regeneration, design carbon bed regeneration time, and design service life...

Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada

DOE PAGES

Eum, Hyung-Il; Gachon, Philippe; Laprise, René

2016-01-01

This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affectedmore » by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. Finally, these results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.« less

Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada

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

Eum, Hyung-Il; Gachon, Philippe; Laprise, René

This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affectedmore » by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. Finally, these results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.« less

Evaluation of Prospective Changes in Temperature Extremes for the CORDEX-Australasia Domain Using the NEX-GDDP Dataset

NASA Astrophysics Data System (ADS)

Turp, M. Tufan; An, Nazan; Kurnaz, M. Levent

2017-04-01

CORDEX-Australasia is a vast domain where comprises primarily Australia, New Zealand, and Papua New Guinea whilst it also covers the islands in the Pacific Ocean such as New Caledonia, Fiji, Tonga, Tuvalu, and Vanuatu as well. Climate of Australasia varies from tropical monsoonal and arid to moist temperate and alpine. The number of studies about the domain of Australasia is very limited and it is in urgent need of further efforts. This research points out the relationship between the climate change and temperature extremes over the domain of Australasia and it investigates the changes in the number of some specific temperature extreme indices (i.e. summer days, consecutive summer days, heat wave duration, very warm days, tropical nights, etc.) as described by the joint CCl/CLIVAR/JCOMM Expert Team (ET) on Climate Change Detection and Indices (ETCCDI). All these extreme indices were also calculated using the NASA Earth Exchange Global Daily Downscaled Projection (NEX-GDDP) dataset. In this study, all these index computations have been employed by utilizing ACCESS1-0 and MPI-ESM-MR global circulation models' bias corrected daily minimum and maximum air temperature variables, which were statistically downscaled to a 0.25 degrees x 0.25 degrees spatial resolution by the Climate Analytics Group and NASA Ames Research Center, under both medium-low and high emission trajectories (i.e. RCP4.5 and RCP8.5). Moreover, the analysis of the projected changes in the temperature extremes was applied for the period of 2081-2100 with respect to the reference period of 1986-2005. Acknowledgements: This research has been supported by Bogazici University Research Fund Grant Number 12220. Climate scenarios used were from the NEX-GDDP dataset, prepared by the Climate Analytics Group and NASA Ames Research Center using the NASA Earth Exchange, and distributed by the NASA Center for Climate Simulation (NCCS).

Measurement and simulation of evapotranspiration at a wetland site in the New Jersey Pinelands

USGS Publications Warehouse

Sumner, David M.; Nicholson, Robert S.; Clark, Kenneth L.

2012-01-01

Evapotranspiration (ET) was monitored above a wetland forest canopy dominated by pitch-pine in the New Jersey Pinelands during November 10, 2004-February 20, 2007, using an eddy-covariance method. Twelve-month ET totals ranged from 786 to 821 millimeters (mm). Minimum and maximum ET rates occurred during December-February and in July, respectively. Relations between ET and several environmental variables (incoming solar radiation, air temperature, relative humidity, soil moisture, and net radiation) were explored. Net radiation (r = 0.72) and air temperature (r = 0.73) were the dominant explanatory variables for daily ET. Air temperature was the dominant control on evaporative fraction with relatively more radiant energy used for ET at higher temperatures. Soil moisture was shown to limit ET during extended dry periods. With volumetric soil moisture below a threshold of about 0.15, the evaporative fraction decreased until rain ended the dry period, and the evaporative fraction sharply recovered. A modified Hargreaves ET model, requiring only easily obtainable daily temperature data, was shown to be effective at simulating measured ET values and has the potential for estimating historical or real-time ET at the wetland site. The average annual ET measured at the wetland site during 2005-06 (801 mm/yr) is about 32 percent higher than previously reported ET for three nearby upland sites during 2005-09. Periodic disturbance by fire and insect defoliation at the upland sites reduced ET. When only undisturbed periods were considered, the wetland ET was 17 percent higher than the undisturbed upland ET. Interannual variability in wetlands ET may be lower than that of uplands ET because the upland stands are more susceptible to periodic drought conditions, disturbance by fire, and insect defoliation. Precipitation during the study period at the nearby Indian Mills weather station was slightly higher than the long-term (1902-2011) annual mean of 1,173 millimeters (mm), with 1,325 and 1,396 mm of precipitation in 2005 and 2006, respectively.

Treating Vomiting

MedlinePlus

... those descibed below. Estimated Oral Fluid and Electrolyte Requirements by Body Weight Body Weight (in pounds) Minimum Daily Fluid Requirements (in ounces)* Electrolyte Solution Requirements for Mild Diarrhea ( ...

46 CFR 153.370 - Minimum relief valve setting for ambient temperature cargo tanks.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 5 2014-10-01 2014-10-01 false Minimum relief valve setting for ambient temperature... temperature cargo tanks. The relief valve setting for a containment system that carries a cargo at ambient temperature must at least equal the cargo's vapor pressure at 46 °C (approx. 115 °F). [CGD 81-078, 50 FR 21173...

46 CFR 153.370 - Minimum relief valve setting for ambient temperature cargo tanks.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 5 2013-10-01 2013-10-01 false Minimum relief valve setting for ambient temperature... temperature cargo tanks. The relief valve setting for a containment system that carries a cargo at ambient temperature must at least equal the cargo's vapor pressure at 46 °C (approx. 115 °F). [CGD 81-078, 50 FR 21173...

46 CFR 153.370 - Minimum relief valve setting for ambient temperature cargo tanks.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 5 2012-10-01 2012-10-01 false Minimum relief valve setting for ambient temperature... temperature cargo tanks. The relief valve setting for a containment system that carries a cargo at ambient temperature must at least equal the cargo's vapor pressure at 46 °C (approx. 115 °F). [CGD 81-078, 50 FR 21173...

