Sex Ratios at Birth and Environmental Temperatures

NASA Astrophysics Data System (ADS)

Lerchl, Alexander

The relationship between average monthly air temperature and sex ratios at birth (SRB) was analyzed for children born in Germany during the period 1946-1995. Both the absolute temperature and - more markedly - the monthly temperature deviations from the overall mean were significantly positively correlated with the SRB (P<0.01) when temperatures were time-lagged against the SRB data by -10 or -11months. It is concluded that the sex of the offspring is partially determined by environmental temperatures prior to conception.

Analysis of the relationship between the monthly temperatures and weather types in Iberian Peninsula

NASA Astrophysics Data System (ADS)

Peña Angulo, Dhais; Trigo, Ricardo; Nicola, Cortesi; José Carlos, González-Hidalgo

2016-04-01

In this study, the relationship between the atmospheric circulation and weather types and the monthly average maximum and minimum temperatures in the Iberian Peninsula is modeled (period 1950-2010). The temperature data used were obtained from a high spatial resolution (10km x 10km) dataset (MOTEDAS dataset, Gonzalez-Hidalgo et al., 2015a). In addition, a dataset of Portuguese temperatures was used (obtained from the Portuguese Institute of Sea and Atmosphere). The weather type classification used was the one developed by Jenkinson and Collison, which was adapted for the Iberian Peninsula by Trigo and DaCamara (2000), using Sea Level Pressure data from NCAR/NCEP Reanalysis dataset (period 1951-2010). The analysis of the behaviour of monthly temperatures based on the weather types was carried out using a stepwise regression procedure of type forward to estimate temperatures in each cell of the considered grid, for each month, and for both maximum and minimum monthly average temperatures. The model selects the weather types that best estimate the temperatures. From the validation model it was obtained the error distribution in the time (months) and space (Iberian Peninsula). The results show that best estimations are obtained for minimum temperatures, during the winter months and in coastal areas. González-Hidalgo J.C., Peña-Angulo D., Brunetti M., Cortesi, C. (2015a): MOTEDAS: a new monthly temperature database for mainland Spain and the trend in temperature (1951-2010). International Journal of Climatology 31, 715-731. DOI: 10.1002/joc.4298

Comparison of ArcGIS and SAS Geostatistical Analyst to Estimate Population-Weighted Monthly Temperature for US Counties

PubMed Central

Xiaopeng, QI; Liang, WEI; BARKER, Laurie; LEKIACHVILI, Akaki; Xingyou, ZHANG

2015-01-01

Temperature changes are known to have significant impacts on human health. Accurate estimates of population-weighted average monthly air temperature for US counties are needed to evaluate temperature’s association with health behaviours and disease, which are sampled or reported at the county level and measured on a monthly—or 30-day—basis. Most reported temperature estimates were calculated using ArcGIS, relatively few used SAS. We compared the performance of geostatistical models to estimate population-weighted average temperature in each month for counties in 48 states using ArcGIS v9.3 and SAS v 9.2 on a CITGO platform. Monthly average temperature for Jan-Dec 2007 and elevation from 5435 weather stations were used to estimate the temperature at county population centroids. County estimates were produced with elevation as a covariate. Performance of models was assessed by comparing adjusted R2, mean squared error, root mean squared error, and processing time. Prediction accuracy for split validation was above 90% for 11 months in ArcGIS and all 12 months in SAS. Cokriging in SAS achieved higher prediction accuracy and lower estimation bias as compared to cokriging in ArcGIS. County-level estimates produced by both packages were positively correlated (adjusted R2 range=0.95 to 0.99); accuracy and precision improved with elevation as a covariate. Both methods from ArcGIS and SAS are reliable for U.S. county-level temperature estimates; However, ArcGIS’s merits in spatial data pre-processing and processing time may be important considerations for software selection, especially for multi-year or multi-state projects. PMID:26167169

Modeling Seasonal Influenza Transmission and Its Association with Climate Factors in Thailand Using Time-Series and ARIMAX Analyses.

PubMed

Chadsuthi, Sudarat; Iamsirithaworn, Sopon; Triampo, Wannapong; Modchang, Charin

2015-01-01

Influenza is a worldwide respiratory infectious disease that easily spreads from one person to another. Previous research has found that the influenza transmission process is often associated with climate variables. In this study, we used autocorrelation and partial autocorrelation plots to determine the appropriate autoregressive integrated moving average (ARIMA) model for influenza transmission in the central and southern regions of Thailand. The relationships between reported influenza cases and the climate data, such as the amount of rainfall, average temperature, average maximum relative humidity, average minimum relative humidity, and average relative humidity, were evaluated using cross-correlation function. Based on the available data of suspected influenza cases and climate variables, the most appropriate ARIMA(X) model for each region was obtained. We found that the average temperature correlated with influenza cases in both central and southern regions, but average minimum relative humidity played an important role only in the southern region. The ARIMAX model that includes the average temperature with a 4-month lag and the minimum relative humidity with a 2-month lag is the appropriate model for the central region, whereas including the minimum relative humidity with a 4-month lag results in the best model for the southern region.

On nonstationarity and antipersistency in global temperature series

NASA Astrophysics Data System (ADS)

KäRner, O.

2002-10-01

Statistical analysis is carried out for satellite-based global daily tropospheric and stratospheric temperature anomaly and solar irradiance data sets. Behavior of the series appears to be nonstationary with stationary daily increments. Estimating long-range dependence between the increments reveals a remarkable difference between the two temperature series. Global average tropospheric temperature anomaly behaves similarly to the solar irradiance anomaly. Their daily increments show antipersistency for scales longer than 2 months. The property points at a cumulative negative feedback in the Earth climate system governing the tropospheric variability during the last 22 years. The result emphasizes a dominating role of the solar irradiance variability in variations of the tropospheric temperature and gives no support to the theory of anthropogenic climate change. The global average stratospheric temperature anomaly proceeds like a 1-dim random walk at least up to 11 years, allowing good presentation by means of the autoregressive integrated moving average (ARIMA) models for monthly series.

Simulation of Tropical Pacific and Atlantic Oceans Using a HYbrid Coordinate Ocean Model

DTIC Science & Technology

2005-01-01

with respect to cotemporal 1m temperature measured by buoys. The cli- matology was created by averaging into monthly means, then calculating...inconsistency could result in part from the different temporal averaging intervals of the two temperature climatologies. This question is further assessed in...observational temperature datasets (drifter and Path- finder) have different temporal averaging intervals. This question is further assessed in

Seasonality of change: Summer warming rates do not fully represent effects of climate change on lake temperatures

USGS Publications Warehouse

Winslow, Luke; Read, Jordan S.; Hansen, Gretchen J. A.; Rose, Kevin C.; Robertson, Dale M.

2017-01-01

Responses in lake temperatures to climate warming have primarily been characterized using seasonal metrics of surface-water temperatures such as summertime or stratified period average temperatures. However, climate warming may not affect water temperatures equally across seasons or depths. We analyzed a long-term dataset (1981–2015) of biweekly water temperature data in six temperate lakes in Wisconsin, U.S.A. to understand (1) variability in monthly rates of surface- and deep-water warming, (2) how those rates compared to summertime average trends, and (3) if monthly heterogeneity in water temperature trends can be predicted by heterogeneity in air temperature trends. Monthly surface-water temperature warming rates varied across the open-water season, ranging from 0.013 in August to 0.073°C yr−1 in September (standard deviation [SD]: 0.025°C yr−1). Deep-water trends during summer varied less among months (SD: 0.006°C yr−1), but varied broadly among lakes (–0.056°C yr−1 to 0.035°C yr−1, SD: 0.034°C yr−1). Trends in monthly surface-water temperatures were well correlated with air temperature trends, suggesting monthly air temperature trends, for which data exist at broad scales, may be a proxy for seasonal patterns in surface-water temperature trends during the open water season in lakes similar to those studied here. Seasonally variable warming has broad implications for how ecological processes respond to climate change, because phenological events such as fish spawning and phytoplankton succession respond to specific, seasonal temperature cues.

Time-series modeling and prediction of global monthly absolute temperature for environmental decision making

NASA Astrophysics Data System (ADS)

Ye, Liming; Yang, Guixia; Van Ranst, Eric; Tang, Huajun

2013-03-01

A generalized, structural, time series modeling framework was developed to analyze the monthly records of absolute surface temperature, one of the most important environmental parameters, using a deterministicstochastic combined (DSC) approach. Although the development of the framework was based on the characterization of the variation patterns of a global dataset, the methodology could be applied to any monthly absolute temperature record. Deterministic processes were used to characterize the variation patterns of the global trend and the cyclic oscillations of the temperature signal, involving polynomial functions and the Fourier method, respectively, while stochastic processes were employed to account for any remaining patterns in the temperature signal, involving seasonal autoregressive integrated moving average (SARIMA) models. A prediction of the monthly global surface temperature during the second decade of the 21st century using the DSC model shows that the global temperature will likely continue to rise at twice the average rate of the past 150 years. The evaluation of prediction accuracy shows that DSC models perform systematically well against selected models of other authors, suggesting that DSC models, when coupled with other ecoenvironmental models, can be used as a supplemental tool for short-term (˜10-year) environmental planning and decision making.

Monthly Surface Air Temperature Time Series Area-Averaged Over the 30-Degree Latitudinal Belts of the Globe

DOE Data Explorer

Lugina, K. M. [Department of Geography, St. Petersburg State University, St. Petersburg, Russia; Groisman, P. Ya. [National Climatic Data Center, Asheville, North Carolina USA); Vinnikov, K. Ya. [Department of Atmospheric Sciences, University of Maryland, College Park, Maryland (USA); Koknaeva, V. V. [State Hydrological Institute, St. Petersburg, Russia; Speranskaya, N. A. [State Hydrological Institute, St. Petersburg, Russia

2006-01-01

The mean monthly and annual values of surface air temperature compiled by Lugina et al. have been taken mainly from the World Weather Records, Monthly Climatic Data for the World, and Meteorological Data for Individual Years over the Northern Hemisphere Excluding the USSR. These published records were supplemented with information from different national publications. In the original archive, after removal of station records believed to be nonhomogeneous or biased, 301 and 265 stations were used to determine the mean temperature for the Northern and Southern hemispheres, respectively. The new version of the station temperature archive (used for evaluation of the zonally-averaged temperatures) was created in 1995. The change to the archive was required because data from some stations became unavailable for analyses in the 1990s. During this process, special care was taken to secure homogeneity of zonally averaged time series. When a station (or a group of stations) stopped reporting, a "new" station (or group of stations) was selected in the same region, and its data for the past 50 years were collected and added to the archive. The processing (area-averaging) was organized in such a way that each time series from a new station spans the reference period (1951-1975) and the years thereafter. It was determined that the addition of the new stations had essentially no effect on the zonally-averaged values for the pre-1990 period.

Satellite-derived ice data sets no. 2: Arctic monthly average microwave brightness temperatures and sea ice concentrations, 1973-1976

NASA Technical Reports Server (NTRS)

Parkinson, C. L.; Comiso, J. C.; Zwally, H. J.

1987-01-01

A summary data set for four years (mid 70's) of Arctic sea ice conditions is available on magnetic tape. The data include monthly and yearly averaged Nimbus 5 electrically scanning microwave radiometer (ESMR) brightness temperatures, an ice concentration parameter derived from the brightness temperatures, monthly climatological surface air temperatures, and monthly climatological sea level pressures. All data matrices are applied to 293 by 293 grids that cover a polar stereographic map enclosing the 50 deg N latitude circle. The grid size varies from about 32 X 32 km at the poles to about 28 X 28 km at 50 deg N. The ice concentration parameter is calculated assuming that the field of view contains only open water and first-year ice with an ice emissivity of 0.92. To account for the presence of multiyear ice, a nomogram is provided relating the ice concentration parameter, the total ice concentration, and the fraction of the ice cover which is multiyear ice.

Intermediate photovoltaic system application experiment operational performance report: Volume 5, for Beverly High School, Beverly, Mass.

NASA Astrophysics Data System (ADS)

1982-02-01

Performance data for the month of January, 1982 for a grid connected photovoltaic power supply in Massachusetts are presented. Data include: monthly and daily electrical energy produced; monthly and daily solar energy incident on the array; monthly and daily array efficiency; plots of energy produced as a function of power level, voltage, cell temperature and time of day; power conditioner input, output and efficiency for each of two individual units and for the total power conditioning system; photovoltaic system efficiency; capacity factor; PV system to load and grid to load energies and corresponding dollar values; daily energy supplies to the load by the PV system; daily PV system availability; monthly and hourly insolation; monthly and hourly temperature average; monthly and hourly wind speed; wind direction distribution; average heating and cooling degree days; number of freeze/thaw cycles; and the data acquisition mode and recording interval plot.

Geostatistical interpolation of individual average monthly temperature supported by MODIS MOD11C3 product

NASA Astrophysics Data System (ADS)

Perčec Tadić, M.

2010-09-01

The increased availability of satellite products of high spatial and temporal resolution together with developing user support, encourages the climatologists to use this data in research and practice. Since climatologists are mainly interested in monthly or even annual averages or aggregates, this high temporal resolution and hence, large amount of data, can be challenging for the less experienced users. Even if the attempt is made to aggregate e. g. the 15' (temporal) MODIS LST (land surface temperature) to daily temperature average, the development of the algorithm is not straight forward and should be done by the experts. Recent development of many temporary aggregated products on daily, several days or even monthly scale substantially decrease the amount of satellite data that needs to be processed and rise the possibility for development of various climatological applications. Here the attempt is presented in incorporating the MODIS satellite MOD11C3 product (Wan, 2009), that is monthly CMG (climate modelling 0.05 degree latitude/longitude grids) LST, as predictor in geostatistical interpolation of climatological data in Croatia. While in previous applications, e. g. in Climate Atlas of Croatia (Zaninović et al. 2008), the static predictors as digital elevation model, distance to the sea, latitude and longitude were used for the interpolation of monthly, seasonal and annual 30-years averages (reference climatology), here the monthly MOD11C3 is used to support the interpolation of the individual monthly average in the regression kriging framework. We believe that this can be a valuable show case of incorporating the remote sensed data for climatological application, especially in the areas that are under-sampled by conventional observations. Zaninović K, Gajić-Čapka M, Perčec Tadić M et al (2008) Klimatski atlas Hrvatske / Climate atlas of Croatia 1961-1990, 1971-2000. Meteorological and Hydrological Service of Croatia, Zagreb, pp 200. Wan Z, 2009: Collection-5 MODIS Land Surface Temperature Products Users' Guide, ICESS, University of California, Santa Barbara, pp 30.

TEMPERATURE SCENARIO DEVELOPMENT USING REGRESSION METHODS

EPA Science Inventory

A method of developing scenarios of future temperature conditions resulting from climatic change is presented. he method is straightforward and can be used to provide information about daily temperature variations and diurnal ranges, monthly average high, and low temperatures, an...

Bayesian Spatiotemporal Analysis of Socio-Ecologic Drivers of Ross River Virus Transmission in Queensland, Australia

PubMed Central

Hu, Wenbiao; Clements, Archie; Williams, Gail; Tong, Shilu; Mengersen, Kerrie

2010-01-01

This study aims to examine the impact of socio-ecologic factors on the transmission of Ross River virus (RRV) infection and to identify areas prone to social and ecologic-driven epidemics in Queensland, Australia. We used a Bayesian spatiotemporal conditional autoregressive model to quantify the relationship between monthly variation of RRV incidence and socio-ecologic factors and to determine spatiotemporal patterns. Our results show that the average increase in monthly RRV incidence was 2.4% (95% credible interval (CrI): 0.1–4.5%) and 2.0% (95% CrI: 1.6–2.3%) for a 1°C increase in monthly average maximum temperature and a 10 mm increase in monthly average rainfall, respectively. A significant spatiotemporal variation and interactive effect between temperature and rainfall on RRV incidence were found. No association between Socio-economic Index for Areas (SEIFA) and RRV was observed. The transmission of RRV in Queensland, Australia appeared to be primarily driven by ecologic variables rather than social factors. PMID:20810846

Comparison between AVHRR surface temperature data and in-situ weather station temperatures over the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Rezvanbehbahani, S.; Csatho, B. M.; Comiso, J. C.; Babonis, G. S.

2011-12-01

Advanced Very-High Resolution Radiometer (AVHRR) images have been exhaustively used to measure surface temperature time series of the Greenland Ice sheet. The purpose of this study is to assess the accuracy of monthly average ice sheet surface temperatures, derived from thermal infrared AVHRR satellite imagery on a 6.25 km grid. In-situ temperature data sets are from the Greenland Collection Network (GC-Net). GC-Net stations comprise sensors monitoring air temperature at 1 and 2 meter above the snow surface, gathered at every 60 seconds and monthly averaged to match the AVHRR temporal resolution. Our preliminary results confirm the good agreement between satellite and in-situ temperature measurements reported by previous studies. However, some large discrepancies still exist. While AVHRR provides ice surface temperature, in-situ stations measure air temperatures at different elevations above the snow surface. Since most in-situ data on ice sheets are collected by Automatic Weather Station (AWS) instruments, it is important to characterize the difference between surface and air temperatures. Therefore, we compared and analyzed average monthly AVHRR ice surface temperatures using data collected in 2002. Differences between these temperatures correlate with in-situ temperatures and GC-Net station elevations, with increasing differences at lower elevations and higher temperatures. The Summit Station (3199 m above sea level) and the Swiss Camp (1176 m above sea level) results were compared as high altitude and low altitude stations for 2002, respectively. Our results show that AVHRR derived temperatures were 0.5°K warmer than AWS temperature at the Summit Station, while this difference was 2.8°K in the opposite direction for the Swiss Camp with surface temperatures being lower than air temperatures. The positive bias of 0.5°K at the high altitude Summit Station (surface warmer than air) is within the retrieval error of AVHRR temperatures and might be in part due to atmospheric inversion. The large negative bias of 2.8°K at the low altitude Swiss Camp (surface colder than the air) could be caused by a combination of different factors including local effects such as more windy circumstances above the snow surface and biases introduced by the cloud-masking applied on the AVHRR images. Usually only satellite images acquired in clear-sky conditions are used for deriving monthly AVHRR average temperatures. Since cloud-free days are usually warmer, satellite derived temperatures tend to underestimate the real average temperatures, especially regions with frequent cloud cover, such as Swiss Camp. Therefore, cautions must be exercised while using ice surface temperatures derived from satellite imagery for glaciological applications. Eliminating the cloudy day's' temperature from the in-situ data prior to the comparison with AVHRR derived temperatures will provide a better assessment of AVHRR surface temperature measurement accuracy.

Effects of temperature variation on suicide in five U.S. counties, 1991-2001

NASA Astrophysics Data System (ADS)

Dixon, P. G.; McDonald, A. N.; Scheitlin, K. N.; Stapleton, J. E.; Allen, J. S.; Carter, W. M.; Holley, M. R.; Inman, D. D.; Roberts, J. B.

2007-05-01

Effects of weather variables on suicide are well-documented, but there is still little consistency among the results of most studies. Nevertheless, most studies show a peak in suicides during the spring season, and this is often attributed to increased temperatures. The purpose of this study is to test the relationship between monthly temperature and monthly suicide, independent of months or seasons, for five counties located across the United States. Harmonic analysis shows that four of the five counties display some seasonal components in the suicide data. However, simple linear regression shows no correlation between suicide and temperature, and discriminant analysis shows that monthly departure from mean annual suicide rates is not a useful tool for identifying months with temperatures that are colder or warmer than the annual average. Therefore, it appears that the seasonality of suicides is due to factors other than temperature.

Impact of climate variability on the transmission risk of malaria in northern Côte d'Ivoire.

PubMed

M'Bra, Richard K; Kone, Brama; Soro, Dramane P; N'krumah, Raymond T A S; Soro, Nagnin; Ndione, Jacques A; Sy, Ibrahima; Ceccato, Pietro; Ebi, Kristie L; Utzinger, Jürg; Schindler, Christian; Cissé, Guéladio

2018-01-01

Since the 1970s, the northern part of Côte d'Ivoire has experienced considerable fluctuation in its meteorology including a general decrease of rainfall and increase of temperature from 1970 to 2000, a slight increase of rainfall since 2000, a severe drought in 2004-2005 and flooding in 2006-2007. Such changing climate patterns might affect the transmission of malaria. The purpose of this study was to analyze climate and environmental parameters associated with malaria transmission in Korhogo, a city in northern Côte d'Ivoire. All data were collected over a 10-year period (2004-2013). Rainfall, temperature and Normalized Difference Vegetation Index (NDVI) were the climate and environmental variables considered. Association between these variables and clinical malaria data was determined, using negative binomial regression models. From 2004 to 2013, there was an increase in the annual average precipitation (1100.3-1376.5 mm) and the average temperature (27.2°C-27.5°C). The NDVI decreased from 0.42 to 0.40. We observed a strong seasonality in these climatic variables, which resembled the seasonality in clinical malaria. An incremental increase of 10 mm of monthly precipitation was, on average, associated with a 1% (95% Confidence interval (CI): 0.7 to 1.2%) and a 1.2% (95% CI: 0.9 to 1.5%) increase in the number of clinical malaria episodes one and two months later respectively. A 1°C increase in average monthly temperature was, on average, associated with a decline of a 3.5% (95% CI: 0.1 to 6.7%) in clinical malaria episodes. A 0.1 unit increase in monthly NDVI was associated with a 7.3% (95% CI: 0.8 to 14.1%) increase in the monthly malaria count. There was a similar increase for the preceding-month lag (6.7% (95% CI: 2.3% to 11.2%)). The study results can be used to establish a malaria early warning system in Korhogo to prepare for outbreaks of malaria, which would increase community resilience no matter the magnitude and pattern of climate change.

Analysis of temperature trends in Northern Serbia

NASA Astrophysics Data System (ADS)

Tosic, Ivana; Gavrilov, Milivoj; Unkašević, Miroslava; Marković, Slobodan; Petrović, Predrag

2017-04-01

An analysis of air temperature trends in Northern Serbia for the annual and seasonal time series is performed for two periods: 1949-2013 and 1979-2013. Three data sets of surface air temperatures: monthly mean temperatures, monthly maximum temperatures, and monthly minimum temperatures are analyzed at 9 stations that have altitudes varying between 75 m and 102 m. Monthly mean temperatures are obtained as the average of the daily mean temperatures, while monthly maximum (minimum) temperatures are the maximum (minimum) values of daily temperatures in corresponding month. Positive trends were found in 29 out of 30 time series, and the negative trend was found only in winter during the period 1979-2013. Applying the Mann-Kendall test, significant positive trends were found in 15 series; 7 in the period 1949-2013 and 8 in the period 1979-2013; and no significant trend was found in 15 series. Significant positive trends are dominated during the year, spring, and summer, where it was found in 14 out of 18 cases. Significant positive trends were found 7, 5, and 3 times in mean, maximum and minimum temperatures, respectively. It was found that the positive temperature trends are dominant in Northern Serbia.

Energetics of thermoregulation by an industrious endotherm.

PubMed

Meehan, Timothy D

2012-01-01

Thermoregulation by modern industrial humans is unique among endothermic animals, in that it is largely accomplished by controlling the temperature of our external environment. The objective of this study was to view the relationship between thermoregulatory energy use and environmental temperature in modern humans from the perspective of comparative physiology. Monthly residential energy use estimates from the US Energy Information Administration were divided by the annual number of American households from the US Census Bureau, giving average monthly energy consumption per American household for the years 2006 through 2010. Monthly energy consumption was then plotted against average monthly temperature across the United States from the National Climatic Data Center. The resulting graph bore a striking resemblance to a classic Scholander-Irving curve, exhibiting clear upper (22°C) and lower (15°C) critical temperatures, and an increase in energy use as temperatures extend above (90 W °C(-1) increase) or below (244 W °C(-1) decrease) those critical temperatures. Allometric equations from comparative physiology indicate that the energetic costs of our current thermoregulatory habits are ∼30 to 50 times those predicted for an endotherm of our size. Modern humans have redefined what it means to be a homeothermic endotherm, using large quantities of extrametabolic energy to regulate the temperature of our surroundings. Despite this sophistication, the signal of our individual physiology is readily discernible in national data on energy consumption. Copyright © 2012 Wiley Periodicals, Inc.

Indoor Temperatures in Patient Waiting Rooms in Eight Rural Primary Health Care Centers in Northern South Africa and the Related Potential Risks to Human Health and Wellbeing

PubMed Central

Wright, Caradee Y.; Street, Renée A.; Cele, Nokulunga; Kunene, Zamantimande; Balakrishna, Yusentha; Albers, Patricia N.; Mathee, Angela

2017-01-01

Increased temperatures affect human health and vulnerable groups including infants, children, the elderly and people with pre-existing diseases. In the southern African region climate models predict increases in ambient temperature twice that of the global average temperature increase. Poor ventilation and lack of air conditioning in primary health care clinics, where duration of waiting time may be as long as several hours, pose a possible threat to patients seeking primary health care. Drawing on information measured by temperature loggers installed in eight clinics in Giyani, Limpopo Province of South Africa, we were able to determine indoor temperatures of waiting rooms in eight rural primary health care facilities. Mean monthly temperature measurements inside the clinics were warmer during the summer months of December, January and February, and cooler during the autumn months of March, April and May. The highest mean monthly temperature of 31.4 ± 2.7 °C was recorded in one clinic during February 2016. Maximum daily indoor clinic temperatures exceeded 38 °C in some clinics. Indoor temperatures were compared to ambient (outdoor) temperatures and the mean difference between the two showed clinic waiting room temperatures were higher by 2–4 °C on average. Apparent temperature (AT) incorporating relative humidity readings made in the clinics showed ‘realfeel’ temperatures were >4 °C higher than measured indoor temperature, suggesting a feeling of ‘stuffiness’ and discomfort may have been experienced in the waiting room areas. During typical clinic operational hours of 8h00 to 16h00, mean ATs fell into temperature ranges associated with heat–health impact warning categories of ‘caution’ and ‘extreme caution’. PMID:28067816

Indoor Temperatures in Patient Waiting Rooms in Eight Rural Primary Health Care Centers in Northern South Africa and the Related Potential Risks to Human Health and Wellbeing.

PubMed

Wright, Caradee Y; Street, Renée A; Cele, Nokulunga; Kunene, Zamantimande; Balakrishna, Yusentha; Albers, Patricia N; Mathee, Angela

2017-01-06

Increased temperatures affect human health and vulnerable groups including infants, children, the elderly and people with pre-existing diseases. In the southern African region climate models predict increases in ambient temperature twice that of the global average temperature increase. Poor ventilation and lack of air conditioning in primary health care clinics, where duration of waiting time may be as long as several hours, pose a possible threat to patients seeking primary health care. Drawing on information measured by temperature loggers installed in eight clinics in Giyani, Limpopo Province of South Africa, we were able to determine indoor temperatures of waiting rooms in eight rural primary health care facilities. Mean monthly temperature measurements inside the clinics were warmer during the summer months of December, January and February, and cooler during the autumn months of March, April and May. The highest mean monthly temperature of 31.4 ± 2.7 °C was recorded in one clinic during February 2016. Maximum daily indoor clinic temperatures exceeded 38 °C in some clinics. Indoor temperatures were compared to ambient (outdoor) temperatures and the mean difference between the two showed clinic waiting room temperatures were higher by 2-4 °C on average. Apparent temperature (AT) incorporating relative humidity readings made in the clinics showed 'realfeel' temperatures were >4 °C higher than measured indoor temperature, suggesting a feeling of 'stuffiness' and discomfort may have been experienced in the waiting room areas. During typical clinic operational hours of 8h00 to 16h00, mean ATs fell into temperature ranges associated with heat-health impact warning categories of 'caution' and 'extreme caution'.

Optimal Detection of Global Warming using Temperature Profiles

NASA Technical Reports Server (NTRS)

Leroy, Stephen S.

1997-01-01

Optimal fingerprinting is applied to estimate the amount of time it would take to detect warming by increased concentrations of carbon dioxide in monthly averages of temperature profiles over the Indian Ocean.

A Temperature-Based Model for Estimating Monthly Average Daily Global Solar Radiation in China

PubMed Central

Li, Huashan; Cao, Fei; Wang, Xianlong; Ma, Weibin

2014-01-01

Since air temperature records are readily available around the world, the models based on air temperature for estimating solar radiation have been widely accepted. In this paper, a new model based on Hargreaves and Samani (HS) method for estimating monthly average daily global solar radiation is proposed. With statistical error tests, the performance of the new model is validated by comparing with the HS model and its two modifications (Samani model and Chen model) against the measured data at 65 meteorological stations in China. Results show that the new model is more accurate and robust than the HS, Samani, and Chen models in all climatic regions, especially in the humid regions. Hence, the new model can be recommended for estimating solar radiation in areas where only air temperature data are available in China. PMID:24605046

Range of monthly mean hourly land surface air temperature diurnal cycle over high northern latitudes

NASA Astrophysics Data System (ADS)

Wang, Aihui; Zeng, Xubin

2014-05-01

Daily maximum and minimum temperatures over global land are fundamental climate variables, and their difference represents the diurnal temperature range (DTR). While the differences between the monthly averaged DTR (MDTR) and the range of monthly averaged hourly temperature diurnal cycle (RMDT) are easy to understand qualitatively, their differences have not been quantified over global land areas. Based on our newly developed in situ data (Climatic Research Unit) reanalysis (Modern-Era Retrospective analysis for Research and Applications) merged hourly temperature data from 1979 to 2009, RMDT in January is found to be much smaller than that in July over high northern latitudes, as it is much more affected by the diurnal radiative forcing than by the horizontal advection of temperature. In contrast, MDTR in January is comparable to that in July over high northern latitudes, but it is much larger than January RMDT, as it primarily reflects the movement of lower frequency synoptic weather systems. The area-averaged RMDT trends north of 40°N are near zero in November, December, and January, while the trends of MDTR are negative. These results suggest the need to use both the traditional MDTR and RMDT suggested here in future observational and modeling studies. Furthermore, MDTR and its trend are more sensitive to the starting hour of a 24 h day used in the calculations than those for RMDT, and this factor also needs to be considered in model evaluations using observational data.

A comparative statistical study of long-term agroclimatic conditions affecting the growth of US winter wheat: Distributions of regional monthly average precipitation on the Great Plains and the state of Maryland and the effect of agroclimatic conditions on yield in the state of Kansas

NASA Technical Reports Server (NTRS)

Welker, J.

1981-01-01

A histogram analysis of average monthly precipitation over 30 and 84 year periods for both Maryland and Kansas was made and the results compared. A second analysis, a statistical assessment of the effect of average monthly precipitation on Kansas winter wheat yield was made. The data sets covered the three periods of 1941-1970, 1887-1970, and 1887-1921. Analyses of the limited data sets used (only the average monthly precipitation and temperature were correlated against yield) indicated that fall precipitation values, especially those of September and October, were more important to winter wheat yield than were spring values, particularly for the period 1941-1970.

Modern average global sea-surface temperature

USGS Publications Warehouse

Schweitzer, Peter N.

1993-01-01

The data contained in this data set are derived from the NOAA Advanced Very High Resolution Radiometer Multichannel Sea Surface Temperature data (AVHRR MCSST), which are obtainable from the Distributed Active Archive Center at the Jet Propulsion Laboratory (JPL) in Pasadena, Calif. The JPL tapes contain weekly images of SST from October 1981 through December 1990 in nine regions of the world ocean: North Atlantic, Eastern North Atlantic, South Atlantic, Agulhas, Indian, Southeast Pacific, Southwest Pacific, Northeast Pacific, and Northwest Pacific. This data set represents the results of calculations carried out on the NOAA data and also contains the source code of the programs that made the calculations. The objective was to derive the average sea-surface temperature of each month and week throughout the whole 10-year series, meaning, for example, that data from January of each year would be averaged together. The result is 12 monthly and 52 weekly images for each of the oceanic regions. Averaging the images in this way tends to reduce the number of grid cells that lack valid data and to suppress interannual variability.

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

Trends in summer bottom-water temperatures on the northern Gulf of Mexico continental shelf from 1985 to 2015.

PubMed

Turner, R Eugene; Rabalais, Nancy N; Justić, Dubravko

2017-01-01

We quantified trends in the 1985 to 2015 summer bottom-water temperature on the northern Gulf of Mexico (nGOM) continental shelf for data collected at 88 stations with depths ranging from 3 to 63 m. The analysis was supplemented with monthly data collected from 1963 to 1965 in the same area. The seasonal summer peak in average bottom-water temperature varied concurrently with air temperature, but with a 2- to 5-month lag. The summer bottom-water temperature declined gradually with depth from 30 oC at stations closest to the shore, to 20 oC at the offshore edge of the study area, and increased an average 0.051 oC y-1 between1963 and 2015. The bottom-water warming in summer for all stations was 1.9 times faster compared to the rise in local summer air temperatures, and 6.4 times faster than the concurrent increase in annual global ocean sea surface temperatures. The annual rise in average summer bottom-water temperatures on the subtropical nGOM continental shelf is comparable to the few published temperature trend estimates from colder environments. These recent changes in the heat storage on the nGOM continental shelf will affect oxygen and carbon cycling, spatial distribution of fish and shrimp, and overall species diversity.

Seasonality in hospital admissions of Crimean-Congo hemorrhagic fever and its dependence on ambient temperature-empirical evidence from Pakistan.

PubMed

Abbas, Tariq; Xu, Zhiwei; Younus, Muhammad; Qayyum, Abdul; Riaz, Muhammad T

2017-11-01

Crimean-Congo hemorrhagic fever (CCHF) has been reported from all provinces of Pakistan. Little is known about the seasonal variations in the disease and its association with weather conditions. In this study, we explored time-series data about monthly number of CCHF admissions (2007-2010) in three public sector hospitals of Quetta-the capital city of Baluchistan province of Pakistan. Cosinor analysis was carried out to investigate seasonality in the data. To assess the effect of average monthly ambient temperature (°C) on disease, a distributed lag nonlinear model (DLNM) was applied. Cosinor model revealed statistically significant seasonality in monthly number of CCHF patients admitted to the study hospitals. The estimated amplitude was 3.24 cases per month with phase in mid-June and low point in mid-December. DLNM confirmed nonlinear and delayed effect of temperature on hospital admissions. At a lag of 2 months, the cumulative relative risk was more than 1 at temperature at 18.37 °C and above. In addition, relative risk was significantly high at 60th (21.98 °C), 70th (24.50 °C), 80th (27.33 °C), and 90th (29.25 °C) percentiles of temperature (relative to median value, 18.37 °C). Inclusion of Eid-al-Adha as a predictor did not improve the fitness of DLNM. Based on our analysis, we concluded significant seasonality in CCHF hospital admissions. Our findings also suggested average monthly ambient temperature (°C) as a significant predictor of CCHF hospitalizations. DLNM presented in this study may be improved with inclusion of other possible time-varying predictors particularly meteorological conditions of this region.

The climate impact on female acute pyelonephritis in Taiwan: A population-based study.

PubMed

Liu, Jui-Ming; Chang, Yu-Lung; Hsu, Ren-Jun; Su, Her-Young; Teng, Sen-Wen; Chang, Fung-Wei

2017-08-01

Urinary tract infection (UTI) is the main reason of community-acquired infection which causes large losses in social economy. The individual as well as climate factors make changes on the incidence. Acute pyelonephritis (APN) is one of the most serious UTI in female. The object of our study is to analyze whether climate factors will have effect on the incidence of female APN in Taiwan. This study consisted of 14,568 female patients with APN from 2001 to 2013 in Taiwan and patients with repeated APN were excluded. The monthly climate data was collected from the Central Weather Bureau. The available monthly climate data included highest, lowest, and average level of temperatures, humidity, rainfall, total rain days, and sunshine hours. The total incidence of female APN was 23.44 each 10,000 populations. The incidence of APN was positively correlated with temperature (r = 0.66), sunshine hours (r = 0.45), rainfall (r = 0.42), rain days (r = 0.29), and humidity (r = 0.23) per month. There is the strongest correlation between the average monthly temperature and the incidence of APN (β = 0.54). The correlation with the incidence of APN was also followed by rain days (β = 0.28) and humidity (β = 0.27). There is a significant expression on the incidence of female APN affected by seasonality and climate parameters. The monthly average temperature has the strongest correlation with female APN. The results of this research may facilitate the potential preventive strategies on female APN. Copyright © 2017. Published by Elsevier B.V.

Clinical Malaria Transmission Trends and Its Association with Climatic Variables in Tubu Village, Botswana: A Retrospective Analysis.

PubMed

Chirebvu, Elijah; Chimbari, Moses John; Ngwenya, Barbara Ntombi; Sartorius, Benn

2016-01-01

Good knowledge on the interactions between climatic variables and malaria can be very useful for predicting outbreaks and preparedness interventions. We investigated clinical malaria transmission patterns and its temporal relationship with climatic variables in Tubu village, Botswana. A 5-year retrospective time series data analysis was conducted to determine the transmission patterns of clinical malaria cases at Tubu Health Post and its relationship with rainfall, flood discharge, flood extent, mean minimum, maximum and average temperatures. Data was obtained from clinical records and respective institutions for the period July 2005 to June 2010, presented graphically and analysed using the Univariate ANOVA and Pearson cross-correlation coefficient tests. Peak malaria season occurred between October and May with the highest cumulative incidence of clinical malaria cases being recorded in February. Most of the cases were individuals aged >5 years. Associations between the incidence of clinical malaria cases and several factors were strong at lag periods of 1 month; rainfall (r = 0.417), mean minimum temperature (r = 0.537), mean average temperature (r = 0.493); and at lag period of 6 months for flood extent (r = 0.467) and zero month for flood discharge (r = 0.497). The effect of mean maximum temperature was strongest at 2-month lag period (r = 0.328). Although malaria transmission patterns varied from year to year the trends were similar to those observed in sub-Saharan Africa. Age group >5 years experienced the greatest burden of clinical malaria probably due to the effects of the national malaria elimination programme. Rainfall, flood discharge and extent, mean minimum and mean average temperatures showed some correlation with the incidence of clinical malaria cases.

40 CFR Table 2 to Subpart Dddd of... - Operating Requirements

Code of Federal Regulations, 2011 CFR

2011-07-01

... minimum temperature established during the performance test Maintain the 3-hour block average THC... representative sample of the catalyst at least every 12 months Maintain the 3-hour block average THC... established according to § 63.2262(m) Maintain the 24-hour block average THC concentration a in the biofilter...

40 CFR Table 2 to Subpart Dddd of... - Operating Requirements

Code of Federal Regulations, 2010 CFR

2010-07-01

... minimum temperature established during the performance test Maintain the 3-hour block average THC... representative sample of the catalyst at least every 12 months Maintain the 3-hour block average THC... established according to § 63.2262(m) Maintain the 24-hour block average THC concentration a in the biofilter...

The effect of climate variability on urinary stone attacks: increased incidence associated with temperature over 18 °C: a population-based study.

PubMed

Park, Hyoung Keun; Bae, Sang Rak; Kim, Satbyul E; Choi, Woo Suk; Paick, Sung Hyun; Ho, Kim; Kim, Hyeong Gon; Lho, Yong Soo

2015-02-01

The aim of this study was to evaluate the effect of seasonal variation and climate parameters on urinary tract stone attack and investigate whether stone attack is increased sharply at a specific point. Nationwide data of total urinary tract stone attack numbers per month between January 2006 and December 2010 were obtained from the Korean Health Insurance Review and Assessment Service. The effects of climatic factors on monthly urinary stone attack were assessed using auto-regressive integrated moving average (ARIMA) regression method. A total of 1,702,913 stone attack cases were identified. Mean monthly and monthly average daily urinary stone attack cases were 28,382 ± 2,760 and 933 ± 85, respectively. The stone attack showed seasonal trends of sharp incline in June, a peak plateau from July to September, and a sharp decline after September. The correlation analysis showed that ambient temperature (r = 0.557, p < 0.001) and relative humidity (r = 0.513, p < 0.001) were significantly associated with urinary stone attack cases. However, after adjustment for trends and seasonality, ambient temperature was the only climate factor associated with the stone attack cases in ARIMA regression test (p = 0.04). Threshold temperature was estimated as 18.4 °C. Risk of urinary stone attack significantly increases 1.71% (1.02-2.41 %, 95% confidence intervals) with a 1 °C increase of ambient temperature above the threshold point. In conclusion, monthly urinary stone attack cases were changed according to seasonal variation. Among the climates variables, only temperature had consistent association with stone attack and when the temperature is over 18.4 °C, urinary stone attack would be increased sharply.

Evapotranspiration and microclimate at a low-level radioactive-waste disposal site in northwestern Illinois

USGS Publications Warehouse

Healy, R.W.; DeVries, M.P.; Sturrock, A.M.

1987-01-01

From July 1982 through June 1984, a study was made of the microclimate and evapotranspiration at a low-level radioactive-waste disposal site near Sheffield, Bureau County, Illinois. Vegetation at the site consists of mixed pasture grasses, primarily brome (Bromus inermis) and red clover (Trifoleum pratense). Three methods were used to estimate evapotranspiration: (1) an energy-budget with the Bowen ratio, (2) an aerodynamic-profile, and (3) a soil-based water-budget. For the aerodynamic-profile method, sensible-heat flux was estimated by a profile equation and evapotranspiration was then calculated as the residual in the energy-balance equation. Estimates by the energy-budget and aerodynamic-profile methods were computed from hourly data, then summed by days and months. Yearly estimates for March through November, by these methods, were quite close--648 and 626 millimeters, respectively. Daily estimates range up to a maximum of about 6 millimeters. The water-budget method produced only monthly estimates based on weekly or biweekly soil-moisture content measurements. The yearly evapotranspiration estimated by this method (which actually included only the months of April through October) was 655 millimeters. The March-through-November average for the three methods of 657 millimeters was equivalent to 70 percent of precipitation. Continuous measurements were made of incoming and reflected shortwave radiation, incoming and emitted longwave radiation, net radiation, soil-heat flux, soil temperature, horizontal windspeed, and wet- and dry-bulb air temperature. Windspeed and air temperature were measured at heights of 0.5 and 2.0 meters (and also at 1.0 meter after September 1983). Soil-moisture content of the soil zone was measured with a gamma-attenuation gage. Annual precipitation (938 millimeters) and average temperature (10.8 degrees Celsius) were virtually identical to long-term averages from nearby National Weather Service stations. Solar radiation averaged 65 percent of that normally expected under clear skies. Net radiation averaged 70.1 watts per square meter and was highest in July and negative during some winter months. Wind direction varied but was predominately out of the south-southeast. Wind speed at the 2-meter height averaged 3.5 meters per second and was slightly higher in winter months than the rest of the year. The amount of water stored within the soil zone was greatest in early spring and least in late summer. Seasonal and diurnal trends in evapotranspiration rates mirrored those in net radiation; July was usually the month with the highest rate. The ratio of sensible- to latent-heat fluxes (commonly called the Bowen ratio) for the 2-year period was 0.38, as averaged from the three methods. Monthly Bowen ratios fluctuated somewhat but averaged about 0.35 for late spring through summer. In fall, the ratio declined to zero or to slightly negative values. When the ratio was negative, the latent-heat flux was slightly greater than the net radiation because of additional energy supplied by the cooling soil and air. Evapotranspiration calculated by the three methods averaged 75 percent of potential evapotranspiration, as estimated by the Penman equation. There was no apparent seasonal trend in the relation between actual and potential evapotranspiration rates.

Argentina soybean yield model

NASA Technical Reports Server (NTRS)

Callis, S. L.; Sakamoto, C.

1984-01-01

A model based on multiple regression was developed to estimate soybean yields for the country of Argentina. A meteorological data set was obtained for the country by averaging data for stations within the soybean growing area. Predictor variables for the model were derived from monthly total precipitation and monthly average temperature. A trend variable was included for the years 1969 to 1978 since an increasing trend in yields due to technology was observed between these years.

Seasonal variations in tuberculosis diagnosis among HIV-positive individuals in Southern Africa: analysis of cohort studies at antiretroviral treatment programmes

PubMed Central

Ballif, Marie; Zürcher, Kathrin; Reid, Stewart E; Boulle, Andrew; Fox, Matthew P; Prozesky, Hans W; Chimbetete, Cleophas; Egger, Matthias; Fenner, Lukas

2018-01-01

Objectives Seasonal variations in tuberculosis diagnoses have been attributed to seasonal climatic changes and indoor crowding during colder winter months. We investigated trends in pulmonary tuberculosis (PTB) diagnosis at antiretroviral therapy (ART) programmes in Southern Africa. Setting Five ART programmes participating in the International Epidemiology Database to Evaluate AIDS in South Africa, Zambia and Zimbabwe. Participants We analysed data of 331 634 HIV-positive adults (>15 years), who initiated ART between January 2004 and December 2014. Primary outcome measure We calculated aggregated averages in monthly counts of PTB diagnoses and ART initiations. To account for time trends, we compared deviations of monthly event counts to yearly averages, and calculated correlation coefficients. We used multivariable regressions to assess associations between deviations of monthly ART initiation and PTB diagnosis counts from yearly averages, adjusted for monthly air temperatures and geographical latitude. As controls, we used Kaposi sarcoma and extrapulmonary tuberculosis (EPTB) diagnoses. Results All programmes showed monthly variations in PTB diagnoses that paralleled fluctuations in ART initiations, with recurrent patterns across 2004–2014. The strongest drops in PTB diagnoses occurred in December, followed by April–May in Zimbabwe and South Africa. This corresponded to holiday seasons, when clinical activities are reduced. We observed little monthly variation in ART initiations and PTB diagnoses in Zambia. Correlation coefficients supported parallel trends in ART initiations and PTB diagnoses (correlation coefficient: 0.28, 95% CI 0.21 to 0.35, P<0.001). Monthly temperatures and latitude did not substantially change regression coefficients between ART initiations and PTB diagnoses. Trends in Kaposi sarcoma and EPTB diagnoses similarly followed changes in ART initiations throughout the year. Conclusions Monthly variations in PTB diagnosis at ART programmes in Southern Africa likely occurred regardless of seasonal variations in temperatures or latitude and reflected fluctuations in clinical activities and changes in health-seeking behaviour throughout the year, rather than climatic factors. PMID:29330173

Analysis of the surface heat balance over the world ocean

NASA Technical Reports Server (NTRS)

Esbensen, S. K.

1981-01-01

It is possible to estimate long term monthly mean latent and sensible heat fluxes over the ocean to within or approximately 20% relative accuracy of the bulk aerodynamic formulas, by using observations of the monthly mean surface wind speed and the monthly mean sea air temperature and humidity differences. It is possible to make an estimate of the fluxes on a month to month basis from monthly averaged surface data.

Comparing daily temperature averaging methods: the role of surface and atmosphere variables in determining spatial and seasonal variability

NASA Astrophysics Data System (ADS)

Bernhardt, Jase; Carleton, Andrew M.

2018-05-01

The two main methods for determining the average daily near-surface air temperature, twice-daily averaging (i.e., [Tmax+Tmin]/2) and hourly averaging (i.e., the average of 24 hourly temperature measurements), typically show differences associated with the asymmetry of the daily temperature curve. To quantify the relative influence of several land surface and atmosphere variables on the two temperature averaging methods, we correlate data for 215 weather stations across the Contiguous United States (CONUS) for the period 1981-2010 with the differences between the two temperature-averaging methods. The variables are land use-land cover (LULC) type, soil moisture, snow cover, cloud cover, atmospheric moisture (i.e., specific humidity, dew point temperature), and precipitation. Multiple linear regression models explain the spatial and monthly variations in the difference between the two temperature-averaging methods. We find statistically significant correlations between both the land surface and atmosphere variables studied with the difference between temperature-averaging methods, especially for the extreme (i.e., summer, winter) seasons (adjusted R2 > 0.50). Models considering stations with certain LULC types, particularly forest and developed land, have adjusted R2 values > 0.70, indicating that both surface and atmosphere variables control the daily temperature curve and its asymmetry. This study improves our understanding of the role of surface and near-surface conditions in modifying thermal climates of the CONUS for a wide range of environments, and their likely importance as anthropogenic forcings—notably LULC changes and greenhouse gas emissions—continues.

Effect of temperature shock and inventory surprises on natural gas and heating oil futures returns.

PubMed

Hu, John Wei-Shan; Hu, Yi-Chung; Lin, Chien-Yu

2014-01-01

The aim of this paper is to examine the impact of temperature shock on both near-month and far-month natural gas and heating oil futures returns by extending the weather and storage models of the previous study. Several notable findings from the empirical studies are presented. First, the expected temperature shock significantly and positively affects both the near-month and far-month natural gas and heating oil futures returns. Next, significant temperature shock has effect on both the conditional mean and volatility of natural gas and heating oil prices. The results indicate that expected inventory surprises significantly and negatively affects the far-month natural gas futures returns. Moreover, volatility of natural gas futures returns is higher on Thursdays and that of near-month heating oil futures returns is higher on Wednesdays than other days. Finally, it is found that storage announcement for natural gas significantly affects near-month and far-month natural gas futures returns. Furthermore, both natural gas and heating oil futures returns are affected more by the weighted average temperature reported by multiple weather reporting stations than that reported by a single weather reporting station.

Effect of Temperature Shock and Inventory Surprises on Natural Gas and Heating Oil Futures Returns

PubMed Central

Hu, John Wei-Shan; Lin, Chien-Yu

2014-01-01

The aim of this paper is to examine the impact of temperature shock on both near-month and far-month natural gas and heating oil futures returns by extending the weather and storage models of the previous study. Several notable findings from the empirical studies are presented. First, the expected temperature shock significantly and positively affects both the near-month and far-month natural gas and heating oil futures returns. Next, significant temperature shock has effect on both the conditional mean and volatility of natural gas and heating oil prices. The results indicate that expected inventory surprises significantly and negatively affects the far-month natural gas futures returns. Moreover, volatility of natural gas futures returns is higher on Thursdays and that of near-month heating oil futures returns is higher on Wednesdays than other days. Finally, it is found that storage announcement for natural gas significantly affects near-month and far-month natural gas futures returns. Furthermore, both natural gas and heating oil futures returns are affected more by the weighted average temperature reported by multiple weather reporting stations than that reported by a single weather reporting station. PMID:25133233

microclim: Global estimates of hourly microclimate based on long-term monthly climate averages

PubMed Central

Kearney, Michael R; Isaac, Andrew P; Porter, Warren P

2014-01-01

The mechanistic links between climate and the environmental sensitivities of organisms occur through the microclimatic conditions that organisms experience. Here we present a dataset of gridded hourly estimates of typical microclimatic conditions (air temperature, wind speed, relative humidity, solar radiation, sky radiation and substrate temperatures from the surface to 1 m depth) at high resolution (~15 km) for the globe. The estimates are for the middle day of each month, based on long-term average macroclimates, and include six shade levels and three generic substrates (soil, rock and sand) per pixel. These data are suitable for deriving biophysical estimates of the heat, water and activity budgets of terrestrial organisms. PMID:25977764

Microclim: Global estimates of hourly microclimate based on long-term monthly climate averages.

PubMed

Kearney, Michael R; Isaac, Andrew P; Porter, Warren P

2014-01-01

The mechanistic links between climate and the environmental sensitivities of organisms occur through the microclimatic conditions that organisms experience. Here we present a dataset of gridded hourly estimates of typical microclimatic conditions (air temperature, wind speed, relative humidity, solar radiation, sky radiation and substrate temperatures from the surface to 1 m depth) at high resolution (~15 km) for the globe. The estimates are for the middle day of each month, based on long-term average macroclimates, and include six shade levels and three generic substrates (soil, rock and sand) per pixel. These data are suitable for deriving biophysical estimates of the heat, water and activity budgets of terrestrial organisms.

Associations between Changes in City and Address Specific Temperature and QT Interval - The VA Normative Aging Study

PubMed Central

Mehta, Amar J.; Kloog, Itai; Zanobetti, Antonella; Coull, Brent A.; Sparrow, David; Vokonas, Pantel; Schwartz, Joel

2014-01-01

Background The underlying mechanisms of the association between ambient temperature and cardiovascular morbidity and mortality are not well understood, particularly for daily temperature variability. We evaluated if daily mean temperature and standard deviation of temperature was associated with heart rate-corrected QT interval (QTc) duration, a marker of ventricular repolarization in a prospective cohort of older men. Methods This longitudinal analysis included 487 older men participating in the VA Normative Aging Study with up to three visits between 2000–2008 (n = 743). We analyzed associations between QTc and moving averages (1–7, 14, 21, and 28 days) of the 24-hour mean and standard deviation of temperature as measured from a local weather monitor, and the 24-hour mean temperature estimated from a spatiotemporal prediction model, in time-varying linear mixed-effect regression. Effect modification by season, diabetes, coronary heart disease, obesity, and age was also evaluated. Results Higher mean temperature as measured from the local monitor, and estimated from the prediction model, was associated with longer QTc at moving averages of 21 and 28 days. Increased 24-hr standard deviation of temperature was associated with longer QTc at moving averages from 4 and up to 28 days; a 1.9°C interquartile range increase in 4-day moving average standard deviation of temperature was associated with a 2.8 msec (95%CI: 0.4, 5.2) longer QTc. Associations between 24-hr standard deviation of temperature and QTc were stronger in colder months, and in participants with diabetes and coronary heart disease. Conclusion/Significance In this sample of older men, elevated mean temperature was associated with longer QTc, and increased variability of temperature was associated with longer QTc, particularly during colder months and among individuals with diabetes and coronary heart disease. These findings may offer insight of an important underlying mechanism of temperature-related cardiovascular morbidity and mortality in an older population. PMID:25238150

Seasonality in hospital admissions of Crimean-Congo hemorrhagic fever and its dependence on ambient temperature—empirical evidence from Pakistan

NASA Astrophysics Data System (ADS)

Abbas, Tariq; Xu, Zhiwei; Younus, Muhammad; Qayyum, Abdul; Riaz, Muhammad T.

2017-11-01

Crimean-Congo hemorrhagic fever (CCHF) has been reported from all provinces of Pakistan. Little is known about the seasonal variations in the disease and its association with weather conditions. In this study, we explored time-series data about monthly number of CCHF admissions (2007-2010) in three public sector hospitals of Quetta—the capital city of Baluchistan province of Pakistan. Cosinor analysis was carried out to investigate seasonality in the data. To assess the effect of average monthly ambient temperature (°C) on disease, a distributed lag nonlinear model (DLNM) was applied. Cosinor model revealed statistically significant seasonality in monthly number of CCHF patients admitted to the study hospitals. The estimated amplitude was 3.24 cases per month with phase in mid-June and low point in mid-December. DLNM confirmed nonlinear and delayed effect of temperature on hospital admissions. At a lag of 2 months, the cumulative relative risk was more than 1 at temperature at 18.37 °C and above. In addition, relative risk was significantly high at 60th (21.98 °C), 70th (24.50 °C), 80th (27.33 °C), and 90th (29.25 °C) percentiles of temperature (relative to median value, 18.37 °C). Inclusion of Eid-al-Adha as a predictor did not improve the fitness of DLNM. Based on our analysis, we concluded significant seasonality in CCHF hospital admissions. Our findings also suggested average monthly ambient temperature (°C) as a significant predictor of CCHF hospitalizations. DLNM presented in this study may be improved with inclusion of other possible time-varying predictors particularly meteorological conditions of this region.

Snow cover and temperature relationships in North America and Eurasia

NASA Technical Reports Server (NTRS)

Foster, J.; Owe, M.; Rango, A.

1983-01-01

In this study the snow cover extent during the autumn months in both North America and Eurasia has been related to the ensuing winter temperature as measured at several locations near the center of each continent. The relationship between autumn snow cover and the ensuing winter temperatures was found to be much better for Eurasia than for North America. For Eurasia the average snow cover extent during the autumn explained as much as 52 percent of the variance in the winter (December-February) temperatures compared to only 12 percent for North America. However, when the average winter snow cover was correlated with the average winter temperature it was found that the relationship was better for North America than for Eurasia. As much as 46 percent of the variance in the winter temperature was explained by the winter snow cover in North America compared to only 12 percent in Eurasia.

Temperature extremes and infant mortality in Bangladesh: Hotter months, lower mortality.

PubMed

Babalola, Olufemi; Razzaque, Abdur; Bishai, David

2018-01-01

Our study aims to obtain estimates of the size effects of temperature extremes on infant mortality in Bangladesh using monthly time series data. Data on temperature, child and infant mortality were obtained for Matlab district of rural Bangladesh for January 1982 to December 2008 encompassing 49,426 infant deaths. To investigate the relationship between mortality and temperature, we adopted a regression with Autoregressive Integrated Moving Average (ARIMA) errors model of seasonally adjusted temperature and mortality data. The relationship between monthly mean and maximum temperature on infant mortality was tested at 0 and 1 month lags respectively. Furthermore, our analysis was stratified to determine if the results differed by gender (boys versus girls) and by age (neonates (≤ 30 days) versus post neonates (>30days and <153days)). Dickey Fuller tests were performed to test for stationarity, and since the time series were non-stationary, we conducted the regression analysis based on the first differences of mortality and temperature. Hotter months were associated with lower infant mortality in Bangladesh. Each degree Celsius increase in mean monthly temperature reduced monthly mortality by 3.672 (SE 1.544, p<0.05) points. A one degree increase in mean monthly temperature one month prior reduced mortality by 0.767 (SE 0.439, p<0.1) for boys and by -0.0764 (SE 0.366, NS) for girls. Beneficial effects of maximum monthly temperature were on the order of 0.623 to -0.712 and statistically significant for girls and boys respectively. Effect sizes of mean monthly temperature were larger for neonates at 1.126 (SE 0.499, p<0.05) than for post-neonates at 0.880 (SE 0.310, p<0.05) reductions in mortality per degree. There is no evidence that infant survival is adversely affected by monthly temperature extremes in Bangladesh. This may reflect a more heightened sensitivity of infants to hypothermia than hyperthermia in this environment.

Temperature extremes and infant mortality in Bangladesh: Hotter months, lower mortality

PubMed Central

Babalola, Olufemi; Razzaque, Abdur

2018-01-01

Background Our study aims to obtain estimates of the size effects of temperature extremes on infant mortality in Bangladesh using monthly time series data. Methods Data on temperature, child and infant mortality were obtained for Matlab district of rural Bangladesh for January 1982 to December 2008 encompassing 49,426 infant deaths. To investigate the relationship between mortality and temperature, we adopted a regression with Autoregressive Integrated Moving Average (ARIMA) errors model of seasonally adjusted temperature and mortality data. The relationship between monthly mean and maximum temperature on infant mortality was tested at 0 and 1 month lags respectively. Furthermore, our analysis was stratified to determine if the results differed by gender (boys versus girls) and by age (neonates (≤ 30 days) versus post neonates (>30days and <153days)). Dickey Fuller tests were performed to test for stationarity, and since the time series were non-stationary, we conducted the regression analysis based on the first differences of mortality and temperature. Results Hotter months were associated with lower infant mortality in Bangladesh. Each degree Celsius increase in mean monthly temperature reduced monthly mortality by 3.672 (SE 1.544, p<0.05) points. A one degree increase in mean monthly temperature one month prior reduced mortality by 0.767 (SE 0.439, p<0.1) for boys and by -0.0764 (SE 0.366, NS) for girls. Beneficial effects of maximum monthly temperature were on the order of 0.623 to -0.712 and statistically significant for girls and boys respectively. Effect sizes of mean monthly temperature were larger for neonates at 1.126 (SE 0.499, p<0.05) than for post-neonates at 0.880 (SE 0.310, p<0.05) reductions in mortality per degree. Conclusion There is no evidence that infant survival is adversely affected by monthly temperature extremes in Bangladesh. This may reflect a more heightened sensitivity of infants to hypothermia than hyperthermia in this environment. PMID:29304145

Cold Tolerance of Megacopta cribraria (Hemiptera: Plataspidae): An Invasive Pest of Soybeans.

PubMed

Grant, Jessica I; Lamp, William O

2017-12-08

Kudzu bug, Megacopta cribraria Fabricius (Hemiptera: Plataspidae), first discovered in the United States in 2009, is an invasive pest of soybeans. From 2013 to 2016, Maryland has been the northern limit of its distribution in the United States. We sought to determine the physiological cold temperature limits, timing of movement to overwintering locations, and to characterize overwintering microhabitat temperature. We measured supercooling point (SCP) on three populations from distinct USDA plant hardiness zones in Maryland and Virginia between October and December of 2015. The average SCP across all sample months and populations was -12.6°C and no consistent trend of month or population location were observed. Additionally, we assessed the lower lethal temperature to kill 50% of the population (LLT50) at the same population locations in October and November 2015. The average LLT50 over both months and all three population locations was -5.1°C. Again, no consistent trend based on population location was observed but we did find a modest depression in the LLT50 values between October and November. We observed that kudzu bug overwinters in leaf litter and begins to move into the litter in late November to early December. Leaf litter moderates day to night temperature differences and was warmer than ambient temperature by an average of 0.7°C. Evidence suggests that the cold tolerance of the kudzu bug limits its distribution north of Maryland. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Geographical, meteorological and vectorial factors related to malaria re-emergence in Huang-Huai River of central China.

PubMed

Zhou, Shui S; Huang, Fang; Wang, Jian J; Zhang, Shao S; Su, Yun P; Tang, Lin H

2010-11-24

Malaria still represents a significant public health problem in China, and the cases dramatically increased in the areas along the Huang-Huai River of central China after 2001. Considering spatial aggregation of malaria cases and specific vectors, the geographical, meteorological and vectorial factors were analysed to determine the key factors related to malaria re-emergence in these particular areas. The geographic information of 357 malaria cases and 603 water bodies in 113 villages were collected to analyse the relationship between the residence of malaria cases and water body. Spearman rank correlation, multiple regression, curve fitting and trend analysis were used to explain the relationship between the meteorological factors and malaria incidence. Entomological investigation was conducted in two sites to get the vectorial capacity and the basic reproductive rate to determine whether the effect of vector lead to malaria re-emergence. The distances from household of cases to the nearest water-body was positive-skew distributed, the median was 60.9 m and 74% malaria cases were inhabited in the extent of 60 m near the water body, and the risk rate of people live there attacked by malaria was higher than others(OR = 1.6, 95%CI (1.042, 2.463), P < 0.05). The annual average temperature and rainfall may have close relationship with annual incidence. The average monthly temperature and rainfall were the key factors, and the correlation coefficients are 0.501 and 0.304(P < 0.01), respectively. Moreover, 75.3% changes of monthly malaria incidence contributed to the average monthly temperature (T(mean)), the average temperature of last two months(T(mean₀₁)) and the average rainfall of current month (R(mean)) and the regression equation was Y = -2.085 + 0.839I₁ + 0.998T(mean₀) - 0.86T(mean₀₁) + 0.16R(mean₀). All the collected mosquitoes were Anopheles sinensis. The vectorial capacity and the basic reproductive rate of An. sinensis in two sites were 0.6969, 0.4983 and 2.1604, 1.5447, respectively. The spatial distribution between malaria cases and water-body, the changing of meteorological factors, and increasing vectorial capacity and basic reproductive rate of An. sinensis leaded to malaria re-emergence in these areas.

Geographical, meteorological and vectorial factors related to malaria re-emergence in Huang-Huai River of central China

PubMed Central

2010-01-01

Background Malaria still represents a significant public health problem in China, and the cases dramatically increased in the areas along the Huang-Huai River of central China after 2001. Considering spatial aggregation of malaria cases and specific vectors, the geographical, meteorological and vectorial factors were analysed to determine the key factors related to malaria re-emergence in these particular areas. Methods The geographic information of 357 malaria cases and 603 water bodies in 113 villages were collected to analyse the relationship between the residence of malaria cases and water body. Spearman rank correlation, multiple regression, curve fitting and trend analysis were used to explain the relationship between the meteorological factors and malaria incidence. Entomological investigation was conducted in two sites to get the vectorial capacity and the basic reproductive rate to determine whether the effect of vector lead to malaria re-emergence. Results The distances from household of cases to the nearest water-body was positive-skew distributed, the median was 60.9 m and 74% malaria cases were inhabited in the extent of 60 m near the water body, and the risk rate of people live there attacked by malaria was higher than others(OR = 1.6, 95%CI (1.042, 2.463), P < 0.05). The annual average temperature and rainfall may have close relationship with annual incidence. The average monthly temperature and rainfall were the key factors, and the correlation coefficients are 0.501 and 0.304(P < 0.01), respectively. Moreover, 75.3% changes of monthly malaria incidence contributed to the average monthly temperature (Tmean), the average temperature of last two months(Tmean01) and the average rainfall of current month (Rmean) and the regression equation was Y = -2.085 + 0.839I1 + 0.998Tmean0 - 0.86Tmean01 + 0.16Rmean0. All the collected mosquitoes were Anopheles sinensis. The vectorial capacity and the basic reproductive rate of An. sinensis in two sites were 0.6969, 0.4983 and 2.1604, 1.5447, respectively. Conclusion The spatial distribution between malaria cases and water-body, the changing of meteorological factors, and increasing vectorial capacity and basic reproductive rate of An. sinensis leaded to malaria re-emergence in these areas. PMID:21092326

Ixodes ricinus parasitism of birds increases at higher winter temperatures.

PubMed

Furness, Robert W; Furness, Euan N

2018-06-01

Increasing winter temperatures are expected to cause seasonal activity of Ixodes ricinus ticks to extend further into the winter. We caught birds during winter months (November to February) at a site in the west of Scotland over a period of 24 years (1993-1994 to 2016-2017) to quantify numbers of attached I. ricinus and to relate these to monthly mean temperature. No adult ticks were found on any of the 21,731 bird captures, but 946 larvae and nymphs were found, with ticks present in all winter months, on 16 different species of bird hosts. All ticks identified to species were I. ricinus. I. ricinus are now active throughout the year in this area providing temperature permits. No I. ricinus were present in seven out of eight months when the mean temperature was below 3.5º C. Numbers of I. ricinus attached to birds increased rapidly with mean monthly temperatures above 7º C. Winter temperatures in Scotland have been above the long-term average in most years in the last two decades, and this is likely to increase risk of tick-borne disease. © 2018 The Society for Vector Ecology.

Analysis of trends in climate, streamflow, and stream temperature in north coastal California

USGS Publications Warehouse

Madej, Mary Ann; Medley, C. Nicholas; Patterson, Glenn; Parker, Melanie J.

2011-01-01

As part of a broader project analyzing trends in climate, streamflow, vegetation, salmon, and ocean conditions in northern California national park units, we compiled average monthly air temperature and precipitation data from 73 climate stations, streamflow data from 21 river gaging stations, and limited stream temperature data from salmon-bearing rivers in north coastal California. Many climate stations show a statistically significant increase in both average maximum and average minimum air temperature in early fall and midwinter during the last century. Concurrently, average September precipitation has decreased. In many coastal rivers, summer low flow has decreased and summer stream temperatures have increased, which affects summer rearing habitat for salmonids. Nevertheless, because vegetative cover has also changed during this time period, we cannot ascribe streamflow changes to climate change without first assessing water budgets. Although shifts in the timing of the centroid of runoff have been documented in snowmelt-dominated watersheds in the western United States, this was not the case in lower elevation coastal rivers analyzed in this study.

Time series analysis of cholera in Matlab, Bangladesh, during 1988-2001.

PubMed

Ali, Mohammad; Kim, Deok Ryun; Yunus, Mohammad; Emch, Michael

2013-03-01

The study examined the impact of in-situ climatic and marine environmental variability on cholera incidence in an endemic area of Bangladesh and developed a forecasting model for understanding the magnitude of incidence. Diarrhoea surveillance data collected between 1988 and 2001 were obtained from a field research site in Matlab, Bangladesh. Cholera cases were defined as Vibrio cholerae O1 isolated from faecal specimens of patients who sought care at treatment centres serving the Matlab population. Cholera incidence for 168 months was correlated with remotely-sensed sea-surface temperature (SST) and in-situ environmental data, including rainfall and ambient temperature. A seasonal autoregressive integrated moving average (SARIMA) model was used for determining the impact of climatic and environmental variability on cholera incidence and evaluating the ability of the model to forecast the magnitude of cholera. There were 4,157 cholera cases during the study period, with an average of 1.4 cases per 1,000 people. Since monthly cholera cases varied significantly by month, it was necessary to stabilize the variance of cholera incidence by computing the natural logarithm to conduct the analysis. The SARIMA model shows temporal clustering of cholera at one- and 12-month lags. There was a 6% increase in cholera incidence with a minimum temperature increase of one degree celsius in the current month. For increase of SST by one degree celsius, there was a 25% increase in the cholera incidence at currrent month and 18% increase in the cholera incidence at two months. Rainfall did not influenc to cause variation in cholera incidence during the study period. The model forecast the fluctuation of cholera incidence in Matlab reasonably well (Root mean square error, RMSE: 0.108). Thus, the ambient and sea-surface temperature-based model could be used in forecasting cholera outbreaks in Matlab.

A simplified water temperature model for the Colorado River below Glen Canyon Dam

USGS Publications Warehouse

Wright, S.A.; Anderson, C.R.; Voichick, N.

2009-01-01

Glen Canyon Dam, located on the Colorado River in northern Arizona, has affected the physical, biological and cultural resources of the river downstream in Grand Canyon. One of the impacts to the downstream physical environment that has important implications for the aquatic ecosystem is the transformation of the thermal regime from highly variable seasonally to relatively constant year-round, owing to hypolimnetic releases from the upstream reservoir, Lake Powell. Because of the perceived impacts on the downstream aquatic ecosystem and native fish communities, the Glen Canyon Dam Adaptive Management Program has considered modifications to flow releases and release temperatures designed to increase downstream temperatures. Here, we present a new model of monthly average water temperatures below Glen Canyon Dam designed for first-order, relatively simple evaluation of various alternative dam operations. The model is based on a simplified heat-exchange equation, and model parameters are estimated empirically. The model predicts monthly average temperatures at locations up to 421 km downstream from the dam with average absolute errors less than 0.58C for the dataset considered. The modelling approach used here may also prove useful for other systems, particularly below large dams where release temperatures are substantially out of equilibrium with meteorological conditions. We also present some examples of how the model can be used to evaluate scenarios for the operation of Glen Canyon Dam.

Evapotranspiration and microclimate at a low-level radioactive-waste disposal site in northwestern Illinois

USGS Publications Warehouse

Healy, R.W.; DeVries, M.P.; Sturrock, Alex M.

1989-01-01

From July 1982 through June 1984, a study was made of the evapotranspiration and microclimate at a low-level radioactive-waste disposal site near Sheffield, Bureau County, Illinois. Vegetation at the site consists of mixed pasture grasses, primarily awnless brome (Bromus inermis) and red clover (Trifoleum pratense). Three methods were used to estimate evapotranspiration: (1) an energy budget with the Bowen ratio, (2) an aerodynamic profile, and (3) a soil-based water budget. For the aerodynamic-profile method, sensible-heat flux was estimated by a profile equation and evapotranspiration was then calculated as the residual in the energy-balance equation. Estimates by the energy-budget and aerodynamic-profile methods were computed from hourly data and then summed by days and months. Yearly estimates (for March through November) by these methods were in close agreement: 648 and 626 millimeters, respectively. Daily estimates reach a maximum of about 6 millimeters. The water-budget method produced only monthly estimates based on weekly or biweekly soil-moisture content measurements. The yearly evapotranspiration estimated by this method (which actually included only the months of April through October) was 655 millimeters. The March-through-November average for the three methods of 657 millimeters was equivalent to 70 percent of total precipitation. Continuous measurements were made of incoming and reflected shortwave radiation, incoming and emitted longwave radiation, net radiation, soil-heat flux, soil temperature, horizontal windspeed, and wet- and dry-bulb air temperature. Windspeed and air temperature were measured at heights of 0.5 and 2.0 meters (and also at 1.0 meter after September 1983). Soilmoisture content of the soil zone was measured with a gamma-attenuation gage. Annual precipitation (938 millimeters) and average temperature (10.8 degrees Celsius) at the Sheffield site were virtually identical to long-term averages from nearby National Weather Service stations. Solar radiation averaged 65 percent of that normally expected under clear skies. Net radiation averaged 70.1 watts per square meter and was highest in July and negative during some winter months. Wind direction varied but was predominately south-southeasterly. Wind speed at the 2-meter height averaged 3.5 meters per second and was slightly higher in winter months than the rest of the year. The amount of water stored within the soil zone was greatest in early spring and least in late summer. Seasonal and diurnal trends of evapotranspiration rates mirrored those of net radiation; July was usually the month with the highest evapotranspiration rate. The ratio of sensible- to latentheat fluxes (commonly called the Bowen ratio) for the 2-year study period was 0.38, as averaged from the three methods. Monthly Bowen ratios fluctuated somewhat but averaged about 0.35 for late spring through summer. In fall, the ratio declined to zero or to slightly negative values. When the ratio was negative, the latent-heat flux was slightly greater than the net radiation because of additional energy supplied by' the cooling soil and air. Evapotranspiration calculated by the three methods averaged 75 percent of potential evapotranspiration, as estimated by the Penman equation. There was no apparent seasonal trend in the relation between actual and potential evapotranspiration rates.

Sea ice and oceanic processes on the Ross Sea continental shelf

NASA Astrophysics Data System (ADS)

Jacobs, S. S.; Comiso, J. C.

1989-12-01

We have investigated the spatial and temporal variability of Antarctic sea ice concentrations on the Ross Sea continental shelf, in relation to oceanic and atmospheric forcing. Sea ice data were derived from Nimbus 7 scanning multichannel microwave radiometer (SMMR) brightness temperatures from 1979-1986. Ice cover over the shelf was persistently lower than above the adjacent deep ocean, averaging 86% during winter with little month-to-month or interannual variability. The large spring Ross Sea polynya on the western shelf results in a longer period of summer insolation, greater surface layer heat storage, and later ice formation in that region the following autumn. Newly identified Pennell and Ross Passage polynyas near the continental shelf break appear to be maintained in part by divergence above a submarine bank and by upwelling of warmer water near the slope front. Warmer subsurface water enters the shelf region year-round and will retard ice growth and enhance heat flux to the atmosphere when entrained in the strong winter vertical circulation. Temperatures at 125-m depth on a mooring near the Ross Ice Shelf during July 1984 averaged 0.15°C above freezing, sufficient to support a vertical heat flux above 100 W/m2. Monthly average subsurface ocean temperatures along the Ross Ice Shelf lag the air temperature cycle and begin to rise several weeks before spring ice breakout. The coarse SMMR resolution and dynamic ice shelf coastlines can compromise the use of microwave sea ice data near continental boundaries.

Climate controls on C3 vs. C4 productivity in North American grasslands from carbon isotope composition of soil organic matter

USGS Publications Warehouse

von Fischer, J.C.; Tieszen, L.L.; Schimel, D.S.

2008-01-01

We analyzed the ??13 C of soil organic matter (SOM) and fine roots from 55 native grassland sites widely distributed across the US and Canadian Great Plains to examine the relative production of C3 vs. C4 plants (hereafter %C4) at the continental scale. Our climate vs. %C4 results agreed well with North American field studies on %C4, but showed bias with respect to %C4 from a US vegetation database (statsgo) and weak agreement with a physiologically based prediction that depends on crossover temperature. Although monthly average temperatures have been used in many studies to predict %C4, our analysis shows that high temperatures are better predictors of %C4. In particular, we found that July climate (average of daily high temperature and month's total rainfall) predicted %C4 better than other months, seasons or annual averages, suggesting that the outcome of competition between C3 and C4 plants in North American grasslands was particularly sensitive to climate during this narrow window of time. Root ??13 C increased about 1??? between the A and B horizon, suggesting that C 4 roots become relatively more common than C3 roots with depth. These differences in depth distribution likely contribute to the isotopic enrichment with depth in SOM where both C3 and C4 grasses are present. ?? 2008 The Authors Journal compilation ?? 2008 Blackwell Publishing Ltd.

Understanding the past to interpret the future: Comparison of simulated groundwater recharge in the upper Colorado River basin (USA) using observed and general-circulation-model historical climate data

USGS Publications Warehouse

Tillman, Fred D.; Gangopadhyay, Subhrendu; Pruitt, Tom

2017-01-01

In evaluating potential impacts of climate change on water resources, water managers seek to understand how future conditions may differ from the recent past. Studies of climate impacts on groundwater recharge often compare simulated recharge from future and historical time periods on an average monthly or overall average annual basis, or compare average recharge from future decades to that from a single recent decade. Baseline historical recharge estimates, which are compared with future conditions, are often from simulations using observed historical climate data. Comparison of average monthly results, average annual results, or even averaging over selected historical decades, may mask the true variability in historical results and lead to misinterpretation of future conditions. Comparison of future recharge results simulated using general circulation model (GCM) climate data to recharge results simulated using actual historical climate data may also result in an incomplete understanding of the likelihood of future changes. In this study, groundwater recharge is estimated in the upper Colorado River basin, USA, using a distributed-parameter soil-water balance groundwater recharge model for the period 1951–2010. Recharge simulations are performed using precipitation, maximum temperature, and minimum temperature data from observed climate data and from 97 CMIP5 (Coupled Model Intercomparison Project, phase 5) projections. Results indicate that average monthly and average annual simulated recharge are similar using observed and GCM climate data. However, 10-year moving-average recharge results show substantial differences between observed and simulated climate data, particularly during period 1970–2000, with much greater variability seen for results using observed climate data.

Intermediate photovoltaic system application experiment operational performance report. Volume 6: Beverly High School, Beverly, Mass.

NASA Astrophysics Data System (ADS)

1982-03-01

Performance data are given for the month of February, 1982 for a photovoltaic power supply at a Massachusetts high school. Data given include: monthly and daily electrical energy yield; monthly and daily insolation; monthly and daily array efficiency; energy production as a function of power level, voltage, cell temperature, and hour of day; insolation as a function of hour of the day; input, output and efficiency for each of two power conditioning units and for the total power conditioning system; energy supplied to the load by the photovoltaic system and by the grid; photovoltaic system efficiency; dollar value of the energy supplied by the photovoltaic system; capacity factor; daily photovoltaic energy to load; daily system availability and hours of daylight; heating and cooling degree days; hourly cell temperature, ambient temperature, wind speed, and insolation; average monthly wind speed; wind direction distribution; and daily data acquisition mode and recording interval plot.

Noninvasive selective cryolipolysis and reperfusion recovery for localized natural fat reduction and contouring.

PubMed

Sasaki, Gordon H; Abelev, Natalie; Tevez-Ortiz, Ana

2014-03-01

Cryolipolysis is a contemporary method of reducing fat by controlled extraction of heat from adipocytes. The authors recorded temperature profiles during a single cryolipolysis treatment/recovery cycle (with and without massage) and report on the clinical safety and efficacy of this procedure. In the pilot study group (PSG), the abdomens of 6 patients were treated with cryolipolysis and subdermal temperatures were recorded. In the clinical treatment group (CTG), 112 patients were treated without temperature recordings and results were evaluated through matched comparison of standardized photographs, caliper measurements, ultrasound imaging, and global assessments. Thirty minutes into the cooling phase, subdermal temperatures of patients in the PSG declined precipitously from pretreatment levels and remained low until the end of treatment. During recovery, subdermal temperatures of the only subject who received massage returned faster and to higher levels than the temperatures of subjects who did not receive massage. Patients in the CTG who were available for follow-up measurements at 6 months (n = 85) demonstrated an average fat reduction of 21.5% by caliper measurements; 6 random patients from this group also showed an average of 19.6% fat reduction by ultrasound imaging at 6 months. Global assessments were highest for the abdomen, hip, and brassiere rolls. Minimal side effects were observed, and patients experienced no significant downtime. Noninvasive cryolipolysis results in a predictable and noticeable fat reduction within 6 months and does not cause skin damage. Profiling of subdermal temperatures may provide additional insights for improving clinical effectiveness and safety. 3.

Investigating the Relationship between Latitude and Temperature

ERIC Educational Resources Information Center

McGivney-Burelle, Jean; McGivney, Raymond J.; McGivney, Katherine G.

2008-01-01

This article describes an engaging, data-gathering activity that allows students to explore relationships between latitude and average monthly temperatures of cities in the Western Hemisphere. This data-gathering activity covered interesting and important mathematical ground and engaged students from the start. While students searched for their…

International reference ionosphere 1990

NASA Technical Reports Server (NTRS)

Bilitza, Dieter; Rawer, K.; Bossy, L.; Kutiev, I.; Oyama, K.-I.; Leitinger, R.; Kazimirovsky, E.

1990-01-01

The International Reference Ionosphere 1990 (IRI-90) is described. IRI described monthly averages of the electron density, electron temperature, ion temperature, and ion composition in the altitude range from 50 to 1000 km for magnetically quiet conditions in the non-auroral ionosphere. The most important improvements and new developments are summarized.

Characterizing the urban temperature trend using seasonal unit root analysis: Hong Kong from 1970 to 2015

NASA Astrophysics Data System (ADS)

To, Wai-Ming; Yu, Tat-Wai

2016-12-01

This paper explores urban temperature in Hong Kong using long-term time series. In particular, the characterization of the urban temperature trend was investigated using the seasonal unit root analysis of monthly mean air temperature data over the period January 1970 to December 2013. The seasonal unit root test makes it possible to determine the stochastic trend of monthly temperatures using an autoregressive model. The test results showed that mean air temperature has increased by 0.169°C (10 yr)-1 over the past four decades. The model of monthly temperature obtained from the seasonal unit root analysis was able to explain 95.9% of the variance in the measured monthly data — much higher than the variance explained by the ordinary least-squares model using annual mean air temperature data and other studies alike. The model accurately predicted monthly mean air temperatures between January 2014 and December 2015 with a root-mean-square percentage error of 4.2%. The correlation between the predicted and the measured monthly mean air temperatures was 0.989. By analyzing the monthly air temperatures recorded at an urban site and a rural site, it was found that the urban heat island effect led to the urban site being on average 0.865°C warmer than the rural site over the past two decades. Besides, the results of correlation analysis showed that the increase in annual mean air temperature was significantly associated with the increase in population, gross domestic product, urban land use, and energy use, with the R2 values ranging from 0.37 to 0.43.

Altering Flight Schedules for Increased Fuel Efficiency

DTIC Science & Technology

2015-06-19

Committee Membership: Dr. Adam D. Reiman Chair (Primary Research Advisor) iv AFIT...vi Acknowledgments I would like to express my sincere appreciation to my faculty advisor, Lieutenant Colonel Adam Reiman , for his...18 Figure 11. Average Monthly Sea Level Temperature vs. Latitude ( Reiman , 2014) ....... 22 Figure 12. Charleston AFB Hourly Temperature

The Carbon Cycle Response to Two El Nino Types: Observational Study

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

Chylek, Petr; Tans, Pieter; Christy, John

Here, we analyze monthly tropical near surface air temperature and Mauna Loa Observatory carbon dioxide (CO 2) data within 1960-2016 to identify different carbon cycle responses for two El Nino types: El Ninos originating in the central tropical Pacific (CP El Nino) and El Ninos originating in the eastern tropical Pacific (EP El Nino). We find significant differences between the two types of El Nino events with respect to time delay of the CO 2 rise rate that follows the increase in tropical near surface air temperatures caused by El Nino events. The average time lag of the CP Elmore » Nino is 4.0±1.7 months, while the mean time lag of EP El Nino is found to be 8.5±2.3 months. The average lag of all considered 1960-2016 El Ninos is 5.2±2.7 months. In contrast the sensitivity of CO2 growth rate to tropical near surface air temperature increase is determined to be about the same for both El Nino types equal to 2.8±0.9 ppmyr -1K -1 (or 5.9±1.9 GtCyr -1K -1). Our results should be useful for the understanding of the carbon cycle and constraining it in climate models.« less

The Carbon Cycle Response to Two El Nino Types: Observational Study

DOE PAGES

Chylek, Petr; Tans, Pieter; Christy, John; ...