46 CFR 153.370 - Minimum relief valve setting for ambient temperature cargo tanks.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 5 2010-10-01 2010-10-01 false Minimum relief valve setting for ambient temperature... temperature cargo tanks. The relief valve setting for a containment system that carries a cargo at ambient temperature must at least equal the cargo's vapor pressure at 46 °C (approx. 115 °F). [CGD 81-078, 50 FR 21173...

46 CFR 153.370 - Minimum relief valve setting for ambient temperature cargo tanks.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 5 2011-10-01 2011-10-01 false Minimum relief valve setting for ambient temperature... temperature cargo tanks. The relief valve setting for a containment system that carries a cargo at ambient temperature must at least equal the cargo's vapor pressure at 46 °C (approx. 115 °F). [CGD 81-078, 50 FR 21173...

Changing risk of spring frost damage in grapevines due to climate change? A case study in the Swiss Rhone Valley.

PubMed

Meier, Michael; Fuhrer, Jürg; Holzkämper, Annelie

2018-06-01

Late spring frost is a severe risk during early plant development. It may cause important economic damage to grapevine production. In a warming climate, late frost risk either could decline due to the reduction in frost days and an advancement of the last day of frost or increase due to a more pronounced shift forward of the start of the active growing period of the plants. These possibilities were analyzed in a case study for two locations in the lower Swiss Rhone Valley (Sion, Aigle) where viticulture is an important part of agriculture. Twelve phenology models were calibrated for the developmental stage BBCH09 (bud burst) using measured or reconstructed temperature data for two vineyards in Changins (1958 to 2012) and Leytron (1977 to 2014) together with observed phenological data. The day of year (DOY) for BBCH09 was then modelled for the years 1951 to 2050 using the best performing phenology model in combination with ten downscaled and bias-corrected climate scenarios. A 100-day period starting with BBCH09 was defined, during which daily mean and minimum temperatures were used to calculate three frost risk indices in each year. These indices were compared between the periods 1961-1990 (reference) and 2021-2050 (climate change scenario). Based on the average of the ensemble of climate model chains, BBCH09 advanced by 9 (range 7-11) (Aigle) and 7 (range 5-8) (Sion) days between the two time periods, similar to the shift in the last day of frost. The separate results of the different model chains suggest that, in the near future, late spring frost risk may increase or decrease, depending on location and climate change projections. While for the reference, the risk is larger at the warmer site (Sion) compared to that at the cooler site (Aigle), for the period 2021-2050, small shifts in both phenology and occurrence of frost (i.e., days with daily minimum temperature below 0 °C) lead to a small decrease in frost risk at the warmer but an increase at the cooler site. However, considerable uncertainties remain that are mostly related to climate model chains. Consequently, shifts in frost risk remain uncertain for the time period considered and the two study locations.

Changing risk of spring frost damage in grapevines due to climate change? A case study in the Swiss Rhone Valley

NASA Astrophysics Data System (ADS)

Meier, Michael; Fuhrer, Jürg; Holzkämper, Annelie

2018-06-01

Late spring frost is a severe risk during early plant development. It may cause important economic damage to grapevine production. In a warming climate, late frost risk either could decline due to the reduction in frost days and an advancement of the last day of frost or increase due to a more pronounced shift forward of the start of the active growing period of the plants. These possibilities were analyzed in a case study for two locations in the lower Swiss Rhone Valley (Sion, Aigle) where viticulture is an important part of agriculture. Twelve phenology models were calibrated for the developmental stage BBCH09 (bud burst) using measured or reconstructed temperature data for two vineyards in Changins (1958 to 2012) and Leytron (1977 to 2014) together with observed phenological data. The day of year (DOY) for BBCH09 was then modelled for the years 1951 to 2050 using the best performing phenology model in combination with ten downscaled and bias-corrected climate scenarios. A 100-day period starting with BBCH09 was defined, during which daily mean and minimum temperatures were used to calculate three frost risk indices in each year. These indices were compared between the periods 1961-1990 (reference) and 2021-2050 (climate change scenario). Based on the average of the ensemble of climate model chains, BBCH09 advanced by 9 (range 7-11) (Aigle) and 7 (range 5-8) (Sion) days between the two time periods, similar to the shift in the last day of frost. The separate results of the different model chains suggest that, in the near future, late spring frost risk may increase or decrease, depending on location and climate change projections. While for the reference, the risk is larger at the warmer site (Sion) compared to that at the cooler site (Aigle), for the period 2021-2050, small shifts in both phenology and occurrence of frost (i.e., days with daily minimum temperature below 0 °C) lead to a small decrease in frost risk at the warmer but an increase at the cooler site. However, considerable uncertainties remain that are mostly related to climate model chains. Consequently, shifts in frost risk remain uncertain for the time period considered and the two study locations.

Changing risk of spring frost damage in grapevines due to climate change? A case study in the Swiss Rhone Valley

NASA Astrophysics Data System (ADS)

Meier, Michael; Fuhrer, Jürg; Holzkämper, Annelie

2018-01-01

Late spring frost is a severe risk during early plant development. It may cause important economic damage to grapevine production. In a warming climate, late frost risk either could decline due to the reduction in frost days and an advancement of the last day of frost or increase due to a more pronounced shift forward of the start of the active growing period of the plants. These possibilities were analyzed in a case study for two locations in the lower Swiss Rhone Valley (Sion, Aigle) where viticulture is an important part of agriculture. Twelve phenology models were calibrated for the developmental stage BBCH09 (bud burst) using measured or reconstructed temperature data for two vineyards in Changins (1958 to 2012) and Leytron (1977 to 2014) together with observed phenological data. The day of year (DOY) for BBCH09 was then modelled for the years 1951 to 2050 using the best performing phenology model in combination with ten downscaled and bias-corrected climate scenarios. A 100-day period starting with BBCH09 was defined, during which daily mean and minimum temperatures were used to calculate three frost risk indices in each year. These indices were compared between the periods 1961-1990 (reference) and 2021-2050 (climate change scenario). Based on the average of the ensemble of climate model chains, BBCH09 advanced by 9 (range 7-11) (Aigle) and 7 (range 5-8) (Sion) days between the two time periods, similar to the shift in the last day of frost. The separate results of the different model chains suggest that, in the near future, late spring frost risk may increase or decrease, depending on location and climate change projections. While for the reference, the risk is larger at the warmer site (Sion) compared to that at the cooler site (Aigle), for the period 2021-2050, small shifts in both phenology and occurrence of frost (i.e., days with daily minimum temperature below 0 °C) lead to a small decrease in frost risk at the warmer but an increase at the cooler site. However, considerable uncertainties remain that are mostly related to climate model chains. Consequently, shifts in frost risk remain uncertain for the time period considered and the two study locations.

OSO 8 observations of wave propagation in the solar chromosphere and transition region

NASA Technical Reports Server (NTRS)

Chipman, E. G.

1978-01-01

The University of Colorado instrument on OSO 8 has been used to observe relative phases of the 300-s intensity variation between the temperature-minimum region and several emission lines formed in the solar chromosphere and chromosphere-corona transition region. The lines used are due to Fe II, Si II, C II, Si IV, and C IV. The scattered light in the spectrograph, which originates almost entirely in the spectral region between 1700 and 1900 A, was used as a probe of the temperature-minimum region. The lines of Fe II, Si II, and C II show almost identical delays of approximately 30 s relative to the temperature minimum, while the intensity oscillations of the lines of Si IV and C IV appear to lead the temperature-minimum intensity oscillations by about 10 s.

The Minimum Data Set Prevalence of Restraint Quality Indicator: Does It Reflect Differences in Care?

ERIC Educational Resources Information Center

Schnelle, John F.; Bates-Jensen, Barbara M.; Levy-Storms, Lene; Grbic, Valena; Yoshii, June; Cadogan, Mary; Simmons, Sandra F.

2004-01-01

Purpose: This study investigated whether the use of restraining devices and related measures of care quality are different in nursing homes that score in the upper and lower quartiles on the Minimum Data Set (MDS) "prevalence of restraint" quality indicator, which assesses daily use of restraining devices when residents are out of bed. Design and…

25 CFR 36.96 - May students be required to assist with daily or weekly cleaning?

Code of Federal Regulations, 2010 CFR

2010-04-01

... 25 Indians 1 2010-04-01 2010-04-01 false May students be required to assist with daily or weekly cleaning? 36.96 Section 36.96 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR EDUCATION MINIMUM ACADEMIC STANDARDS FOR THE BASIC EDUCATION OF INDIAN CHILDREN AND NATIONAL CRITERIA FOR DORMITORY...

25 CFR 36.96 - May students be required to assist with daily or weekly cleaning?

Code of Federal Regulations, 2014 CFR

2014-04-01

... 25 Indians 1 2014-04-01 2014-04-01 false May students be required to assist with daily or weekly cleaning? 36.96 Section 36.96 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR EDUCATION MINIMUM ACADEMIC STANDARDS FOR THE BASIC EDUCATION OF INDIAN CHILDREN AND NATIONAL CRITERIA FOR DORMITORY...

25 CFR 36.96 - May students be required to assist with daily or weekly cleaning?

Code of Federal Regulations, 2011 CFR

2011-04-01

... 25 Indians 1 2011-04-01 2011-04-01 false May students be required to assist with daily or weekly cleaning? 36.96 Section 36.96 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR EDUCATION MINIMUM ACADEMIC STANDARDS FOR THE BASIC EDUCATION OF INDIAN CHILDREN AND NATIONAL CRITERIA FOR DORMITORY...

25 CFR 36.96 - May students be required to assist with daily or weekly cleaning?

Code of Federal Regulations, 2012 CFR

2012-04-01

... 25 Indians 1 2012-04-01 2011-04-01 true May students be required to assist with daily or weekly cleaning? 36.96 Section 36.96 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR EDUCATION MINIMUM ACADEMIC STANDARDS FOR THE BASIC EDUCATION OF INDIAN CHILDREN AND NATIONAL CRITERIA FOR DORMITORY...

25 CFR 36.96 - May students be required to assist with daily or weekly cleaning?

Code of Federal Regulations, 2013 CFR

2013-04-01

... 25 Indians 1 2013-04-01 2013-04-01 false May students be required to assist with daily or weekly cleaning? 36.96 Section 36.96 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR EDUCATION MINIMUM ACADEMIC STANDARDS FOR THE BASIC EDUCATION OF INDIAN CHILDREN AND NATIONAL CRITERIA FOR DORMITORY...

The Elderly Population with Chronic Functional Disability: Implications for Home Care Eligibility.

ERIC Educational Resources Information Center

Stone, Robyn I.; Murtaugh, Christopher M.

1990-01-01

Assessed effect of changes in minimum number of activities of daily living (ALD) and instrumental activities of daily living (IADL) limitations, types of help, and duration of disability required on size of population potentially eligible for home care benefits. Only 411,000 elders met restrictive disability criteria; over 4 million would qualify…

Prediction of summer maximum and minimum temperature over the central and western United States: the roles of soil moisture and sea surface temperature

USGS Publications Warehouse

Alfaro, Eric J.; Gershunov, Alexander; Cayan, Daniel R.