2017-11-22

Here, we analyze monthly tropical near surface air temperature and Mauna Loa Observatory carbon dioxide (CO 2) data within 1960-2016 to identify different carbon cycle responses for two El Nino types: El Ninos originating in the central tropical Pacific (CP El Nino) and El Ninos originating in the eastern tropical Pacific (EP El Nino). We find significant differences between the two types of El Nino events with respect to time delay of the CO 2 rise rate that follows the increase in tropical near surface air temperatures caused by El Nino events. The average time lag of the CP Elmore » Nino is 4.0±1.7 months, while the mean time lag of EP El Nino is found to be 8.5±2.3 months. The average lag of all considered 1960-2016 El Ninos is 5.2±2.7 months. In contrast the sensitivity of CO2 growth rate to tropical near surface air temperature increase is determined to be about the same for both El Nino types equal to 2.8±0.9 ppmyr -1K -1 (or 5.9±1.9 GtCyr -1K -1). Our results should be useful for the understanding of the carbon cycle and constraining it in climate models.« less

An analysis of the influence of the local effects of climatic and hydrological factors affecting new malaria cases in riverine areas along the Rio Negro and surrounding Puraquequara Lake, Amazonas, Brazil.

PubMed

Coutinho, Paulo Eduardo Guzzo; Candido, Luiz Antonio; Tadei, Wanderli Pedro; da Silva Junior, Urbano Lopes; Correa, Honorly Katia Mestre

2018-04-26

A study was conducted at three sampling regions along the Rio Negro and surrounding Puraquequara Lake, Amazonas, Brazil. The aim was to determine the influence of the local effects of climatic and hydrological variables on new malaria cases. Data was gathered on the river level, precipitation, air temperature, and the number of new cases of autochthonous malaria between January 2003 and December 2013. Monthly averages, time series decompositions, cross-correlations, and multiple regressions revealed different relationships at each location. The sampling region in the upper Rio Negro indicated no statistically significant results. However, monthly averages suggest that precipitation and air temperature correlate positively with the occurrence of new cases of malaria. In the mid Rio Negro and Puraquequara Lake, the river level positively correlated, and temperature negatively correlated with new transmissions, while precipitation correlated negatively in the mid Rio Negro and positively on the lake. Overall, the river level is a key variable affecting the formation of breeding sites, while precipitation may either develop or damage them. A negative temperature correlation is associated with the occurrence of new annual post-peak cases of malaria, when the monthly average exceeds 28.5 °C. This suggests that several factors contribute to the occurrence of new malaria cases as higher temperatures are reached at the same time as precipitation and the river levels are lowest. Differences between signals and correlation lags indicate that local characteristics have an impact on how different variables influence the disease vector's life cycle, pathogens, and consequently, new cases of malaria.

Long-term ozone and temperature correlations above SANAE, Antarctica

NASA Technical Reports Server (NTRS)

Bodeker, Gregory E.; Scourfield, Malcolm W. J.

1994-01-01

A significant decline in Antarctic total column ozone and upper air temperatures has been observed in recent years. Furthermore, high correlations between monthly mean values of ozone and stratospheric temperature have been measured above Syowa, Antarctica. For the observations reported here, data from TOMS (Total Ozone Mapping Spectrometer) aboard the Nimbus 7 satellite have been used to examine the 1980 to 1990 decrease in total column ozone above the South African Antarctic base of SANAE (70 deg 18 min S, 2 deg 21 min W). The cooling of the Antarctic stratosphere above SANAE during this period has been investigated by examining upper air temperatures at the 150, 100, 70, 50, and 30 hPa levels obtained from daily radiosonde balloon launches. Furthermore, these two data sets have been used to examine long-term, medium-term, and short-term correlations between total column ozone and the temperatures at each of the five levels. The trend in SANAE total column ozone has been found to be -4.9 DU/year, while upper air temperatures have been found to decrease at around 0.3 C/year. An analysis of monthly average SANAE total column ozone has shown the decrease to be most severe during the month of September with a trend of -7.7 DU/year. A strong correlation (r(exp 2) = 0.92) has been found between yearly average total column ozone and temperature at the 100 hPa level. Daily ozone and temperature correlations show high values from September to November, at a time when the polar vortex is breaking down.

Detection of trends and break points in temperature: the case of Umbria (Italy) and Guadalquivir Valley (Spain)

NASA Astrophysics Data System (ADS)

Herrera-Grimaldi, Pascual; García-Marín, Amanda; Ayuso-Muñoz, José Luís; Flamini, Alessia; Morbidelli, Renato; Ayuso-Ruíz, José Luís

2018-02-01

The increase of air surface temperature at global scale is a fact with values around 0.85 °C since the late nineteen century. Nevertheless, the increase is not equally distributed all over the world, varying from one region to others. Thus, it becomes interesting to study the evolution of temperature indices for a certain area in order to analyse the existence of climatic trend in it. In this work, monthly temperature time series from two Mediterranean areas are used: the Umbria region in Italy, and the Guadalquivir Valley in southern Spain. For the available stations, six temperature indices (three annual and three monthly) of mean, average maximum and average minimum temperature have been obtained, and the existence of trends has been studied by applying the non-parametric Mann-Kendall test. Both regions show a general increase in all temperature indices, being the pattern of the trends clearer in Spain than in Italy. The Italian area is the only one at which some negative trends are detected. The presence of break points in the temperature series has been also studied by using the non-parametric Pettit test and the parametric standard normal homogeneity test (SNHT), most of which may be due to natural phenomena.

Variation in the sensitivity of organismal body temperature to climate change over local and geographic scales.

PubMed

Gilman, Sarah E; Wethey, David S; Helmuth, Brian

2006-06-20

Global climate change is expected to have broad ecological consequences for species and communities. Attempts to forecast these consequences usually assume that changes in air or water temperature will translate into equivalent changes in a species' organismal body temperature. This simple change is unlikely because an organism's body temperature is determined by a complex series of interactions between the organism and its environment. Using a biophysical model, validated with 5 years of field observations, we examined the relationship between environmental temperature change and body temperature of the intertidal mussel Mytilus californianus over 1,600 km of its geographic distribution. We found that at all locations examined simulated changes in air or water temperature always produced less than equivalent changes in the daily maximum mussel body temperature. Moreover, the magnitude of body temperature change was highly variable, both within and among locations. A simulated 1 degrees C increase in air or water temperature raised the maximum monthly average of daily body temperature maxima by 0.07-0.92 degrees C, depending on the geographic location, vertical position, and temperature variable. We combined these sensitivities with predicted climate change for 2100 and calculated increases in monthly average maximum body temperature of 0.97-4.12 degrees C, depending on location and climate change scenario. Thus geographic variation in body temperature sensitivity can modulate species' experiences of climate change and must be considered when predicting the biological consequences of climate change.

Sensitive study of the climatological SST by using ATSR global SST data sets

NASA Astrophysics Data System (ADS)

Xue, Yong; Lawrence, Sean P.; Llewellyn-Jones, David T.

1995-12-01

Climatological sea surface temperature (SST) is an initial step for global climate processing monitoring. A comparison has been made by using Oberhuber's SST data set and two years monthly averaged SST from ATSR thermal band data to force the OGCM. In the eastern Pacific Ocean, these make only a small difference to model SST. In the western Pacific Ocean, the use of Oberhuber's data set gives higher climatological SST than that using ATSR data. The SSTs were also simulated for 1992 using climatological SSTs from two years monthly averaged ATSR data and Oberhuber data. The forcing with SST from ATSR data was found to give better SST simulation than that from Oberhuber's data. Our study has confirmed that ATSR can provide accurate monthly averaged global SST for global climate processing monitoring.

Troposphere-stratosphere (surface-55 km) monthly general circulation statistics for the Northern Hemisphere-four year averages

NASA Technical Reports Server (NTRS)

Wu, M. F.; Geller, M. A.; Olson, J. G.; Gelman, M. E.

1984-01-01

This report presents four year averages of monthly mean Northern Hemisphere general circulation statistics for the period from 1 December 1978 through 30 November 1982. Computations start with daily maps of temperature for 18 pressure levels between 1000 and 0.4 mb that were supplied by NOAA/NMC. Geopotential height and geostrophic wind are constructed using the hydrostatic and geostrophic formulae. Fields presented in this report are zonally averaged temperature, mean zonal wind, and amplitude and phase of the planetary waves in geopotential height with zonal wavenumbers 1-3. The northward fluxes of heat and eastward momentum by the standing and transient eddies along with their wavenumber decomposition and Eliassen-Palm flux propagation vectors and divergences by the standing and transient eddies along with their wavenumber decomposition are also given. Large annual and interannual variations are found in each quantity especially in the stratosphere in accordance with the changes in the planetary wave activity. The results are shown both in graphic and tabular form.

An assessment of satellite temperature distributions used to derive the net diabatic transport for zonally averaged models of the middle atmosphere

NASA Technical Reports Server (NTRS)

Remsberg, Ellis E.; Bhatt, Praful P.; Miles, Thomas

1994-01-01

Determinations of the zonally averaged and diabatically derived residual mean circulation (RMC) are particularly sensitive to the assumed zonal mean temperature distribution used as input. Several different middle atmosphere satellite temperature distributions have been employed in models and are compared here: a 4-year (late 1978 to early 1982) National Meteorological Center (NMC) climatology, the Barnett and Corney (or BC) climatology, and the 7 months of Nimbus 7 limb infrared monitor of the stratosphere (LIMS) temperatures. All three climatologies are generally accurate below the 10 hPa level, but there are systematic differences between them of up to +/-5 K in the upper stratosphere and lower mesosphere. The NMC/LIMS differences are evaluated using time series of rocketsonde and reconstructed satellite temperatures at station locations. Much of those biases can be explained by the differing vertical resolutions for the satellite-derived temperatures; the time series of reconstructed LIMS profiles have higher resolution and are more accurate. Because the LIMS temperatures are limited to just two full seasons, one cannot obtain monthly RMCs from them for an annual model calculation. Two alternate monthly climatologies are examined briefly: the 4-year Nimbus 7 stratospheric and mesospheric sounder (SAMS) temperatures and for the mesosphere the distribution from the Solar Mesosphere Explorer (SME), both of which are limb viewers of medium vertical resolution. There are also differences of the order of +/-5 K for those data sets. It is concluded that a major source of error in the determination of diabatic RMCs is a persistent pattern of temperature bias whose characteristics vary according to the vertical resolution of each individual climatology.

Do initial conditions matter? A comparison of model climatologies generated from different initial states

NASA Technical Reports Server (NTRS)

Spar, J.; Cohen, C.; Wu, P.

1981-01-01

A coarse mesh (8 by 10) 7 layer global climate model was used to compute 15 months of meteorological history in two perpetual January experiments on a water planet (without continents) with a zonally symmetric climatological January sea surface temperature field. In the first of the two water planet experiments the initial atmospheric state was a set of zonal mean values of specific humidity, temperature, and wind at each latitude. In the second experiment the model was initialized with globally uniform mean values of specific humidity and temperature on each sigma level surface, constant surface pressure (1010 mb), and zero wind everywhere. A comparison was made of the mean January climatic states generated by the two water planet experiments. The first two months of each 15 January run were discarded, and 13 month averages were computed from months 3 through 15.

Development of a database-driven system for simulating water temperature in the lower Yakima River main stem, Washington, for various climate scenarios

USGS Publications Warehouse

Voss, Frank; Maule, Alec

2013-01-01

A model for simulating daily maximum and mean water temperatures was developed by linking two existing models: one developed by the U.S. Geological Survey and one developed by the Bureau of Reclamation. The study area included the lower Yakima River main stem between the Roza Dam and West Richland, Washington. To automate execution of the labor-intensive models, a database-driven model automation program was developed to decrease operation costs, to reduce user error, and to provide the capability to perform simulations quickly for multiple management and climate change scenarios. Microsoft© SQL Server 2008 R2 Integration Services packages were developed to (1) integrate climate, flow, and stream geometry data from diverse sources (such as weather stations, a hydrologic model, and field measurements) into a single relational database; (2) programmatically generate heavily formatted model input files; (3) iteratively run water temperature simulations; (4) process simulation results for export to other models; and (5) create a database-driven infrastructure that facilitated experimentation with a variety of scenarios, node permutations, weather data, and hydrologic conditions while minimizing costs of running the model with various model configurations. As a proof-of-concept exercise, water temperatures were simulated for a "Current Conditions" scenario, where local weather data from 1980 through 2005 were used as input, and for "Plus 1" and "Plus 2" climate warming scenarios, where the average annual air temperatures used in the Current Conditions scenario were increased by 1degree Celsius (°C) and by 2°C, respectively. Average monthly mean daily water temperatures simulated for the Current Conditions scenario were compared to measured values at the Bureau of Reclamation Hydromet gage at Kiona, Washington, for 2002-05. Differences ranged between 1.9° and 1.1°C for February, March, May, and June, and were less than 0.8°C for the remaining months of the year. The difference between current conditions and measured monthly values for the two warmest months (July and August) were 0.5°C and 0.2°C, respectively. The model predicted that water temperature generally becomes less sensitive to air temperature increases as the distance from the mouth of the river decreases. As a consequence, the difference between climate warming scenarios also decreased. The pattern of decreasing sensitivity is most pronounced from August to October. Interactive graphing tools were developed to explore the relative sensitivity of average monthly and mean daily water temperature to increases in air temperature for model output locations along the lower Yakima River main stem.

Increasing trend in the average temperature in Finland, 1847-2012

NASA Astrophysics Data System (ADS)

Mikkonen, Santtu; Laine, Marko; Mäkelä, Hanna M.; Gregow, Hilppa; Tuomenvirta, Heikki; Lahtinen, Matti; Laaksonen, Ari

2014-05-01

The global average temperature has increased by about 0.8 ° C since the mid-19th century. It has been shown that this increase is statistically significant and that it can, for the most part, be attributed to human-induced climate change (IPCC 2007). A temperature increase is obvious also in regional and local temperatures in many parts of the world. However, compared with the global average temperature, the regional and local temperatures exhibit higher levels of noise, which has largely been removed from the global temperature due to the higher level of averaging. Because Finland is located in northern latitudes, it is subject to the polar amplification of climate change-induced warming, which is due to the enhanced melting of snow and ice and other feedback mechanisms. Therefore, warming in Finland is expected to be approximately 50% higher than the global average. Conversely, the location of Finland between the Atlantic Ocean and continental Eurasia causes the weather to be very variable, and thus the temperature signal is rather noisy. The change in mean temperature in Finland was investigated with Dynamic Linear Models (DLM) in order to define the sign and the magnitude of the trend in the temperature time series within the last 165 years. The data consisted of gridded monthly mean temperatures. The grid has a 10 km spatial resolution, and it was created by interpolating a homogenized temperature series measured at Finnish weather stations. Seasonal variation in temperature and the autocorrelation structure of the time series were taken account in the DLM models. We found that the Finnish temperature time series exhibits a statistically significant increasing trend, which is consistent with human-induced global warming. The mean temperature has risen clearly over 2° C in the years 1847-2012, which amounts to 0.16 ° C/decade. The warming rate before 1940's was close to the linear trend for the whole period, whereas the temperature change in the mid-20th century was negligible. However, the warming after the late 1960s has been remarkably fast. The model indicates that within the last 40 years the rate of change has been as high as 0.30 ° C/decade. The increase in temperature has been highest in spring and in late autumn but the change in summer months has not been so evident. The observed warming is somewhat higher than the global trend, which confirms the assumption that warming is stronger in higher latitudes.

Canadian crop calendars in support of the early warning project

NASA Technical Reports Server (NTRS)

Trenchard, M. H.; Hodges, T. (Principal Investigator)

1980-01-01

The Canadian crop calendars for LACIE are presented. Long term monthly averages of daily maximum and daily minimum temperatures for subregions of provinces were used to simulate normal daily maximum and minimum temperatures. The Robertson (1968) spring wheat and Williams (1974) spring barley phenology models were run using the simulated daily temperatures and daylengths for appropriate latitudes. Simulated daily temperatures and phenology model outputs for spring wheat and spring barley are given.

Time Series Analysis of Cholera in Matlab, Bangladesh, during 1988-2001

PubMed Central

Kim, Deok Ryun; Yunus, Mohammad; Emch, Michael

2013-01-01

The study examined the impact of in-situ climatic and marine environmental variability on cholera incidence in an endemic area of Bangladesh and developed a forecasting model for understanding the magnitude of incidence. Diarrhoea surveillance data collected between 1988 and 2001were obtained from a field research site in Matlab, Bangladesh. Cholera cases were defined as Vibrio cholerae O1 isolated from faecal specimens of patients who sought care at treatment centres serving the Matlab population. Cholera incidence for 168 months was correlated with remotely-sensed sea-surface temperature (SST) and in-situ environmental data, including rainfall and ambient temperature. A seasonal autoregressive integrated moving average (SARIMA) model was used for determining the impact of climatic and environmental variability on cholera incidence and evaluating the ability of the model to forecast the magnitude of cholera. There were 4,157 cholera cases during the study period, with an average of 1.4 cases per 1,000 people. Since monthly cholera cases varied significantly by month, it was necessary to stabilize the variance of cholera incidence by computing the natural logarithm to conduct the analysis. The SARIMA model shows temporal clustering of cholera at one- and 12-month lags. There was a 6% increase in cholera incidence with a minimum temperature increase of one degree celsius in the current month. For increase of SST by one degree celsius, there was a 25% increase in the cholera incidence at currrent month and 18% increase in the cholera incidence at two months. Rainfall did not influenc to cause variation in cholera incidence during the study period. The model forecast the fluctuation of cholera incidence in Matlab reasonably well (Root mean square error, RMSE: 0.108). Thus, the ambient and sea-surface temperature-based model could be used in forecasting cholera outbreaks in Matlab. PMID:23617200

Air temperature changes in Toruń (central Poland) from 1871 to 2010

NASA Astrophysics Data System (ADS)

Pospieszyńska, Aleksandra; Przybylak, Rajmund

2018-02-01

The article presents a detailed analysis of changes in air temperature in Toruń in the period 1871-2010 on the basis of homogenised monthly, seasonal and annual air temperature series which have been newly constructed (i.e. extended by the 50 years of 1871-1920). Over the 140-year study period, a sizeable and statistically significant increase of 0.1 °C per decade was found in the air temperature in Toruń. The greatest increases occurred for spring and winter, at 0.12 and 0.11 °C, respectively. A lesser warming, meanwhile, was recorded for autumn (0.10 °C/10 years), and particularly for summer (0.07 °C/10 years). The air temperature trends are statistically significant for all seasons. Air temperature differences between the monthly averages of three analysed subperiods (1871-1900, 1901-1950 and 1951-2010) and averages for the entire period under review rarely exceeded ± 0.5 °C. In all of these periods, the highest average air temperatures occurred in July and the lowest in January. The period of 1981-2010 had the highest frequency of occurrence of very and extremely warm seasons and years. Meanwhile, the highest frequency of very and extremely cool seasons and years was recorded in the 1940s and in the nineteenth century. In the period of 1871-2010, winters shortened markedly (by 7%) and summers lengthened by 3.8%. All of the presented aspects of air temperature in Toruń, which is representative of the climate of central Poland, are in close agreement with the findings of analogous studies of the same for other areas of Poland and Central Europe.

Forest dynamics to precipitation and temperature in the Gulf of Mexico coastal region.

PubMed

Li, Tianyu; Meng, Qingmin

2017-05-01

The forest is one of the most significant components of the Gulf of Mexico (GOM) coast. It provides livelihood to inhabitant and is known to be sensitive to climatic fluctuations. This study focuses on examining the impacts of temperature and precipitation variations on coastal forest. Two different regression methods, ordinary least squares (OLS) and geographically weighted regression (GWR), were employed to reveal the relationship between meteorological variables and forest dynamics. OLS regression analysis shows that changes in precipitation and temperature, over a span of 12 months, are responsible for 56% of NDVI variation. The forest, which is not particularly affected by the average monthly precipitation in most months, is observed to be affected by cumulative seasonal and annual precipitation explicitly. Temperature and precipitation almost equally impact on NDVI changes; about 50% of the NDVI variations is explained in OLS modeling, and about 74% of the NDVI variations is explained in GWR modeling. GWR analysis indicated that both precipitation and temperature characterize the spatial heterogeneity patterns of forest dynamics.

Forest dynamics to precipitation and temperature in the Gulf of Mexico coastal region

NASA Astrophysics Data System (ADS)

Li, Tianyu; Meng, Qingmin

2017-05-01

The forest is one of the most significant components of the Gulf of Mexico (GOM) coast. It provides livelihood to inhabitant and is known to be sensitive to climatic fluctuations. This study focuses on examining the impacts of temperature and precipitation variations on coastal forest. Two different regression methods, ordinary least squares (OLS) and geographically weighted regression (GWR), were employed to reveal the relationship between meteorological variables and forest dynamics. OLS regression analysis shows that changes in precipitation and temperature, over a span of 12 months, are responsible for 56% of NDVI variation. The forest, which is not particularly affected by the average monthly precipitation in most months, is observed to be affected by cumulative seasonal and annual precipitation explicitly. Temperature and precipitation almost equally impact on NDVI changes; about 50% of the NDVI variations is explained in OLS modeling, and about 74% of the NDVI variations is explained in GWR modeling. GWR analysis indicated that both precipitation and temperature characterize the spatial heterogeneity patterns of forest dynamics.

Seasonal Variability in Tropospheric Ozone Distribution Over Qatar

NASA Astrophysics Data System (ADS)

Ayoub, Mohammed; Ackermann, Luis

2015-04-01

We report on the vertical distribution and seasonal variability in tropospheric ozone over the Middle East through one year of weekly ozonesondes launched from Doha, Qatar during 2014. A total of 49 2Z-V7 DMT/EN-SCI Electrochemical Concentration Cell (ECC) ozonesondes employing a 1% buffered potassium iodide solution (KI), coupled with iMet-1-RS GPS radiosondes were launched around 1300 local time. The authors used the SkySonde telemetry software (developed by CIRES and NOAA/ESRL) and developed robust in-house data quality assurance and validation methodologies. The average height of the thermal tropopause is between 15-17.5 km (125-85 hPa). Monthly average relative humidity around the tropopause shows an enhancement during the months of June through the beginning of October. Monthly average temperature profiles show the development of the subtropical subsidence inversion around 5-6 km (450-520 hPa) between the months of April through October. The subsidence inversion is strongest during the months of June and July and is accompanied by a sharp drop in relative humidity over a 100-300 m in the vertical. The monthly average ozone background concentration between the Planetary Boundary Layer (PBL) height and the subsidence inversion increases from 50 ppb in the winter to almost 80 ppb in the summer months. An enhancement of up to 50% in the average ozone in the mid-to-upper troposphere (above the subsidence inversion) is strongest during the summer months (June through September) and results in average concentrations between 80-100 ppb. In the upper troposphere (above 13 km/200 hPa) ozone concentrations are highest during the spring and summer months. This is coupled with a drop in the average height of the tropopause. HYSPLIT back-trajectory analysis shows the enhancement in mid-to-upper tropospheric ozone in the summer is due to persistent high pressure over the Middle East between the months of June through September. Evidence of Stratosphere-Troposphere Exchange (STE) in the winter and spring months and Monsoonal outflow observed in late summer are also reflected in the ozone profiles and HYSPLIT back-trajectories.

Arctic sea ice albedo from AVHRR

NASA Technical Reports Server (NTRS)

Lindsay, R. W.; Rothrock, D. A.

1994-01-01

The seasonal cycle of surface albedo of sea ice in the Arctic is estimated from measurements made with the Advanced Very High Resolution Radiometer (AVHRR) on the polar-orbiting satellites NOAA-10 and NOAA-11. The albedos of 145 200-km-square cells are analyzed. The cells are from March through September 1989 and include only those for which the sun is more than 10 deg above the horizon. Cloud masking is performed manually. Corrections are applied for instrument calibration, nonisotropic reflection, atmospheric interference, narrowband to broadband conversion, and normalization to a common solar zenith angle. The estimated albedos are relative, with the instrument gain set to give an albedo of 0.80 for ice floes in March and April. The mean values for the cloud-free portions of individual cells range from 0.18 to 0.91. Monthly averages of cells in the central Arctic range from 0.76 in April to 0.47 in August. The monthly averages of the within-cell standard deviations in the central Arctic are 0.04 in April and 0.06 in September. The surface albedo and surface temperature are correlated most strongly in March (R = -0.77) with little correlation in the summer. The monthly average lead fraction is determined from the mean potential open water, a scaled representation of the temperature or albedo between 0.0 (for ice) and 1.0 (for water); in the central Arctic it rises from an average 0.025 in the spring to 0.06 in September. Sparse data on aerosols, ozone, and water vapor in the atmospheric column contribute uncertainties to instantaneous, area-average albedos of 0.13, 0.04, and 0.08. Uncertainties in monthly average albedos are not this large. Contemporaneous estimation of these variables could reduce the uncertainty in the estimated albedo considerably. The poor calibration of AVHRR channels 1 and 2 is another large impediment to making accurate albedo estimates.

Seasonality of Human Leptospirosis in Reunion Island (Indian Ocean) and Its Association with Meteorological Data

PubMed Central

Desvars, Amélie; Jégo, Sylvaine; Chiroleu, Frédéric; Bourhy, Pascale; Cardinale, Eric; Michault, Alain

2011-01-01

Background Leptospirosis is a disease which occurs worldwide but particularly affects tropical areas. Transmission of the disease is dependent on its excretion by reservoir animals and the presence of moist environment which allows the survival of the bacteria. Methods and Findings A retrospective study was undertaken to describe seasonal patterns of human leptospirosis cases reported by the Centre National de Références des Leptospiroses (CNRL, Pasteur Institute, Paris) between 1998 and 2008, to determine if there was an association between the occurrence of diagnosed cases and rainfall, temperature and global solar radiation (GSR). Meteorological data were recorded in the town of Saint-Benoît (Météo France “Beaufonds-Miria” station), located on the windward (East) coast. Time-series analysis was used to identify the variables that best described and predicted the occurrence of cases of leptospirosis on the island. Six hundred and thirteen cases were reported during the 11-year study period, and 359 cases (58.56%) were diagnosed between February and May. A significant correlation was identified between the number of cases in a given month and the associated cumulated rainfall as well as the mean monthly temperature recorded 2 months prior to diagnosis (r = 0.28 and r = 0.23 respectively). The predictive model includes the number of cases of leptospirosis recorded 1 month prior to diagnosis (b = 0.193), the cumulated monthly rainfall recorded 2 months prior to diagnosis (b = 0.145), the average monthly temperature recorded 0 month prior to diagnosis (b = 3.836), and the average monthly GSR recorded 0 month prior to diagnosis (b = −1.293). Conclusions Leptospirosis has a seasonal distribution in Reunion Island. Meteorological data can be used to predict the occurrence of the disease and our statistical model can help to implement seasonal prevention measures. PMID:21655257

Long-Term Prediction of Emergency Department Revenue and Visitor Volume Using Autoregressive Integrated Moving Average Model

PubMed Central

Chen, Chieh-Fan; Ho, Wen-Hsien; Chou, Huei-Yin; Yang, Shu-Mei; Chen, I-Te; Shi, Hon-Yi

2011-01-01

This study analyzed meteorological, clinical and economic factors in terms of their effects on monthly ED revenue and visitor volume. Monthly data from January 1, 2005 to September 30, 2009 were analyzed. Spearman correlation and cross-correlation analyses were performed to identify the correlation between each independent variable, ED revenue, and visitor volume. Autoregressive integrated moving average (ARIMA) model was used to quantify the relationship between each independent variable, ED revenue, and visitor volume. The accuracies were evaluated by comparing model forecasts to actual values with mean absolute percentage of error. Sensitivity of prediction errors to model training time was also evaluated. The ARIMA models indicated that mean maximum temperature, relative humidity, rainfall, non-trauma, and trauma visits may correlate positively with ED revenue, but mean minimum temperature may correlate negatively with ED revenue. Moreover, mean minimum temperature and stock market index fluctuation may correlate positively with trauma visitor volume. Mean maximum temperature, relative humidity and stock market index fluctuation may correlate positively with non-trauma visitor volume. Mean maximum temperature and relative humidity may correlate positively with pediatric visitor volume, but mean minimum temperature may correlate negatively with pediatric visitor volume. The model also performed well in forecasting revenue and visitor volume. PMID:22203886

Long-term prediction of emergency department revenue and visitor volume using autoregressive integrated moving average model.

PubMed

Chen, Chieh-Fan; Ho, Wen-Hsien; Chou, Huei-Yin; Yang, Shu-Mei; Chen, I-Te; Shi, Hon-Yi

2011-01-01

This study analyzed meteorological, clinical and economic factors in terms of their effects on monthly ED revenue and visitor volume. Monthly data from January 1, 2005 to September 30, 2009 were analyzed. Spearman correlation and cross-correlation analyses were performed to identify the correlation between each independent variable, ED revenue, and visitor volume. Autoregressive integrated moving average (ARIMA) model was used to quantify the relationship between each independent variable, ED revenue, and visitor volume. The accuracies were evaluated by comparing model forecasts to actual values with mean absolute percentage of error. Sensitivity of prediction errors to model training time was also evaluated. The ARIMA models indicated that mean maximum temperature, relative humidity, rainfall, non-trauma, and trauma visits may correlate positively with ED revenue, but mean minimum temperature may correlate negatively with ED revenue. Moreover, mean minimum temperature and stock market index fluctuation may correlate positively with trauma visitor volume. Mean maximum temperature, relative humidity and stock market index fluctuation may correlate positively with non-trauma visitor volume. Mean maximum temperature and relative humidity may correlate positively with pediatric visitor volume, but mean minimum temperature may correlate negatively with pediatric visitor volume. The model also performed well in forecasting revenue and visitor volume.

Estimation of sampling error uncertainties in observed surface air temperature change in China

NASA Astrophysics Data System (ADS)

Hua, Wei; Shen, Samuel S. P.; Weithmann, Alexander; Wang, Huijun

2017-08-01

This study examines the sampling error uncertainties in the monthly surface air temperature (SAT) change in China over recent decades, focusing on the uncertainties of gridded data, national averages, and linear trends. Results indicate that large sampling error variances appear at the station-sparse area of northern and western China with the maximum value exceeding 2.0 K2 while small sampling error variances are found at the station-dense area of southern and eastern China with most grid values being less than 0.05 K2. In general, the negative temperature existed in each month prior to the 1980s, and a warming in temperature began thereafter, which accelerated in the early and mid-1990s. The increasing trend in the SAT series was observed for each month of the year with the largest temperature increase and highest uncertainty of 0.51 ± 0.29 K (10 year)-1 occurring in February and the weakest trend and smallest uncertainty of 0.13 ± 0.07 K (10 year)-1 in August. The sampling error uncertainties in the national average annual mean SAT series are not sufficiently large to alter the conclusion of the persistent warming in China. In addition, the sampling error uncertainties in the SAT series show a clear variation compared with other uncertainty estimation methods, which is a plausible reason for the inconsistent variations between our estimate and other studies during this period.

Modeling the Effect of Summertime Heating on Urban Runoff Temperature

NASA Astrophysics Data System (ADS)

Thompson, A. M.; Gemechu, A. L.; Norman, J. M.; Roa-Espinosa, A.

2007-12-01

Urban impervious surfaces absorb and store thermal energy, particularly during warm summer months. During a rainfall/runoff event, thermal energy is transferred from the impervious surface to the runoff, causing it to become warmer. As this higher temperature runoff enters receiving waters, it can be harmful to coldwater habitat. A simple model has been developed for the net energy flux at the impervious surfaces of urban areas to account for the heat transferred to runoff. Runoff temperature is determined as a function of the physical characteristics of the impervious areas, the weather, and the heat transfer between the moving film of runoff and the heated impervious surfaces that commonly exist in urban areas. Runoff from pervious surfaces was predicted using the Green- Ampt Mein-Larson infiltration excess method. Theoretical results were compared to experimental results obtained from a plot-scale field study conducted at the University of Wisconsin's West Madison Agricultural Research Station. Surface temperatures and runoff temperatures from asphalt and sod plots were measured throughout 15 rainfall simulations under various climatic conditions during the summers of 2004 and 2005. Average asphalt runoff temperatures ranged from 23.2°C to 37.1°C. Predicted asphalt runoff temperatures were in close agreement with measured values for most of the simulations (average RMSE = 4.0°C). Average pervious runoff temperatures ranged from 19.7° to 29.9°C and were closely approximated by the rainfall temperature (RMSE = 2.8°C). Predicted combined asphalt and sod runoff temperatures using a flow-weighted average were in close agreement with observed values (average RMSE = 3.5°C).

Climatic factors and community - associated methicillin-resistant Staphylococcus aureus skin and soft-tissue infections - a time-series analysis study.

PubMed

Sahoo, Krushna Chandra; Sahoo, Soumyakanta; Marrone, Gaetano; Pathak, Ashish; Lundborg, Cecilia Stålsby; Tamhankar, Ashok J

2014-08-29

Skin and soft tissue infections caused by Staphylococcus aureus (SA-SSTIs) including methicillin-resistant Staphylococcus aureus (MRSA) have experienced a significant surge all over the world. Changing climatic factors are affecting the global burden of dermatological infections and there is a lack of information on the association between climatic factors and MRSA infections. Therefore, association of temperature and relative humidity (RH) with occurrence of SA-SSTIs (n = 387) and also MRSA (n = 251) was monitored for 18 months in the outpatient clinic at a tertiary care hospital located in Bhubaneswar, Odisha, India. The Kirby-Bauer disk diffusion method was used for antibiotic susceptibility testing. Time-series analysis was used to investigate the potential association of climatic factors (weekly averages of maximum temperature, minimum temperature and RH) with weekly incidence of SA-SSTIs and MRSA infections. The analysis showed that a combination of weekly average maximum temperature above 33 °C coinciding with weekly average RH ranging between 55% and 78%, is most favorable for the occurrence of SA-SSTIs and MRSA and within these parameters, each unit increase in occurrence of MRSA was associated with increase in weekly average maximum temperature of 1.7 °C (p = 0.044) and weekly average RH increase of 10% (p = 0.097).

Prairie falcons quit nesting in response to spring snowstorm

Treesearch

John R. Squires; Stanley H. Anderson; Robert Oakleaf

1991-01-01

A small population of Prairie Falcons (Falco mexicanus) (mean = 6 pairs/year) nesting in northcentral Wyoming quit nesting in response to a severe spring snowstorm in 1984. Temperatures during the April storm were similar to years when the falcons reproduced successfully, but the monthly snowfall was 89.2 cm as compared to the 30-yr monthly average of 29.92 cm...

Brazil soybean yield covariance model

NASA Technical Reports Server (NTRS)

Callis, S. L.; Sakamoto, C.

1984-01-01

A model based on multiple regression was developed to estimate soybean yields for the seven soybean-growing states of Brazil. The meteorological data of these seven states were pooled and the years 1975 to 1980 were used to model since there was no technological trend in the yields during these years. Predictor variables were derived from monthly total precipitation and monthly average temperature.

Stochastic model stationarization by eliminating the periodic term and its effect on time series prediction

NASA Astrophysics Data System (ADS)

Moeeni, Hamid; Bonakdari, Hossein; Fatemi, Seyed Ehsan

2017-04-01

Because time series stationarization has a key role in stochastic modeling results, three methods are analyzed in this study. The methods are seasonal differencing, seasonal standardization and spectral analysis to eliminate the periodic effect on time series stationarity. First, six time series including 4 streamflow series and 2 water temperature series are stationarized. The stochastic term for these series obtained with ARIMA is subsequently modeled. For the analysis, 9228 models are introduced. It is observed that seasonal standardization and spectral analysis eliminate the periodic term completely, while seasonal differencing maintains seasonal correlation structures. The obtained results indicate that all three methods present acceptable performance overall. However, model accuracy in monthly streamflow prediction is higher with seasonal differencing than with the other two methods. Another advantage of seasonal differencing over the other methods is that the monthly streamflow is never estimated as negative. Standardization is the best method for predicting monthly water temperature although it is quite similar to seasonal differencing, while spectral analysis performed the weakest in all cases. It is concluded that for each monthly seasonal series, seasonal differencing is the best stationarization method in terms of periodic effect elimination. Moreover, the monthly water temperature is predicted with more accuracy than monthly streamflow. The criteria of the average stochastic term divided by the amplitude of the periodic term obtained for monthly streamflow and monthly water temperature were 0.19 and 0.30, 0.21 and 0.13, and 0.07 and 0.04 respectively. As a result, the periodic term is more dominant than the stochastic term for water temperature in the monthly water temperature series compared to streamflow series.

Monthly mean simulation experiments with a course-mesh global atmospheric model

NASA Technical Reports Server (NTRS)

Spar, J.; Klugman, R.; Lutz, R. J.; Notario, J. J.

1978-01-01

Substitution of observed monthly mean sea-surface temperatures (SSTs) as lower boundary conditions, in place of climatological SSTs, failed to improve the model simulations. While the impact of SST anomalies on the model output is greater at sea level than at upper levels the impact on the monthly mean simulations is not beneficial at any level. Shifts of one and two days in initialization time produced small, but non-trivial, changes in the model-generated monthly mean synoptic fields. No improvements in the mean simulations resulted from the use of either time-averaged initial data or re-initialization with time-averaged early model output. The noise level of the model, as determined from a multiple initial state perturbation experiment, was found to be generally low, but with a noisier response to initial state errors in high latitudes than the tropics.

Effect of Temperature on Feeding Period of Larval Blacklegged Ticks (Acari: Ixodidae) on Eastern Fence Lizards.

PubMed

Rulison, Eric L; Lebrun, Roger A; Ginsberg, Howard S

2014-11-01

Ambient temperature can influence tick development time, and can potentially affect tick interactions with pathogens and with vertebrate hosts. We studied the effect of ambient temperature on duration of attachment of larval blacklegged ticks, Ixodes scapularis Say, to eastern fence lizards, Sceloporus undulatus (Bosc & Daudin). Feeding periods of larvae that attached to lizards under preferred temperature conditions for the lizards (WARM treatment: temperatures averaged 36.6°C at the top of the cage and 25.8°C at the bottom, allowing behavioral thermoregulation) were shorter than for larvae on lizards held under cool conditions (COOL treatment temperatures averaged 28.4°C at top of cage and 24.9°C at the bottom). The lizards were infested with larvae four times at roughly monthly intervals. Larval numbers successfully engorging and dropping declined and feeding period was longer after the first infestation. © 2014 Entomological Society of America.

Global Distributions of Temperature Variances At Different Stratospheric Altitudes From Gps/met Data

NASA Astrophysics Data System (ADS)

Gavrilov, N. M.; Karpova, N. V.; Jacobi, Ch.

The GPS/MET measurements at altitudes 5 - 35 km are used to obtain global distribu- tions of small-scale temperature variances at different stratospheric altitudes. Individ- ual temperature profiles are smoothed using second order polynomial approximations in 5 - 7 km thick layers centered at 10, 20 and 30 km. Temperature inclinations from the averaged values and their variances obtained for each profile are averaged for each month of year during the GPS/MET experiment. Global distributions of temperature variances have inhomogeneous structure. Locations and latitude distributions of the maxima and minima of the variances depend on altitudes and season. One of the rea- sons for the small-scale temperature perturbations in the stratosphere could be internal gravity waves (IGWs). Some assumptions are made about peculiarities of IGW gener- ation and propagation in the tropo-stratosphere based on the results of GPS/MET data analysis.

Effect of temperature on feeding period of larval blacklegged ticks (Acari: Ixodidae) on eastern fence lizards

USGS Publications Warehouse

Rulison, Eric L.; LeBrun, Roger A.; Ginsberg, Howard S.

2014-01-01

Ambient temperature can influence tick development time, and can potentially affect tick interactions with pathogens and with vertebrate hosts. We studied the effect of ambient temperature on duration of attachment of larval blacklegged ticks, Ixodes scapularis Say, to eastern fence lizards, Sceloporus undulatus (Bose & Daudin). Feeding periods of larvae that attached to lizards under preferred temperature conditions for the lizards (WARM treatment: temperatures averaged 36.6°C at the top of the cage and 25.8°C at the bottom, allowing behavioral thermoregulation) were shorter than for larvae on lizards held under cool conditions (COOL treatment temperatures averaged 28.4°C at top of cage and 24.9°C at the bottom). The lizards were infested with larvae four times at roughly monthly intervals. Larval numbers successfully engorging and dropping declined and feeding period was longer after the first infestation.

Response of Arctic Snow and Sea Ice Extents to Melt Season Atmospheric Forcing Across the Land-Ocean Boundary

NASA Astrophysics Data System (ADS)

Bliss, A. C.; Anderson, M. R.

2011-12-01

Little research has gone into studying the concurrent variations in the annual loss of continental snow cover and sea ice extent across the land-ocean boundary, however, the analysis of these data averaged spatially over three study regions located in North America and Eastern and Western Russia, reveals a distinct difference in the response of anomalous snow and sea ice conditions to the atmospheric forcing. This study compares the monthly continental snow cover and sea ice extent loss in the Arctic, during the melt season months (May-August) for the period 1979-2007, with regional atmospheric conditions known to influence summer melt including: mean sea level pressures, 925 hPa air temperatures, and mean 2 m U and V wind vectors from NCEP/DOE Reanalysis 2. The monthly hemispheric snow cover extent data used are from the Rutgers University Global Snow Lab and sea ice extents for this study are derived from the monthly passive microwave satellite Bootstrap algorithm sea ice concentrations available from the National Snow and Ice Data Center. Three case study years (1985, 1996, and 2007) are used to compare the direct response of monthly anomalous sea ice and snow cover areal extents to monthly mean atmospheric forcing averaged spatially over the extent of each study region. This comparison is then expanded for all summer months over the 29 year study period where the monthly persistence of sea ice and snow cover extent anomalies and changes in the sea ice and snow conditions under differing atmospheric conditions are explored further. The monthly anomalous atmospheric conditions are classified into four categories including: warmer temperatures with higher pressures, warmer temperatures with lower pressures, cooler temperatures with higher pressures, and cooler temperatures with lower pressures. Analysis of the atmospheric conditions surrounding anomalous loss of snow and ice cover over the independent study regions indicates that conditions of warmer temperatures advected via southerly winds are effective at forcing melt, while conditions of anomalously cool temperatures with persistent, strong northeasterly winds in the later melt season months are also effective at removing anomalous extents of sea ice cover, likely through ice divergence. Normalized sea ice extent anomalies, regardless of the snow cover, tend to persist in the same positive or negative directions (or remain near normal) from month to month over the summer season in 73.6% of cases from June to July, in 69% of cases from July to August, and in 54% of cases for the entire season (June-August) for the 29 year study period. However, when shifts in the sea ice extent anomaly directions from the conditions present in the early melt season occur, it is generally associated with a shift in the atmospheric conditions forcing the change in sea ice extent loss for the region.

Heat wave hazard classification and risk assessment using artificial intelligence fuzzy logic.

PubMed

Keramitsoglou, Iphigenia; Kiranoudis, Chris T; Maiheu, Bino; De Ridder, Koen; Daglis, Ioannis A; Manunta, Paolo; Paganini, Marc

2013-10-01

The average summer temperatures as well as the frequency and intensity of hot days and heat waves are expected to increase due to climate change. Motivated by this consequence, we propose a methodology to evaluate the monthly heat wave hazard and risk and its spatial distribution within large cities. A simple urban climate model with assimilated satellite-derived land surface temperature images was used to generate a historic database of urban air temperature fields. Heat wave hazard was then estimated from the analysis of these hourly air temperatures distributed at a 1-km grid over Athens, Greece, by identifying the areas that are more likely to suffer higher temperatures in the case of a heat wave event. Innovation lies in the artificial intelligence fuzzy logic model that was used to classify the heat waves from mild to extreme by taking into consideration their duration, intensity and time of occurrence. The monthly hazard was subsequently estimated as the cumulative effect from the individual heat waves that occurred at each grid cell during a month. Finally, monthly heat wave risk maps were produced integrating geospatial information on the population vulnerability to heat waves calculated from socio-economic variables.

EnviroAtlas - Minimum Temperature 1950 - 2099 for the Conterminous United States

EPA Pesticide Factsheets

The EnviroAtlas Climate Scenarios were generated from NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30) ensemble averages (the average of over 30 available climate models) for each of the four representative concentration pathways (RCP) for the contiguous U.S. at 30 arc-second (approx. 800 m2) spatial resolution. NEX-DCP30 mean monthly minimum temperature for the 4 RCPs (2.6, 4.5, 6.0, 8.5) were organized by season (Winter, Spring, Summer, and Fall) and annually for the years 2006 00e2?? 2099. Additionally, mean monthly minimum temperature for the ensemble average of all historic runs is organized similarly for the years 1950 00e2?? 2005. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

EnviroAtlas - Maximum Temperature 1950 - 2099 for the Conterminous United States

EPA Pesticide Factsheets

The EnviroAtlas Climate Scenarios were generated from NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30) ensemble averages (the average of over 30 available climate models) for each of the four representative concentration pathways (RCP) for the contiguous U.S. at 30 arc-second (approx. 800 m2) spatial resolution. NEX-DCP30 mean monthly maximum temperature for the 4 RCPs (2.6, 4.5, 6.0, 8.5) were organized by season (Winter, Spring, Summer, and Fall) and annually for the years 2006 00e2?? 2099. Additionally, mean monthly maximum temperature for the ensemble average of all historic runs is organized similarly for the years 1950 00e2?? 2005. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Seasonal Snow Extent and Snow Volume in South America Using SSM/I Passive Microwave Data

NASA Technical Reports Server (NTRS)

Foster, James L.; Chang, A. T. C.; Hall, D. K.; Kelly, R.; Houser, Paul (Technical Monitor)

2001-01-01

Seasonal snow cover in South America was examined in this study using passive microwave satellite data from the Special Sensor Microwave Imagers (SSM/I) on board Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1992-1998, both snow cover extent and snow depth (snow mass) were investigated during the winter months (May-August) in the Patagonia region of Argentina. Since above normal temperatures in this region are typically above freezing, the coldest winter month was found to be not only the month having the most extensive snow cover but also the month having the deepest snows. For the seven-year period of this study, the average snow cover extent (May-August) was about 0.46 million sq km and the average monthly snow mass was about 1.18 x 10(exp 13) kg. July 1992 was the month having the greatest snow extent (nearly 0.8 million sq km) and snow mass (approximately 2.6 x 10(exp 13) kg).

The Relationship Between Monthdisease Incidence Rate and Climatic Factor of Classical Swine Fever

NASA Astrophysics Data System (ADS)

Wang, Hongbin; Xu, Danning; Xiao, Jianhua; Zhang, Ru; Dong, Jing

The Swine Fever is a kind of acute, highly infective epidemic disease of animals; it is name as Classical Swine Fever (CSF) by World animal Health organization. Meteorological factors such as temperature, air pressure and rainfall affect the epidemic of CSF significantly through intermediary agent and CSF viral directly. However there is significant difference among different region for mode of effects. Accordingly, the analyze must adopt different methods. The dependability between incidence rate each month of CSF and meteorological factors from 1999 to 2004 was analyzed in this paper. The function of meteorological factors on CSF was explored and internal law was expected to be discovered. The correlation between the incidence rate of Swine Fever and meteorological factors, thus the foundation analysis of the early warning and the decision-making was made, the result indicated that the incidence rate of CSF has negative correlation with temperature, rainfall, cloudage; relative humidity has positive correlation with disease; for air pressure, except average air pressure of one month, other air pressure factors have positive correlation with disease; for wind speed, except Difference among moths of wind speed and average temperature of one month. have positive correlation with disease, other wind speed factors has negative correlation with disease.

Death from respiratory diseases and temperature in Shiraz, Iran (2006-2011).

PubMed

Dadbakhsh, Manizhe; Khanjani, Narges; Bahrampour, Abbas; Haghighi, Pegah Shoae

2017-02-01

Some studies have suggested that the number of deaths increases as temperatures drops or rises above human thermal comfort zone. The present study was conducted to evaluate the relation between respiratory-related mortality and temperature in Shiraz, Iran. In this ecological study, data about the number of respiratory-related deaths sorted according to age and gender as well as average, minimum, and maximum ambient air temperatures during 2007-2011 were examined. The relationship between air temperature and respiratory-related deaths was calculated by crude and adjusted negative binomial regression analysis. It was adjusted for humidity, rainfall, wind speed and direction, and air pollutants including CO, NO x , PM 10 , SO 2 , O 3 , and THC. Spearman and Pearson correlations were also calculated between air temperature and respiratory-related deaths. The analysis was done using MINITAB16 and STATA 11. During this period, 2598 respiratory-related deaths occurred in Shiraz. The minimum number of respiratory-related deaths among all subjects happened in an average temperature of 25 °C. There was a significant inverse relationship between average temperature- and respiratory-related deaths among all subjects and women. There was also a significant inverse relationship between average temperature and respiratory-related deaths among all subjects, men and women in the next month. The results suggest that cold temperatures can increase the number of respiratory-related deaths and therefore policies to reduce mortality in cold weather, especially in patients with respiratory diseases should be implemented.

Death from respiratory diseases and temperature in Shiraz, Iran (2006-2011)

NASA Astrophysics Data System (ADS)

Dadbakhsh, Manizhe; Khanjani, Narges; Bahrampour, Abbas; Haghighi, Pegah Shoae

2017-02-01

Some studies have suggested that the number of deaths increases as temperatures drops or rises above human thermal comfort zone. The present study was conducted to evaluate the relation between respiratory-related mortality and temperature in Shiraz, Iran. In this ecological study, data about the number of respiratory-related deaths sorted according to age and gender as well as average, minimum, and maximum ambient air temperatures during 2007-2011 were examined. The relationship between air temperature and respiratory-related deaths was calculated by crude and adjusted negative binomial regression analysis. It was adjusted for humidity, rainfall, wind speed and direction, and air pollutants including CO, NOx, PM10, SO2, O3, and THC. Spearman and Pearson correlations were also calculated between air temperature and respiratory-related deaths. The analysis was done using MINITAB16 and STATA 11. During this period, 2598 respiratory-related deaths occurred in Shiraz. The minimum number of respiratory-related deaths among all subjects happened in an average temperature of 25 °C. There was a significant inverse relationship between average temperature- and respiratory-related deaths among all subjects and women. There was also a significant inverse relationship between average temperature and respiratory-related deaths among all subjects, men and women in the next month. The results suggest that cold temperatures can increase the number of respiratory-related deaths and therefore policies to reduce mortality in cold weather, especially in patients with respiratory diseases should be implemented.

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

Dougan, P.M.

During the year, design, construction and installation of all project equipment was completed, and continuous steam injection began on September 18, 1979 and continued until February 29, 1980. In the five-month period of steam injection, 235,060 barrels of water as steam at an average wellhead pressure of 1199 psig and an average wellhead temperature of 456/sup 0/F were injected into the eight project injection wells. Operation of the project at design temperature and pressure (1000/sup 0/F and 1500 psig) was not possible due to continuing problems with surface equipment. Environmental monitoring at the project site continued during startup and operation.

Rainfall and temperature changes and variability in the Upper East Region of Ghana

NASA Astrophysics Data System (ADS)

Issahaku, Abdul-Rahaman; Campion, Benjamin Betey; Edziyie, Regina

2016-08-01

The aim of the research was to assess the current trend and variation in rainfall and temperature in the Upper East Region, Ghana, using time series moving average analysis and decomposition methods. Meteorological data obtained from the Ghana Meteorological Agency in Accra, Ghana, from 1954 to 2014 were used in the models. The additive decomposition model was used to analyze the rainfall because the seasonal variation was relatively constant over time, while the multiplicative model was used for both the daytime and nighttime temperatures because their seasonal variations increase over time. The monthly maximum and the minimum values for the entire period were as follows: rainfall 455.50 and 0.00 mm, nighttime temperature 29.10°C and 13.25°C and daytime temperature 41.10°C and 26.10°C, respectively. Also, while rainfall was decreasing, nighttime and daytime temperatures were increasing in decadal times. Since both the daytime and nighttime temperatures were increasing and rainfall was decreasing, climate extreme events such as droughts could result and affect agriculture in the region, which is predominantly rain fed. Also, rivers, dams, and dugouts are likely to dry up in the region. It was also observed that there was much variation in rainfall making prediction difficult. Day temperatures were generally high with the months of March and April have been the highest. The months of December recorded the lowest night temperature. Inhabitants are therefore advised to sleep in well-ventilated rooms during the warmest months and wear protective clothing during the cold months to avoid contracting climate-related diseases.

Regional hydrologic response of loblolly pine to air temperature and precipitation changes

Treesearch

Steven G. McNulty; James M. Vose; Wayne T. Swank

1997-01-01

Large deviations in average annual air temperatures and total annual precipitation were observed across the Southern United States during the last 50 years, and these fluctuations could become even larger during the next century. The authors used PnET-IIS, a monthly time-step forest process model that uses soil, vegetation, and climate inputs to assess the influence of...

Middle Atmosphere Program. Handbook for MAP, Volume 5

NASA Technical Reports Server (NTRS)

Sechrist, C. F., Jr. (Editor)

1982-01-01

The variability of the stratosphere during the winter in the Northern Hemisphere is considered. Long term monthly mean 30-mbar maps are presented that include geopotential heights, temperatures, and standard deviations of 15 year averages. Latitudinal profiles of mean zonal winds and temperatures are given along with meridional time sections of derived quantities for the winters 1965/66 to 1980/81.

Carbon exchange and quantum efficiency of ecosystem carbon storage in mature deciduous and old-growth coniferous forest in central New England in 2001

NASA Astrophysics Data System (ADS)

Hadley, J. L.; Urbanski, S. P.

2002-12-01

Carbon storage in forests of the northeastern U.S. and adjacent Canada may be a significant carbon sink, as forests and soils in this region have recovered after agricultural abandonment in the 19th century. Data collected during the 1990's showed that an area of 70 to 100 year old deciduous forest on abandoned farmland in central Massachusetts stored an average of 2.0 Mg C/ha/yr in trees and soil. During 2001 we measured carbon exchange and environmental parameters (above-canopy air temperature, atmospheric humidity, photosynthetically active radiation (PAR) and soil temperature) in both the 70-100 year old deciduous forest and in a nearby eastern hemlock (Tsuga canadensis L.)-dominated forest with trees up to 220 years old that was never cleared for agricultural use. The deciduous forest stored more than 4 Mg C/ ha in 2001, far higher than in any previous year since measurements started in 1991. Highest monthly deciduous forest carbon storage (1.8 - 1.9 Mg ha-1 month-1) occurred in July and August. The hemlock forest stored about 3 Mg C/ha, with peak storage in April and May (0.8 - 0.9Mg C ha-1 month-1), and little or no C storage during August. The differences in carbon storage between the two forests were related to differences in quantum use efficiency. Quantum efficiency of ecosystem carbon storage in the foliated deciduous forest averaged about 0.16 g C /mol PAR and was insensitive to temperature after leaf maturation. In contrast, the average hemlock forest quantum efficiency declined from about 0.10 g C /mol PAR at daily average above-canopy air temperature (T{a}{v}{g}) = 5 oC to zero quantum efficiency (no net carbon storage) at T{a}{v}{g} = 23 oC. Optimum temperatures for carbon storage in the hemlock forest occurred in April. Differences between the two forests are likely due primarily to a higher maximum photosynthetic rate and a more positive temperature response of leaf-level photosynthesis in red oak (the dominant deciduous species) as compared with eastern hemlock. Maintenance of high soil respiration in the hemlock forest during warm dry summer weather may also contribute to declining quantum efficiency of carbon storage in the hemlock forest during the summer.

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.

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.

An analysis of Solar Mesospheric Explorer temperatures for the upper stratosphere and mesosphere

NASA Technical Reports Server (NTRS)

Clancy, R. Todd; Rusch, David W.

1993-01-01

We proposed to analyze Solar Mesosphere Explorer (SME) limb profiles of Rayleigh scattered solar flux at wavelengths of 304, 313, and 443 nm to retrieve atmospheric temperature profiles over the 40-65 km altitude region. These temperatures can be combined with the previous analysis of SME 296 nm limb radiances to construct a monthly average climatology of atmospheric temperatures over the 40-90 km, upper stratosphere-mesosphere region, with approximately 4 km vertical resolution. We proposed to investigate the detailed nature of the global temperature structure of this poorly measured region, based on these 1982-1986 SME temperatures. The average vertical structure of temperatures between the stratopause and mesopause has never been determined globally with vertical resolution sufficient to retrieve even scale-height structures. Hence, the SME temperatures provided a unique opportunity to study the detailed thermal structure of the mesosphere, in advance of Upper Atmosphere Research Satellite (UARS) measurements and the Thermosphere Ionosphere Mesosphere Energy and Dynamics (TIMED) mission.

Hospitalizations for heat-stress illness varies between rural and urban areas: an analysis of Illinois data, 1987-2014.

PubMed

Jagai, Jyotsna S; Grossman, Elena; Navon, Livia; Sambanis, Apostolis; Dorevitch, Samuel

2017-04-07

The disease burden due to heat-stress illness (HSI), which can result in significant morbidity and mortality, is expected to increase as the climate continues to warm. In the United States (U.S.) much of what is known about HSI epidemiology is from analyses of urban heat waves. There is limited research addressing whether HSI hospitalization risk varies between urban and rural areas, nor is much known about additional diagnoses of patients hospitalized for HSI. Hospitalizations in Illinois for HSI (ICD-9-CM codes 992.x or E900) in the months of May through September from 1987 to 2014 (n = 8667) were examined. Age-adjusted mean monthly hospitalization rates were calculated for each county using U.S. Census population data. Counties were categorized into five urban-rural strata using Rural Urban Continuum Codes (RUCC) (RUCC1, most urbanized to RUCC5, thinly populated). Average maximum monthly temperature (°C) was calculated for each county using daily data. Multi-level linear regression models were used, with county as the fixed effect and temperature as random effect, to model monthly hospitalization rates, adjusting for the percent of county population below the poverty line, percent of population that is Non-Hispanic Black, and percent of the population that is Hispanic. All analyses were stratified by county RUCC. Additional diagnoses of patients hospitalized for HSI and charges for hospitalization were summarized. Highest rates of HSI hospitalizations were seen in the most rural, thinly populated stratum (mean annual summer hospitalization rate of 1.16 hospitalizations per 100,000 population in the thinly populated strata vs. 0.45 per 100,000 in the metropolitan urban strata). A one-degree Celsius increase in maximum monthly average temperature was associated with a 0.34 increase in HSI hospitalization rate per 100,000 population in the thinly populated counties compared with 0.02 per 100,000 in highly urbanized counties. The most common additional diagnoses of patients hospitalized with HSI were dehydration, electrolyte abnormalities, and acute renal disorders. Total and mean hospital charges for HSI cases were $167.7 million and $20,500 (in 2014 US dollars). Elevated temperatures appear to have different impacts on HSI hospitalization rates as function of urbanization. The most rural and the most urbanized counties of Illinois had the largest increases in monthly hospitalization rates for HSI per unit increase in the average monthly maximum temperature. This suggests that vulnerability of communities to heat is complex and strategies to reduce HSI may need to be tailored to the degree of urbanization of a county.

Meteorological variables and bacillary dysentery cases in Changsha City, China.

PubMed

Gao, Lu; Zhang, Ying; Ding, Guoyong; Liu, Qiyong; Zhou, Maigeng; Li, Xiujun; Jiang, Baofa

2014-04-01

This study aimed to investigate the association between meteorological-related risk factors and bacillary dysentery in a subtropical inland Chinese area: Changsha City. The cross-correlation analysis and the Autoregressive Integrated Moving Average with Exogenous Variables (ARIMAX) model were used to quantify the relationship between meteorological factors and the incidence of bacillary dysentery. Monthly mean temperature, mean relative humidity, mean air pressure, mean maximum temperature, and mean minimum temperature were significantly correlated with the number of bacillary dysentery cases with a 1-month lagged effect. The ARIMAX models suggested that a 1°C rise in mean temperature, mean maximum temperature, and mean minimum temperature might lead to 14.8%, 12.9%, and 15.5% increases in the incidence of bacillary dysentery disease, respectively. Temperature could be used as a forecast factor for the increase of bacillary dysentery in Changsha. More public health actions should be taken to prevent the increase of bacillary dysentery disease with consideration of local climate conditions, especially temperature.

Meteorological Variables and Bacillary Dysentery Cases in Changsha City, China

PubMed Central

Gao, Lu; Zhang, Ying; Ding, Guoyong; Liu, Qiyong; Zhou, Maigeng; Li, Xiujun; Jiang, Baofa

2014-01-01

This study aimed to investigate the association between meteorological-related risk factors and bacillary dysentery in a subtropical inland Chinese area: Changsha City. The cross-correlation analysis and the Autoregressive Integrated Moving Average with Exogenous Variables (ARIMAX) model were used to quantify the relationship between meteorological factors and the incidence of bacillary dysentery. Monthly mean temperature, mean relative humidity, mean air pressure, mean maximum temperature, and mean minimum temperature were significantly correlated with the number of bacillary dysentery cases with a 1-month lagged effect. The ARIMAX models suggested that a 1°C rise in mean temperature, mean maximum temperature, and mean minimum temperature might lead to 14.8%, 12.9%, and 15.5% increases in the incidence of bacillary dysentery disease, respectively. Temperature could be used as a forecast factor for the increase of bacillary dysentery in Changsha. More public health actions should be taken to prevent the increase of bacillary dysentery disease with consideration of local climate conditions, especially temperature. PMID:24591435

Intra-Seasonal Monthly Oscillations in Stratospheric NCEP Data and Model Results

NASA Technical Reports Server (NTRS)

Mayr, H. G.; Mengel, J. G.; Huang, F. T.; Nash, E. R.

2009-01-01

Intra-seasonal oscillations (ISO) are observed in the zonal-mean of mesospheric wind and temperature measurements-and the numerical spectral model (NSM) generates such oscillations. Relatively large temperature ISO are evident also in stratospheric CPC (NCEP) data at high latitudes, where the NSM produces amplitudes around 3 K at 30 km. Analyzing the NCEP data for the years 1996-2006, we find in Fourier spectra signatures of oscillations with periods between 1.7 and 3 months. With statistical confidence levels exceeding 70%, the spectral features are induced by nonlinear interactions involving the annual and semi-annual variations. The synthesized data show for the 10-year average that the temperature ISO peak in winter, having amplitudes close to 4 K. The synthesized complete spectrum for periods around 2 months produces oscillations, varying from year to year, which can reach peak amplitudes of 15 and 5 K respectively at northern and southern polar latitudes.

Seasonal temperature variation around the mesopause inferred from a VHF meteor radar at King Sejong Station (62S, 59W), Antarctica

NASA Astrophysics Data System (ADS)

Kim, Yongha; Kim, Jeong-Han; Lee, Changsup; Jee, Gun-Hwa

A VHF meteor radar, installed at King Sejong Station in March, 2007, has been detecting echoes from more than 20,000 meteors per day. Meteor echoes are decayed typically within seconds as meteors spread away by atmospheric diffusion. The diffusion coefficients can thus be obtained from decay times of meteor echo signals, providing with information on the atmospheric temperatures and pressures at meteor altitudes from 70 to 100 km. In this study, we present altitude profiles of 15-min averaged diffusion coefficients in each month, which clearly show a minimum at 80 - 85 km. The minimum appears at higher altitude during austral summer than winter, and seems to be near the lower level of two temperature minimum structure around the mesopause seen by TIMED/SABER data at high latitudes. The higher mesopause level (95-100 km) of the SABER data does not appear in our diffusion profiles probably because it is too close the limit of meaningful diffusion coefficients that can be derived from meteor decay detection. In order to understand temperature variation around the mesopause more directly, we will discuss various methods to extract temperature profiles from the diffusion profiles. We will also present monthly averaged OH and O2 airglow temperatures observed at the same site, and compare them with those derived from the meteor radar observation.

Climatic Factors and Community — Associated Methicillin-Resistant Staphylococcus aureus Skin and Soft-Tissue Infections — A Time-Series Analysis Study

PubMed Central

Sahoo, Krushna Chandra; Sahoo, Soumyakanta; Marrone, Gaetano; Pathak, Ashish; Lundborg, Cecilia Stålsby; Tamhankar, Ashok J.

2014-01-01

Skin and soft tissue infections caused by Staphylococcus aureus (SA-SSTIs) including methicillin-resistant Staphylococcus aureus (MRSA) have experienced a significant surge all over the world. Changing climatic factors are affecting the global burden of dermatological infections and there is a lack of information on the association between climatic factors and MRSA infections. Therefore, association of temperature and relative humidity (RH) with occurrence of SA-SSTIs (n = 387) and also MRSA (n = 251) was monitored for 18 months in the outpatient clinic at a tertiary care hospital located in Bhubaneswar, Odisha, India. The Kirby-Bauer disk diffusion method was used for antibiotic susceptibility testing. Time-series analysis was used to investigate the potential association of climatic factors (weekly averages of maximum temperature, minimum temperature and RH) with weekly incidence of SA-SSTIs and MRSA infections. The analysis showed that a combination of weekly average maximum temperature above 33 °C coinciding with weekly average RH ranging between 55% and 78%, is most favorable for the occurrence of SA-SSTIs and MRSA and within these parameters, each unit increase in occurrence of MRSA was associated with increase in weekly average maximum temperature of 1.7 °C (p = 0.044) and weekly average RH increase of 10% (p = 0.097). PMID:25177823

Uncertainties in observations and climate projections for the North East India

NASA Astrophysics Data System (ADS)

Soraisam, Bidyabati; Karumuri, Ashok; D. S., Pai

2018-01-01

The Northeast-India has undergone many changes in climatic-vegetation related issues in the last few decades due to increased human activities. However, lack of observations makes it difficult to ascertain the climate change. The study involves the mean, seasonal cycle, trend and extreme-month analysis for summer-monsoon and winter seasons of observed climate data from Indian Meteorological Department (1° × 1°) and Aphrodite & CRU-reanalysis (both 0.5° × 0.5°), and five regional-climate-model simulations (LMDZ, MPI, GFDL, CNRM and ACCESS) data from AR5/CORDEX-South-Asia (0.5° × 0.5°). Long-term (1970-2005) observed, minimum and maximum monthly temperature and precipitation, and the corresponding CORDEX-South-Asia data for historical (1970-2005) and future-projections of RCP4.5 (2011-2060) have been analyzed for long-term trends. A large spread is found across the models in spatial distributions of various mean maximum/minimum climate statistics, though models capture a similar trend in the corresponding area-averaged seasonal cycles qualitatively. Our observational analysis broadly suggests that there is no significant trend in rainfall. Significant trends are observed in the area-averaged minimum temperature during winter. All the CORDEX-South-Asia simulations for the future project either a decreasing insignificant trend in seasonal precipitation, but increasing trend for both seasonal maximum and minimum temperature over the northeast India. The frequency of extreme monthly maximum and minimum temperature are projected to increase. It is not clear from future projections how the extreme rainfall months during JJAS may change. The results show the uncertainty exists in the CORDEX-South-Asia model projections over the region in spite of the relatively high resolution.

Climate variability, weather and enteric disease incidence in New Zealand: time series analysis.

PubMed

Lal, Aparna; Ikeda, Takayoshi; French, Nigel; Baker, Michael G; Hales, Simon

2013-01-01

Evaluating the influence of climate variability on enteric disease incidence may improve our ability to predict how climate change may affect these diseases. To examine the associations between regional climate variability and enteric disease incidence in New Zealand. Associations between monthly climate and enteric diseases (campylobacteriosis, salmonellosis, cryptosporidiosis, giardiasis) were investigated using Seasonal Auto Regressive Integrated Moving Average (SARIMA) models. No climatic factors were significantly associated with campylobacteriosis and giardiasis, with similar predictive power for univariate and multivariate models. Cryptosporidiosis was positively associated with average temperature of the previous month (β =  0.130, SE =  0.060, p <0.01) and inversely related to the Southern Oscillation Index (SOI) two months previously (β =  -0.008, SE =  0.004, p <0.05). By contrast, salmonellosis was positively associated with temperature (β  = 0.110, SE = 0.020, p<0.001) of the current month and SOI of the current (β  = 0.005, SE = 0.002, p<0.050) and previous month (β  = 0.005, SE = 0.002, p<0.05). Forecasting accuracy of the multivariate models for cryptosporidiosis and salmonellosis were significantly higher. Although spatial heterogeneity in the observed patterns could not be assessed, these results suggest that temporally lagged relationships between climate variables and national communicable disease incidence data can contribute to disease prediction models and early warning systems.

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.

Impacts of peatland forestation on regional climate conditions in Finland

NASA Astrophysics Data System (ADS)

Gao, Yao; Markkanen, Tiina; Backman, Leif; Henttonen, Helena M.; Pietikäinen, Joni-Pekka; Laaksonen, Ari

2014-05-01

Climate response to anthropogenic land cover change happens more locally and occurs on a shorter time scale than the global warming due to increased GHGs. Over the second half of last Century, peatlands were vastly drained in Finland to stimulate forest growth for timber production. In this study, we investigate the biophysical effects of peatland forestation on near-surface climate conditions in Finland. For this, the regional climate model REMO, developed in Max Plank Institute (currently in Climate Service Center, Germany), provides an effective way. Two sets of 15-year climate simulations were done by REMO, using the historic (1920s; The 1st Finnish National Forest Inventory) and present-day (2000s; the 10th Finnish National Forest Inventory) land cover maps, respectively. The simulated surface air temperature and precipitation were then analyzed. In the most intensive peatland forestation area in Finland, the differences in monthly averaged daily mean surface air temperature show a warming effect around 0.2 to 0.3 K in February and March and reach to 0.5 K in April, whereas a slight cooling effect, less than 0.2 K, is found from May till October. Consequently, the selected snow clearance dates in model gridboxes over that area are advanced 0.5 to 4 days in the mean of 15 years. The monthly averaged precipitation only shows small differences, less than 10 mm/month, in a varied pattern in Finland from April to September. Furthermore, a more detailed analysis was conducted on the peatland forestation area with a 23% decrease in peatland and a 15% increase in forest types. 11 day running means of simulated temperature and energy balance terms, as well as snow depth were averaged over 15 years. Results show a positive feedback induced by peatland forestation between the surface air temperature and snow depth in snow melting period. This is because the warmer temperature caused by lower surface albedo due to more forest in snow cover period leads to a quicker and earlier snow melting. Meanwhile, surface albedo is reduced and consequently surface air temperature is increased. Additionally, the maximum difference from individual gridboxes in this area over 15 years of 11 day running means of daily mean surface air temperature reaches 2 K, which is four times as much as the maximum difference of 15-year regional average of that. This illustrates that the spring warming effect from peatland forestation in Finland is highly heterogeneous spatially and temporally.

New results on equatorial thermospheric winds and temperatures from Ethiopia, Africa

NASA Astrophysics Data System (ADS)

Tesema, Fasil; Mesquita, Rafael; Meriwether, John; Damtie, Baylie; Nigussie, Melessew; Makela, Jonathan; Fisher, Daniel; Harding, Brian; Yizengaw, Endawoke; Sanders, Samuel

2017-03-01

Measurements of equatorial thermospheric winds, temperatures, and 630 nm relative intensities were obtained using an imaging Fabry-Perot interferometer (FPI), which was recently deployed at Bahir Dar University in Ethiopia (11.6° N, 37.4° E, 3.7° N magnetic). The results obtained in this study cover 6 months (53 nights of useable data) between November 2015 and April 2016. The monthly-averaged values, which include local winter and equinox seasons, show the magnitude of the maximum monthly-averaged zonal wind is typically within the range of 70 to 90 ms-1 and is eastward between 19:00 and 21:00 LT. Compared to prior studies of the equatorial thermospheric wind for this local time period, the magnitude is considerably weaker as compared to the maximum zonal wind speed observed in the Peruvian sector but comparable to Brazilian FPI results. During the early evening, the meridional wind speeds are 30 to 50 ms-1 poleward during the winter months and 10 to 25 ms-1 equatorward in the equinox months. The direction of the poleward wind during the winter months is believed to be mainly caused by the existence of the interhemispheric wind flow from the summer to winter hemispheres. An equatorial wind surge is observed later in the evening and is shifted to later local times during the winter months and to earlier local times during the equinox months. Significant night-to-night variations are also observed in the maximum speed of both zonal and meridional winds. The temperature observations show the midnight temperature maximum (MTM) to be generally present between 00:30 and 02:00 LT. The amplitude of the MTM was ˜ 110 K in January 2016 with values smaller than this in the other months. The local time difference between the appearance of the MTM and a pre-midnight equatorial wind was generally 60 to 180 min. A meridional wind reversal was also observed after the appearance of the MTM (after 02:00 LT). Climatological models, HWM14 and MSIS-00, were compared to the observations and the HWM14 model generally predicted the zonal wind observations well with the exception of higher model values by 25 ms-1 in the winter months. The HWM14 model meridional wind showed generally good agreement with the observations. Finally, the MSIS-00 model overestimated the temperature by 50 to 75 K during the early evening hours of local winter months. Otherwise, the agreement was generally good, although, in line with prior studies, the model failed to reproduce the MTM peak for any of the 6 months compared with the FPI data.

Animal reservoir, natural and socioeconomic variations and the transmission of hemorrhagic fever with renal syndrome in Chenzhou, China, 2006-2010.

PubMed

Xiao, Hong; Tian, Huai-Yu; Gao, Li-Dong; Liu, Hai-Ning; Duan, Liang-Song; Basta, Nicole; Cazelles, Bernard; Li, Xiu-Jun; Lin, Xiao-Ling; Wu, Hong-Wei; Chen, Bi-Yun; Yang, Hui-Suo; Xu, Bing; Grenfell, Bryan

2014-01-01

China has the highest incidence of hemorrhagic fever with renal syndrome (HFRS) worldwide. Reported cases account for 90% of the total number of global cases. By 2010, approximately 1.4 million HFRS cases had been reported in China. This study aimed to explore the effect of the rodent reservoir, and natural and socioeconomic variables, on the transmission pattern of HFRS. Data on monthly HFRS cases were collected from 2006 to 2010. Dynamic rodent monitoring data, normalized difference vegetation index (NDVI) data, climate data, and socioeconomic data were also obtained. Principal component analysis was performed, and the time-lag relationships between the extracted principal components and HFRS cases were analyzed. Polynomial distributed lag (PDL) models were used to fit and forecast HFRS transmission. Four principal components were extracted. Component 1 (F1) represented rodent density, the NDVI, and monthly average temperature. Component 2 (F2) represented monthly average rainfall and monthly average relative humidity. Component 3 (F3) represented rodent density and monthly average relative humidity. The last component (F4) represented gross domestic product and the urbanization rate. F2, F3, and F4 were significantly correlated, with the monthly HFRS incidence with lags of 4 months (r = -0.289, P<0.05), 5 months (r = -0.523, P<0.001), and 0 months (r = -0.376, P<0.01), respectively. F1 was correlated with the monthly HFRS incidence, with a lag of 4 months (r = 0.179, P = 0.192). Multivariate PDL modeling revealed that the four principal components were significantly associated with the transmission of HFRS. The monthly trend in HFRS cases was significantly associated with the local rodent reservoir, climatic factors, the NDVI, and socioeconomic conditions present during the previous months. The findings of this study may facilitate the development of early warning systems for the control and prevention of HFRS and similar diseases.

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.

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.

The warmer the weather, the more gram-negative bacteria - impact of temperature on clinical isolates in intensive care units.

PubMed

Schwab, Frank; Gastmeier, Petra; Meyer, Elisabeth

2014-01-01

We investigated the relationship between average monthly temperature and the most common clinical pathogens causing infections in intensive care patients. A prospective unit-based study in 73 German intensive care units located in 41 different hospitals and 31 different cities with total 188,949 pathogen isolates (102,377 Gram-positives and 86,572 Gram-negatives) from 2001 to 2012. We estimated the relationship between the number of clinical pathogens per month and the average temperature in the month of isolation and in the month prior to isolation while adjusting for confounders and long-term trends using time series analysis. Adjusted incidence rate ratios for temperature parameters were estimated based on generalized estimating equation models which account for clustering effects. The incidence density of Gram-negative pathogens was 15% (IRR 1.15, 95%CI 1.10-1.21) higher at temperatures ≥ 20°C than at temperatures below 5°C. E. cloacae occurred 43% (IRR=1.43; 95%CI 1.31-1.56) more frequently at high temperatures, A. baumannii 37% (IRR=1.37; 95%CI 1.11-1.69), S. maltophilia 32% (IRR=1.32; 95%CI 1.12-1.57), K. pneumoniae 26% (IRR=1.26; 95%CI 1.13-1.39), Citrobacter spp. 19% (IRR=1.19; 95%CI 0.99-1.44) and coagulase-negative staphylococci 13% (IRR=1.13; 95%CI 1.04-1.22). By contrast, S. pneumoniae 35% (IRR=0.65; 95%CI 0.50-0.84) less frequently isolated at high temperatures. For each 5°C increase, we observed a 3% (IRR=1.03; 95%CI 1.02-1.04) increase of Gram-negative pathogens. This increase was highest for A. baumannii with 8% (IRR=1.08; 95%CI 1.05-1.12) followed by K. pneumoniae, Citrobacter spp. and E. cloacae with 7%. Clinical pathogens vary by incidence density with temperature. Significant higher incidence densities of Gram-negative pathogens were observed during summer whereas S. pneumoniae peaked in winter. There is increasing evidence that different seasonality due to physiologic changes underlies host susceptibility to different bacterial pathogens. Even if the underlying mechanisms are not yet clear, the temperature-dependent seasonality of pathogens has implications for infection control and study design.

Tropical and subtropical humid forests

Treesearch

S.J. Hall

2011-01-01

Tropical humid forests of the United States are located below 1000 m in elevation and experience average year-round temperatures between 20 °C to 26 °C, receive more than 1500 mm of precipitation annually, and experience fewer than three dry months per year.

The effects of atmospheric processes on tehran smog forming.

PubMed

Mohammadi, H; Cohen, D; Babazadeh, M; Rokni, L

2012-01-01

Air pollution is one of the most important problems in urban areas that always threaten citizen's health. Photochemical smog is one of the main factors of air pollution in large cities like Tehran. Usually smog is not only a part of nature, but is being analyzed as an independent matter, which highly affects on the nature. It has been used as relationship between atmospheric elements such as temperature, pressure, relative humidity, wind speed with inversion in the time of smog forming and weather map in 500 Hpa level during 9 years descriptive static by using correlation coefficient in this analyze. Results show that there is a meaningful correlation between atmospheric elements and smog forming. This relation is seen between monthly average of these elements and monthly average of smog forming. However, when temperature decreases, corresponding pressure will increase and result of this will be smog forming. Usually smog increases in cold months of year due to enter cold high pressure air masses in Iran during December and January that is simultaneous with decreasing temperature and air pressure increases and inversion height distance decreases from the earth surface which cause to integrate air pollution under its surface, will cause to form smog in Tehran. It shows a meaningful and strong relation, based on resultant relations by correlation coefficient from inversion height and smog forming, so that obtained figure is more than 60% .

Linking the isotopic composition of monthly precipitation, cave drip water and tree ring cellulose - 15 years of monitoring and data-model comparison

NASA Astrophysics Data System (ADS)

Labuhn, Inga; Genty, Dominique; Daux, Valérie; Bourges, François; Hoffmann, Georg

2013-04-01

The isotopic composition of proxies used for palaeoclimate reconstruction, like tree ring cellulose or speleothem calcite, is controlled to a large extent by the isotopic composition of precipitation. In order to calibrate and interpret these proxies in terms of climate, it is necessary to study water isotopes in rainfall and their link with the proxies' source water. We present 10 to 15-year series of stable hydrogen and oxygen isotopes in monthly precipitation from three sites in the south of France, along with corresponding REMOiso model simulations, a monitoring of cave drip water from two of these sites (Villars cave in the south-west and Chauvet cave in the south-east), as well as measurements of oxygen isotopes in tree ring cellulose from oak trees growing in the same area. The isotopic composition of monthly precipitation at the three sites displays a typical annual cycle. At the south-west sites, under Atlantic influence, the interannual variability is much more pronounced during the winter months than during the summer, whereas the south-eastern Mediterranean site shows the same variability throughout the year. The model simulations are able to reproduce the annual cycle of monthly precipitation δ18O as well as the intra-seasonal variability. Compared to the data, however, the modelled average isotopic values and the seasonal amplitude are overestimated. Correlations between temperature and precipitation δ18O are generally weak at all our sites, on both the monthly and the annual scale, even when using temperature averages weighted by the amount of precipitation. Consequently, a proxy which is controlled by the δ18O of precipitation cannot be directly interpreted in terms of temperature in this region. The isotopic composition of cave drip water in both caves remains stable throughout the monitoring period. By calculating different weighted averages of precipitation δ18O for time periods ranging from months to years, we demonstrate that the cave drip water isotopic composition is the result of several years of rainfall mixing. The precipitation of every month must be considered in order to attain the drip water values, which means that rain water infiltrates throughout the year. There is no modification of the soil water isotopic composition by evaporation and no seasonal bias introduced by transpiring plants; they use water from reserves which represents several months or years of mixing. For the interpretation of tree ring cellulose δ18O, this implies that - at least for the monitoring period of 15 years - the source water signal is more or less constant. Therefore, the variability of cellulose δ18O must be mainly due to evaporation at the leaf level, which is strongly dependent on summer temperature. Insights on the variability and temperature correlations of stable isotopes in precipitation and on the origin and composition of cave drip water are important for the interpretation of proxies. Long-term monitoring is needed for model validation, and the locally validated and corrected model can provide longer time series for a reliable proxy calibration.

Exploring the Appropriate Drought Index in a Humid Tropical Area with Complex Terrain

NASA Astrophysics Data System (ADS)

Lee, C. H.; Chen, W. T.; Lo, M. H.; Chu, J. L.; Chen, Y. J.; Chen, Y. M.

2017-12-01

The goal of the present study is to identify the most appropriate index to monitor droughts in Taiwan, an extremely humid region with steep terrain. Three drought indices were calculated using in situ high resolution rainfall observations and compared: the Standardized Precipitation Index (SPI), the self-calibrating Palmer Drought Severity Index (sc-PDSI), and the Standardized Precipitation Evapotranspiration Index (SPEI). In Taiwan, the average amount of precipitation is around 2500 mm per year, which is six times of the global average. However, with the complexity of topography and the uneven distribution throughout the year in Taiwan, abundant rainfall during the wet season is mostly lost as runoff. Severe droughts occur frequently at approximately once per decade, while moderate droughts occur every 2 years. Earlier studies indicated that the SPI is limited in describing drought events because the temperature effect is not taken into account in SPI as in the sc-PDSI. In addition, SPEI, which take the Penman-Monteith Potential Evapotranspiration (PET_pm) into account, is also considered in the present study. The atmospheric water demand increases as temperature increasing, which is reflected in PET_pm. To calculate the three drought indices, we will use the monthly average temperature to calculate the PET_pm and monthly accumulated precipitation from automatic weather stations from the Central Weather Bureau. All of the detected droughts are evaluated against the dataset of historical drought records in Taiwan. We explore whether the temperature is an important factor for the occurrence of droughts in Taiwan first. In addition to severe droughts, we expect that SPEI and sc-PDSI can detect more moderate droughts in Taiwan. Second, we survey the performance of three drought indices for the detection of droughts in Taiwan. Because the soil water model used in sc-PDSI doesn't consider the effect of steep terrain, and because SPI only considers the monthly precipitation, we expect SPEI to be the more appropriate index for monitoring drought events in Taiwan.

The physiological demands of horseback mustering when wearing an equestrian helmet.

PubMed

Taylor, Nigel A S; Caldwell, Joanne N; Dyer, Rodd

2008-09-01

The hottest months on northern Australian cattle stations are from September to November, and it is during these months that horseback cattle mustering occurs. Stockmen wear clothing that restricts heat loss, and protective helmets have recently been introduced. Anecdotal evidence points to the possibility that helmets may increase the probability of developing heat illness, or reducing workplace performance. In this project, we quantified the working (thermal) environment on such cattle stations, and measured the metabolic demands on, and concurrent physiological strain in stockmen during mustering, whilst wearing an equestrian helmet. During horseback work, the average heart rate was 102.0 beats min(-1) (SD 14.0), with almost 90% of the time (238 min) spent working at intensities <50% of the heart rate reserve. The projected metabolic heat production during mustering ranged between 178 and 333 W (women), and between 212 and 542 W (men). The average core temperature was 37.6 degrees C, while the mean skin temperature averaged 34.1 degrees C. It was concluded that the working environment is, on average, thermally uncompensable during the mustering season. However, horseback mustering per se is a relatively low-intensity activity, interspersed with short periods of high-intensity work. This activity level was reflected within core temperatures, which rarely climbed above values associated with light-moderate exercise. Thus, whilst the climatic state was uncompensable, stockmen used behavioural strategies to minimise the risk of heat illness. Finally, it was observed that the helmet, though unpleasant to wear, did not appear to increase thermal strain in a manner that would disadvantage stockmen.