2006-01-01

A statistical model based on canonical correlation analysis (CCA) was used to explore climatic associations and predictability of June–August (JJA) maximum and minimum surface air temperatures (Tmax and Tmin) as well as the frequency of Tmax daily extremes (Tmax90) in the central and western United States (west of 90°W). Explanatory variables are monthly and seasonal Pacific Ocean SST (PSST) and the Climate Division Palmer Drought Severity Index (PDSI) during 1950–2001. Although there is a positive correlation between Tmax and Tmin, the two variables exhibit somewhat different patterns and dynamics. Both exhibit their lowest levels of variability in summer, but that of Tmax is greater than Tmin. The predictability of Tmax is mainly associated with local effects related to previous soil moisture conditions at short range (one month to one season), with PSST providing a secondary influence. Predictability of Tmin is more strongly influenced by large-scale (PSST) patterns, with PDSI acting as a short-range predictive influence. For both predictand variables (Tmax and Tmin), the PDSI influence falls off markedly at time leads beyond a few months, but a PSST influence remains for at least two seasons. The maximum predictive skill for JJA Tmin, Tmax, and Tmax90 is from May PSST and PDSI. Importantly, skills evaluated for various seasons and time leads undergo a seasonal cycle that has maximum levels in summer. At the seasonal time frame, summer Tmax prediction skills are greatest in the Midwest, northern and central California, Arizona, and Utah. Similar results were found for Tmax90. In contrast, Tmin skill is spread over most of the western region, except for clusters of low skill in the northern Midwest and southern Montana, Idaho, and northern Arizona.

Projected Changes in Temperature and Precipitation Extremes over China as Measured by 50-yr Return Values and Periods Based on a CMIP5 Ensemble

NASA Astrophysics Data System (ADS)

Xu, Ying; Gao, Xuejie; Giorgi, Filippo; Zhou, Botao; Shi, Ying; Wu, Jie; Zhang, Yongxiang

2018-04-01

Future changes in the 50-yr return level for temperature and precipitation extremes over mainland China are investigated based on a CMIP5 multi-model ensemble for RCP2.6, RCP4.5 and RCP8.5 scenarios. The following indices are analyzed: TXx and TNn (the annual maximum and minimum of daily maximum and minimum surface temperature), RX5day (the annual maximum consecutive 5-day precipitation) and CDD (maximum annual number of consecutive dry days). After first validating the model performance, future changes in the 50-yr return values and return periods for these indices are investigated along with the inter-model spread. Multi-model median changes show an increase in the 50-yr return values of TXx and a decrease for TNn, more specifically, by the end of the 21st century under RCP8.5, the present day 50-yr return period of warm events is reduced to 1.2 yr, while extreme cold events over the country are projected to essentially disappear. A general increase in RX5day 50-yr return values is found in the future. By the end of the 21st century under RCP8.5, events of the present RX5day 50-yr return period are projected to reduce to < 10 yr over most of China. Changes in CDD-50 show a dipole pattern over China, with a decrease in the values and longer return periods in the north, and vice versa in the south. Our study also highlights the need for further improvements in the representation of extreme events in climate models to assess the future risks and engineering design related to large-scale infrastructure in China.

Torpor and activity in a free-ranging tropical bat: implications for the distribution and conservation of mammals?

NASA Astrophysics Data System (ADS)

Geiser, Fritz; Stawski, Clare; Bondarenco, Artiom; Pavey, Chris R.

2011-05-01

Bats are most diverse in the tropics, but there are no quantitative data on torpor use for energy conservation by any tropical bat in the wild. We examined the thermal biology, activity patterns and torpor use of two tree-roosting long-eared bats ( Nyctophilus geoffroyi, 7.8 g) in tropical northern Australia in winter using temperature telemetry. Bats commenced activity about 20 min after sunset, ended activity about 2.5 h before sunrise and entered torpor everyday in the early morning even when minimum ambient temperatures ( T a) were as high as 23°C. On average, bats remained torpid for almost 5 h, mean minimum skin temperature ( T skin) measured was 22.8 ± 0.1°C and daily T skin minima were correlated with T a. Our study shows that even in the tropics, torpor is frequently employed by bats, suggesting that worldwide most bat species are heterothermic and use torpor for energy conservation. We propose that the ability of employing torpor and the resulting highly plastic energy requirements may partially explain why these small insectivorous bats can inhabit almost the entire Australian continent despite vastly different climatic and likely trophic conditions. Reduced energy requirements also may permit survival in degraded or modified habitats, reduce the need for foraging and reduce exposure to predators. Thus, the ability to employ torpor may be one important reason for why most Australian bats and other heterothermic mammals have not gone extinct whereas many obligatory homeothermic mammals that cannot employ torpor and have high energy and foraging requirements have suffered high rates of extinctions.

[Temporal change in annual air temperature and heat island effect in a coastal city and an inland city at mid-latitude in China during 1956-1998].

PubMed

Chao, Lu-men; Sun, Jian-xin

2009-12-01

Temporal changes in air temperature and urban heat island (UHI) effects during 1956-1998 were compared between a coastal city, Ji' nan, and an inland city, Xi' an, which were similar in latitude, size and development. During 1956-1978, except that the annual mean minimum temperature in Ji' nan increased by 0.37 degrees C x 10 a(-1), the temperature variables in the two cities did not display any apparent trend. During 1979-1998, all temperature variables of the two cities showed an increasing trend. Comparing with that in Ji' nan, the increasing rate of annual mean maximum temperature and annual mean temperature in Xi' an was greater, but that of annual mean minimum temperature was smaller. In the two cities, heat island effect occurred during 1956-1978 but without any apparent trend, whereas during 1979-1998, this effect increased with time, especially in Xi' an where the annual mean minimum temperature and annual mean temperature increased by 0.22 degrees C x 10 a(-1) and 0.32 degrees C x 10 a(-1), respectively. Both the level and the inter-annual variation of the heat island effect were much greater in Ji' nan than in Xi' an, but the increasing rate of this effect was greater in Xi' an than in Ji' nan. Obvious differences were observed in the increasing rate of annual mean maximum air temperature, annual mean air temperature, and annual mean minimum temperature as well as the heat island effect in Ji' nan, whereas negligible differences were found in Xi' an. Among the three temperature variables, annual mean minimum temperature displayed the most obvious increasing trend and was most affected by heat island effect, while annual mean maximum temperature was most variable inter-annually. Geographical location not only affected the magnitude of urban warming, but also affected the mode of urban warming and the strength of heat island effect.

Future changes of temperature and heat waves in Ontario, Canada

NASA Astrophysics Data System (ADS)

Li, Zhong; Huang, Guohe; Huang, Wendy; Lin, Qianguo; Liao, Renfei; Fan, Yurui

2018-05-01

Apparent changes in the temperature patterns in recent years brought many challenges to the province of Ontario, Canada. As the need for adapting to climate change challenges increases, the development of reliable climate projections becomes a crucial task. In this study, a regional climate modeling system, Providing Regional Climates for Impacts Studies (PRECIS), is used to simulate the temperature patterns in Ontario. Three PRECIS runs with a resolution of 25 km × 25 km are carried out to simulate the present (1961-1990) temperature variations. There is a good match between the simulated and observed data, which validates the performance of PRECIS in reproducing temperature changes in Ontario. Future changes of daily maximum, mean, and minimum temperatures during the period 2071-2100 are then projected under the IPCC SRES A2 and B2 emission scenarios using PRECIS. Spatial variations of annual mean temperature, mean diurnal range, and temperature seasonality are generated. Furthermore, heat waves defined based on the exceedance of local climatology and their temporal and spatial characteristics are analyzed. The results indicate that the highest temperature and the most intensive heat waves are most likely to occur at the Toronto-Windsor corridor in Southern Ontario. The Northern Ontario, in spite of the relatively low projected temperature, would be under the risk of long-lasting heat waves, and thus needs effective measures to enhance its climate resilience in the future. This study can assist the decision makers in better understanding the future temperature changes in Ontario and provide decision support for mitigating heat-related loss.

Dynamic temperature and humidity environmental profiles: impact for future emergency and disaster preparedness and response.

PubMed

Ferguson, William J; Louie, Richard F; Tang, Chloe S; Paw U, Kyaw Tha; Kost, Gerald J

2014-02-01

During disasters and complex emergencies, environmental conditions can adversely affect the performance of point-of-care (POC) testing. Knowledge of these conditions can help device developers and operators understand the significance of temperature and humidity limits necessary for use of POC devices. First responders will benefit from improved performance for on-site decision making. To create dynamic temperature and humidity profiles that can be used to assess the environmental robustness of POC devices, reagents, and other resources (eg, drugs), and thereby, to improve preparedness. Surface temperature and humidity data from the National Climatic Data Center (Asheville, North Carolina USA) was obtained, median hourly temperature and humidity were calculated, and then mathematically stretched profiles were created to include extreme highs and lows. Profiles were created for: (1) Banda Aceh, Indonesia at the time of the 2004 Tsunami; (2) New Orleans, Louisiana USA just before and after Hurricane Katrina made landfall in 2005; (3) Springfield, Massachusetts USA for an ambulance call during the month of January 2009; (4) Port-au-Prince, Haiti following the 2010 earthquake; (5) Sendai, Japan for the March 2011 earthquake and tsunami with comparison to the colder month of January 2011; (6) New York, New York USA after Hurricane Sandy made landfall in 2012; and (7) a 24-hour rescue from Hawaii USA to the Marshall Islands. Profiles were validated by randomly selecting 10 days and determining if (1) temperature and humidity points fell inside and (2) daily variations were encompassed. Mean kinetic temperatures (MKT) were also assessed for each profile. Profiles accurately modeled conditions during emergency and disaster events and enclosed 100% of maximum and minimum temperature and humidity points. Daily variations also were represented well with 88.6% (62/70) of temperature readings and 71.1% (54/70) of relative humidity readings falling within diurnal patterns. Days not represented well primarily had continuously high humidity. Mean kinetic temperature was useful for severity ranking. Simulating temperature and humidity conditions clearly reveals operational challenges encountered during disasters and emergencies. Understanding of environmental stresses and MKT leads to insights regarding operational robustness necessary for safe and accurate use of POC devices and reagents. Rescue personnel should understand these principles before performing POC testing in adverse environments.

Evaluation of the Environmental Bias on Accelerometer-Measured Total Daily Activity Counts and Owner Survey Responses in Dogs with Osteoarthritis.

PubMed

Katz, Erin M; Scott, Ruth M; Thomson, Christopher B; Mesa, Eileen; Evans, Richard; Conzemius, Michael G

2017-11-01

Objective  To determine if environmental variables affect the average daily activity counts (AC) of dogs with osteoarthritis (OA) and/or owners' perception of their dog's clinical signs or quality of life. Methods  The AC and Canine Brief Pain Inventory (CBPI) owner questionnaires of 62 dogs with OA were compared with daily environmental variables including the following: average temperature (°C), high temperature (°C), low temperature (°C), relative humidity (%), total precipitation (mm), average barometric pressure (hPa) and total daylight hours. Results  Daily AC significantly correlated with average temperature and total daylight hours, but average temperature and total daylight hours accounted for less than 1% of variation in AC. No other significant relationships were found between daily AC and daily high temperature, low temperature, relative humidity, total precipitation or average barometric pressure. No statistical relationship was found between daily AC and the CBPI, nor between environmental variables and the CBPI. Canine Brief Pain Inventory scores for pain severity and pain interference decreased significantly over the test period. Clinical Significance  The relationship between daily AC and average temperature and total daylight hours was significant, but unlikely to be clinically significant. Thus, environmental variables do not appear to have a clinically relevant bias on AC or owner CBPI questionnaires. The decrease over time in CBPI pain severity and pain interference values suggests owners completing the CBPI in this study were influenced by a caregiver placebo effect. Schattauer GmbH Stuttgart.