Freezability and semen parameters in candidates of sperm bank donors: 1992-2010.

PubMed

Yogev, Leah; Paz, Gedalia; Kleiman, Sandra E; Shabtai, Esther; Gamzu, Ronni; Botchan, Amnon; Lehavi, Ofer; Yavetz, Haim; Hauser, Ron

2012-01-01

There has been considerable concern worldwide about possible semen quality deterioration over the last 2 decades. The aim of this study was to evaluate freezability and semen quality of healthy young males during the years 1992-2010. A total of 1211 young (20-32 years old) candidates for sperm bank donation were recruited into the study with no exclusion criteria. They were instructed to observe 2 to 3 days of abstinence from sexual activity, and most of them supplied 2 specimens each. Average values of the various semen parameters, including freezing survival, were calculated for each participant. The change in different semen parameters over years, according to yearly and monthly average temperatures, was evaluated by SAS PROC SURVEYREG analysis. During that period, there were significant increases in motility and vitality percentages, as well as in the percentage of thawed sperm motility. The parameters of volume, concentration, normal morphology, total count, and total motile count showed a significant decrease with years (P < .01). The significant increase in average yearly temperature (P < .004) had limited, nonsignificant association with any of the semen variables. However, average monthly temperature contributed significantly to the trend of semen quality parameters (ie, specimen volume, concentration, percentage of normal morphology, and thawed motility). To the best of our knowledge, this is the first demonstration of the occurrence of an improvement in percent thawed motility over the years, and its significance lies in enabling a higher proportion of sperm bank candidates to be suitable for donation. It is suggested that the global warming phenomenon might have only partial contribution to semen variable changes over the years.

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.

Bioclimatic predictors for supporting ecological applications in the conterminous United States

USGS Publications Warehouse

O'Donnel, Michael S.; Ignizio, Drew A.

2012-01-01

The U.S. Geological Survey (USGS) has developed climate indices, referred to as bioclimatic predictors, which highlight climate conditions best related to species physiology. A set of 20 bioclimatic predictors were developed as Geographic Information Systems (GIS) continuous raster surfaces for each year between 1895 and 2009. The Parameter-elevation Regression on Independent Slopes Model (PRISM) and down-scaled PRISM data, which included both averaged multi-year and averaged monthly climate summaries, was used to develop these multi-scale bioclimatic predictors. Bioclimatic predictors capture information about annual conditions (annual mean temperature, annual precipitation, annual range in temperature and precipitation), as well as seasonal mean climate conditions and intra-year seasonality (temperature of the coldest and warmest months, precipitation of the wettest and driest quarters). Examining climate over time is useful when quantifying the effects of climate changes on species' distributions for past, current, and forecasted scenarios. These data, which have not been readily available to scientists, can provide biologists and ecologists with relevant and multi-scaled climate data to augment research on the responses of species to changing climate conditions. The relationships established between species demographics and distributions with bioclimatic predictors can inform land managers of climatic effects on species during decisionmaking processes.

2016 Climate Trends Continue to Break Records

NASA Image and Video Library

2017-12-08

Two key climate change indicators -- global surface temperatures and Arctic sea ice extent -- have broken numerous records through the first half of 2016, according to NASA analyses of ground-based observations and satellite data. Each of the first six months of 2016 set a record as the warmest respective month globally in the modern temperature record, which dates to 1880, according to scientists at NASA's Goddard Institute for Space Studies (GISS) in New York. The six-month period from January to June was also the planet's warmest half-year on record, with an average temperature 1.3 degrees Celsius (2.4 degrees Fahrenheit) warmer than the late nineteenth century. Read more: go.nasa.gov/29SQngq Credit: NASA/Goddard NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Influence of the Aral Sea negative water balance on its seasonal circulation and ventilation patterns: use of a 3d hydrodynamic model.

NASA Astrophysics Data System (ADS)

Sirjacobs, D.; Grégoire, M.; Delhez, E.; Nihoul, J.

2003-04-01

Within the context of the EU INCO-COPERNICUS program "Desertification in the Aral Sea Region: A study of the Natural and Anthropogenic Impacts" (Contract IAC2-CT-2000-10023), a large-scale 3D hydrodynamic model was adapted to address specifically the macroscale processes affecting the Aral Sea water circulation and ventilation. The particular goal of this research is to simulate the effect of lasting negative water balance on the 3D seasonal circulation, temperature, salinity and water-mixing fields of the Aral Sea. The original Aral Sea seasonal hydrodynamism is simulated with the average seasonal forcings corresponding to the period from 1956 to 1960. This first investigation concerns a period of relative stability of the water balance, before the beginning of the drying process. The consequences of the drying process on the hydrodynamic of the Sea will be studied by comparing this first results with the simulation representing the average situation for the years 1981 to 1985, a very low river flow period. For both simulation periods, the forcing considered are the seasonal fluctuations of wind fields, precipitation, evaporation, river discharge and salinity, cloud cover, air temperature and humidity. The meteorological forcings were adapted to the common optimum one-month temporal resolution of the available data sets. Monthly mean kinetic energy flux and surface tensions were calculated from daily ECMWF wind data. Monthly in situ precipitation, surface air temperature and humidity fields were interpolated from data obtained from the Russian Hydrological and Meteorological Institute. Monthly water discharge and average salinity of the river water were considered for both Amu Darya and Syr Darya river over each simulation periods. The water mass conservation routines allowed the simulation of a changing coastline by taking into account local drying and flooding events of particular grid points. Preliminary barotropic runs were realised (for the 1951-1960 situation, before drying up began) in order to get a first experience of the behaviour of the hydrodynamic model. These first runs provide results about the evolution of the following state variables: elevation of the sea surface, 3D fields of vertical and horizontal flows, 2D fields of average horizontal flows and finally the 3D fields of turbulent kinetic energy. The mean seasonal salinity and temperature fields (in-situ data gathered by the Russian Hydrological and Meteorological Institute) are available for the two simulated periods and will allow a first validation of the hydrodynamic model. Various satellites products were identified, collected and processed in the frame of this research project and will be used for the validation of the model outputs. Seasonal level changes measurements derived from water table change will serve for water balance validation and sea surface temperature for hydrodynamics validation.

Social play behavior in infant Sichuan snub-nosed monkeys (Rhinopithecus roxellana) in Qinling Mountains, China.

PubMed

Li, Yinhua; Guo, Songtao; Ji, Weihong; He, Gang; Wang, Xiaowei; Li, Baoguo

2011-09-01

We describe the development of social play behavior and assess factors influencing the development of play in infant Sichuan snub-nosed monkeys (Rhinopithecus roxellana). Infant snub-nosed monkeys began to exhibit social play at 3 months of age, when they spent an average 0.89% of time engaging in this behavior (range: 0.7-1.12%). At 6 months of age, there was a significant increase in the proportion of time spent in social play, averaging 9.78% of observation time (range: 4.92-17.08%). However, from 7 to 9 months of age during the winter, social play decreased gradually before rising again from 10 months of age in the spring. Play behavior in infant snub-nosed monkeys is influenced by environmental temperature. Males were observed to play more than females, although further data on this are required. Social rank did not influence the social play of wild Sichuan snub-nosed monkey infants. © 2011 Wiley-Liss, Inc.

Antartic sea ice, 1973 - 1976: Satellite passive-microwave observations

NASA Technical Reports Server (NTRS)

Zwally, H. J.; Comiso, J. C.; Parkinson, C. L.; Campbell, W. J.; Carsey, F. D.; Gloersen, P.

1983-01-01

Data from the Electrically Scanning Microwave Radiometer (ESMR) on the Nimbus 5 satellite are used to determine the extent and distribution of Antarctic sea ice. The characteristics of the southern ocean, the mathematical formulas used to obtain quantitative sea ice concentrations, the general characteristics of the seasonal sea ice growth/decay cycle and regional differences, and the observed seasonal growth/decay cycle for individual years and interannual variations of the ice cover are discussed. The sea ice data from the ESMR are presented in the form of color-coded maps of the Antarctic and the southern oceans. The maps show brightness temperatures and concentrations of pack ice averaged for each month, 4-year monthly averages, and month-to-month changes. Graphs summarizing the results, such as areas of sea ice as a function of time in the various sectors of the southern ocean are included. The images demonstrate that satellite microwave data provide unique information on large-scale sea ice conditions for determining climatic conditions in polar regions and possible global climatic changes.

Optimization of ultrasonic emulsification conditions for the production of orange peel essential oil nanoemulsions.

PubMed

Hashtjin, Adel Mirmajidi; Abbasi, Soleiman

2015-05-01

The aim of the present study was to investigate the influence of emulsifying conditions on some physical and rheological properties of orange peel essential oil (OPEO) in water nanoemulsions. In this regard, using the response surface methodology, the influence of ultrasonication conditions including sonication amplitude (70-100 %), sonication time (90-150 s) and process temperature (5-45 °C) on the mean droplets diameter (Z-average value), polydispersity index (PDI), and viscosity of the OPEO nanoemulsions was evaluated. In addition, the flow behavior and stability of selected nanoemulsions was evaluated during storage (up to 3 months) at different temperatures (5, 25 and 45 °C). Based on the results of the optimization, the optimum conditions for producing OPEO nanoemulsions (Z-average value 18.16 nm) were determined as 94 % (sonication amplitude), 138 s (sonication time) and 37 °C (process temperature). Moreover, analysis of variance (ANOVA) showed high coefficients of determination values (R (2) > 0.95) for the response surface models of the energy input and Z-average. In addition, the flow behavior of produced nanoemulsions was Newtonian, and the effect of time and storage temperature as well as their interactions on the Z-average value was highly significant (P < 0.0001).

Long-term projections and acclimatization scenarios of temperature-related mortality in Europe.

PubMed

Ballester, Joan; Robine, Jean-Marie; Herrmann, François Richard; Rodó, Xavier

2011-06-21

The steady increase in greenhouse gas concentrations is inducing a detectable rise in global temperatures. The sensitivity of human societies to warming temperatures is, however, a transcendental question not comprehensively addressed to date. Here we show the link between temperature, humidity and daily numbers of deaths in nearly 200 European regions, which are subsequently used to infer transient projections of mortality under state-of-the-art high-resolution greenhouse gas scenario simulations. Our analyses point to a change in the seasonality of mortality, with maximum monthly incidence progressively shifting from winter to summer. The results also show that the rise in heat-related mortality will start to completely compensate the reduction of deaths from cold during the second half of the century, amounting to an average drop in human lifespan of up 3-4 months in 2070-2100. Nevertheless, projections suggest that human lifespan might indeed increase if a substantial degree of adaptation to warm temperatures takes place.

Climatological characteristics in the extreme hyper-arid region of Pampas de La Joya, Peru. Astrobiological approach in four years of observation: 2004-2008

NASA Astrophysics Data System (ADS)

Valdivia-Silva, Julio E.; Navarro-González, Rafael; Fletcher, Lauren; Pérez-Montaño, Saúl; Condori-Apaza, Reneé; Ortega-Gutiérrez, Fernando; McKay, Christopher

2012-01-01

This study reports the environmental conditions of temperature, moisture and radiation for four years (May 2004 to July 2008) in the area known as Pampas de La Joya in southern Peru, which recently has been considered as a new Mars analogue. The period of evaluation includes the El Niño Southern Oscillation (ENSO) during the months of September 2006 to March 2007, which, despite not having catastrophic effects like its predecessor on 1997-1998, showed an interesting increase in humidity. Our data describe the extreme conditions present in the region and their relationship with the presence of potential habitats that could allow for the survival of micro-organisms. The average environmental temperature was 18.9°C, with a maximum of 35.9°C and a minimum of -4.5°C. The annual average incident solar radiation was 508 W m-2, with high near 1060 W m-2 at noon during the driest period between September and March. The average relative humidity (RH) was 29.5, 20.1 and 20.4% for air, soil and rock, respectively. The RH had higher values at night due to fog during the months of June and August, and during the early morning between December and March. During the months of ENSO event there were four episodes of precipitation (1.1, 1.5, 2.0 and 0.9 mm), of which three increased soil and rock moisture on an average more than 45% and persisted for over 15 days after precipitation, while the atmospheric environment had no significant variations. Finally, quartz rocks and evaporite minerals colonized with micro-organisms were found as the only micro-habitats, in this region, capable of supporting life in this extreme environment.

Coastal upwelling seasonality and variability of temperature and chlorophyll in a small coastal embayment

NASA Astrophysics Data System (ADS)

Walter, Ryan K.; Armenta, Kevin J.; Shearer, Brandon; Robbins, Ian; Steinbeck, John

2018-02-01

While the seasonality of wind-driven coastal upwelling in eastern boundary upwelling systems has long been established, many studies describe two distinct seasons (upwelling and non-upwelling), a generalized framework that does not capture details relevant to marine ecosystems. In this contribution, we present a more detailed description of the annual cycle and upwelling seasonality for an understudied location along the central California coast. Using both the mean monthly upwelling favorable wind stress and the monthly standard deviation, we define the following seasons (contiguous months) and a transitional period (non-contiguous months): "Winter Storms" season (Dec-Jan-Feb), "Upwelling Transition" period (Mar and Jun), "Peak Upwelling" season (Apr-May), "Upwelling Relaxation" season (Jul-Aug-Sep), and "Winter Transition" season (Oct-Nov). In order to describe the oceanic response to this upwelling wind seasonality, we take advantage of nearly a decade of full water-column measurements of temperature and chlorophyll made using an automated profiling system at the end of the California Polytechnic State University Pier in San Luis Obispo Bay, a small ( 2 km wide near study site) and shallow ( 10 m average bay depth) coastal embayment. Variability and average-year patterns are described inside the bay during the various upwelling seasons. Moreover, the role of the local coastline orientation and topography on bay dynamics is also assessed using long-term measurements collected outside of the bay. The formation of a seasonally variable upwelling shadow system and potential nearshore retention zone is discussed. The observations presented provide a framework on which to study interannual changes to the average-year seasonal cycle, assess the contribution of higher-frequency features to nearshore variability, and better predict dynamically and ecologically important events.

Predictability of monthly temperature and precipitation using automatic time series forecasting methods

NASA Astrophysics Data System (ADS)

Papacharalampous, Georgia; Tyralis, Hristos; Koutsoyiannis, Demetris

2018-02-01

We investigate the predictability of monthly temperature and precipitation by applying automatic univariate time series forecasting methods to a sample of 985 40-year-long monthly temperature and 1552 40-year-long monthly precipitation time series. The methods include a naïve one based on the monthly values of the last year, as well as the random walk (with drift), AutoRegressive Fractionally Integrated Moving Average (ARFIMA), exponential smoothing state-space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components (BATS), simple exponential smoothing, Theta and Prophet methods. Prophet is a recently introduced model inspired by the nature of time series forecasted at Facebook and has not been applied to hydrometeorological time series before, while the use of random walk, BATS, simple exponential smoothing and Theta is rare in hydrology. The methods are tested in performing multi-step ahead forecasts for the last 48 months of the data. We further investigate how different choices of handling the seasonality and non-normality affect the performance of the models. The results indicate that: (a) all the examined methods apart from the naïve and random walk ones are accurate enough to be used in long-term applications; (b) monthly temperature and precipitation can be forecasted to a level of accuracy which can barely be improved using other methods; (c) the externally applied classical seasonal decomposition results mostly in better forecasts compared to the automatic seasonal decomposition used by the BATS and Prophet methods; and (d) Prophet is competitive, especially when it is combined with externally applied classical seasonal decomposition.

Impact of meteorological changes on the incidence of scarlet fever in Hefei City, China

NASA Astrophysics Data System (ADS)

Duan, Yu; Huang, Xiao-lei; Wang, Yu-jie; Zhang, Jun-qing; Zhang, Qi; Dang, Yue-wen; Wang, Jing

2016-10-01

Studies on scarlet fever with meteorological factors included were few. We aimed to illustrate meteorological factors' effects on monthly incidence of scarlet fever. Cases of scarlet fever were collected from the report of legal infectious disease in Hefei City from 1985 to 2006; the meteorological data were obtained from the weather bureau of Hefei City. Monthly incidence and corresponding meteorological data in these 22 years were used to develop the model. The model of auto regressive integrated moving average with covariates was used in statistical analyses. There was a highest peak from March to June and a small peak from November to January. The incidence of scarlet fever ranges from 0 to 0.71502 (per 105 population). SARIMAX (1,0,0)(1,0,0)12 model was fitted with monthly incidence and meteorological data optimally. It was shown that relative humidity ( β = -0.002, p = 0.020), mean temperature ( β = 0.006, p = 0.004), and 1 month lag minimum temperature ( β = -0.007, p < 0.001) had effect on the incidence of scarlet fever in Hefei. Besides, the incidence in a previous month (AR( β) = 0.469, p < 0.001) and in 12 months before (SAR( β) = 0.255, p < 0.001) was positively associated with the incidence. This study shows that scarlet fever incidence was negatively associated with monthly minimum temperature and relative humidity while was positively associated with mean temperature in Hefei City, China. Besides, the ARIMA model could be useful not only for prediction but also for the analysis of multiple correlations.

The geographical co-distribution and socio-ecological drivers of childhood pneumonia and diarrhoea in Queensland, Australia.

PubMed

Xu, Z; Hu, W; Tong, S

2015-04-01

SUMMARY This study aimed to explore the spatio-temporal patterns, geographical co-distribution, and socio-ecological drivers of childhood pneumonia and diarrhoea in Queensland. A Bayesian conditional autoregressive model was used to quantify the impacts of socio-ecological factors on both childhood pneumonia and diarrhoea at a postal area level. A distinct seasonality of childhood pneumonia and diarrhoea was found. Childhood pneumonia and diarrhoea were mainly distributed in the northwest of Queensland. Mount Isa city was the high-risk cluster where childhood pneumonia and diarrhoea co-distributed. Emergency department visits (EDVs) for pneumonia increased by 3% per 10-mm increase in monthly average rainfall in wet seasons. By comparison, a 10-mm increase in monthly average rainfall may cause an increase of 4% in EDVs for diarrhoea. Monthly average temperature was negatively associated with EDVs for childhood diarrhoea in wet seasons. Low socioeconomic index for areas (SEIFA) was associated with high EDVs for childhood pneumonia. Future pneumonia and diarrhoea prevention and control measures in Queensland should focus more on Mount Isa.

Definition of SMOS Level 3 Land Products for the Villafranca del Castillo Data Processing Centre (CP34)

NASA Astrophysics Data System (ADS)

Lopez-Baeza, E.; Monsoriu Torres, A.; Font, J.; Alonso, O.

2009-04-01

The ESA SMOS (Soil Moisture and Ocean Salinity) Mission is planned to be launched in July 2009. The satellite will measure soil moisture over the continents and surface salinity of the oceans at resolutions that are sufficient for climatological-type studies. This paper describes the procedure to be used at the Spanish SMOS Level 3 and 4 Data Processing Centre (CP34) to generate Soil Moisture and other Land Surface Product maps from SMOS Level 2 data. This procedure can be used to map Soil Moisture, Vegetation Water Content and Soil Dielectric Constant data into different pre-defined spatial grids with fixed temporal frequency. The L3 standard Land Surface Products to be generated at CP34 are: Soil Moisture products: maximum spatial resolution with no spatial averaging, temporal averaging of 3 days, daily generation maximum spatial resolution with no spatial averaging, temporal averaging of 10 days, generation frequency of once every 10 days. b': maximum spatial resolution with no spatial averaging, temporal averaging of monthly decades (1st to 10th of the month, 11th to 20th of the month, 21st to last day of the month), generation frequency of once every decade monthly average, temporal averaging from L3 decade averages, monthly generation Seasonal average, temporal averaging from L3 monthly averages, seasonally generation yearly average, temporal averaging from L3 monthly averages, yearly generation Vegetation Water Content products: maximum spatial resolution with no spatial averaging, temporal averaging of 10 days, generation frequency of once every 10 days. a': maximum spatial resolution with no spatial averaging, temporal averaging of monthly decades (1st to 10th of the month, 11th to 20th of the month, 21st to last day of the month) using simple averaging method over the L2 products in ISEA grid, generation frequency of once every decade monthly average, temporal averaging from L3 decade averages, monthly generation seasonal average, temporal averaging from L3 monthly averages, seasonally generation yearly average, temporal averaging from L3 monthly averages, yearly generation Dielectric Constant products: (the dielectric constant products are delivered together with soil moisture products, with the same averaging periods and generation frequency): maximum spatial resolution with no spatial averaging, temporal averaging of 3 days, daily generation maximum spatial resolution with no spatial averaging, temporal averaging of 10 days, generation frequency of once every 10 days. b': maximum spatial resolution with no spatial averaging, temporal averaging of monthly decades (1st to 10th of the month, 11th to 20th of the month, 21st to last day of the month), generation frequency of once every decade monthly average, temporal averaging from L3 decade averages, monthly generation seasonal average, temporal averaging from L3 monthly averages, seasonally generation yearly average, temporal averaging from L3 monthly averages, yearly generation.

Global climate change and toxicology: Exacerbation of toxicity of pollutants by thermal stress

EPA Science Inventory

Relatively small elevations in the average global temperature can translate to greater incidences of heat alerts during the summer months, an effect that is especially prevalent in urban areas where simultaneous exposure to heat stress and excessive levels of air pollutants is co...

Climatic Variables and Malaria Morbidity in Mutale Local Municipality, South Africa: A 19-Year Data Analysis

PubMed Central

Botai, Joel O.; Rautenbach, Hannes; Ncongwane, Katlego P.; Botai, Christina M.

2017-01-01

The north-eastern parts of South Africa, comprising the Limpopo Province, have recorded a sudden rise in the rate of malaria morbidity and mortality in the 2017 malaria season. The epidemiological profiles of malaria, as well as other vector-borne diseases, are strongly associated with climate and environmental conditions. A retrospective understanding of the relationship between climate and the occurrence of malaria may provide insight into the dynamics of the disease’s transmission and its persistence in the north-eastern region. In this paper, the association between climatic variables and the occurrence of malaria was studied in the Mutale local municipality in South Africa over a period of 19-year. Time series analysis was conducted on monthly climatic variables and monthly malaria cases in the Mutale municipality for the period of 1998–2017. Spearman correlation analysis was performed and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model was developed. Microsoft Excel was used for data cleaning, and statistical software R was used to analyse the data and develop the model. Results show that both climatic variables’ and malaria cases’ time series exhibited seasonal patterns, showing a number of peaks and fluctuations. Spearman correlation analysis indicated that monthly total rainfall, mean minimum temperature, mean maximum temperature, mean average temperature, and mean relative humidity were significantly and positively correlated with monthly malaria cases in the study area. Regression analysis showed that monthly total rainfall and monthly mean minimum temperature (R2 = 0.65), at a two-month lagged effect, are the most significant climatic predictors of malaria transmission in Mutale local municipality. A SARIMA (2,1,2) (1,1,1) model fitted with only malaria cases has a prediction performance of about 51%, and the SARIMAX (2,1,2) (1,1,1) model with climatic variables as exogenous factors has a prediction performance of about 72% in malaria cases. The model gives a close comparison between the predicted and observed number of malaria cases, hence indicating that the model provides an acceptable fit to predict the number of malaria cases in the municipality. To sum up, the association between the climatic variables and malaria cases provides clues to better understand the dynamics of malaria transmission. The lagged effect detected in this study can help in adequate planning for malaria intervention. PMID:29117114

Climatic Variables and Malaria Morbidity in Mutale Local Municipality, South Africa: A 19-Year Data Analysis.

PubMed

Adeola, Abiodun M; Botai, Joel O; Rautenbach, Hannes; Adisa, Omolola M; Ncongwane, Katlego P; Botai, Christina M; Adebayo-Ojo, Temitope C

2017-11-08

The north-eastern parts of South Africa, comprising the Limpopo Province, have recorded a sudden rise in the rate of malaria morbidity and mortality in the 2017 malaria season. The epidemiological profiles of malaria, as well as other vector-borne diseases, are strongly associated with climate and environmental conditions. A retrospective understanding of the relationship between climate and the occurrence of malaria may provide insight into the dynamics of the disease's transmission and its persistence in the north-eastern region. In this paper, the association between climatic variables and the occurrence of malaria was studied in the Mutale local municipality in South Africa over a period of 19-year. Time series analysis was conducted on monthly climatic variables and monthly malaria cases in the Mutale municipality for the period of 1998-2017. Spearman correlation analysis was performed and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model was developed. Microsoft Excel was used for data cleaning, and statistical software R was used to analyse the data and develop the model. Results show that both climatic variables' and malaria cases' time series exhibited seasonal patterns, showing a number of peaks and fluctuations. Spearman correlation analysis indicated that monthly total rainfall, mean minimum temperature, mean maximum temperature, mean average temperature, and mean relative humidity were significantly and positively correlated with monthly malaria cases in the study area. Regression analysis showed that monthly total rainfall and monthly mean minimum temperature ( R ² = 0.65), at a two-month lagged effect, are the most significant climatic predictors of malaria transmission in Mutale local municipality. A SARIMA (2,1,2) (1,1,1) model fitted with only malaria cases has a prediction performance of about 51%, and the SARIMAX (2,1,2) (1,1,1) model with climatic variables as exogenous factors has a prediction performance of about 72% in malaria cases. The model gives a close comparison between the predicted and observed number of malaria cases, hence indicating that the model provides an acceptable fit to predict the number of malaria cases in the municipality. To sum up, the association between the climatic variables and malaria cases provides clues to better understand the dynamics of malaria transmission. The lagged effect detected in this study can help in adequate planning for malaria intervention.

Environmental Predictors of Seasonal Influenza Epidemics across Temperate and Tropical Climates

PubMed Central

Tamerius, James D.; Shaman, Jeffrey; Alonso, Wladmir J.; Bloom-Feshbach, Kimberly; Uejio, Christopher K.; Comrie, Andrew; Viboud, Cécile

2013-01-01

Human influenza infections exhibit a strong seasonal cycle in temperate regions. Recent laboratory and epidemiological evidence suggests that low specific humidity conditions facilitate the airborne survival and transmission of the influenza virus in temperate regions, resulting in annual winter epidemics. However, this relationship is unlikely to account for the epidemiology of influenza in tropical and subtropical regions where epidemics often occur during the rainy season or transmit year-round without a well-defined season. We assessed the role of specific humidity and other local climatic variables on influenza virus seasonality by modeling epidemiological and climatic information from 78 study sites sampled globally. We substantiated that there are two types of environmental conditions associated with seasonal influenza epidemics: “cold-dry” and “humid-rainy”. For sites where monthly average specific humidity or temperature decreases below thresholds of approximately 11–12 g/kg and 18–21°C during the year, influenza activity peaks during the cold-dry season (i.e., winter) when specific humidity and temperature are at minimal levels. For sites where specific humidity and temperature do not decrease below these thresholds, seasonal influenza activity is more likely to peak in months when average precipitation totals are maximal and greater than 150 mm per month. These findings provide a simple climate-based model rooted in empirical data that accounts for the diversity of seasonal influenza patterns observed across temperate, subtropical and tropical climates. PMID:23505366

The impact of an extreme case of irrigation on the southeastern United States climate

NASA Astrophysics Data System (ADS)

Selman, Christopher; Misra, Vasubandhu

2017-02-01

The impacts of irrigation on southeast United States diurnal climate are investigated using simulations from a regional climate model. An extreme case is assumed, wherein irrigation is set to 100 % of field capacity over the growing season of May through October. Irrigation is applied to the root zone layers of 10-40 and 40-100 cm soil layers only. It is found that in this regime there is a pronounced decrease in monthly averaged temperatures in irrigated regions across all months. In non-irrigated areas a slight warming is simulated. Diurnal maximum temperatures in irrigated areas warm, while diurnal minimum temperatures cool. The daytime warming is attributed to an increase in shortwave flux at the surface owing to diminished low cloud cover. Nighttime and daily mean cooling result as a consequence repartitioning of energy into latent heat flux over sensible heat flux, and of a higher net downward ground heat flux. Excess heat is transported into the deep soil layer, preventing a rapidly intensifying positive feedback loop. Both diurnal and monthly average precipitations are reduced over irrigated areas at a magnitude and spatial pattern similar to one another. Due to the excess moisture availability, evaporation is seen to increase, but this is nearly balanced by a corresponding reduction in sensible heat flux. Concomitant with additional moisture availability is an increase in both transient and stationary moisture flux convergences. However, despite the increase, there is a large-scale stabilization of the atmosphere stemming from a cooled surface.

The Warmer the Weather, the More Gram-Negative Bacteria - Impact of Temperature on Clinical Isolates in Intensive Care Units

PubMed Central

Schwab, Frank; Gastmeier, Petra; Meyer, Elisabeth

2014-01-01

Background We investigated the relationship between average monthly temperature and the most common clinical pathogens causing infections in intensive care patients. Methods A prospective unit-based study in 73 German intensive care units located in 41 different hospitals and 31 different cities with total 188,949 pathogen isolates (102,377 Gram-positives and 86,572 Gram-negatives) from 2001 to 2012. We estimated the relationship between the number of clinical pathogens per month and the average temperature in the month of isolation and in the month prior to isolation while adjusting for confounders and long-term trends using time series analysis. Adjusted incidence rate ratios for temperature parameters were estimated based on generalized estimating equation models which account for clustering effects. Results The incidence density of Gram-negative pathogens was 15% (IRR 1.15, 95%CI 1.10–1.21) higher at temperatures ≥20°C than at temperatures below 5°C. E. cloacae occurred 43% (IRR = 1.43; 95%CI 1.31–1.56) more frequently at high temperatures, A. baumannii 37% (IRR = 1.37; 95%CI 1.11–1.69), S. maltophilia 32% (IRR = 1.32; 95%CI 1.12–1.57), K. pneumoniae 26% (IRR = 1.26; 95%CI 1.13–1.39), Citrobacter spp. 19% (IRR = 1.19; 95%CI 0.99–1.44) and coagulase-negative staphylococci 13% (IRR = 1.13; 95%CI 1.04–1.22). By contrast, S. pneumoniae 35% (IRR = 0.65; 95%CI 0.50–0.84) less frequently isolated at high temperatures. For each 5°C increase, we observed a 3% (IRR = 1.03; 95%CI 1.02–1.04) increase of Gram-negative pathogens. This increase was highest for A. baumannii with 8% (IRR = 1.08; 95%CI 1.05–1.12) followed by K. pneumoniae, Citrobacter spp. and E. cloacae with 7%. Conclusion Clinical pathogens vary by incidence density with temperature. Significant higher incidence densities of Gram-negative pathogens were observed during summer whereas S. pneumoniae peaked in winter. There is increasing evidence that different seasonality due to physiologic changes underlies host susceptibility to different bacterial pathogens. Even if the underlying mechanisms are not yet clear, the temperature-dependent seasonality of pathogens has implications for infection control and study design. PMID:24599500

Continuous selection pressure to improve temperature acclimation of Tisochrysis lutea

PubMed Central

Grimaud, Ghjuvan; Rumin, Judith; Bougaran, Gaël; Talec, Amélie; Gachelin, Manon; Boutoute, Marc; Pruvost, Eric; Bernard, Olivier; Sciandra, Antoine

2017-01-01

Temperature plays a key role in outdoor industrial cultivation of microalgae. Improving the thermal tolerance of microalgae to both daily and seasonal temperature fluctuations can thus contribute to increase their annual productivity. A long term selection experiment was carried out to increase the thermal niche (temperature range for which the growth is possible) of a neutral lipid overproducing strain of Tisochrysis lutea. The experimental protocol consisted to submit cells to daily variations of temperature for 7 months. The stress intensity, defined as the amplitude of daily temperature variations, was progressively increased along successive selection cycles. Only the amplitude of the temperature variations were increased, the daily average temperature was kept constant along the experiment. This protocol resulted in a thermal niche increase by 3°C (+16.5%), with an enhancement by 9% of the maximal growth rate. The selection process also affected T. lutea physiology, with a feature generally observed for ‘cold-temperature’ type of adaptation. The amount of total and neutral lipids was significantly increased, and eventually productivity was increased by 34%. This seven month selection experiment, carried out in a highly dynamic environment, challenges some of the hypotheses classically advanced to explain the temperature response of microalgae. PMID:28902878

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

NASA Technical Reports Server (NTRS)

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

1995-01-01

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

Recent Global Warming As Depicted by AIRS, GISSTEMP, and MERRA-2

NASA Astrophysics Data System (ADS)

Susskind, J.; Iredell, L. F.; Lee, J. N.

2017-12-01

We observed anomalously warm global mean surface temperatures since 2015. The year 2016 represents the warmest annual mean surface skin and surface air temperatures in the AIRS observational period, September 2002 through August 2017. Additionally, AIRS monthly mean surface skin temperature, from January 2016 through September 2016, and November 2016, were the warmest observed for each month of the year. Continuing this trend, the AIRS global surface temperatures of 2017 February and April show the second greatest positive anomalies from average. This recent warming is particularly significant over the Arctic where the snow and sea ice melt is closely tied to the spring and summer surface temperatures. In this paper, we show the global distribution of surface temperature anomalies as observed by AIRS over the period September 2002 through August 2017 and compare them with those from the GISSTEMP and MERRA-2 surface temperatures. The spatial patterns of warm and cold anomalies for a given month show reasonably good agreement in all three data set. AIRS anomalies, which do not have the benefit of in-situ measurements, are in almost perfect agreement with those of MERRA-2, which does use in-situ surface measurements. GISSTEMP anomaly patterns for the most part look similar to those of AIRS and MERRA-2, but are more spread out spatially, and consequently are also weaker.

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).

Protected Area Tourism in a Changing Climate: Will Visitation at US National Parks Warm Up or Overheat?

PubMed

Fisichelli, Nicholas A; Schuurman, Gregor W; Monahan, William B; Ziesler, Pamela S

2015-01-01

Climate change will affect not only natural and cultural resources within protected areas but also tourism and visitation patterns. The U.S. National Park Service systematically collects data regarding its 270+ million annual recreation visits, and therefore provides an opportunity to examine how human visitation may respond to climate change from the tropics to the polar regions. To assess the relationship between climate and park visitation, we evaluated historical monthly mean air temperature and visitation data (1979-2013) at 340 parks and projected potential future visitation (2041-2060) based on two warming-climate scenarios and two visitation-growth scenarios. For the entire park system a third-order polynomial temperature model explained 69% of the variation in historical visitation trends. Visitation generally increased with increasing average monthly temperature, but decreased strongly with temperatures > 25°C. Linear to polynomial monthly temperature models also explained historical visitation at individual parks (R2 0.12-0.99, mean = 0.79, median = 0.87). Future visitation at almost all parks (95%) may change based on historical temperature, historical visitation, and future temperature projections. Warming-mediated increases in potential visitation are projected for most months in most parks (67-77% of months; range across future scenarios), resulting in future increases in total annual visits across the park system (8-23%) and expansion of the visitation season at individual parks (13-31 days). Although very warm months at some parks may see decreases in future visitation, this potential change represents a relatively small proportion of visitation across the national park system. A changing climate is likely to have cascading and complex effects on protected area visitation, management, and local economies. Results suggest that protected areas and neighboring communities that develop adaptation strategies for these changes may be able to both capitalize on opportunities and minimize detriment related to changing visitation.

Protected Area Tourism in a Changing Climate: Will Visitation at US National Parks Warm Up or Overheat?

PubMed Central

Fisichelli, Nicholas A.; Schuurman, Gregor W.; Monahan, William B.; Ziesler, Pamela S.

2015-01-01

Climate change will affect not only natural and cultural resources within protected areas but also tourism and visitation patterns. The U.S. National Park Service systematically collects data regarding its 270+ million annual recreation visits, and therefore provides an opportunity to examine how human visitation may respond to climate change from the tropics to the polar regions. To assess the relationship between climate and park visitation, we evaluated historical monthly mean air temperature and visitation data (1979–2013) at 340 parks and projected potential future visitation (2041–2060) based on two warming-climate scenarios and two visitation-growth scenarios. For the entire park system a third-order polynomial temperature model explained 69% of the variation in historical visitation trends. Visitation generally increased with increasing average monthly temperature, but decreased strongly with temperatures > 25°C. Linear to polynomial monthly temperature models also explained historical visitation at individual parks (R2 0.12-0.99, mean = 0.79, median = 0.87). Future visitation at almost all parks (95%) may change based on historical temperature, historical visitation, and future temperature projections. Warming-mediated increases in potential visitation are projected for most months in most parks (67–77% of months; range across future scenarios), resulting in future increases in total annual visits across the park system (8–23%) and expansion of the visitation season at individual parks (13–31 days). Although very warm months at some parks may see decreases in future visitation, this potential change represents a relatively small proportion of visitation across the national park system. A changing climate is likely to have cascading and complex effects on protected area visitation, management, and local economies. Results suggest that protected areas and neighboring communities that develop adaptation strategies for these changes may be able to both capitalize on opportunities and minimize detriment related to changing visitation. PMID:26083361

Forecasting malaria incidence based on monthly case reports and environmental factors in Karuzi, Burundi, 1997–2003

PubMed Central

Gomez-Elipe, Alberto; Otero, Angel; van Herp, Michel; Aguirre-Jaime, Armando

2007-01-01

Background The objective of this work was to develop a model to predict malaria incidence in an area of unstable transmission by studying the association between environmental variables and disease dynamics. Methods The study was carried out in Karuzi, a province in the Burundi highlands, using time series of monthly notifications of malaria cases from local health facilities, data from rain and temperature records, and the normalized difference vegetation index (NDVI). Using autoregressive integrated moving average (ARIMA) methodology, a model showing the relation between monthly notifications of malaria cases and the environmental variables was developed. Results The best forecasting model (R2adj = 82%, p < 0.0001 and 93% forecasting accuracy in the range ± 4 cases per 100 inhabitants) included the NDVI, mean maximum temperature, rainfall and number of malaria cases in the preceding month. Conclusion This model is a simple and useful tool for producing reasonably reliable forecasts of the malaria incidence rate in the study area. PMID:17892540

Spatio-temporal heterogeneity of malaria morbidity in Ghana: Analysis of routine health facility data

PubMed Central

Malm, Keziah; Peprah, Nana Yaw; Silal, Sheetal P.

2018-01-01

Background Malaria incidence is largely influenced by vector abundance. Among the many interconnected factors relating to malaria transmission, weather conditions such as rainfall and temperature are known to create suitable environmental conditions that sustain reproduction and propagation of anopheles mosquitoes and malaria parasites. In Ghana, climatic conditions vary across the country. Understanding the heterogeneity of malaria morbidity using data sourced from a recently setup data repository for routine health facility data could support planning. Methods Monthly aggregated confirmed uncomplicated malaria cases from the District Health Information Management System and average monthly rainfall and temperature records obtained from the Ghana Meteorological Agency from 2008 to 2016 were analysed. Univariate time series models were fitted to the malaria, rainfall and temperature data series. After pre-whitening the morbidity data, cross correlation analyses were performed. Subsequently, transfer function models were developed for the relationship between malaria morbidity and rainfall and temperature. Results Malaria morbidity patterns vary across zones. In the Guinea savannah, morbidity peaks once in the year and twice in both the Transitional forest and Coastal savannah, following similar patterns of rainfall at the zonal level. While the effects of rainfall on malaria morbidity are delayed by a month in the Guinea savannah and Transitional Forest zones those of temperature are delayed by two months in the Transitional forest zone. In the Coastal savannah however, incidence of malaria is significantly associated with two months lead in rainfall and temperature. Conclusion Data captured on the District Health Information Management System has been used to demonstrate heterogeneity in the dynamics of malaria morbidity across the country. Timing of these variations could guide the deployment of interventions such as indoor residual spraying, Seasonal Malaria Chemoprevention or vaccines to optimise effectiveness on zonal basis. PMID:29377908

Spatio-temporal heterogeneity of malaria morbidity in Ghana: Analysis of routine health facility data.

PubMed

Awine, Timothy; Malm, Keziah; Peprah, Nana Yaw; Silal, Sheetal P

2018-01-01

Malaria incidence is largely influenced by vector abundance. Among the many interconnected factors relating to malaria transmission, weather conditions such as rainfall and temperature are known to create suitable environmental conditions that sustain reproduction and propagation of anopheles mosquitoes and malaria parasites. In Ghana, climatic conditions vary across the country. Understanding the heterogeneity of malaria morbidity using data sourced from a recently setup data repository for routine health facility data could support planning. Monthly aggregated confirmed uncomplicated malaria cases from the District Health Information Management System and average monthly rainfall and temperature records obtained from the Ghana Meteorological Agency from 2008 to 2016 were analysed. Univariate time series models were fitted to the malaria, rainfall and temperature data series. After pre-whitening the morbidity data, cross correlation analyses were performed. Subsequently, transfer function models were developed for the relationship between malaria morbidity and rainfall and temperature. Malaria morbidity patterns vary across zones. In the Guinea savannah, morbidity peaks once in the year and twice in both the Transitional forest and Coastal savannah, following similar patterns of rainfall at the zonal level. While the effects of rainfall on malaria morbidity are delayed by a month in the Guinea savannah and Transitional Forest zones those of temperature are delayed by two months in the Transitional forest zone. In the Coastal savannah however, incidence of malaria is significantly associated with two months lead in rainfall and temperature. Data captured on the District Health Information Management System has been used to demonstrate heterogeneity in the dynamics of malaria morbidity across the country. Timing of these variations could guide the deployment of interventions such as indoor residual spraying, Seasonal Malaria Chemoprevention or vaccines to optimise effectiveness on zonal basis.

Seasonal Snow Extent and Snow Mass in South America Using SMMR and SSM/I Passive Microwave Data (1979-2003)

NASA Technical Reports Server (NTRS)

Foster, J. L.; Hall, D. K.; Chiu, L.; Kelly, R. E.; Powell, H.; Chiu, L.