Increased coronary heart disease and stroke hospitalisations from ambient temperatures in Ontario

PubMed Central

Bai, Li; Li, Qiongsi; Wang, Jun; Lavigne, Eric; Gasparrini, Antonio; Copes, Ray; Yagouti, Abderrahmane; Burnett, Richard T; Goldberg, Mark S; Cakmak, Sabit; Chen, Hong

2018-01-01

Objective To assess the associations between ambient temperatures and hospitalisations for coronary heart disease (CHD) and stroke. Methods Our study comprised all residents living in Ontario, Canada, 1996–2013. For each of 14 health regions, we fitted a distributed lag non-linear model to estimate the cold and heat effects on hospitalisations from CHD, acute myocardial infarction (AMI), stroke and ischaemic stroke, respectively. These effects were pooled using a multivariate meta-analysis. We computed attributable hospitalisations for cold and heat, defined as temperatures above and below the optimum temperature (corresponding to the temperature of minimum morbidity) and for moderate and extreme temperatures, defined using cut-offs at the 2.5th and 97.5th temperature percentiles. Results Between 1996 and 2013, we identified 1.4 million hospitalisations from CHD and 355 837 from stroke across Ontario. On cold days with temperature corresponding to the 1st percentile of temperature distribution, we found a 9% increase in daily hospitalisations for CHD (95% CI 1% to 16%), 29% increase for AMI (95% CI 15% to 45%) and 11% increase for stroke (95% CI 1% to 22%) relative to days with an optimal temperature. High temperatures (the 99th percentile) also increased CHD hospitalisations by 6% (95% CI 1% to 11%) relative to the optimal temperature. These estimates translate into 2.49% of CHD hospitalisations attributable to cold and 1.20% from heat. Additionally, 1.71% of stroke hospitalisations were attributable to cold. Importantly, moderate temperatures, rather than extreme temperatures, yielded the most of the cardiovascular burdens from temperatures. Conclusions Ambient temperatures, especially in moderate ranges, may be an important risk factor for cardiovascular-related hospitalisations. PMID:29101264

Processing and Monthly Summaries of Downscaled Climate Data for Knoxville, Tennessee and Surrounding Region

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

Sylvester, Linda; Omitaomu, Olufemi A.; Parish, Esther S.

2016-09-01

Oak Ridge National Laboratory (ORNL) and the City of Knoxville, Tennessee have partnered to work on a Laboratory Directed Research and Development (LDRD) project towards investigating climate change, mitigation, and adaptation measures in mid-sized cities. ORNL has statistically and dynamically downscaled ten Global Climate Models (GCMs) to both 1 km and 4 km resolutions. The processing and summary of those ten gridded datasets for use in a web-based tool is described. The summaries of each model are shown individually to assist in determining the similarities and differences between the model scenarios. The variables of minimum and maximum daily temperature andmore » total monthly precipitation are summarized for the area of Knoxville, Tennessee for the periods of 1980-2005 and 2025-2050.« less

Effects of Ambient Temperature on Growth Performance, Blood Metabolites, and Immune Cell Populations in Korean Cattle Steers.

PubMed

Kang, H J; Lee, I K; Piao, M Y; Gu, M J; Yun, C H; Kim, H J; Kim, K H; Baik, M

2016-03-01

Exposure to cold may affect growth performance in accordance with the metabolic and immunological activities of animals. We evaluated whether ambient temperature affects growth performance, blood metabolites, and immune cell populations in Korean cattle. Eighteen Korean cattle steers with a mean age of 10 months and a mean weight of 277 kg were used. All steers were fed a growing stage-concentrate diet at a rate of 1.5% of body weight and Timothy hay ad libitum for 8 weeks. Experimental period 1 (P1) was for four weeks from March 7 to April 3 and period 2 (P2) was four weeks from April 4 to May 1. Mean (8.7°C) and minimum (1.0°C) indoor ambient temperatures during P1 were lower (p<0.001) than those (13.0°C and 6.2°C, respectively) during P2. Daily dry matter feed intake in both the concentrate diet and forage groups was higher (p<0.001) during P2 than P1. Average daily weight gain was higher (p<0.001) during P2 (1.38 kg/d) than P1 (1.13 kg/d). Feed efficiency during P2 was higher (p = 0.015) than P1. Blood was collected three times; on March 7, April 4, and May 2. Nonesterified fatty acids (NEFA) were higher on March 7 than April 4 and May 2. Blood cortisol, glucose, and triglyceride concentrations did not differ among months. Blood CD4+, CD8+, and CD4+CD25+ T cell percentages were higher, while CD8+CD25+ T cell percentage was lower, during the colder month of March than during May, suggesting that ambient temperature affects blood T cell populations. In conclusion, colder ambient temperature decreased growth and feed efficiency in Korean cattle steers. The higher circulating NEFA concentrations observed in March compared to April suggest that lipolysis may occur at colder ambient temperatures to generate heat and maintain body temperature, resulting in lower feed efficiency in March.

Ambient high temperature and mortality in Jinan, China: A study of heat thresholds and vulnerable populations.

PubMed

Li, Jing; Xu, Xin; Yang, Jun; Liu, Zhidong; Xu, Lei; Gao, Jinghong; Liu, Xiaobo; Wu, Haixia; Wang, Jun; Yu, Jieqiong; Jiang, Baofa; Liu, Qiyong

2017-07-01

Understanding the health consequences of continuously rising temperatures-as is projected for China-is important in terms of developing heat-health adaptation and intervention programs. This study aimed to examine the association between mortality and daily maximum (T max ), mean (T mean ), and minimum (T min ) temperatures in warmer months; to explore threshold temperatures; and to identify optimal heat indicators and vulnerable populations. Daily data on temperature and mortality were obtained for the period 2007-2013. Heat thresholds for condition-specific mortality were estimated using an observed/expected analysis. We used a generalised additive model with a quasi-Poisson distribution to examine the association between mortality and T max /T min /T mean values higher than the threshold values, after adjustment for covariates. T max /T mean /T min thresholds were 32/28/24°C for non-accidental deaths; 32/28/24°C for cardiovascular deaths; 35/31/26°C for respiratory deaths; and 34/31/28°C for diabetes-related deaths. For each 1°C increase in T max /T mean /T min above the threshold, the mortality risk of non-accidental-, cardiovascular-, respiratory, and diabetes-related death increased by 2.8/5.3/4.8%, 4.1/7.2/6.6%, 6.6/25.3/14.7%, and 13.3/30.5/47.6%, respectively. Thresholds for mortality differed according to health condition when stratified by sex, age, and education level. For non-accidental deaths, effects were significant in individuals aged ≥65 years (relative risk=1.038, 95% confidence interval: 1.026-1.050), but not for those ≤64 years. For most outcomes, women and people ≥65 years were more vulnerable. High temperature significantly increases the risk of mortality in the population of Jinan, China. Climate change with rising temperatures may bring about the situation worse. Public health programs should be improved and implemented to prevent and reduce health risks during hot days, especially for the identified vulnerable groups. Copyright © 2017. Published by Elsevier Inc.

Effects of diurnal variations in temperature on non-accidental mortality among the elderly population of Montreal, Québec, 1984-2007.

PubMed

Vutcovici, Maria; Goldberg, Mark S; Valois, Marie-France

2014-07-01

The association between ambient temperature and mortality has been studied extensively. Recent data suggest an independent role of diurnal temperature variations in increasing daily mortality. Elderly adults-a growing subgroup of the population in developed countries-may be more susceptible to the effects of temperature variations. The aim of this study was to determine whether variations in diurnal temperature were associated with daily non-accidental mortality among residents of Montreal, Québec, who were 65 years of age and over during the period between 1984 and 2007. We used distributed lag non-linear Poisson models constrained over a 30-day lag period, adjusted for temporal trends, mean daily temperature, and mean daily concentrations of nitrogen dioxide and ozone to estimate changes in daily mortality with diurnal temperature. We found, over the 30 day lag period, a cumulative increase in daily mortality of 5.12% [95% confidence interval (CI): 0.02-10.49%] for a change from 5.9 °C to 11.1 °C (25th to 75th percentiles) in diurnal temperature, and a 11.27% (95%CI: 2.08-21.29%) increase in mortality associated with an increase of diurnal temperature from 11.1 to 17.5 °C (75th to 99th percentiles). The results were relatively robust to adjustment for daily mean temperature. We found that, in Montreal, diurnal variations in temperature are associated with a small increase in non-accidental mortality among the elderly population. More studies are needed in different geographical locations to confirm this effect.

Modeling monthly meteorological and agronomic frost days, based on minimum air temperature, in Center-Southern Brazil

NASA Astrophysics Data System (ADS)

Alvares, Clayton Alcarde; Sentelhas, Paulo César; Stape, José Luiz

2017-09-01

Although Brazil is predominantly a tropical country, frosts are observed with relative high frequency in the Center-Southern states of the country, affecting mainly agriculture, forestry, and human activities. Therefore, information about the frost climatology is of high importance for planning of these activities. Based on that, the aims of the present study were to develop monthly meteorological (F MET) and agronomic (F AGR) frost day models, based on minimum shelter air temperature (T MN), in order to characterize the temporal and spatial frost days variability in Center-Southern Brazil. Daily minimum air temperature data from 244 weather stations distributed across the study area were used, being 195 for developing the models and 49 for validating them. Multivariate regression models were obtained to estimate the monthly T MN, once the frost day models were based on this variable. All T MN regression models were statistically significant (p < 0.001), presenting adjusted R 2 between 0.69 and 0.90. Center-Southern Brazil is mainly hit by frosts from mid-fall (April) to mid-spring (October). The period from November to March is considered as frost-free, being very rare a frost day within that period. Monthly F MET and F AGR presented significant sigmoidal relationships with T MN (p < 0.0001), with adjusted R 2 above of 0.82. The residuals of the frost day models were random, which means that the sigmoidal models performed quite well for interpreting the frost day variability throughout the study area. The highlands of Santa Catarina, Rio Grande do Sul, São Paulo, and Minas Gerais had in average more than 25 and 13 frosts per year, respectively, for F MET and F AGR. The F MET and F AGR maps developed in this study for Center-Southern Brazil is a useful tool for farmers, foresters, and researchers, since they contribute to reduce frost spatial and temporal uncertainty, helping in planning project for strategic purposes. Furthermore, the monthly F MET and F AGR maps for this Brazilian region are the first zoning of these variables for the country.

Circadian misalignment affects sleep and medication use before and during spaceflight

PubMed Central

Flynn-Evans, Erin E; Barger, Laura K; Kubey, Alan A; Sullivan, Jason P; Czeisler, Charles A

2016-01-01

Sleep deficiency and the use of sleep-promoting medication are prevalent during spaceflight. Operations frequently dictate work during the biological night and sleep during the biological day, which contribute to circadian misalignment. We investigated whether circadian misalignment was associated with adverse sleep outcomes before (preflight) and during spaceflight missions aboard the International Space Station (ISS). Actigraphy and photometry data for 21 astronauts were collected over 3,248 days of long-duration spaceflight on the ISS and 11 days prior to launch (n=231 days). Sleep logs, collected one out of every 3 weeks in flight and daily on Earth, were used to determine medication use and subjective ratings of sleep quality. Actigraphy and photometry data were processed using Circadian Performance Simulation Software to calculate the estimated endogenous circadian temperature minimum. Sleep episodes were classified as aligned or misaligned relative to the estimated endogenous circadian temperature minimum. Mixed-effects regression models accounting for repeated measures were computed by data collection interval (preflight, flight) and circadian alignment status. The estimated endogenous circadian temperature minimum occurred outside sleep episodes on 13% of sleep episodes during preflight and on 19% of sleep episodes during spaceflight. The mean sleep duration in low-Earth orbit on the ISS was 6.4±1.2 h during aligned and 5.4±1.4 h (P<0.01) during misaligned sleep episodes. During aligned sleep episodes, astronauts rated their sleep quality as significantly better than during misaligned sleep episodes (66.8±17.7 vs. 60.2±21.0, P<0.01). Sleep-promoting medication use was significantly higher during misaligned (24%) compared with aligned (11%) sleep episodes (P<0.01). Use of any medication was significantly higher on days when sleep episodes were misaligned (63%) compared with when sleep episodes were aligned (49%; P<0.01). Circadian misalignment is associated with sleep deficiency and increased medication use during spaceflight. These findings suggest that there is an immediate need to deploy and assess effective countermeasures to minimize circadian misalignment and consequent adverse sleep outcomes both before and during spaceflight. PMID:28725719