2007-01-01

Seasonal snow cover in South America was examined in this study using passive microwave satellite data from the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-satellite and the Special Sensor Microwave Imagers (SSM/I) on board Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1979-2003, both snow cover extent and snow depth (snow mass) were investigated during coldest months (May-September), primarily in the Patagonia area of Argentina and in Chile. Most of the seasonal snow in South America is in the Patagonia region of Argentina. Since winter temperatures in this region are often above freezing, the coldest winter month was found to be the month having the most extensive snow cover and also usually the month having the deepest snow cover as well. Sharp year-to-year differences were recorded using the passive microwave observations. The average snow cover extent for July, the month with the greatest average snow extent during the 25-year period of record, is 320,700 km(exp 2). In July of 1984, the average monthly snow cover was 701,250 km(exp 2) - the most extensive coverage observed between 1979 and 2003. However, in July of 1989, snow cover extent was only 120 km(exp 2). The 25-year period of record shows a sinusoidal like pattern, though there appears to be no obvious trend in either increasing or decreasing snow extent or snow mass between 1979 and 2003.

Seasonal Snow Extent and Snow Mass in South America using SMMR and SSM/I Passive Microwave Data (1979-2006)

NASA Technical Reports Server (NTRS)

Foster, J. L.; Hall, D. K.; Kelly, R. E. J.; Chiu, L.

2008-01-01

Seasonal snow cover in South America was examined in this study using passive microwave satellite data from the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-7 satellite and the Special Sensor Microwave Imagers (SSM/I) onboard Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1979-2006, both snow cover extent and snow water equivalent (snow mass) were investigated during the coldest months (May-September), primarily in the Patagonia area of Argentina and in the Andes of Chile, Argentina and Bolivia, where most of the seasonal snow is found. Since winter temperatures in this region are often above freezing, the coldest winter month was found to be the month having the most extensive snow cover and usually the month having the deepest snow cover as well. Sharp year-to-year differences were recorded using the passive microwave observations. The average snow cover extent for July, the month with the greatest average extent during the 28-year period of record, is 321,674 km(exp 2). In July of 1984, the average monthly snow cover extent was 701,250 km(exp 2) the most extensive coverage observed between 1979 and 2006. However, in July of 1989, snow cover extent was only 120,000 km(exp 2). The 28-year period of record shows a sinusoidal like pattern for both snow cover and snow mass, though neither trend is significant at the 95% level.

Benchmarking homogenization algorithms for monthly data

NASA Astrophysics Data System (ADS)

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

2013-09-01

The COST (European Cooperation in Science and Technology) Action ES0601: Advances in homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies. The algorithms were validated against a realistic benchmark dataset. Participants provided 25 separate homogenized contributions as part of the blind study as well as 22 additional solutions submitted after the details of the imposed inhomogeneities were revealed. These homogenized datasets were assessed by a number of performance metrics including i) the centered root mean square error relative to the true homogeneous values at various averaging scales, ii) the error in linear trend estimates and iii) traditional contingency skill scores. The metrics were computed both using the individual station series as well as the network average regional series. The performance of the contributions depends significantly on the error metric considered. Although relative homogenization algorithms typically improve the homogeneity of temperature data, only the best ones improve precipitation data. Moreover, state-of-the-art relative homogenization algorithms developed to work with an inhomogeneous reference are shown to perform best. The study showed that currently automatic algorithms can perform as well as manual ones.

Weather variability, tides, and Barmah Forest virus disease in the Gladstone region, Australia.

PubMed

Naish, Suchithra; Hu, Wenbiao; Nicholls, Neville; Mackenzie, John S; McMichael, Anthony J; Dale, Pat; Tong, Shilu

2006-05-01

In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (b=0.15, p-value<0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (b=-1.03, p-value=0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention.

Relating annual increments of the endangered Blanding's turtle plastron growth to climate

PubMed Central

Richard, Monik G; Laroque, Colin P; Herman, Thomas B

2014-01-01

This research is the first published study to report a relationship between climate variables and plastron growth increments of turtles, in this case the endangered Nova Scotia Blanding's turtle (Emydoidea blandingii). We used techniques and software common to the discipline of dendrochronology to successfully cross-date our growth increment data series, to detrend and average our series of 80 immature Blanding's turtles into one common chronology, and to seek correlations between the chronology and environmental temperature and precipitation variables. Our cross-dated chronology had a series intercorrelation of 0.441 (above 99% confidence interval), an average mean sensitivity of 0.293, and an average unfiltered autocorrelation of 0.377. Our master chronology represented increments from 1975 to 2007 (33 years), with index values ranging from a low of 0.688 in 2006 to a high of 1.303 in 1977. Univariate climate response function analysis on mean monthly air temperature and precipitation values revealed a positive correlation with the previous year's May temperature and current year's August temperature; a negative correlation with the previous year's October temperature; and no significant correlation with precipitation. These techniques for determining growth increment response to environmental variables should be applicable to other turtle species and merit further exploration. PMID:24963390

Relating annual increments of the endangered Blanding's turtle plastron growth to climate.

PubMed

Richard, Monik G; Laroque, Colin P; Herman, Thomas B

2014-05-01

This research is the first published study to report a relationship between climate variables and plastron growth increments of turtles, in this case the endangered Nova Scotia Blanding's turtle (Emydoidea blandingii). We used techniques and software common to the discipline of dendrochronology to successfully cross-date our growth increment data series, to detrend and average our series of 80 immature Blanding's turtles into one common chronology, and to seek correlations between the chronology and environmental temperature and precipitation variables. Our cross-dated chronology had a series intercorrelation of 0.441 (above 99% confidence interval), an average mean sensitivity of 0.293, and an average unfiltered autocorrelation of 0.377. Our master chronology represented increments from 1975 to 2007 (33 years), with index values ranging from a low of 0.688 in 2006 to a high of 1.303 in 1977. Univariate climate response function analysis on mean monthly air temperature and precipitation values revealed a positive correlation with the previous year's May temperature and current year's August temperature; a negative correlation with the previous year's October temperature; and no significant correlation with precipitation. These techniques for determining growth increment response to environmental variables should be applicable to other turtle species and merit further exploration.

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.

Geographical Detector-Based Risk Factors Assessment of the Hand-Foot-Mouth Disease in China

NASA Astrophysics Data System (ADS)

Huang, J.

2017-12-01

Background: Hand, foot and mouth disease(HFMD) is a common infectious disease, causing thousands of deaths among children in China. This study focused on analyzing the impacts of different populations and different industry structures on HFMD incidence in China. Methods: We collected HFMD cases from 2307 counties during May 2008 in China. The potential risk factors included: monthly mean temperature, monthly mean relative humidity, monthly precipitation, different population density, different industry structures. Geographical detector technique was used to analyze the main and interactive effect of potential risk factors on HFMD incidence. Result: Using risk detector, we found the most serious HFMD incidence mainly located in the Yangtze River delta and the Pearl River delta. When the temperature was high, the incidence of HFMD was also high. This finding indicates that there is a correlation between monthly mean temperature and the incidence of HFMD. Similar analysis was undertaken to analyze the correlation between other variables and the incidence of HFMD using the risk detector. Using factor detector, we found the effect of risk factors on the incidence of HFMD, and this was ranked by PD value as follows: density of children aged 0-9 years (0.25) > tertiary industry (0.23) > GDP (0.20) >middle school student density (0.13) > relative humidity (0.12) >average temperature (0.11) >first industry (0.05). Using ecological detector, we found that child density, tertiary industry, and GDP had a strong effect on the incidence of HFMD. Using interactive detector, we found that the interactive PD value of tertiary industry and child population density was 0.42, which of GDP and tertiary industry was 0.34, that of child population density and GDP was 0.35, and that of average temperature and relative humidity was 0.28. All of these interactive PD values appeared to be higher than any PD value of sole risk factors. The combinations of the above-mentioned risk factors could effectively explain spatial variability of the incidence of HFMD in China.

Impact of meteorological factors on the incidence of bacillary dysentery in Beijing, China: A time series analysis (1970-2012).

PubMed

Yan, Long; Wang, Hong; Zhang, Xuan; Li, Ming-Yue; He, Juan

2017-01-01

Influence of meteorological variables on the transmission of bacillary dysentery (BD) is under investigated topic and effective forecasting models as public health tool are lacking. This paper aimed to quantify the relationship between meteorological variables and BD cases in Beijing and to establish an effective forecasting model. A time series analysis was conducted in the Beijing area based upon monthly data on weather variables (i.e. temperature, rainfall, relative humidity, vapor pressure, and wind speed) and on the number of BD cases during the period 1970-2012. Autoregressive integrated moving average models with explanatory variables (ARIMAX) were built based on the data from 1970 to 2004. Prediction of monthly BD cases from 2005 to 2012 was made using the established models. The prediction accuracy was evaluated by the mean square error (MSE). Firstly, temperature with 2-month and 7-month lags and rainfall with 12-month lag were found positively correlated with the number of BD cases in Beijing. Secondly, ARIMAX model with covariates of temperature with 7-month lag (β = 0.021, 95% confidence interval(CI): 0.004-0.038) and rainfall with 12-month lag (β = 0.023, 95% CI: 0.009-0.037) displayed the highest prediction accuracy. The ARIMAX model developed in this study showed an accurate goodness of fit and precise prediction accuracy in the short term, which would be beneficial for government departments to take early public health measures to prevent and control possible BD popularity.

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.

Evaluation of Greenland near surface air temperature datasets

DOE PAGES

Reeves Eyre, J. E. Jack; Zeng, Xubin

2017-07-05

Near-surface air temperature (SAT) over Greenland has important effects on mass balance of the ice sheet, but it is unclear which SAT datasets are reliable in the region. Here extensive in situ SAT measurements ( ∼  1400 station-years) are used to assess monthly mean SAT from seven global reanalysis datasets, five gridded SAT analyses, one satellite retrieval and three dynamically downscaled reanalyses. Strengths and weaknesses of these products are identified, and their biases are found to vary by season and glaciological regime. MERRA2 reanalysis overall performs best with mean absolute error less than 2 °C in all months. Ice sheet-average annual mean SAT frommore » different datasets are highly correlated in recent decades, but their 1901–2000 trends differ even in sign. Compared with the MERRA2 climatology combined with gridded SAT analysis anomalies, thirty-one earth system model historical runs from the CMIP5 archive reach  ∼  5 °C for the 1901–2000 average bias and have opposite trends for a number of sub-periods.« less

Evaluation of Greenland near surface air temperature datasets

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

Reeves Eyre, J. E. Jack; Zeng, Xubin

Near-surface air temperature (SAT) over Greenland has important effects on mass balance of the ice sheet, but it is unclear which SAT datasets are reliable in the region. Here extensive in situ SAT measurements ( ∼  1400 station-years) are used to assess monthly mean SAT from seven global reanalysis datasets, five gridded SAT analyses, one satellite retrieval and three dynamically downscaled reanalyses. Strengths and weaknesses of these products are identified, and their biases are found to vary by season and glaciological regime. MERRA2 reanalysis overall performs best with mean absolute error less than 2 °C in all months. Ice sheet-average annual mean SAT frommore » different datasets are highly correlated in recent decades, but their 1901–2000 trends differ even in sign. Compared with the MERRA2 climatology combined with gridded SAT analysis anomalies, thirty-one earth system model historical runs from the CMIP5 archive reach  ∼  5 °C for the 1901–2000 average bias and have opposite trends for a number of sub-periods.« less

Impact of meteorological changes on the incidence of scarlet fever in Hefei City, China.

PubMed

Duan, Yu; Huang, Xiao-Lei; Wang, Yu-Jie; Zhang, Jun-Qing; Zhang, Qi; Dang, Yue-Wen; Wang, Jing

2016-10-01

Studies on scarlet fever with meteorological factors included were few. We aimed to illustrate meteorological factors' effects on monthly incidence of scarlet fever. Cases of scarlet fever were collected from the report of legal infectious disease in Hefei City from 1985 to 2006; the meteorological data were obtained from the weather bureau of Hefei City. Monthly incidence and corresponding meteorological data in these 22 years were used to develop the model. The model of auto regressive integrated moving average with covariates was used in statistical analyses. There was a highest peak from March to June and a small peak from November to January. The incidence of scarlet fever ranges from 0 to 0.71502 (per 10 5 population). SARIMAX (1,0,0)(1,0,0) 12 model was fitted with monthly incidence and meteorological data optimally. It was shown that relative humidity (β = -0.002, p = 0.020), mean temperature (β = 0.006, p = 0.004), and 1 month lag minimum temperature (β = -0.007, p < 0.001) had effect on the incidence of scarlet fever in Hefei. Besides, the incidence in a previous month (AR(β) = 0.469, p < 0.001) and in 12 months before (SAR(β) = 0.255, p < 0.001) was positively associated with the incidence. This study shows that scarlet fever incidence was negatively associated with monthly minimum temperature and relative humidity while was positively associated with mean temperature in Hefei City, China. Besides, the ARIMA model could be useful not only for prediction but also for the analysis of multiple correlations.

White sturgeon mitigation and restoration in the Columbia and Snake rivers upstream from Bonneville Dam, Annual Progress Report April 2005 - March 2006. Report C.

USGS Publications Warehouse

Parsley, M.J.; Kofoot, P.

2007-01-01

River discharge and water temperatures that occurred during April through July 2005 provided conditions suitable for spawning by white sturgeon downstream from Bonneville, The Dalles, John Day, and McNary dams. Optimal spawning temperatures in the four tailraces occurred for 3-4 weeks and coincided with the peak of the river hydrograph. However, the peak of the hydrograph occurred in mid May and discharges dropped quickly and water temperature rose during June, which is reflected in the monthly and annual indices of suitable spawning habitat. Indices of available spawning habitat for the month of June 2005 were less than one-half of the average of the period from 1985-2004. Bottom-trawl sampling in the Bonneville Reservoir revealed the presence of young-of-the-year (YOY) white sturgeon but the proportion of positive tows was quite low at 0.06.

Spatially distinct effects of preceding precipitation on heat stress over Eastern China

NASA Astrophysics Data System (ADS)

Tang, Q.; Liu, X.; Zhang, X.; Groisman, P. Y.; Sun, S.; Lu, H.; Li, Z.

2017-12-01

In many terrestrial regions, higher than usual surface temperatures are associated with (or even are induced by) surface moisture deficits. When in the warm season temperatures become anomalously high, their extreme values affect human beings causing heat stress. Besides increased temperature, rising humidity may also have substantial implications for human body thermal comfort. However, effects of surface moisture on heat stress, when considering both temperature and humidity, are less known. In this study, the relationship between the number of hot days in July as indicated by the wet-bulb globe temperature (WBGT) and preceding 3-month precipitation was assessed over Eastern China. It is found that the probability of occurrence of the above-the-average number of hot days exceeds 0.7 after preceding precipitation deficit in northeastern China, but is less than 0.3 in southeastern China. Generally, over Eastern China, precipitation in preceding months is negatively correlated with temperature and positively correlated with specific humidity in July. The combined effects generate a spatially distinct pattern: precipitation deficits in preceding months enhance heat stress in northeastern China while in southern China these deficits are associated with reduction of heat stress. In the south, abundant preceding precipitation tends to increase atmospheric humidity that is instrumental for increase of heat stress. These results contribute predictive information about the probability of mid-summer heat stress in Eastern China a few weeks ahead of its occurrence.

Ground-water temperature of the Wyoming quadrangle in central Delaware : with application to ground-water-source heat pumps

USGS Publications Warehouse

Hodges, Arthur L.

1982-01-01

Ground-water temperature was measured during a one-year period (1980-81) in 20 wells in the Wyoming Quadrangle in central Delaware. Data from thermistors set at fixed depths in two wells were collected twice each week, and vertical temperature profiles of the remaining 18 wells were made monthly. Ground-water temperature at 8 feet below land surface in well Jc55-1 ranged from 45.0 degrees F in February to 70.1 degrees F in September. Temperature at 35 feet below land surface in the same well reached a minimum of 56.0 degrees F in August, and a maximum of 57.8 degrees F in February. Average annual temperature of ground water at 25 feet below land surface in all wells ranged from 54.6 degrees F to 57.8 degrees F. Variations of average temperature probably reflect the presence or absence of forestation in the recharge areas of the wells. Ground-water-source heat pumps supplied with water from wells 30 or more feet below land surface will operate more efficiently in both heating and cooling modes than those supplied with water from shallower depths. (USGS)

Modeling the Response of Anopheles gambiae (Diptera: Culicidae) Populations in the Kenya Highlands to a Rise in Mean Annual Temperature.

PubMed

Wallace, Dorothy; Prosper, Olivia; Savos, Jacob; Dunham, Ann M; Chipman, Jonathan W; Shi, Xun; Ndenga, Bryson; Githeko, Andrew

2017-03-01

A dynamical model of Anopheles gambiae larval and adult populations is constructed that matches temperature-dependent maturation times and mortality measured experimentally as well as larval instar and adult mosquito emergence data from field studies in the Kenya Highlands. Spectral classification of high-resolution satellite imagery is used to estimate household density. Indoor resting densities collected over a period of one year combined with predictions of the dynamical model give estimates of both aquatic habitat and total adult mosquito densities. Temperature and precipitation patterns are derived from monthly records. Precipitation patterns are compared with average and extreme habitat estimates to estimate available aquatic habitat in an annual cycle. These estimates are coupled with the original model to produce estimates of adult and larval populations dependent on changing aquatic carrying capacity for larvae and changing maturation and mortality dependent on temperature. This paper offers a general method for estimating the total area of aquatic habitat in a given region, based on larval counts, emergence rates, indoor resting density data, and number of households.Altering the average daily temperature and the average daily rainfall simulates the effect of climate change on annual cycles of prevalence of An. gambiae adults. We show that small increases in average annual temperature have a large impact on adult mosquito density, whether measured at model equilibrium values for a single square meter of habitat or tracked over the course of a year of varying habitat availability and temperature. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Comparative climatology of four marine stratocumulus regimes

NASA Technical Reports Server (NTRS)

Hanson, Howard P.

1990-01-01

The climatology of marine stratocumulus (MSc) cloud regimes off the west coasts of California, Peru, Morocco, and Angola are examined. Long-term, annual averages are presented for several quantities of interest in the four MSc regimes. The climatologies were constructed using the Comprehensive Ocean-Atmosphere Data Set (COADS). A 40 year time series of observations was extracted for 32 x 32 deg analysis domains. The data were taken from the monthly-averaged, 2 deg product. The resolution of the analysis is therefore limited to scales of greater than 200 km with submonthly variability not resolved. The averages of total cloud cover, sea surface temperature, and surface pressure are presented.

Turtles (Chelodina longicollis) regulate muscle metabolic enzyme activity in response to seasonal variation in body temperature.

PubMed

Seebacher, F; Sparrow, J; Thompson, M B

2004-04-01

Fluctuations in the thermal environment may elicit different responses in animals: migration to climatically different areas, regulation of body temperature, modification of biochemical reaction rates, or assuming a state of dormancy. Many ectothermic reptiles are active over a range of body temperatures that vary seasonally. Here we test the hypothesis that metabolic enzyme activity acclimatises seasonally in freshwater turtles (Chelodina longicollis) in addition to, or instead of, behavioural regulation of body temperatures. We measured body temperatures in free-ranging turtles (n = 3) by radiotelemetry, and we assayed phosphofructokinase (PFK), lactate dehydrogenase (LDH), citrate synthase (CS) and cytochrome c oxidase (CCO) activities in early autumn (March, n = 10 turtles), late autumn (May, n = 7) and mid-winter (July, n = 7) over a range of assay temperatures (10 degrees C, 15 degrees C, 20 degrees C, 25 degrees C). Body temperatures were either not different from, or higher than expected from a theoretical null-distribution of a randomly moving animal. Field body temperatures at any season were lower, however, than expected from animals that maximised their sun exposure. Turtles maintained constant PFK, LDH and CCO activities in different months, despite body temperature differences of nearly 13.0 degrees C between March (average daily body temperature = 24.4 degrees C) and July (average = 11.4 degrees C). CS activity did not vary between March and May (average daily body temperature = 20.2 degrees C), but it decreased in July. Thus C. longicollis use a combination of behavioural thermoregulation and biochemical acclimatisation in response to seasonally changing thermal conditions. Ectothermic reptiles were often thought not to acclimatise biochemically, and our results show that behavioural attainment of a preferred body temperature is not mandatory for activity or physiological performance in turtles. Copyright 2004 Springer-Verlag

Flow Estimate of Carbon Dioxide in a Amazon River Hydrological Station

NASA Astrophysics Data System (ADS)

Moura, J. M. S.; Ferreira, R. B., Jr.; Tapajós, R. P.

2014-12-01

Recent measurements in the Amazon suggest that the flow of CO2 in surface waters may reach the order of 1GT per year and isotopic analyzes suggest that this carbon is a direct result of organic matter degradation (OMD) in rivers and the measured concentration exceeds the value expected for there to be equilibrium with the atmosphere (Richey et al, 2002). This study aimed to measure and check the seasonal variability of CO2 fluxes in a range of six months (September 2013-February 2014) in the Strait Óbidos hydrological station located geographically in the coordinates 55 ° 1 '4 "S and 55 ° 31' 4" W. In addiction, it is intended to correlate the data with physical-chemical water parameters pH, dissolved oxygen (DO), and temperature and humidity. The method used for the measurement of CO2 concentration in the atmosphere-water interface is the floating chamber liked with an infrared gas analyzer (IRGA- Infrared Gas Analyzer). The physical-chemical parameters of water were measured using a multiparameter probe YSI Professional Plus model. The preliminary results shows values average CO2 flux was approximately 15.65 1,01ppm / m2s-1 for the months of September and October and between the months of November, 2013 and February 2014 the CO2 flux average was 4.40 + 1.94 ppm / m2s-1. In addiction to the high temperature in dry season, in the water column there is sufficient convection for the existence of gases transport from water to atmosphere, resulting in increase of exchange. Thus, the decreased amount of radiation and consequently the low temperatures in the humid period (on average 27.2 ° C) should affect the OMD in the river, responsible for the production of dissolved CO2. Keywords: CO2 flux, seasonal variability, amazon river

Acute and persistent effects of pre- and posthatching thermal environments on growth and metabolism in the red-eared slider turtle, Trachemys scripta elegans.

PubMed

Ligon, Day B; Peterson, Charles C; Lovern, Matthew B

2012-04-01

Many ectotherms possess the capacity to survive a wide range of thermal conditions. Long-term exposure to temperature can induce acclimational and/or organizational effects, and the developmental stage at which temperature exposure occurs may affect the type, degree, and persistence of these effects. We incubated red-eared slider turtle embryos at three different constant temperatures (T(inc); 26.5, 28.5, 30.5°C), then divided the resulting hatchlings between two water temperatures (T(water); 25, 30°C). We calculated growth rates to assess the short- and long-term effects of thermal experience on this metabolically costly process. We also measured resting metabolic rate (RMR) at three body temperatures (T(body;) 26.5, 28.5, 30.5°C) shortly after hatching and 6 months posthatching to characterize the degree and persistence of acclimation to T(inc) and T(water) . Hatchling RMRs were affected by T(body) and T(inc) , and fit a pattern consistent with positive but incomplete metabolic compensation to T(inc) . Average growth rates over the first 11 weeks posthatching were strongly affected by T(water) but only marginally influenced by T(inc) , and only at T(water) = 30°C. Six-month RMRs exhibited strong acclimation to T(water) consistent with positive metabolic compensation. However, within each T(water) treatment, RMR fit patterns indicative of inverse metabolic compensation to T(inc) , opposite of the pattern observed in hatchlings. Average growth rates calculated over 6 months continued to show a strong effect of T(water) , and the previously weak effect of T(inc) observed within the 30°C T(water) treatment became more pronounced. Our results suggest that metabolic compensation was reversible regardless of the life stage during which exposure occurred, and therefore is more appropriately considered acclimational than organizational. © 2012 WILEY PERIODICALS, INC.

Evidence for developmental thermal acclimation in the damselfish, Pomacentrus moluccensis

NASA Astrophysics Data System (ADS)

Grenchik, M. K.; Donelson, J. M.; Munday, P. L.

2013-03-01

Tropical species are predicted to have limited capacity for acclimation to global warming. This study investigated the potential for developmental thermal acclimation by the tropical damselfish Pomacentrus moluccensis to ocean temperatures predicted to occur over the next 50-100 years. Newly settled juveniles were reared for 4 months in four temperature treatments, consisting of the current-day summer average (28.5 °C) and up to 3 °C above the average (29.5, 30.5 and 31.5 °C). Resting metabolic rate (RMR) of fish reared at 29.5 and 31.5 °C was significantly higher than the control group reared at 28.5 °C. In contrast, RMR of fish reared at 30.5 °C was not significantly different from the control group, indicating these fish had acclimated to their rearing temperature. Furthermore, fish that developed in 30.5 and 31.5 °C exhibited an enhanced ability to deal with acute temperature increases. These findings illustrate that developmental acclimation may help coral reef fish cope with warming ocean temperatures.

Recent accelerated warming of the continental shelf off New Jersey: Observations from the CMV Oleander expendable bathythermograph line

NASA Astrophysics Data System (ADS)

Forsyth, Jacob Samuel Tse; Andres, Magdalena; Gawarkiewicz, Glen G.

2015-03-01

Expendable bathythermographs (XBTs) have been launched along a repeat track from New Jersey to Bermuda from the CMV Oleander through the NOAA/NEFSC Ship of Opportunity Program about 14 times per year since 1977. The XBT temperatures on the Middle Atlantic Bight shelf are binned with 10 km horizontal and 5 m vertical resolution to produce monthly, seasonally, and annually averaged cross-shelf temperature sections. The depth-averaged shelf temperature, Ts, calculated from annually averaged sections that are spatially averaged across the shelf, increases at 0.026 ± 0.001°C yr-1 from 1977 to 2013, with the recent trend substantially larger than the overall 37 year trend (0.11 ± 0.02°C yr-1 since 2002). The Oleander temperature sections suggest that the recent acceleration in warming on the shelf is not confined to the surface, but occurs throughout the water column with some contribution from interactions between the shelf and the adjacent Slope Sea reflected in cross-shelf motions of the shelfbreak front. The local warming on the shelf cannot explain the region's amplified rate of sea level rise relative to the global mean. Additionally, Ts exhibits significant interannual variability with the warmest anomalies increasing in intensity over the 37 year record even as the cold anomalies remain relatively uniform throughout the record. Ts anomalies are not correlated with annually averaged coastal sea level anomalies at zero lag. However, positive correlation is found between 2 year lagged Ts anomalies and coastal sea level anomalies, suggesting that the region's sea level anomalies may serve as a predictor of shelf temperature.

Study on Climate and Grassland Fire in HulunBuir, Inner Mongolia Autonomous Region, China

PubMed Central

Liu, Meifang; Zhao, Jianjun; Guo, Xiaoyi; Zhang, Zhengxiang; Tan, Gang; Yang, Jihong

2017-01-01

Grassland fire is one of the most important disturbance factors of the natural ecosystem. Climate factors influence the occurrence and development of grassland fire. An analysis of the climate conditions of fire occurrence can form the basis for a study of the temporal and spatial variability of grassland fire. The purpose of this paper is to study the effects of monthly time scale climate factors on the occurrence of grassland fire in HulunBuir, located in the northeast of the Inner Mongolia Autonomous Region in China. Based on the logistic regression method, we used the moderate-resolution imaging spectroradiometer (MODIS) active fire data products named thermal anomalies/fire daily L3 Global 1km (MOD14A1 (Terra) and MYD14A1 (Aqua)) and associated climate data for HulunBuir from 2000 to 2010, and established the model of grassland fire climate index. The results showed that monthly maximum temperature, monthly sunshine hours and monthly average wind speed were all positively correlated with the fire climate index; monthly precipitation, monthly average temperature, monthly average relative humidity, monthly minimum relative humidity and the number of days with monthly precipitation greater than or equal to 5 mm were all negatively correlated with the fire climate index. We used the active fire data from 2011 to 2014 to validate the fire climate index during this time period, and the validation result was good (Pearson’s correlation coefficient was 0.578), which showed that the fire climate index model was suitable for analyzing the occurrence of grassland fire in HulunBuir. Analyses were conducted on the temporal and spatial distribution of the fire climate index from January to December in the years 2011–2014; it could be seen that from March to May and from September to October, the fire climate index was higher, and that the fire climate index of the other months is relatively low. The zones with higher fire climate index are mainly distributed in Xin Barag Youqi, Xin Barag Zuoqi, Zalantun Shi, Oroqen Zizhiqi, and Molidawa Zizhiqi; the zones with medium fire climate index are mainly distributed in Chen Barag Qi, Ewenkizu Zizhiqi, Manzhouli Shi, and Arun Qi; and the zones with lower fire climate index are mainly distributed in Genhe Shi, Ergun city, Yakeshi Shi, and Hailar Shi. The results of this study will contribute to the quantitative assessment and management of early warning and forecasting for mid-to long-term grassland fire risk in HulunBuir. PMID:28304336

[Multi-temporal scale analysis of impacts of extreme high temperature on net carbon uptake in subtropical coniferous plantation.

PubMed

Zhang, Mi; Wen, Xue Fa; Zhang, Lei Ming; Wang, Hui Min; Guo, Yi Wen; Yu, Gui Rui

2018-02-01

Extreme high temperature is one of important extreme weathers that impact forest ecosystem carbon cycle. In this study, applying CO 2 flux and routine meteorological data measured during 2003-2012, we examined the impacts of extreme high temperature and extreme high temperature event on net carbon uptake of subtropical coniferous plantation in Qianyanzhou. Combining with wavelet analysis, we analyzed environmental controls on net carbon uptake at different temporal scales, when the extreme high temperature and extreme high temperature event happened. The results showed that mean daily cumulative NEE decreased by 51% in the days with daily maximum air temperature range between 35 ℃ and 40 ℃, compared with that in the days with the range between 30 ℃ and 34 ℃. The effects of the extreme high temperature and extreme high temperature event on monthly NEE and annual NEE related to the strength and duration of extreme high tempe-rature event. In 2003, when strong extreme high temperature event happened, the sum of monthly cumulative NEE in July and August was only -11.64 g C·m -2 ·(2 month) -1 . The value decreased by 90%, compared with multi-year average value. At the same time, the relative variation of annual NEE reached -6.7%. In July and August, when the extreme high temperature and extreme high temperature event occurred, air temperature (T a ) and vapor press deficit (VPD) were the dominant controller for the daily variation of NEE. The coherency between NEE T a and NEE VPD was 0.97 and 0.95, respectively. At 8-, 16-, and 32-day periods, T a , VPD, soil water content at 5 cm depth (SWC), and precipitation (P) controlled NEE. The coherency between NEE SWC and NEE P was higher than 0.8 at monthly scale. The results indicated that atmospheric water deficit impacted NEE at short temporal scale, when the extreme high temperature and extreme high temperature event occurred, both of atmospheric water deficit and soil drought stress impacted NEE at long temporal scales in this ecosystem.

The effect of length and starting year on trend analyses of temperatures in Spanish mainland (1951-2010). Seasonal analysis: Winter (II)

NASA Astrophysics Data System (ADS)

Salinas Solé, Celia; Peña Angulo, Dhais; Gonzalez Hidalgo, Jose Carlos; Brunetti, Michele

2017-04-01

In this poster we applied the moving window approach (see Poster I of this collection) to analyze trends of winter and its corresponding months (December, January, February) temperature mean values of maximum (Tmax) and minimum (Tmin) in Spanish mainland to detect the effects of length period and starting year. Monthly series belong to Monthly Temperature dataset of Spanish mainland (MOTEDAS). Database contains in its grid format of 5236 pixels of monthly series (10x10 km). The threshold used in spatial analyses considers 20% of land under significant trend (p<0.05). The most striking results are as follow: • Seasonal trend analyses of Tmax shows that global trend 1951-2010 was positive and significant mostly in central-western areas; from 1970 to 2010 there is less than 20% of land with significant trend. In the case of Tmin no relevant significant period is detected. • Monthly Tmax analyses show that December significant trend changed from positive (>20%) in between 1955-2010 until 1962-2010, to negative from 1976-2010. Meanwhile January does not show relevant period with significant trend; finally Tmax in February shows different periods with positive significant trend (>20% of land) 1951-2010 to 1954-2010 and 1962-2010 to 1968-2010. No significant trend is detected after this data. • Monthly Tmin trend analyses show that except exceptional period, no months present any significant trend. As conclusions, we have detected that for winter and winter-months, Tmax trends are not significant from 1970 across Spanish mainland. In the case of Tmin we conclude that no significant trend have been occurred in any temporal windows analyzed. Results differ from what traditionally has been assumed that the increase of the average annual temperature was due to the increase of trends in the winter season. And these analyses also show that seasonal trend values could hide monthly behavior. So extreme caution should be taken into account when seasonal values are offered.

Nonlinear Impact of Temperature on Mortality in France

NASA Astrophysics Data System (ADS)

Zhang, A. T.

2016-12-01

Anthropogenic climate change is posing unprecedented challenges to human welfare, yet there is much uncertainty about the cost of its impact. Accurate quantification of the social cost of carbon is crucial for designing effective climate policies that reduce emissions and mitigate the adverse impact of global warming, and human health is an important component of the calculation. Despite a growing body of literature documenting the relationship between temperature and mortality in the U.S., similar results using nationwide data have not been clearly established in other countries. Using random monthly variations in temperature for over a decade, this paper finds a statistically significant nonlinear relationship between monthly mortality rate and daily temperature in France between 1998 and 2012. Extremely hot days are associated with significantly higher mortality rates: One additional day with a mean temperature above 30°C, relative to a day in the 12°C to 15°C range, leads to 10 extra all-age, all-gender monthly deaths per 100,000. The effect of cold temperatures is milder: An extremely cold day with an average temperature from -9 °C to -6 °C increases all-age, all-gender mortality rate by about 1.2 per 100,000 each month. There is also notable heterogeneity in the observed nonlinear relationship across age groups and gender, in which males and the elderly are generally more susceptible to extreme temperatures than females and the young. This highlights that children and youth may be well protected through adaptive behaviors, such as spending more time indoors in temperature-controlled rooms and staying hydrated. Compared to studies done in the U.S., extremely hot days >30°C leads to considerably more deaths in France. Preliminary evidence suggests that there has been very limited adaptation despite two prominent heat waves in 2003 and 2006, although further analysis of electricity consumption and air conditioning usage is needed to ascertain the extent to which protective behavior mitigates mortality risks from temperature extremes.

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.

Food Crops Response to Climate Change

NASA Astrophysics Data System (ADS)

Butler, E.; Huybers, P.

2009-12-01

Projections of future climate show a warming world and heterogeneous changes in precipitation. Generally, warming temperatures indicate a decrease in crop yields where they are currently grown. However, warmer climate will also open up new areas at high latitudes for crop production. Thus, there is a question whether the warmer climate with decreased yields but potentially increased growing area will produce a net increase or decrease of overall food crop production. We explore this question through a multiple linear regression model linking temperature and precipitation to crop yield. Prior studies have emphasised temporal regression which indicate uniformly decreased yields, but neglect the potentially increased area opened up for crop production. This study provides a compliment to the prior work by exploring this spatial variation. We explore this subject with a multiple linear regression model from temperature, precipitation and crop yield data over the United States. The United States was chosen as the training region for the model because there are good crop data available over the same time frame as climate data and presumably the yield from crops in the United States is optimized with respect to potential yield. We study corn, soybeans, sorghum, hard red winter wheat and soft red winter wheat using monthly averages of temperature and precipitation from NCEP reanalysis and yearly yield data from the National Agriculture Statistics Service for 1948-2008. The use of monthly averaged temperature and precipitation, which neglect extreme events that can have a significant impact on crops limits this study as does the exclusive use of United States agricultural data. The GFDL 2.1 model under a 720ppm CO2 scenario provides temperature and precipitation fields for 2040-2100 which are used to explore how the spatial regions available for crop production will change under these new conditions.

An investigation on thermal patterns in Iran based on spatial autocorrelation

NASA Astrophysics Data System (ADS)

Fallah Ghalhari, Gholamabbas; Dadashi Roudbari, Abbasali

2018-02-01

The present study aimed at investigating temporal-spatial patterns and monthly patterns of temperature in Iran using new spatial statistical methods such as cluster and outlier analysis, and hotspot analysis. To do so, climatic parameters, monthly average temperature of 122 synoptic stations, were assessed. Statistical analysis showed that January with 120.75% had the most fluctuation among the studied months. Global Moran's Index revealed that yearly changes of temperature in Iran followed a strong spatially clustered pattern. Findings showed that the biggest thermal cluster pattern in Iran, 0.975388, occurred in May. Cluster and outlier analyses showed that thermal homogeneity in Iran decreases in cold months, while it increases in warm months. This is due to the radiation angle and synoptic systems which strongly influence thermal order in Iran. The elevations, however, have the most notable part proved by Geographically weighted regression model. Iran's thermal analysis through hotspot showed that hot thermal patterns (very hot, hot, and semi-hot) were dominant in the South, covering an area of 33.5% (about 552,145.3 km2). Regions such as mountain foot and low lands lack any significant spatial autocorrelation, 25.2% covering about 415,345.1 km2. The last is the cold thermal area (very cold, cold, and semi-cold) with about 25.2% covering about 552,145.3 km2 of the whole area of Iran.

A spline model of climate for the Western United States

Treesearch

Gerald E. Rehfeldt

2006-01-01

Monthly climate data of average, minimum, and maximum temperature and precipitation normalized for the period 1961 through 1990 were accumulated from approximately 3,000 weather stations in the Western United States and Southwestern Canada. About two-thirds of these observations were available from the weather services of the two countries while the remaining third...

Perception and management of fever in infants up to six months of age: A survey of US pediatricans

PubMed Central

2010-01-01

Background A fever is an increase in the body's temperature above normal. This study examined how US pediatricians perceive and manage fever generally versus fever occurring after vaccination in infants up to six months of age. Methods A web-based survey of 400 US pediatricians subscribing to the Physician Desk Reference was conducted in December 2008. Data were collected on the respondents' socio-demographics, number of years in practice, type of practice, their definition of fever severity in infants, and their recommendations for managing fever. Generalized Estimating Equations were used to estimate the odds of a pediatrician recommending an emergency room visit (ER) or a hospital admission, office visits, or other treatment option, as a function of infant's age, temperature, whether the infant has recently received a vaccine, and whether the fever was reported during or after office hours, adjusting for practice type and socio-demographic variables. Results On average, the 400 responding pediatricians' (64% were female, average age of 49 years, years in practice = 20 years) threshold for extremely serious fever was ≥39.5°C and ≥ 40.0°C for infants 0-2 month and >2-6 month of age respectively. Infants were more likely to be referred to an ER or hospital admission if they were ≤ 2 months of age (Odds Ratio [OR], 29.13; 95% Confidence interval [95% CI], 23.69-35.82) or >2-4 months old (OR 3.37; 95% CI 2.99-3.81) versus > 4 to 6 months old or if they had a temperature ≥ 40.0°C (OR 21.06; 95% CI 17.20-25.79) versus a temperature of 38.0-38.5°C. Fever after vaccination (OR 0.29; 95% CI 0.25-0.33) or reported during office hours (OR 0.17; 95% CI 0.15-0.20) were less likely to result in referral to ER or hospital admission. Conclusion Within this sample of US pediatricians, perception of the severity of fever in infants, as well as the response to infant fever are likely to depend on the infant's age. Recommendations for the management of fever in infants are likely to depend on fever severity level, the infant age, timing in relation to recent vaccination, and the time of day fever is reported. Our results indicate that US pediatricians are more concerned about general fever than fever following vaccination. PMID:21176190

[Research on climatic factors of ecology suitability regionalization of atractylodis].

PubMed

Tan, Zhe-tian; Wang, Hao; Zhu, Shou-dong; Yan, Yu-ping; Guo, Lan-ping; Zheng, Yu-guang

2015-11-01

Through study on the correlation between atractylodis lactones ingredient content and climatic factors, we research regionalization from climatic of five main producing provinces of the country, in order to provide a scientific basis for atractylodis' conscious cultivation. By sampling from 40 origins which from five main producing provinces of the country, we use SPSS to analysis variation of atractylodis lactones ingredient content in different conditions of climatic factors and the effect of each factors. Then according to the relationship between atractylodis lactones ingredient content and climatic factors, we use ArcGIS to conduct ecological suitability regionalization based on climatic factors. The most suitable climatic condition for cultivation of atractylodis: the wettest month precipitation 220-230 mm, the warmest average temperature 25 degrees C, the average temperature of driest season 10 degrees C.

Nearshore Satellite Data as Relative Indicators of Intertidal Organism Physiological Stress

NASA Astrophysics Data System (ADS)

Matzelle, A.; Helmuth, B.; Lakshmi, V.

2011-12-01

The physiological performance of intertidal and shallow subtidal invertebrates and algae is significantly affected by water temperature, and so the ability to measure and model onshore water temperatures is critical for ecological and biogeographic studies. Because of the localized influences of processes such as upwelling, mixing, and surface heating from solar radiation, nearshore water temperatures can differ from those measured directly offshore by buoys and satellites. It remains an open question what the magnitude of the differences in these temperatures are, and whether "large pixel" measurements can serve as an effective proxy for onshore processes, particularly when extrapolating from laboratory physiological studies to field conditions. We compared 9 years of nearshore (~10km) MODIS (Terra and Aqua overpasses) SST data against in situ measurements of water temperature conducted at two intertidal sites in central Oregon- Boiler Bay and Strawberry Hill. We collapsed data into increasingly longer temporal averages to address the correlation and absolute differences between onshore and nearshore temperatures over daily, weekly and monthly timescales. Results indicate that nearshore SST is a reasonable proxy for onshore water temperature, and that the strength of the correlation increases with decreasing temporal resolution. Correlations between differences in maxima are highest, followed by average and minima, and were lower at a site with regular upwelling. While average differences ranged from ~0.199-1.353°C, absolute differences across time scales were ~0.446-6.906°C, and were highest for cold temperatures. The results suggest that, at least at these two sites, SST can be used as a relative proxy for general trends only, especially over longer time scales.

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.

The Impact of Sea Ice Concentration Accuracies on Climate Model Simulations with the GISS GCM

NASA Technical Reports Server (NTRS)

Parkinson, Claire L.; Rind, David; Healy, Richard J.; Martinson, Douglas G.; Zukor, Dorothy J. (Technical Monitor)

2000-01-01

The Goddard Institute for Space Studies global climate model (GISS GCM) is used to examine the sensitivity of the simulated climate to sea ice concentration specifications in the type of simulation done in the Atmospheric Modeling Intercomparison Project (AMIP), with specified oceanic boundary conditions. Results show that sea ice concentration uncertainties of +/- 7% can affect simulated regional temperatures by more than 6 C, and biases in sea ice concentrations of +7% and -7% alter simulated annually averaged global surface air temperatures by -0.10 C and +0.17 C, respectively, over those in the control simulation. The resulting 0.27 C difference in simulated annual global surface air temperatures is reduced by a third, to 0.18 C, when considering instead biases of +4% and -4%. More broadly, least-squares fits through the temperature results of 17 simulations with ice concentration input changes ranging from increases of 50% versus the control simulation to decreases of 50% yield a yearly average global impact of 0.0107 C warming for every 1% ice concentration decrease, i.e., 1.07 C warming for the full +50% to -50% range. Regionally and on a monthly average basis, the differences can be far greater, especially in the polar regions, where wintertime contrasts between the +50% and -50% cases can exceed 30 C. However, few statistically significant effects are found outside the polar latitudes, and temperature effects over the non-polar oceans tend to be under 1 C, due in part to the specification of an unvarying annual cycle of sea surface temperatures. The +/- 7% and 14% results provide bounds on the impact (on GISS GCM simulations making use of satellite data) of satellite-derived ice concentration inaccuracies, +/- 7% being the current estimated average accuracy of satellite retrievals and +/- 4% being the anticipated improved average accuracy for upcoming satellite instruments. Results show that the impact on simulated temperatures of imposed ice concentration changes is least in summer, encouragingly the same season in which the satellite accuracies are thought to be worst. Hence the impact of satellite inaccuracies is probably less than the use of an annually averaged satellite inaccuracy would suggest.

The Influence of Weather Conditions on Joint Pain in Older People with Osteoarthritis: Results from the European Project on OSteoArthritis.

PubMed

Timmermans, Erik J; Schaap, Laura A; Herbolsheimer, Florian; Dennison, Elaine M; Maggi, Stefania; Pedersen, Nancy L; Castell, Maria Victoria; Denkinger, Michael D; Edwards, Mark H; Limongi, Federica; Sánchez-Martínez, Mercedes; Siviero, Paola; Queipo, Rocio; Peter, Richard; van der Pas, Suzan; Deeg, Dorly J H

2015-10-01

This study examined whether daily weather conditions, 3-day average weather conditions, and changes in weather conditions influence joint pain in older people with osteoarthritis (OA) in 6 European countries. Data from the population-based European Project on OSteoArthritis were used. The American College of Rheumatology classification criteria were used to diagnose OA in older people (65-85 yrs). After the baseline interview, at 6 months, and after the 12-18 months followup interview, joint pain was assessed using 2-week pain calendars. Daily values for temperature, precipitation, atmospheric pressure, relative humidity, and wind speed were obtained from local weather stations. Multilevel regression modelling was used to examine the pain-weather associations, adjusted for several confounders. The study included 810 participants with OA in the knee, hand, and/or hip. After adjustment, there were significant associations of joint pain with daily average humidity (B = 0.004, p < 0.01) and 3-day average humidity (B = 0.004, p = 0.01). A significant interaction effect was found between daily average humidity and temperature on joint pain. The effect of humidity on pain was stronger in relatively cold weather conditions. Changes in weather variables between 2 consecutive days were not significantly associated with reported joint pain. The associations between pain and daily average weather conditions suggest that a causal relationship exist between joint pain and weather variables, but the associations between day-to-day weather changes and pain do not confirm causation. Knowledge about the relationship between joint pain in OA and weather may help individuals with OA, physicians, and therapists to better understand and manage fluctuations in pain.

20 CFR 226.62 - Computing average monthly compensation.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false Computing average monthly compensation. 226... RETIREMENT ACT COMPUTING EMPLOYEE, SPOUSE, AND DIVORCED SPOUSE ANNUITIES Years of Service and Average Monthly Compensation § 226.62 Computing average monthly compensation. The employee's average monthly compensation is...

Water temperature behaviour in the River Loire since 1976 and 1881

NASA Astrophysics Data System (ADS)

Moatar, Florentina; Gailhard, Joël

2006-05-01

Analysis of monthly mean river temperatures, recorded on an hourly basis in the middle reaches of the Loire since 1976, allows reconstruction by multiple linear regression of the annual, spring and summer water temperatures from equivalent information on air temperatures and river discharge. Since 1881, the average annual and summer temperatures of the Loire have risen by approximately 0.8 °C, this increase accelerating since the late 1980s due to the rise in air temperature and also to lower discharge rates. In addition, the thermal regime in the Orleans to Blois reach is considerably affected by the inflow of groundwater from the Calcaires de Beauce aquifer, as shown by the summer energy balance. To cite this article: F. Moatar, J. Gailhard, C. R. Geoscience 338 (2006).

Establishing a baseline precipitation and temperature regime for the Guianas from observations and reanalysis data

NASA Astrophysics Data System (ADS)

Bovolo, C. Isabella; Pereira, Ryan; Parkin, Geoff; Wagner, Thomas

2010-05-01

The tropical rainforests of the Guianas, north of the Amazon, are home to several Amerindian communities, hold high levels of biodiversity and, importantly, remain some of the world's most pristine and intact rainforests. Not only do they have important functions in the global carbon cycle, but they regulate the local and regional climate and help generate rain over vast distances. Despite their significance however, the climate and hydrology of this region is poorly understood. It is important to establish the current climate regime of the area as a baseline against which any impacts of future climate change or deforestation can be measured but observed historical climate datasets are generally sparse and of low quality. Here we examine the available precipitation and temperature datasets for the region and derive tentative precipitation and temperature maps focussed on Guyana. To overcome the limitations in the inadequate observational data coverage we also make use of a reanalysis dataset from the European Centre for Medium-range Weather Forecasts (ECMWF). The ECMWF ERA40 dataset comprises a spatially consistent global historical climate for the period 1957-2002 at a ~125 km2 (1.125 degree) resolution at the equator and is particularly valuable for establishing the climate of data-poor areas. Once validated for the area of interest, ERA40 is used to determine the precipitation and temperature regime of the Guianas. Grid-cell by grid-cell analysis provides a complete picture of spatial patterns of averaged monthly precipitation variability across the area, vital for establishing a basis from which to compare any future effects of climate change. This is the first comprehensive study of the recent historical climate and its variability in this area, placing a new hydroclimate monitoring and research program at the Iwokrama International Centre for Rainforest Conservation and Development, Guyana, into the broader climate context. Mean differences (biases) and annual average spatial correlations are examined between modelled ERA40 and observed time series comparing the seasonal cycles and the yearly, monthly and monthly anomaly time series. This is to evaluate if the reanalysis data correctly reproduces the areally averaged observed mean annual precipitation, interannual variability and seasonal precipitation cycle over the region. Results show that reanalysis precipitation for the region compares favourably with areally averaged observations where available, although the model underestimates precipitation in some zones of higher elevation. Also ERA40 data is slightly positively biased along the coast and negatively biased inland. Comparisons between observed and modelled data show that although correlations of annual time series are low (<0.6), correlations of monthly time series reach 0.8 demonstrating that the model captures much of the seasonal variation in precipitation. However correlations between monthly precipitation anomalies, where the averaged seasonal cycle has been removed from the comparison, are lower (< 0.6). As precipitation observations are not assimilated into the reanalysis these results provide a good validation of model performance. The seasonal cycle of precipitation is found to be highly variable across the region. Two wet-seasons (June and December) occur in northern Guyana which relate to the twice yearly passage of the inter-tropical convergence zone whereas a single wet season (April-August) occurs in the savannah zone, which stretches from Venezuela through the southern third of Guyana. The climate transition zone lies slightly north of the distinctive forest-savannah boundary which suggests that the boundary may be highly sensitive to future alterations in climate, such as those due to climate change or deforestation.

Variation of Surface Air Temperature in Relation to El Nino and Cataclysmic Volcanic Eruptions, 1796-1882

NASA Technical Reports Server (NTRS)

Wilson, Robert M.

1999-01-01

During the contemporaneous interval of 1796-1882 a number of significant decreases in temperature are found in the records of Central England and Northern Ireland. These decreases appear to be related to the occurrences of El Nino and/or cataclysmic volcanic eruptions. For example, a composite of residual temperatures of the Central England dataset, centering temperatures on the yearly onsets of 20 El Nino of moderate to stronger strength, shows that, on average, the change in temperature varied by about +/- 0.3 C from normal being warmer during the boreal fall-winter leading up to the El Nino year and cooler during the spring-summer of the El Nino year. Also, the influence of El Nino on Central England temperatures appears to last about 1-2 years. Similarly, a composite of residual temperatures of the Central England dataset, centering temperatures on the month of eruption for 26 cataclysmic volcanic eruptions, shows that, on average, the change in temperature decreased by about 0.1 - 0.2 C, typically, 1-2 years after the eruption, although for specific events, like Tambora, the decrease was considerably greater. Additionally, tropical eruptions appear to produce greater changes in temperature than extratropical eruptions, and eruptions occurring in boreal spring-summer appear to produce greater changes in temperature than those occurring in fall-winter.

Winter honey bee colony losses, Varroa destructor control strategies, and the role of weather conditions: Results from a survey among beekeepers.

PubMed

Beyer, Marco; Junk, Jürgen; Eickermann, Michael; Clermont, Antoine; Kraus, François; Georges, Carlo; Reichart, Andreas; Hoffmann, Lucien

2018-06-01

Sets of treatments that were applied against varroa mites in the Luxembourgish beekeeper community were surveyed annually with a questionnaire between the winters 2010/11 and 2014/15. The average temperature and the precipitation sum of the month, when the respective varroa control method was applied were considered as co-variables when evaluating the efficacy of varroa control regimes. Success or failure of control regimes was evaluated based on the percentage of colonies lost per apiary in the winter following the treatment(s). Neither a positive nor a negative effect of formic acid (concentration 60%, w/v) on the colony losses could be found, irrespective of the weather conditions around the time of application. The higher concentration of 85% formic acid was linked with reduced colony losses when applications were done in August. Colony losses were reduced when Thymovar was applied in July or August, but applications in September were associated with increased losses compared with apiaries not treated with Thymovar during the same period. Apilife application in July as well as Apivar applications between July and September were associated with reduced colony losses. The removal of the drone brood and trickled oxalic acid application had beneficial effects when being done in April and December, respectively. Relatively warm (3.0±1.3°C) and wet (507.0±38.6mm/2months) conditions during the winter months December and January and relatively cool (17.2±1.4°C average monthly temperature) and wet (110.8±55.5mm/month) conditions in July were associated with elevated honey bee colony losses. Copyright © 2018 Elsevier Ltd. All rights reserved.

The population density of Lymnaea columella (Say, 1817) (Mollusca, Lymnaeidae) an intermediate host of Fasciola hepatica (Linnaeus, 1758), in the Caparaó microregion, ES, Brazil.

PubMed

D'Almeida, S C G; Freitas, D F; Carneiro, M B; Camargo, P F; Azevedo, J C; Martins, I V F

2016-06-01

The aim of this study was to monitor the population density of Lymnaea columella, an intermediate host of Fasciola hepatica, in various aquatic habitats and in drinking water in the area of the Instituto Federal de Educação, Ciência e Tecnologia do Espírito Santo, on Caparaó Microregion, municipality of Alegre, state of Espírito Santo, Brazil. Monthly samplings were performed at certain points between drainage areas and drinking water in cattle and goat production systems during the years 2010 to 2013. The mean temperature, precipitation and the frequency of samples of L. columella were analysed graphically according the monthly average during the study period. A total of 2,038 molluscs were collected, 1558 of which were L. columella, that predominated in all sampled points. The highest average of specimens observed for L. columella was in the years 2010 and 2013 (51.0), and occurred decreased in 2011 (19.8). The temperature and precipitation averaged is 23.7 °C and 141 mm/year, respectively. Rainfall peak occurred in March (2011, 2013) and November (2012), during these periods the population of L. columella growth. There was no significant difference in the relationship between the specimens observed with seasons (dry-wet), thus the population of L. columella remained stable and can be found throughout the year.

The forcing of monthly precipitation variability over Southwest Asia during the Boreal cold season

USGS Publications Warehouse

Hoell, Andrew; Shukla, Shraddhanand; Barlow, Mathew; Cannon, Forest; Kelley, Colin; Funk, Christopher C.

2015-01-01

Southwest Asia, deemed as the region containing the countries of Afghanistan, Iran, Iraq and Pakistan, is water scarce and receives nearly 75% of its annual rainfall during8 the boreal cold season of November-April. The forcing of Southwest Asia precipitation has been previously examined for the entire boreal cold season from the perspective of climate variability originating over the Atlantic and tropical Indo-Pacific Oceans. Here, we examine the inter-monthly differences in precipitation variability over Southwest Asia and the atmospheric conditions directly responsible in forcing monthly November-April precipitation. Seasonally averaged November-April precipitation over Southwest Asia is significantly correlated with sea surface temperature (SST) patterns consistent with Pacific Decadal Variability (PDV), the El Nino-Southern Oscillation (ENSO) and the warming trend of SST (Trend). On the contrary, the precipitation variability during individual months of November-April are unrelated and are correlated with SST signatures that include PDV, ENSO and Trend in different combinations. Despite strong inter-monthly differences in precipitation variability during November- April over Southwest Asia, similar atmospheric circulations, highlighted by a stationary equivalent barotropic Rossby wave centered over Iraq, force the monthly spatial distributions of precipitation. Tropospheric waves on the eastern side of the equivalent barotropic Rossby wave modifies the flux of moisture and advects the mean temperature gradient, resulting in temperature advection that is balanced by vertical motions over Southwest Asia. The forcing of monthly Southwest Asia precipitation by equivalent barotropic Rossby waves is different than the forcing by baroclinic Rossby waves associated with tropically-forced-only modes of climate variability.

Weather Variability, Tides, and Barmah Forest Virus Disease in the Gladstone Region, Australia

PubMed Central

Naish, Suchithra; Hu, Wenbiao; Nicholls, Neville; Mackenzie, John S.; McMichael, Anthony J.; Dale, Pat; Tong, Shilu

2006-01-01

In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (β = 0.15, p-value < 0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (β = −1.03, p-value = 0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention. PMID:16675420

Crowdsourcing urban air temperatures from smartphone battery temperatures

NASA Astrophysics Data System (ADS)

Overeem, Aart; Robinson, James C. R.; Leijnse, Hidde; Steeneveld, Gert-Jan; Horn, Berthold K. P.; Uijlenhoet, Remko

2014-05-01

Accurate air temperature observations in urban areas are important for meteorology and energy demand planning. They are indispensable to study the urban heat island effect and the adverse effects of high temperatures on human health. However, the availability of temperature observations in cities is often limited. Here we show that relatively accurate air temperature information for the urban canopy layer can be obtained from an alternative, nowadays omnipresent source: smartphones. In this study, battery temperatures were collected by an Android application for smartphones. It has been shown that a straightforward heat transfer model can be employed to estimate daily mean air temperatures from smartphone battery temperatures for eight major cities around the world. The results demonstrate the enormous potential of this crowdsourcing application for real-time temperature monitoring in densely populated areas. Battery temperature data were collected by users of an Android application for cell phones (opensignal.com). The application automatically sends battery temperature data to a server for storage. In this study, battery temperatures are averaged in space and time to obtain daily averaged battery temperatures for each city separately. A regression model, which can be related to a physical model, is employed to retrieve daily air temperatures from battery temperatures. The model is calibrated with observed air temperatures from a meteorological station of an airport located in or near the city. Time series of air temperatures are obtained for each city for a period of several months, where 50% of the data is for independent verification. The methodology has been applied to Buenos Aires, London, Los Angeles, Paris, Mexico City, Moscow, Rome, and Sao Paulo. The evolution of the retrieved air temperatures often correspond well with the observed ones. The mean absolute error of daily air temperatures is less than 2 degrees Celsius, and the bias is within 1 degree Celsius. This shows that monitoring air temperatures employing an Android application holds great promise. This study will particularly focus on new results: The methodology has been applied to data from three cities in the Netherlands (Amsterdam, Rotterdam, and Utrecht) for the period June - August 2013. It is shown that on average 282 battery temperature readings per day are already sufficient to accurately estimate daily-averaged air temperatures. Results clearly deteriorate when on average only 80 battery temperature readings are available. Since 75% of the world's population has a cell phone, 20% of the land surface of the earth has cellular telephone coverage, and 500 million devices use the Android operating system, there is a huge potential for measuring air temperatures employing cell phones. This could eventually lead to real-time world-wide temperature maps over the continents.

Enabling NLDAS-2 Anomaly Analysis Using Giovanni

NASA Astrophysics Data System (ADS)

Loeser, C.; Rui, H.; Teng, W. L.; Vollmer, B.; Mocko, D. M.

2017-12-01

A newly implemented feature in Giovanni (GES DISC Interactive Online Visualization and Analysis Interface) allows users to explore and visualize anomaly data from the NLDAS-2 Primary Forcing and Noah model data sets. For a given measurement and location, an anomaly describes how conditions for a particular time period compare to normal conditions, based on long-term averages. Analyzing anomalies is important for monitoring droughts, determining weather trends, and studying land surface processes relevant for meteorology, hydrology, and climate. Using Giovanni to analyze anomalies for NLDAS-2 data allows for these studies to be efficiently conducted for the central North American region. Phase 2 of NLDAS (NLDAS-2) currently runs at an 1/8th degree resolution, in near-real time, with data sets extending back to January 1979. NLDAS-2 provides data for soil moisture, precipitation, temperature, and other hydrology measurements. Hourly, monthly, and 30-year (1980-2009) monthly climatology data are available for several land surface models and forcing data sets. The Giovanni anomaly tool calculates monthly anomalies, for a given user-defined variable, as the difference between the NLDAS-2 monthly climatology data and the monthly data. The resulting anomaly describes how a chosen month compares to the 30-year monthly average. The presentation will demonstrate the capabilities and usefulness of Giovanni's anomaly tool, detail the recently added NLDAS-2 variables for which anomalies are available, and show how users can access the data.

Enabling NLDAS-2 Anomaly Analysis Using Giovanni

NASA Technical Reports Server (NTRS)

Loeser, Carlee; Rui, Hualan; Teng, William; Vollmer, Bruce; Mocko, David

2017-01-01

A newly implemented feature in Giovanni (GES DISC Interactive Online Visualization and Analysis Interface) allows users to explore and visualize anomaly data from the NLDAS-2 Primary Forcing and Noah model data sets. For a given measurement and location, an anomaly describes how conditions for a particular time period compare to normal conditions, based on long-term averages. Analyzing anomalies is important for monitoring droughts, determining weather trends, and studying land surface processes relevant for meteorology, hydrology, and climate. Using Giovanni to analyze anomalies for NLDAS-2 data allows for these studies to be efficiently conducted for the central North American region. Phase 2 of NLDAS (NLDAS-2) currently runs at an 1/8th degree resolution, in near-real time, with data sets extending back to January 1979. NLDAS-2 provides data for soil moisture, precipitation, temperature, and other hydrology measurements. Hourly, monthly, and 30-year (1980-2009) monthly climatology data are available for several land surface models and forcing data sets. The Giovanni anomaly tool calculates monthly anomalies, for a given user-defined variable, as the difference between the NLDAS-2 monthly climatology data and the monthly data. The resulting anomaly describes how a chosen month compares to the 30-year monthly average. The presentation will demonstrate the capabilities and usefulness of Giovanni's anomaly tool, detail the recently added NLDAS-2 variables for which anomalies are available, and show how users can access the data.

Ecological covariates based predictive model of malaria risk in the state of Chhattisgarh, India.

PubMed

Kumar, Rajesh; Dash, Chinmaya; Rani, Khushbu

2017-09-01

Malaria being an endemic disease in the state of Chhattisgarh and ecologically dependent mosquito-borne disease, the study is intended to identify the ecological covariates of malaria risk in districts of the state and to build a suitable predictive model based on those predictors which could assist developing a weather based early warning system. This secondary data based analysis used one month lagged district level malaria positive cases as response variable and ecological covariates as independent variables which were tested with fixed effect panelled negative binomial regression models. Interactions among the covariates were explored using two way factorial interaction in the model. Although malaria risk in the state possesses perennial characteristics, higher parasitic incidence was observed during the rainy and winter seasons. The univariate analysis indicated that the malaria incidence risk was statistically significant associated with rainfall, maximum humidity, minimum temperature, wind speed, and forest cover ( p  < 0.05). The efficient predictive model include the forest cover [IRR-1.033 (1.024-1.042)], maximum humidity [IRR-1.016 (1.013-1.018)], and two-way factorial interactions between district specific averaged monthly minimum temperature and monthly minimum temperature, monthly minimum temperature was statistically significant [IRR-1.44 (1.231-1.695)] whereas the interaction term has a protective effect [IRR-0.982 (0.974-0.990)] against malaria infections. Forest cover, maximum humidity, minimum temperature and wind speed emerged as potential covariates to be used in predictive models for modelling the malaria risk in the state which could be efficiently used for early warning systems in the state.

Diel stream temperature regimes of Bukovsky regions of the conterminous United States

NASA Astrophysics Data System (ADS)

Ferencz, Stephen B.; Cardenas, M. Bayani

2017-03-01

Stream temperature which varies over daily to seasonal timescales is a primary control on myriad ecological, biogeochemical, and physical processes. Yet geographic patterns of its diel variations have not been fully characterized. Using daily temperature records spanning 15 years (2000-2014), monthly averaged mean daily temperature and diel temperature range were calculated for streams distributed across six Bukovsky regions of the conterminous U.S. Across all six regions, diel temperature fluctuations were lowest during the winter, around 1-2°C. During the summer there was wide distribution in diel temperatures (2°C-12°C). The regions revealed distinct differences in diel patterns for small and medium streams, but not for large streams. Small and medium streams exhibited notable hysteresis in their annual progression of diel temperature ranges, with larger diel temperature fluctuations in the spring than in the fall.

Spatially distinct effects of preceding precipitation on heat stress over eastern China

NASA Astrophysics Data System (ADS)

Liu, Xingcai; Tang, Qiuhong; Zhang, Xuejun; Groisman, Pavel; Sun, Siao; Lu, Hui; Li, Zhe

2017-11-01

In many terrestrial regions, higher than usual surface temperatures are associated with (or are even induced by) surface moisture deficits. When in the warm season temperatures become anomalously high, their extreme values affect human beings causing heat stress. Besides increased temperature, rising humidity may also have substantial implications for bodily thermal comfort. However, the effects of surface moisture on heat stress, when considering both temperature and humidity, are less known. In this study, the relationship between the number of hot days in July as indicated by the wet-bulb globe temperature and the preceding three months of precipitation was assessed over eastern China. It is found that the probability of occurrence of above the average number of hot days exceeds 0.7 after a preceding precipitation deficit in northeastern China, but is less than 0.3 in southeastern China. Generally, over eastern China, the precipitation in the preceding months is negatively correlated with temperature and positively correlated with specific humidity in July. The combined effects generate a spatially distinct pattern: precipitation deficits in preceding months enhance heat stress in northeastern China while in southern China these deficits are associated with reduction of heat stress. In the south, abundant preceding precipitation tends to increase atmospheric humidity that is instrumental for the increase of heat stress. These results contribute predictive information about the probability of mid-summer heat stress in eastern China a few weeks ahead of its occurrence.

Herbarium specimens, photographs, and field observations show Philadelphia area plants are responding to climate change.

PubMed

Panchen, Zoe A; Primack, Richard B; Anisko, Tomasz; Lyons, Robert E

2012-04-01

The global climate is changing rapidly and is expected to continue changing in coming decades. Studying changes in plant flowering times during a historical period of warming temperatures gives us a way to examine the impacts of climate change and allows us to predict further changes in coming decades. The Greater Philadelphia region has a long and rich history of botanical study and documentation, with abundant herbarium specimens, field observations, and botanical photographs from the mid-1800s onward. These extensive records also provide an opportunity to validate methodologies employed by other climate change researchers at a different biogeographical area and with a different group of species. Data for 2539 flowering records from 1840 to 2010 were assessed to examine changes in flowering response over time and in relation to monthly minimum temperatures of 28 Piedmont species native to the Greater Philadelphia region. Regression analysis of the date of flowering with year or with temperature showed that, on average, the Greater Philadelphia species studied are flowering 16 d earlier over the 170-yr period and 2.7 d earlier per 1°C rise in monthly minimum temperature. Of the species studied, woody plants with short flowering duration are the best indicators of a warming climate. For monthly minimum temperatures, temperatures 1 or 2 mo prior to flowering are most significantly correlated with flowering time. Studies combining herbarium specimens, photographs, and field observations are an effective method for detecting the effects of climate change on flowering times.

Epifauna and thermal additions in the upper Patuxent River estuary

USGS Publications Warehouse

Cory, R.L.; Nauman, J.W.

1969-01-01

In the upper Patuxent Estuary environmental changes in temperature, salinity, and turbidity over a 5-year period are linked to changes in epifaunal production and species distribution. During 1967 a series of monthly panels showed dry weight production averaged 2.8 times greater in a steam electric station heated effluent than in the intake. A downriver shift in epifanual production in 1967 and changes in species abundance was noted and attributed to natural changes in salinity and turbidity and man-induced changes in temperature. ?? 1969 Estuarine Research Federation.

Validating Satellite-Derived Land Surface Temperature with in Situ Measurements: A Public Health Perspective

PubMed Central

Brines, Shannon J.; Brown, Daniel G.; Dvonch, J. Timothy; Gronlund, Carina J.; Zhang, Kai; Oswald, Evan M.; O’Neill, Marie S.

2013-01-01

Background: Land surface temperature (LST) and percent surface imperviousness (SI), both derived from satellite imagery, have been used to characterize the urban heat island effect, a phenomenon in which urban areas are warmer than non-urban areas. Objectives: We aimed to assess the correlations between LSTs and SI images with actual temperature readings from a ground-based network of outdoor monitors. Methods: We evaluated the relationships among a) LST calculated from a 2009 summertime satellite image of the Detroit metropolitan region, Michigan; b) SI from the 2006 National Land Cover Data Set; and c) ground-based temperature measurements monitored during the same time period at 19 residences throughout the Detroit metropolitan region. Associations between these ground-based temperatures and the average LSTs and SI at different radii around the point of the ground-based temperature measurement were evaluated at different time intervals. Spearman correlation coefficients and corresponding p-values were calculated. Results: Satellite-derived LST and SI values were significantly correlated with 24-hr average and August monthly average ground temperatures at all but two of the radii examined (100 m for LST and 0 m for SI). Correlations were also significant for temperatures measured between 0400 and 0500 hours for SI, except at 0 m, but not LST. Statistically significant correlations ranging from 0.49 to 0.91 were observed between LST and SI. Conclusions: Both SI and LST could be used to better understand spatial variation in heat exposures over longer time frames but are less useful for estimating shorter-term, actual temperature exposures, which can be useful for public health preparedness during extreme heat events. PMID:23777856

The temporal and spatial distribution characteristics of air pollution index and meteorological elements in Beijing, Tianjin and Shijiazhuang, China.

PubMed

Huading, Shi; Critto, Andrea; Torresan, Silvia; Qingxian, Gao

2018-06-13

With the rapid economic development and the continuous population growth, several important cities in China suffer serious air pollution, especially in the Beijing-Tianjin-Hebei economic developing area. Based on the daily air pollution index (API) and surface meteorological elements in Beijing, Tianjin and Shijiazhuang from 2001 to 2010, the relationships between API and meteorological elements were analyzed. The statistical analysis focused on the relationships at seasonal and monthly average scales, on different air pollution grades and air pollution processes. The results revealed that the air pollution conditions in the three areas gradually improved from 2001 to 2010, especially during summer; and the worst conditions in air quality were recorded in Beijing in spring due to the influences of dust, while in Tianjin and Shijiazhuang in winter due to household heating. Meteorological elements exhibited different influences on air pollution, showing similar relationships between API in monthly averages and four meteorological elements (i.e., the average, maximum and minimum temperatures, maximum air pressure, vapor pressure, and maximum wind speed); while the relationships on a seasonal average scale demonstrated significant differences. Compared with seasonal and monthly average scales of API, the relation coefficients based on different air pollution grades were significatively lower; while the relationship between API and meteorological elements based on air pollution process reduced the smoothing effect due to the average processing of seasonal and monthly API and improved the accuracy of the results based on different air pollution grades. Finally, statistical analysis of the distribution of pollution days in different wind directions indicated the directions of extreme and maximum wind speeds that mainly influence air pollution; representing a valuable information that could support the definition of air pollution control strategies through the identification of the regions (and the located emission sources) where to focus the implementation of emission reduction actions. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Association between Childhood Diarrhoeal Incidence and Climatic Factors in Urban and Rural Settings in the Health District of Mbour, Senegal

PubMed Central

Thiam, Sokhna; Diène, Aminata N.; Sy, Ibrahima; Winkler, Mirko S.; Schindler, Christian; Ndione, Jacques A.; Faye, Ousmane; Vounatsou, Penelope; Utzinger, Jürg; Cissé, Guéladio

2017-01-01

We assessed the association between childhood diarrhoeal incidence and climatic factors in rural and urban settings in the health district of Mbour in western Senegal. We used monthly diarrhoeal case records among children under five years registered in 24 health facilities over a four-year period (2011–2014). Climatic data (i.e., daily temperature, night temperature and rainfall) for the same four-year period were obtained. We performed a negative binomial regression model to establish the relationship between monthly diarrhoeal incidence and climatic factors of the same and the previous month. There were two annual peaks in diarrhoeal incidence: one during the cold dry season and one during the rainy season. We observed a positive association between diarrhoeal incidence and high average temperature of 36 °C and above and high cumulative monthly rainfall at 57 mm and above. The association between diarrhoeal incidence and temperature was stronger in rural compared to urban settings, while higher rainfall was associated with higher diarrhoeal incidence in the urban settings. Concluding, this study identified significant health–climate interactions and calls for effective preventive measures in the health district of Mbour. Particular attention should be paid to urban settings where diarrhoea was most common in order to reduce the high incidence in the context of climatic variability, which is expected to increase in urban areas in the face of global warming. PMID:28895927

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

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

USGS Publications Warehouse

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

2002-01-01

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

A new meteorological record for Cádiz (Spain) 1806-1852: Implications for climatic reconstructions

NASA Astrophysics Data System (ADS)

Gallego, David; Garcia-Herrera, Ricardo; Calvo, Natalia; Ribera, Pedro

2007-06-01

A new documentary source of data for wind, atmospheric pressure and air temperature for the city of Cádiz (southern Spain) has been abstracted, analyzed and compared with present-day data. Wind records cover the period 1806-1852 with three observations per day. Instrumental pressure and temperature cover the period 1825-1852. While the historical pressure series shows average values very close to that found for the period 1971-2000, temperature shows a large asymmetric seasonal warming, with increments in the order of 2°C for the winter months and almost no change for summer. Wind measurements have been transformed into their numerical equivalents and then compared with present-day values. The analysis shows that the numerical estimation of ancient wind forces observed at Cádiz, while providing a robust climatic signal, has a strong bias to larger values than their instrumental equivalents. Despite the uncertainties involved in the interpretation of early wind series, this effect could be related to the recording of "average wind gusts" rather than average winds as measured by today's anemometers. In consequence, wind climatologies based on historical data, which recently are becoming available to the scientific community, should be used carefully.

Short communication: Changes in body temperature of calves up to 2 months of age as affected by time of day, age, and ambient temperature.

PubMed

Hill, T M; Bateman, H G; Suarez-Mena, F X; Dennis, T S; Schlotterbeck, R L

2016-11-01

Extensive measurements of calf body temperature are limited in the literature. In this study, body temperatures were collected by taping a data logger to the skin over the tail vein opposing the rectum of Holstein calves between 4 and 60d of age during 3 different periods of the summer and fall. The summer period was separated into moderate (21-33°C average low to high) and hot (25-37°C) periods, whereas the fall exhibited cool (11-19°C) ambient temperatures. Tail temperatures were compared in a mixed model ANOVA using ambient temperature, age of calf, and time of day (10-min increments) as fixed effects and calf as a random effect. Measures within calf were modeled as repeated effects of type autoregressive 1. Calf temperature increased 0.0325°C (±0.00035) per 1°C increase in ambient temperature. Body temperature varied in a distinct, diurnal pattern with time of day, with body temperatures being lowest around 0800h and highest between 1700 and 2200h. During periods of hot weather, the highest calf temperature was later in the day (~2200h). Calf minimum, maximum, and average body temperatures were all higher in hot than in moderate periods and higher in moderate than in cool periods. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Two-story residence with solar heating--Newman, Georgia

NASA Technical Reports Server (NTRS)

1981-01-01

Report evaluates performance of warm-air collector system for 11 month period and provides operation and maintenance information. System consists of 14 warm air collectors, rock-storage bin, air handler, heat exchangers, hot-water preheat tank, associated controls, plumbing, and air ducting. Average building temperature was maintained at 72 F (22 C); solar equipment provided 47 percent of space-heating requirement.

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...

Core temperature rhythms in normal and tumor-bearing mice.

PubMed

Griffith, D J; Busot, J C; Lee, W E; Djeu, D J

1993-01-01

The core temperature temporal behavior of DBA/2 mice (11 normal and 13 with an ascites tumor) was studied using surgically implanted radio telemetry transmitters. Normal mice continuously displayed a stable 24 hour temperature rhythm. Tumor-bearers displayed a progressive deterioration of the temperature rhythm following inoculation with tumor cells. While such disruptions have been noted by others, details on the dynamics of the changes have been mostly qualitative, often due to time-averaging or steady-state analysis of the data. The present study attempts to quantify the dynamics of the disruption of temperature rhythm (when present) by continuously monitoring temperatures over periods up to a month. Analysis indicated that temperature regulation in tumor-bearers was adversely affected during the active period only. Furthermore, it appears that the malignancy may be influencing temperature regulation via pathways not directly attributable to the energy needs of the growing tumor.

Weather variability and the incidence of cryptosporidiosis: comparison of time series poisson regression and SARIMA models.

PubMed

Hu, Wenbiao; Tong, Shilu; Mengersen, Kerrie; Connell, Des

2007-09-01

Few studies have examined the relationship between weather variables and cryptosporidiosis in Australia. This paper examines the potential impact of weather variability on the transmission of cryptosporidiosis and explores the possibility of developing an empirical forecast system. Data on weather variables, notified cryptosporidiosis cases, and population size in Brisbane were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics for the period of January 1, 1996-December 31, 2004, respectively. Time series Poisson regression and seasonal auto-regression integrated moving average (SARIMA) models were performed to examine the potential impact of weather variability on the transmission of cryptosporidiosis. Both the time series Poisson regression and SARIMA models show that seasonal and monthly maximum temperature at a prior moving average of 1 and 3 months were significantly associated with cryptosporidiosis disease. It suggests that there may be 50 more cases a year for an increase of 1 degrees C maximum temperature on average in Brisbane. Model assessments indicated that the SARIMA model had better predictive ability than the Poisson regression model (SARIMA: root mean square error (RMSE): 0.40, Akaike information criterion (AIC): -12.53; Poisson regression: RMSE: 0.54, AIC: -2.84). Furthermore, the analysis of residuals shows that the time series Poisson regression appeared to violate a modeling assumption, in that residual autocorrelation persisted. The results of this study suggest that weather variability (particularly maximum temperature) may have played a significant role in the transmission of cryptosporidiosis. A SARIMA model may be a better predictive model than a Poisson regression model in the assessment of the relationship between weather variability and the incidence of cryptosporidiosis.

Small change, big difference: Sea surface temperature distributions for tropical coral reef ecosystems, 1950-2011

NASA Astrophysics Data System (ADS)

Lough, J. M.

2012-09-01

Changes in tropical sea surface temperature (SST) are examined over the period 1950-2011 during which global average temperature warmed by 0.4°C. Average tropical SST is warming about 70% of the global average rate. Spatially, significant warming between the two time periods, 1950-1980 and 1981-2011, has occurred across 65% of the tropical oceans. Coral reef ecosystems occupy 10% of the tropical oceans, typically in regions of warmer (+1.8°C) and less variable SST (80% of months within 3.3°C range) compared to non-reef areas (80% of months within 7.0°C range). SST is a primary controlling factor of coral reef distribution and coral reef organisms have already shown their sensitivity to the relatively small amount of warming observed so far through, for example, more frequent coral bleaching events and outbreaks of coral disease. Experimental evidence is also emerging of possible thermal thresholds in the range 30°C-32°C for some physiological processes of coral reef organisms. Relatively small changes in SST have already resulted in quite large differences in SST distribution with a maximum ‘hot spot’ of change in the near-equatorial Indo-Pacific which encompasses both the Indo-Pacific warm pools and the center of coral reef biodiversity. Identification of this hot spot of SST change is not new but this study highlights its significance with respect to tropical coral reef ecosystems. Given the modest amount of warming to date, changes in SST distribution are of particular concern for coral reefs given additional local anthropogenic stresses on many reefs and ongoing ocean acidification likely to increasingly compromise coral reef processes.

Thermal Efficiency of Lava Tubes of the Pu'u O'o-Kupaianaha Eruption, Kilauea Volcano, Hawaii

NASA Astrophysics Data System (ADS)

Helz, R. T.; Heliker, C.; Hon, K.; Mangan, M. T.

2002-12-01

We have applied glass geothermometry to a suite of very glassy lava samples collected from the upper (pond) and lower (coast) ends of the Episode 48 tube system, throughout the lifetime of the Kupaianaha pond, and also to a small suite of skylight samples collected from various tubes active between 1987 and 1993. The results for the pond-coast pairs are: (1) From November 1986 through January 1988 (15 months), the average change in glass quenching temperature from pond to coast (for 12 pairs) is 12.4°C. The average increase in crystallinity (inferred from observed enrichment of TiO2 and K2O in the coastal glasses) is 11-12% by weight. (2) For the 23 months from February 1988 through November 1989, the average change in inferred quenching temperature (for 25 pairs) is 8.4°C. The average increase in crystallinity is 4-5% by weight. Within this part of the data set, pond and coastal temperatures rise and fall together much of the time, even though these temporal fluctuations are at or below the limit of resolution of glass geothermometry (ΔT < 3 degrees). (3) The minimum difference in temperature for any pond-coast pair is 7°C. Twenty-four (out of 37) pairs have ΔT = 7-9°C, over the three year period. About half of the skylight samples have glass MgO contents consistent with their linear position along the tube system. In other samples, the skylight glasses are displaced to lower MgO contents, suggesting that such samples are not consistently as well-quenched as the pond and littoral spatter samples. For the data from 1992-93, the new tube system was 2 km shorter than the earlier, Kupaianaha-fed tubes. The best-documented ΔT of 6°C for some 1993 samples observed for this 10-km long tube, gives exactly the same temperature decrease with distance (0.6°/km) as the limiting ΔT of 7°C observed for the 12-km Kupaianaha tube systems. This cooling rate may represent the limiting thermal efficiency of tubes of the current Kilauea East Rift eruption.

Climate data by elevation in the Great Smoky Mountains: a database and graphical displays for 1947 - 1950 with comparison to long-term data

USGS Publications Warehouse

Busing, Richard T.; Stephens, Luther A.; Clebsch, Edward E.C.

2004-01-01

A climate data set is presented for four sites spanning the elevation gradient in the Great Smoky Mountains from Gatlinburg to Clingmans Dome. Monthly mean values for cloud cover, temperature, humidity, precipitation, and soil moisture are included. Stephens (1969) is the source of all summarized mean monthly data. Values are the averages of four years (1947-1950) with moderate to high precipitation. Graphical displays show strong climatic patterns of variation among seasons and elevations. The upper stations had lower temperatures and higher precipitation totals; however, temperature lapse rates and variation in vapor pressure deficits decreased at upper elevations. To examine how well the four-year sample represents the long-term climate, temperature and precipitation for the Gatlinburg (1460 ft elevation at park headquarters) station were compared between the years in the sample and the years in the full record from 1928 to 2003. Trends related to season and elevation are consistent with earlier studies and provide a basis for interpretation of climate dynamics in the southern Appalachian Mountains.

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.

Dissolved oxygen saturation controls PAH biodegradation in freshwater estuary sediments.

PubMed

Boyd, T J; Montgomery, M T; Steele, J K; Pohlman, J W; Reatherford, S R; Spargo, B J; Smith, D C

2005-02-01

Polycyclic aromatic hydrocarbons (PAHs) are common contaminants in terrestrial and aquatic environments and can represent a significant constituent of the carbon pool in coastal sediments. We report here the results of an 18-month seasonal study of PAH biodegradation and heterotrophic bacterial production and their controlling biogeochemical factors from 186 sediment samples taken in a tidally influenced freshwater estuary. For each sampling event, measurements were averaged from 25-45 stations covering approximately 250 km(2). There was a clear relationship between bacterial production and ambient temperature, but none between production and bottom water dissolved oxygen (DO) % saturation or PAH concentrations. In contrast with other studies, we found no effect of temperature on the biodegradation of naphthalene, phenanthrene, or fluoranthene. PAH mineralization correlated with bottom water DO saturation above 70% (r(2) > 0.99). These results suggest that the proportional utilization of PAH carbon to natural organic carbon is as much as three orders of magnitude higher during cooler months, when water temperatures are lower and DO % saturation is higher. Infusion of cooler, well-oxygenated water to the water column overlying contaminated sediments during the summer months may stimulate PAH metabolism preferentially over non-PAH organic matter.

Modeling seasonal leptospirosis transmission and its association with rainfall and temperature in Thailand using time-series and ARIMAX analyses.