Circadian misalignment affects sleep and medication use before and during spaceflight.

PubMed

Flynn-Evans, Erin E; Barger, Laura K; Kubey, Alan A; Sullivan, Jason P; Czeisler, Charles A

2016-01-01

Sleep deficiency and the use of sleep-promoting medication are prevalent during spaceflight. Operations frequently dictate work during the biological night and sleep during the biological day, which contribute to circadian misalignment. We investigated whether circadian misalignment was associated with adverse sleep outcomes before (preflight) and during spaceflight missions aboard the International Space Station (ISS). Actigraphy and photometry data for 21 astronauts were collected over 3,248 days of long-duration spaceflight on the ISS and 11 days prior to launch ( n =231 days). Sleep logs, collected one out of every 3 weeks in flight and daily on Earth, were used to determine medication use and subjective ratings of sleep quality. Actigraphy and photometry data were processed using Circadian Performance Simulation Software to calculate the estimated endogenous circadian temperature minimum. Sleep episodes were classified as aligned or misaligned relative to the estimated endogenous circadian temperature minimum. Mixed-effects regression models accounting for repeated measures were computed by data collection interval (preflight, flight) and circadian alignment status. The estimated endogenous circadian temperature minimum occurred outside sleep episodes on 13% of sleep episodes during preflight and on 19% of sleep episodes during spaceflight. The mean sleep duration in low-Earth orbit on the ISS was 6.4±1.2 h during aligned and 5.4±1.4 h ( P <0.01) during misaligned sleep episodes. During aligned sleep episodes, astronauts rated their sleep quality as significantly better than during misaligned sleep episodes (66.8±17.7 vs. 60.2±21.0, P <0.01). Sleep-promoting medication use was significantly higher during misaligned (24%) compared with aligned (11%) sleep episodes ( P <0.01). Use of any medication was significantly higher on days when sleep episodes were misaligned (63%) compared with when sleep episodes were aligned (49%; P <0.01). Circadian misalignment is associated with sleep deficiency and increased medication use during spaceflight. These findings suggest that there is an immediate need to deploy and assess effective countermeasures to minimize circadian misalignment and consequent adverse sleep outcomes both before and during spaceflight.

Impacts of updated green vegetation fraction data on WRF simulations of the 2006 European heat wave

NASA Astrophysics Data System (ADS)

Refslund, J.; Dellwik, E.; Hahmann, A. N.; Barlage, M. J.; Boegh, E.

2012-12-01

Climate change studies suggest an increase in heat wave occurrences over Europe in the coming decades. Extreme events with excessive heat and associated drought will impact vegetation growth and health and lead to alterations in the partitioning of the surface energy. In this study, the atmospheric conditions during the heat wave year 2006 over Europe were simulated using the Weather Research and Forecasting (WRF) model. To account for the drought effects on the vegetation, new high-resolution green vegetation fraction (GVF) data were developed for the domain using NDVI data from MODIS satellite observations. Many empirical relationships exist to convert NDVI to GVF and both a linear and a quadratic formulation were evaluated. The new GVF product has a spatial resolution of 1 km2 and a temporal resolution of 8 days. To minimize impacts from low-quality satellite retrievals in the NDVI series, as well as for comparison with the default GVF climatology in WRF, a new background climatology using 10 recent years of observations was also developed. The annual time series of the new GVF climatology was compared to the default WRF GVF climatology at 18 km2 grid resolution for the most common land use classes in the European domain. The new climatology generally has higher GVF levels throughout the year, in particular an extended autumnal growth season. Comparison of 2006 GVF with the climatology clearly indicates vegetation stresses related to heat and drought. The GVF product based on a quadratic NDVI relationship shows the best agreement with the magnitude and annual range of the default input data, in addition to including updated seasonality for various land use classes. The new GVF products were tested in WRF and found to work well for the spring of 2006 where the difference between the default and new GVF products was small. The WRF 2006 heat wave simulations were verified by comparison with daily gridded observations of mean, minimum and maximum temperature and daily precipitation. The simulation using the new GVF product with a quadratic relationship to NDVI resulted in a consistent improvement of modeled temperatures during the heat wave period, where the mean temperature cold bias of the model was reduced by 10% for the whole domain and by 30-50% in areas severely affected by the heat wave. More improvement was found in the simulation of minimum temperature and less in maximum temperature and the impact on precipitation was not significant. The results show that model simulations during heat waves and droughts, when vegetation condition deviates from climatology, require updated land surface properties in order to obtain reliably accurate results.

Daily rhythmicity of body temperature in the dog.

PubMed

Refinetti, R; Piccione, G

2003-08-01

Research over the past 50 years has demonstrated the existence of circadian or daily rhythmicity in the body core temperature of a large number of mammalian species. However, previous studies have failed to identify daily rhythmicity of body temperature in dogs. We report here the successful recording of daily rhythms of rectal temperature in female Beagle dogs. The low robustness of the rhythms (41% of maximal robustness) and the small range of excursion (0.5 degrees C) are probably responsible for previous failures in detecting rhythmicity in dogs.