PubMed

Chadsuthi, Sudarat; Modchang, Charin; Lenbury, Yongwimon; Iamsirithaworn, Sopon; Triampo, Wannapong

2012-07-01

To study the number of leptospirosis cases in relations to the seasonal pattern, and its association with climate factors. Time series analysis was used to study the time variations in the number of leptospirosis cases. The Autoregressive Integrated Moving Average (ARIMA) model was used in data curve fitting and predicting the next leptospirosis cases. We found that the amount of rainfall was correlated to leptospirosis cases in both regions of interest, namely the northern and northeastern region of Thailand, while the temperature played a role in the northeastern region only. The use of multivariate ARIMA (ARIMAX) model showed that factoring in rainfall (with an 8 months lag) yields the best model for the northern region while the model, which factors in rainfall (with a 10 months lag) and temperature (with an 8 months lag) was the best for the northeastern region. The models are able to show the trend in leptospirosis cases and closely fit the recorded data in both regions. The models can also be used to predict the next seasonal peak quite accurately. Copyright © 2012 Hainan Medical College. Published by Elsevier B.V. All rights reserved.

Striped bass annual site fidelity and habitat utilization in J. Strom Thurmond Reservoir, South Carolina-Georgia

USGS Publications Warehouse

Young, S.P.; Isely, J.J.

2002-01-01

Forty-eight adult striped bass Morone saxatilis (3.2-19.1 kg) were captured by electrofishing in the tailrace of Richard B. Russell Dam and in the upper reaches of two major tributaries; they were implanted with temperature-sensitive radio transmitters and tracked approximately bimonthly for 20 months. As J. Strom Thurmond Reservoir downstream from the dam became thermally stratified in May, fish vacated the tributaries. From June to October, all striped bass were found within the reservoir's historical Savannah River channel. By August, most of the instrumented fish were found in the upper section of the reservoir, where optimal habitat was available throughout the summer owing to cool, artificially oxygenated hypolimnetic discharges from Richard B. Russell Dam. In mid-October the reservoir destratified, and fish dispersed from their up-reservoir summering areas and redistributed themselves throughout the reservoir. During early winter, the striped bass returned to tributary habitat or down-reservoir areas and generally used these locations throughout the winter. The fish exhibited a high degree of site fidelity to their summering areas, source tributaries (after fall dispersal and throughout the winter), and spring spawning areas. Mean movement rates were highest in the spring and fall, corresponding to the migration from tributaries in May and the return migration after fall dispersal. Mean movement rates were lowest in summer and winter, corresponding to the periods of high fidelity to summering and wintering areas. The average monthly temperatures and dissolved oxygen concentrations in areas used by striped bass were 19.0-20.4??C and 4.86-6.44 mg/L during May-October, which corresponded to average monthly habitat suitability index values of 0.76-0.98. Striped bass avoided temperatures above 25.1??C and dissolved oxygen concentrations less than 2.3 mg/L.

Impacts of climate change on the world's most exceptional ecoregions

PubMed Central

Beaumont, Linda J.; Pitman, Andrew; Perkins, Sarah; Zimmermann, Niklaus E.; Yoccoz, Nigel G.; Thuiller, Wilfried

2011-01-01

The current rate of warming due to increases in greenhouse gas (GHG) emissions is very likely unprecedented over the last 10,000 y. Although the majority of countries have adopted the view that global warming must be limited to <2 °C, current GHG emission rates and nonagreement at Copenhagen in December 2009 increase the likelihood of this limit being exceeded by 2100. Extensive evidence has linked major changes in biological systems to 20th century warming. The “Global 200” comprises 238 ecoregions of exceptional biodiversity [Olson DM, Dinerstein E (2002) Ann Mo Bot Gard 89:199–224]. We assess the likelihood that, by 2070, these iconic ecoregions will regularly experience monthly climatic conditions that were extreme in 1961–1990. Using >600 realizations from climate model ensembles, we show that up to 86% of terrestrial and 83% of freshwater ecoregions will be exposed to average monthly temperature patterns >2 SDs (2σ) of the 1961–1990 baseline, including 82% of critically endangered ecoregions. The entire range of 89 ecoregions will experience extreme monthly temperatures with a local warming of <2 °C. Tropical and subtropical ecoregions, and mangroves, face extreme conditions earliest, some with <1 °C warming. In contrast, few ecoregions within Boreal Forests and Tundra biomes will experience such extremes this century. On average, precipitation regimes do not exceed 2σ of the baseline period, although considerable variability exists across the climate realizations. Further, the strength of the correlation between seasonal temperature and precipitation changes over numerous ecoregions. These results suggest many Global 200 ecoregions may be under substantial climatic stress by 2100. PMID:21262825

Stable isotope record in annually laminated lake sediments from Lake Żabińskie (NE Poland) for the last millennium.

NASA Astrophysics Data System (ADS)

Gabryś, Alicja; Piotrowska, Natalia; Tylmann, Wojciech; Bonk, Alicja; Filipiak, Janusz; Wacnik, Agnieszka; Hernandez-Almeida, Ivan; Grosjean, Martin

2015-04-01

Stable isotope record of carbon (13C) and oxygen (18O) has been analysed from an annually laminated sediment from Lake Zabinskie (Mazurian Lakeland, NE Poland) with high resolution (1-3 yrs). The sediment layers which were formed in each year during the last millennium contain information about environmental changes in the past. The calcite layers are formed in lake sediment in warm months of the year, therefore the reconstruction of summer climate variables in the past is potentially possible. The investigation of correlation between isotope dataset and instrumental climate data for years 1897-2008 AD confirmed that theory. The record of temperature, precipitation and SPEI (Standardised Precipitation Evaporation Index) coefficient, which is a combination of both temperature and precipitation, was tested. The strongest linear correlations were found for most samples for June, July, August (JJA) months but in some cases the correlation coefficient was stronger when also May was taken into account. For the whole 120-yrs series the correlation between δ18O and average JJA temperature is 0.007, average JJA precipitation is 0.16 and average JJA SPEI is 0.20. Analyzing the results for 1897-2008 we can distinguish period 1960-2008 with relevantly stronger correlations: R(temperature) = 0.19, R(precipitation) = 0.20 and R(SPEI) = 0.45. This period is connected with cessation of human activity close to Lake Zabinskie. Reconstruction of climate variables for the last millennium was made using transfer function obtained for calibration period (1897-2008). Reconstructions showed that known climate extremes like Medieval Warm Period, Little Ice Age with Sporer (1420-1570), Maunder (1645-1715) and Dalton (1790-1820) Minimum was recorded in sediment from Lake Zabinskie. The presented study is a part of the project "Climate of northern Poland during the last 1000 years: Constraining the future with the past (CLIMPOL)", funded within Polish-Swiss Research Programme. http://www.climpol.ug.edu.pl

Effects of a coastal power plant thermal discharge on phytoplankton community structure in Zhanjiang Bay, China.

PubMed

Li, Xue-Ying; Li, Bin; Sun, Xing-Li

2014-04-15

The effects of a thermal discharge from a coastal power plant on phytoplankton were determined in Zhanjiang Bay. Monthly cruises were undertaken at four tide times during April-October 2011. There were significant differences for dominant species among seven sampling months and four sampling tides. Species diversity (H') and Evenness showed a distinct increasing gradient from the heated water source to the control zone and fluctuated during four tides with no visible patterns. Species richness, cell count and Chl a at mixed and control zones were significantly higher than heated zones, and showed tidal changes with no obvious patterns. The threshold temperature of phytoplankton species can be regarded as that of phytoplankton community at ebb slack. The average threshold temperature over phytoplankton species, cell count and Chl a, and the threshold temperature of cell count can be regarded as that of phytoplankton community at flood slack during spring and neap respectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

20 CFR 404.220 - Average-monthly-wage method.

Code of Federal Regulations, 2010 CFR

2010-04-01

... average-monthly-wage method if it is to your advantage. Being eligible for either the average-monthly-wage method or the modified average-monthly-wage method does not preclude your eligibility under the old-start...

Soil Variable Permeability and Water Phase Change Dynamics in a Wastewater Spray Irrigation Agricultural System Located in a Seasonably Cold Climate

NASA Astrophysics Data System (ADS)

Darnault, C. J. G.; Daniel, T. J.; Billy, G.; Hopkins, I.; Guo, L.; Jin, Z.; Gall, H. E.; Lin, H.

2017-12-01

The permeability of the upper meter of soils in frozen conditions, commonly referred to as the active layer, can vary exponentially given the time of year. Variable moisture contents along with temperature, radiation, and slope angle of the soil surface can result in variable depths of frozen soils, which can cause the formation of low permeability ice lenses well into the spring thaw period. The wastewater irrigation site known as the "Living Filter" located in State College, PA has been in continuous operation since 1962. On average 5500 m3/day of wastewater is applied to the site annually, even in the winter months when average temperatures can dip as low as -7 °C during the month of January. The Living Filter is not permitted to discharge to surface water and is intended to recharge the Spring Creek basin that directly underlies the site, therefore runoff from the site is not permitted. We hypothesize that water infiltrates the upper meter of the subsurface during the winter in several different ways such as preferential pathways in the ice layer created by plant stems and weak patches of ice thawed by the warm wastewater. 2D conceptual models of the phase change between ice and water in the soil were created in order to predict soil permeability and its change in temperature. The 2D conceptual models can be correlated between observed soil moisture content and soil temperature data in order to validate the model given spray irrigation and weather patterns. By determining the permeability of the frozen soils, irrigation practices can be adjusted for the winter months so as to reduce the risk of any accidental wastewater runoff. The impact of this study will result in a better understanding of the multiphase dynamics of the active layer and their implication on soil hydrology at the Living Filter and other seasonally frozen sites.

Climatic variation and age-specific survival in Asian elephants from Myanmar.

PubMed

Mumby, Hannah S; Courtiol, Alexandre; Mar, Khyne U; Lummaa, Virpi

2013-05-01

Concern about climate change has intensified interest in understanding how climatic variability affects animal life histories. Despite such effects being potentially most dramatic in large, long-lived, and slowly reproducing terrestrial mammals, little is known of the effects of climatic variation on survival in those species. Asian elephants (Elephas maximus) are endangered across their distribution, and inhabit regions characterized by high seasonality of temperature and rainfall. We investigated the effects of monthly climatic variation on survival and causes of death in Asian elephants using a unique demographic data set of 1024 semi-captive, longitudinally monitored elephants from four sites in Myanmar between 1965 and 2000. Temperature had a significant effect on survival in both sexes and across all ages. For elephants between 1 month and 17 years of age, maximal survival was reached at -24 degrees C, and any departures from this temperature increased mortality, whereas neonates and mature elephants had maximal survival at even lower temperatures. Although males experienced higher mortality overall, sex differences in these optimal temperatures were small. Because the elephants spent more time during a year in temperatures above 24 degrees C than in temperatures below it, most deaths occurred at hot (temperatures>24 degrees C) rather than cold periods. Decreased survival at higher temperatures resulted partially from increased deaths from infectious disease and heat stroke, whereas the lower survival in the coldest months was associated with an increase in noninfectious diseases and poor health in general. Survival was also related to rainfall, with the highest survival rates during the wettest months for all ages and sexes. Our results show that even the normal-range monsoon variation in climate can exert a large impact on elephant survival in Myanmar, leading to extensive absolute differences in mortality; switching from favorable to unfavorable climatic conditions within average years doubled the odds for mortality. The persistence of a long-term trend toward higher global temperatures, combined with the possibility of higher variation in temperature between seasons, may pose a challenge to the survival of species such as Asian elephants.

Climate impact on suicide rates in Finland from 1971 to 2003

NASA Astrophysics Data System (ADS)

Ruuhela, Reija; Hiltunen, Laura; Venäläinen, Ari; Pirinen, Pentti; Partonen, Timo

2009-03-01

Seasonal patterns of death from suicide are well-documented and have been attributed to climatic factors such as solar radiation and ambient temperature. However, studies on the impact of weather and climate on suicide are not consistent, and conflicting data have been reported. In this study, we performed a correlation analysis between nationwide suicide rates and weather variables in Finland during the period 1971-2003. The weather parameters studied were global solar radiation, temperature and precipitation, and a range of time spans from 1 month to 1 year were used in order to elucidate the dose-response relationship, if any, between weather variables and suicide. Single and multiple linear regression models show weak associations using 1-month and 3-month time spans, but robust associations using a 12-month time span. Cumulative global solar radiation had the best explanatory power, while average temperature and cumulative precipitation had only a minor impact on suicide rates. Our results demonstrate that winters with low global radiation may increase the risk of suicide. The best correlation found was for the 5-month period from November to March; the inter-annual variability in the cumulative global radiation for that period explained 40 % of the variation in the male suicide rate and 14 % of the variation in the female suicide rate, both at a statistically significant level. Long-term variations in global radiation may also explain, in part, the observed increasing trend in the suicide rate until 1990 and the decreasing trend since then in Finland.

Bleaching increases likelihood of disease on Acropora palmata (Lamarck) in Hawksnest Bay, St John, US Virgin Islands

USGS Publications Warehouse

Muller, E.M.; Rogers, Caroline S.; Spitzack, Anthony S.; van Woesik, R.

2007-01-01

Anomalously high water temperatures may enhance the likelihood of coral disease outbreaks by increasing the abundance or virulence of pathogens, or by increasing host susceptibility. This study tested the compromised-host hypothesis, and documented the relationship between disease and temperature, through monthly monitoring of Acropora palmata colonies from May 2004 to December 2006, in Hawksnest Bay, St John, US Virgin Islands (USVI). Disease prevalence and the rate of change in prevalence showed a positive linear relationship with water temperature and rate of change in water temperature, respectively, but only in 2005 during prolonged periods of elevated temperature. Both bleached and unbleached colonies showed a positive relationship between disease prevalence and temperature in 2005, but the average area of disease-associated mortality increased only for bleached corals, indicating host susceptibility, rather than temperature per se, influenced disease severity on A. palmata.

Bleaching increases likelihood of disease on Acropora palmata (Lamarck) in Hawksnest Bay, St John, US Virgin Islands

USGS Publications Warehouse

Muller, E.M.; Rogers, C.S.; Spitzack, Anthony S.; van Woesik, R.

2008-01-01

Anomalously high water temperatures may enhance the likelihood of coral disease outbreaks by increasing the abundance or virulence of pathogens, or by increasing host susceptibility. This study tested the compromised-host hypothesis, and documented the relationship between disease and temperature, through monthly monitoring of Acropora palmata colonies from May 2004 to December 2006, in Hawksnest Bay, St John, US Virgin Islands (USVI). Disease prevalence and the rate of change in prevalence showed a positive linear relationship with water temperature and rate of change in water temperature, respectively, but only in 2005 during prolonged periods of elevated temperature. Both bleached and unbleached colonies showed a positive relationship between disease prevalence and temperature in 2005, but the average area of disease-associated mortality increased only for bleached corals, indicating host susceptibility, rather than temperature per se, influenced disease severity on A. palmata. ?? 2007 Springer-Verlag.

Bleaching increases likelihood of disease on Acropora palmata (Lamarck) in Hawksnest Bay, St John, US Virgin Islands

NASA Astrophysics Data System (ADS)

Muller, E. M.; Rogers, C. S.; Spitzack, A. S.; van Woesik, R.

2008-03-01

Anomalously high water temperatures may enhance the likelihood of coral disease outbreaks by increasing the abundance or virulence of pathogens, or by increasing host susceptibility. This study tested the compromised-host hypothesis, and documented the relationship between disease and temperature, through monthly monitoring of Acropora palmata colonies from May 2004 to December 2006, in Hawksnest Bay, St John, US Virgin Islands (USVI). Disease prevalence and the rate of change in prevalence showed a positive linear relationship with water temperature and rate of change in water temperature, respectively, but only in 2005 during prolonged periods of elevated temperature. Both bleached and unbleached colonies showed a positive relationship between disease prevalence and temperature in 2005, but the average area of disease-associated mortality increased only for bleached corals, indicating host susceptibility, rather than temperature per se, influenced disease severity on A. palmata.

Understanding the influence of climate change on the embodied energy of water supply.

PubMed

Mo, Weiwei; Wang, Haiying; Jacobs, Jennifer M

2016-05-15

The current study aims to advance understandings on how and to what degree climate change will affect the life cycle chemical and energy uses of drinking water supply. A dynamic life cycle assessment was performed to quantify historical monthly operational embodied energy of a selected water supply system located in northeast US. Comprehensive multivariate and regression analyses were then performed to understand the statistical correlation among monthly life cycle energy consumptions, three water quality indicators (UV254, pH, and water temperature), and five climate indicators (monthly mean temperature, monthly mean maximum/minimum temperatures, total precipitation, and total snow fall). Thirdly, a calculation was performed to understand how volumetric and total life cycle energy consumptions will change under two selected IPCC emission scenarios (A2 and B1). It was found that volumetric life cycle energy consumptions are highest in winter months mainly due to the higher uses of natural gas in the case study system, but total monthly life cycle energy consumptions peak in both July and January because of the increasing water demand in summer months. Most of the variations in chemical and energy uses can be interpreted by water quality and climate variations except for the use of soda ash. It was also found that climate change might lead to an average decrease of 3-6% in the volumetric energy use of the case study system by the end of the century. This result combined with conclusions reached by previous climate versus water supply studies indicates that effects of climate change on drinking water supply might be highly dependent on the geographical location and treatment process of individual water supply systems. Copyright © 2016 Elsevier Ltd. All rights reserved.

Regression modeling of gas-particle partitioning of atmospheric oxidized mercury from temperature data

NASA Astrophysics Data System (ADS)

Cheng, Irene; Zhang, Leiming; Blanchard, Pierrette

2014-10-01

Models describing the partitioning of atmospheric oxidized mercury (Hg(II)) between the gas and fine particulate phases were developed as a function of temperature. The models were derived from regression analysis of the gas-particle partitioning parameters, defined by a partition coefficient (Kp) and Hg(II) fraction in fine particles (fPBM) and temperature data from 10 North American sites. The generalized model, log(1/Kp) = 12.69-3485.30(1/T) (R2 = 0.55; root-mean-square error (RMSE) of 1.06 m3/µg for Kp), predicted the observed average Kp at 7 of the 10 sites. Discrepancies between the predicted and observed average Kp were found at the sites impacted by large Hg sources because the model had not accounted for the different mercury speciation profile and aerosol compositions of different sources. Site-specific equations were also generated from average Kp and fPBM corresponding to temperature interval data. The site-specific models were more accurate than the generalized Kp model at predicting the observations at 9 of the 10 sites as indicated by RMSE of 0.22-0.5 m3/µg for Kp and 0.03-0.08 for fPBM. Both models reproduced the observed monthly average values, except for a peak in Hg(II) partitioning observed during summer at two locations. Weak correlations between the site-specific model Kp or fPBM and observations suggest the role of aerosol composition, aerosol water content, and relative humidity factors on Hg(II) partitioning. The use of local temperature data to parameterize Hg(II) partitioning in the proposed models potentially improves the estimation of mercury cycling in chemical transport models and elsewhere.

A study of urban heat island and its association with particulate matter during winter months over Delhi.

PubMed

Pandey, Puneeta; Kumar, Dinesh; Prakash, Amit; Masih, Jamson; Singh, Manoj; Kumar, Surendra; Jain, Vinod Kumar; Kumar, Krishan

2012-01-01

Day and night time thermal mapping of Delhi has been done with MODIS satellite data for the months of November and December for years 2007, 2008, 2009 and 2010. The study reveals the formation of day time "cool island" over central parts of Delhi which are found to be cooler by a maximum of 4-6 °C than the surrounding rural areas. During the night time, however, the central parts of Delhi are found to be warmer by a maximum of 4-7 °C or even more than the surrounding rural areas thus confirming the formation of nocturnal urban heat island over Delhi. Measurements of solar spectral irradiance over Delhi reveal significantly lower values as compared to a rural site located south-west of Delhi, during the low wind conditions in the months of November and December. Analysis of average monthly temporal data of surface wind speed and particulate matter concentration over Delhi reveals a strong anti-correlation between wind speed and particulate matter concentration. High values of particulate matter during low wind conditions seem to favor the so called "cool island" over Delhi. Analysis of radiosonde data of 975 hPa and 850 hPa temperatures over Delhi during November and December from 1973 to 2010 reveals a warming trend at the 850 hPa level and an overall declining trend of ∆T between 975 hPa temperatures and 850 hPa temperatures, thus indicating a weakening of vertical thermal gradients over Delhi during these months. The study suggests that urban areas behave more like moderators of diurnal temperature variation in low wind conditions. Copyright © 2011 Elsevier B.V. All rights reserved.

Long-term hydrothermal temperature and pressure monitoring equipped with a Kuroko cultivation apparatus on the deep-sea artificial hydrothermal vent at the middle Okinawa Trough

NASA Astrophysics Data System (ADS)

Masaki, Y.; Nozaki, T.; Saruhashi, T.; Kyo, M.; Sakurai, N.; Yokoyama, T.; Akiyama, K.; Watanabe, M.; Kumagai, H.; Maeda, L.; Kinoshita, M.

2017-12-01

The middle Okinawa Trough, located along the Ryukyu- arc on the margin of the East China Sea, has several active hydrothermal fields. From February to March 2016, Cruise CK16-01 by D/V Chikyu targeted the Iheya-North Knoll and southern flank of the Iheya Minor Ridge to comprehend sub-seafloor geological structure and polymetallic sulfide mineralization. In this cruise, we installed two Kuroko cultivation apparatuses equipped with P/T sensors, flowmeter and load cell to monitor pressure, temperature and flow rate of hydrothermal fluid discharged from the artificial hydrothermal vent together with weight of hydrothermal precipitate. During Cruise KR16-17 in January 2017, two cultivation cells with sensor loggers were successfully recovered by ROV Kaiko MK-IV and R/V Kairei. We report these physical sensor data obtained by more than 10 months monitoring at two deep-sea artificial hydrothermal vents through many first and challenging operations.Hole C9017B at southern flank of the Iheya Minor Ridge (water depth of 1,500 mbsl), fluid temperature was constant ca. 75 ºC for 5 months from the beginning of monitoring. Then temperature gradually decrease to be 40 ºC. In November 2016, temperature and pressure suddenly dropped and quickly recovered due to the disturbance of subseafloor hydrology, induced by another drilling operation at Hole C9017A which is 10.8 meters northeastward from Hole C9017B during Cruise CK16-05. Temperature data exhibit conspicuous periodic 12.4hour cycles and this is attributable to oceanic tidal response. The amplitude of temperature variations increased along with decline of the temperature variations increased along with decline of the temperature. The average flow rate was 67 L/min for 9 hours from the onset of monitoring.Hole C9024A at the Iheya-North Knoll (water depth of 1,050 msl), the maximum temperature reached 308 ºC, which is similar to the maximum value of 311 ºC obtained from the ROV thermometer. The average flow rate was 289 L/min for 8 days from onset of monitoring.

Water-temperature, specific-conductance, and meteorological data for the Tualatin River basin, Oregon, 1994-95

USGS Publications Warehouse

Risley, John C.; Doyle, Micelis C.

1997-01-01

Water-temperature, air-temperature, specific- conductance, wind-speed, and solar-radiation data are presented from a study conducted in the Tualatin River Basin in northwestern Oregon during 7-month periods from May 1 through November 30, 1994 and May 1 through November 30, 1995. The study was done to assist local and State agencies in understanding temporal and spatial patterns of water temperatures in the river, determining the relation between water temperature and human activities, and developing urban and agricultural management strategies for controlling impacts on stream temperatures. Data were collected at 14 fixed-station continuous monitoring sites located on or near the main stem and major tributaries. Data fromtemperature and specific-conductance sites were collected instantaneously every 30 minutes on the hour and half hour. Wind-speed and solar-radiation data at two sites were averaged every 60 minutes. Wind-speed and solar-radiation data at a third site were averaged every 30 minutes. Water temperature data were also collected during seven synoptic surveys near the two main wastewater-treatment plants. The surveys were conducted during the low-flow period from August to October of 1994 and August to September 1995. During each survey, up to six recording temperature probes were positioned at locations upstream and downstream of plant effluent outlets. The probes collected data every 16 minutes over 48-hour periods.

Winter Season Mortality: Will Climate Warming Bring Benefits?

PubMed

Kinney, Patrick L; Schwartz, Joel; Pascal, Mathilde; Petkova, Elisaveta; Tertre, Alain Le; Medina, Sylvia; Vautard, Robert

2015-06-01

Extreme heat events are associated with spikes in mortality, yet death rates are on average highest during the coldest months of the year. Under the assumption that most winter excess mortality is due to cold temperature, many previous studies have concluded that winter mortality will substantially decline in a warming climate. We analyzed whether and to what extent cold temperatures are associated with excess winter mortality across multiple cities and over multiple years within individual cities, using daily temperature and mortality data from 36 US cities (1985-2006) and 3 French cities (1971-2007). Comparing across cities, we found that excess winter mortality did not depend on seasonal temperature range, and was no lower in warmer vs. colder cities, suggesting that temperature is not a key driver of winter excess mortality. Using regression models within monthly strata, we found that variability in daily mortality within cities was not strongly influenced by winter temperature. Finally we found that inadequate control for seasonality in analyses of the effects of cold temperatures led to spuriously large assumed cold effects, and erroneous attribution of winter mortality to cold temperatures. Our findings suggest that reductions in cold-related mortality under warming climate may be much smaller than some have assumed. This should be of interest to researchers and policy makers concerned with projecting future health effects of climate change and developing relevant adaptation strategies.

Winter season mortality: will climate warming bring benefits?

NASA Astrophysics Data System (ADS)

Kinney, Patrick L.; Schwartz, Joel; Pascal, Mathilde; Petkova, Elisaveta; Le Tertre, Alain; Medina, Sylvia; Vautard, Robert

2015-06-01

Extreme heat events are associated with spikes in mortality, yet death rates are on average highest during the coldest months of the year. Under the assumption that most winter excess mortality is due to cold temperature, many previous studies have concluded that winter mortality will substantially decline in a warming climate. We analyzed whether and to what extent cold temperatures are associated with excess winter mortality across multiple cities and over multiple years within individual cities, using daily temperature and mortality data from 36 US cities (1985-2006) and 3 French cities (1971-2007). Comparing across cities, we found that excess winter mortality did not depend on seasonal temperature range, and was no lower in warmer vs. colder cities, suggesting that temperature is not a key driver of winter excess mortality. Using regression models within monthly strata, we found that variability in daily mortality within cities was not strongly influenced by winter temperature. Finally we found that inadequate control for seasonality in analyses of the effects of cold temperatures led to spuriously large assumed cold effects, and erroneous attribution of winter mortality to cold temperatures. Our findings suggest that reductions in cold-related mortality under warming climate may be much smaller than some have assumed. This should be of interest to researchers and policy makers concerned with projecting future health effects of climate change and developing relevant adaptation strategies.

CERES Monthly TOA and SRB Averages (SRBAVG) data in HDF-EOS Grid (CER_SRBAVG_Terra-FM2-MODIS_Edition2C)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly TOA/Surface Averages (SRBAVG) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SRBAVG is also produced for combinations of scanner instruments. The monthly average regional flux is estimated using diurnal models and the 1-degree regional fluxes at the hour of observation from the CERES SFC product. A second set of monthly average fluxes are estimated using concurrent diurnal information from geostationary satellites. These fluxes are given for both clear-sky and total-sky scenes and are spatially averaged from 1-degree regions to 1-degree zonal averages and a global average. For each region, the SRBAVG also contains hourly average fluxes for the month and an overall monthly average. The cloud properties from SFC are column averaged and are included on the SRBAVG. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-02-01; Stop_Date=2003-02-28] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

CERES Monthly TOA and SRB Averages (SRBAVG) data in HDF-EOS Grid (CER_SRBAVG_TRMM-PFM-VIRS_Edition2B)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly TOA/Surface Averages (SRBAVG) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SRBAVG is also produced for combinations of scanner instruments. The monthly average regional flux is estimated using diurnal models and the 1-degree regional fluxes at the hour of observation from the CERES SFC product. A second set of monthly average fluxes are estimated using concurrent diurnal information from geostationary satellites. These fluxes are given for both clear-sky and total-sky scenes and are spatially averaged from 1-degree regions to 1-degree zonal averages and a global average. For each region, the SRBAVG also contains hourly average fluxes for the month and an overall monthly average. The cloud properties from SFC are column averaged and are included on the SRBAVG. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-02-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

CERES Monthly TOA and SRB Averages (SRBAVG) data in HDF-EOS Grid (CER_SRBAVG_Terra-FM1-MODIS_Edition2C)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly TOA/Surface Averages (SRBAVG) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SRBAVG is also produced for combinations of scanner instruments. The monthly average regional flux is estimated using diurnal models and the 1-degree regional fluxes at the hour of observation from the CERES SFC product. A second set of monthly average fluxes are estimated using concurrent diurnal information from geostationary satellites. These fluxes are given for both clear-sky and total-sky scenes and are spatially averaged from 1-degree regions to 1-degree zonal averages and a global average. For each region, the SRBAVG also contains hourly average fluxes for the month and an overall monthly average. The cloud properties from SFC are column averaged and are included on the SRBAVG. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-02-01; Stop_Date=2003-02-28] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

CERES Monthly TOA and SRB Averages (SRBAVG) data in HDF-EOS Grid (CER_SRBAVG_Terra-FM1-MODIS_Edition2D)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly TOA/Surface Averages (SRBAVG) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SRBAVG is also produced for combinations of scanner instruments. The monthly average regional flux is estimated using diurnal models and the 1-degree regional fluxes at the hour of observation from the CERES SFC product. A second set of monthly average fluxes are estimated using concurrent diurnal information from geostationary satellites. These fluxes are given for both clear-sky and total-sky scenes and are spatially averaged from 1-degree regions to 1-degree zonal averages and a global average. For each region, the SRBAVG also contains hourly average fluxes for the month and an overall monthly average. The cloud properties from SFC are column averaged and are included on the SRBAVG. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-02-01; Stop_Date=2004-05-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

Effects of clouds on the Earth radiation budget; Seasonal and inter-annual patterns

NASA Technical Reports Server (NTRS)

Dhuria, Harbans L.

1992-01-01

Seasonal and regional variations of clouds and their effects on the climatological parameters were studied. The climatological parameters surface temperature, solar insulation, short-wave absorbed, long wave emitted, and net radiation were considered. The data of climatological parameters consisted of about 20 parameters of Earth radiation budget and clouds of 2070 target areas which covered the globe. It consisted of daily and monthly averages of each parameter for each target area for the period, Jun. 1979 - May 1980. Cloud forcing and black body temperature at the top of the atmosphere were calculated. Interactions of clouds, cloud forcing, black body temperature, and the climatological parameters were investigated and analyzed.

On the relationship between water vapor over the oceans and sea surface temperature

NASA Technical Reports Server (NTRS)

Stephens, Graeme L.

1990-01-01

Monthly mean precipitable water data obtained from passive microwave radiometry were correlated with the National Meteorological Center (NMC) blended sea surface temperature data. It is shown that the monthly mean water vapor content of the atmosphere above the oceans can generally be prescribed from the sea surface temperature with a standard deviation of 0.36 g/sq cm. The form of the relationship between precipitable water and sea surface temperature in the range T (sub s) greater than 18 C also resembles that predicted from simple arguments based on the Clausius-Clapeyron relationship. The annual cycle of the globally integrated mass of Scanning Multichannel Microwave Radiometer (SMMR) water vapor is shown to differ from analyses of other water vapor data in both phase and amplitude and these differences point to a significant influence of the continents on water vapor. Regional scale analyses of water vapor demonstrate that monthly averaged water vapor data, when contrasted with the bulk sea surface temperature relationship developed in this study, reflect various known characteristics of the time mean large-scale circulation over the oceans. A water vapor parameter is introduced to highlight the effects of large-scale motion on atmospheric water vapor. Based on the magnitude of this parameter, it is shown that the effects of large-scale flow on precipitable water vapor are regionally dependent, but for the most part, the influence of circulation is generally less than about + or - 20 percent of the seasonal mean.

On the relationship between water vapor over the oceans and sea surface temperature

NASA Technical Reports Server (NTRS)

Stephens, Graeme L.

1989-01-01

Monthly mean precipitable water data obtained from passive microwave radiometry were correlated with the National Meteorological Center (NMC) blended sea surface temperature data. It is shown that the monthly mean water vapor content of the atmosphere above the oceans can generally be prescribed from the sea surface temperature with a standard deviation of 0.36 g/sq cm. The form of the relationship between precipitable water and sea surface temperature in the range T(sub s) greater than 18 C also resembles that predicted from simple arguments based on the Clausius-Clapeyron relationship. The annual cycle of the globally integrated mass of Scanning Multichannel Microwave Radiometer (SMMR) water vapor is shown to differ from analyses of other water vapor data in both phase and amplitude and these differences point to a significant influence of the continents on water vapor. Regional scale analyses of water vapor demonstrate that monthly averaged water vapor data, when contrasted with the bulk sea surface temperature relationship developed in this study, reflect various known characteristics of the time mean large-scale circulation over the oceans. A water vapor parameter is introduced to highlight the effects of large-scale motion on atmospheric water vapor. Based on the magnitude of this parameter, it is shown that the effects of large-scale flow on precipitable water vapor are regionally dependent, but for the most part, the influence of circulation is generally less than about + or - 20 percent of the seasonal mean.

Spatial and seasonal dynamics of surface soil carbon in the Luquillo Experimental Forest, Puerto Rico.

Treesearch

Hongqing Wang; Joseph D. Cornell; Charles A.S. Hall; David P. Marley

2002-01-01

We developed a spatially-explicit version of the CENTURY soil model to characterize the storage and flux of soil organic carbon (SOC, 0–30 cm depth) in the Luquillo Experimental Forest (LEF), Puerto Rico as a function of climate, vegetation, and soils. The model was driven by monthly estimates of average air temperature, precipitation, and potential evapotranspiration...

Equilibrium moisture content of wood in outdoor locations in the United States and worldwide

Treesearch

W. T. Simpson

1998-01-01

With relative humidity and temperature data from the National Oceanic and Atmospheric Administration, the average equilibrium moisture content for each month of the year was calculated for 262 locations in the United States and 122 locations outside the United States. As an aid for storage of kiln-dried lumber, a graph is presented for determining the reduction in...

EnviroAtlas - Potential Evapotranspiration 1950 - 2099 for the Conterminous United States

EPA Pesticide Factsheets

The EnviroAtlas Climate Scenarios were generated from NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30) ensemble averages (the average of over 30 available climate models) for each of the four representative concentration pathways (RCP) for the contiguous U.S. at 30 arc-second (approx. 800 m2) spatial resolution. In addition to the three climate variables provided by the NEX-DCP30 dataset (minimum monthly temperature, maximum monthly temperature, and precipitation) a corresponding estimate of potential evapotranspiration (PET) was developed to match the spatial and temporal scales of the input dataset. PET represents the cumulative amount of water returned to the atmosphere due to evaporation from Earth00e2??s surface and plant transpiration under ideal circumstances (i.e., a vegetated surface shading the ground and unlimited water supply). PET was calculated using the Hamon PET equation (Hamon, 1961) and CBM model for daylength (Forsythe et al. 1995) for the 4 RCPs (2.6, 4.5, 6.0, 8.5) and organized by season (Winter, Spring, Summer, and Fall) and annually for the years 2006 00e2?? 2099. Additionally, PET was calculated for the ensemble average of all historic runs and organized similarly for the years 1950 00e2?? 2005. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-u

Retrieval of air temperatures from crowd-sourced battery temperatures of cell phones

NASA Astrophysics Data System (ADS)

Overeem, Aart; Robinson, James; Leijnse, Hidde; Uijlenhoet, Remko; Steeneveld, Gert-Jan; Horn, Berthold K. P.

2013-04-01

Accurate air temperature observations are important for urban meteorology, for example to study the urban heat island and adverse effects of high temperatures on human health. The number of available temperature observations is often relatively limited. A new development is presented to derive temperature information for the urban canopy from an alternative source: cell phones. Battery temperature data were collected by users of an Android application for cell phones (opensignal.com). The application automatically sends battery temperature data to a server for storage. In this study, battery temperatures are averaged in space and time to obtain daily averaged battery temperatures for each city separately. A regression model, which can be related to a physical model, is employed to retrieve daily air temperatures from battery temperatures. The model is calibrated with observed air temperatures from a meteorological station of an airport located in or near the city. Time series of air temperatures are obtained for each city for a period of several months, where 50% of the data is for independent verification. Results are presented for Buenos Aires, London, Los Angeles, Paris, Mexico City, Moscow, Rome, and Sao Paulo. The evolution of the retrieved air temperatures often correspond well with the observed ones. The mean absolute error of daily air temperatures is less than 2 degrees Celsius, and the bias is within 1 degree Celsius. This shows that monitoring air temperatures employing an Android application holds great promise. Since 75% of the world's population has a cell phone, 20% of the land surface of the earth has cellular telephone coverage, and 500 million devices use the Android operating system, there is a huge potential for measuring air temperatures employing cell phones. This could eventually lead to real-time world-wide temperature maps.

Weather Types, temperature and relief relationship in the Iberian Peninsula: A regional adiabatic processes under directional weather types

NASA Astrophysics Data System (ADS)

Peña Angulo, Dhais; Trigo, Ricardo; Cortesi, Nicola; Gonzalez-Hidalgo, Jose Carlos

2016-04-01

We have analyzed at monthly scale the spatial distribution of Pearson correlation between monthly mean of maximum (Tmax) and minimum (Tmin) temperatures with weather types (WTs) in the Iberian Peninsula (IP), represent them in a high spatial resolution grid (10km x 10km) from MOTEDAS dataset (Gonzalez-Hidalgo et al., 2015a). The WT classification was that developed by Jenkinson and Collison, adapted to the Iberian Peninsula by Trigo and DaCamara, using Sea Level Pressure data from NCAR/NCEP Reanalysis dataset (period 1951-2010). The spatial distribution of Pearson correlations shows a clear zonal gradient in Tmax under the zonal advection produced in westerly (W) and easterly (E) flows, with negative correlation in the coastland where the air mass come from but positive correlation to the inland areas. The same is true under North-West (NW), North-East (NE), South-West (SW) and South-East (SE) WTs. These spatial gradients are coherent with the spatial distribution of the main mountain chain and offer an example of regional adiabatic phenomena that affect the entire IP (Peña-Angulo et al., 2015b). These spatial gradients have not been observed in Tmin. We suggest that Tmin values are less sensitive to changes in Sea Level Pressure and more related to local factors. These directional WT present a monthly frequency over 10 days and could be a valuable tool for downscaling processes. González-Hidalgo J.C., Peña-Angulo D., Brunetti M., Cortesi, C. (2015a): MOTEDAS: a new monthly temperature database for mainland Spain and the trend in temperature (1951-2010). International Journal of Climatology 31, 715-731. DOI: 10.1002/joc.4298 Peña-Angulo, D., Trigo, R., Cortesi, C., González-Hidalgo, J.C. (2015b): The influence of weather types on the monthly average maximum and minimum temperatures in the Iberian Peninsula. Submitted to Hydrology and Earth System Sciences.

20 CFR 404.221 - Computing your average monthly wage.

Code of Federal Regulations, 2010 CFR

2010-04-01

... your average monthly wage, we consider all the wages, compensation, self-employment income, and deemed... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Computing your average monthly wage. 404.221... DISABILITY INSURANCE (1950- ) Computing Primary Insurance Amounts Average-Monthly-Wage Method of Computing...

20 CFR 404.221 - Computing your average monthly wage.

Code of Federal Regulations, 2011 CFR

2011-04-01

... your average monthly wage, we consider all the wages, compensation, self-employment income, and deemed... 20 Employees' Benefits 2 2011-04-01 2011-04-01 false Computing your average monthly wage. 404.221... DISABILITY INSURANCE (1950- ) Computing Primary Insurance Amounts Average-Monthly-Wage Method of Computing...

A Case Study to Improve Emergency Room Patient Flow at Womack Army Medical Center

DTIC Science & Technology

2009-06-01

use just the previous month, moving average 2-month period ( MA2 ) uses the average from the previous two months, moving average 3-month period (MA3...ED prior to discharge by provider) MA2 /MA3/MA4 - moving averages of 2-4 months in length MAD - mean absolute deviation (measure of accuracy for

Climate Variation at Flagstaff, Arizona - 1950 to 2007

USGS Publications Warehouse

Hereford, Richard

2007-01-01

INTRODUCTION Much scientific research demonstrates the existence of recent climate variation, particularly global warming. Climate prediction models forecast that climate will change; it will become warmer, droughts will increase in number and severity, and extreme climate events will recur often?desiccating aridity, extremely wet, unusually warm, or even frigid at times. However, the global models apply to average conditions in large grids approximately 150 miles on an edge (Thorpe, 2005), and how or whether specific areas within a grid are affected is unclear. Flagstaff's climate is mentioned in the context of global change, but information is lacking on the amount and trend of changes in precipitation, snowfall, and temperature. The purpose of this report is to understand what may be happening to Flagstaff's climate by reviewing local climate history. Flagstaff is in north-central Arizona south of San Francisco Mountain, which reaches 12,633 feet, the highest in Arizona (fig. 1). At 6,900 feet, surrounded by ponderosa pine forest, Flagstaff enjoys a four-season climate; winter-daytime temperatures are cool, averaging 45 degrees (Fahrenheit). Summer-daytime temperatures are comfortable, averaging 80 degrees, which is pleasant compared with nearby low-elevation deserts. Flagstaff?s precipitation averages 22-inches per year with a range of 9 to 39 inches. Snowfall occurs each season, averaging 97 inches annually. This report, written for the non-technical reader, interprets climate variation at Flagstaff as observed at the National Weather Service (NWS) station at Pulliam Field (or Airport), a first-order weather station staffed by meteorologists (Staudenmaier and others, 2007). The station is on a flat-topped ridge surrounded by forest 5-miles south of Flagstaff at an elevation of 7,003 feet. Data used in this analysis are daily measurements of precipitation (including snowfall) and temperature (maximum and minimum) covering the period from 1950, when the station began operation, through spring 2007. Conversations with Byron Peterson and Michael Staudenmaier of the NWS helped us understand the difficulties of collecting consistent weather data, operation of the station, and Flagstaff's climate. Weather is the daily or even instantaneous state of temperature and precipitation. Climate is the average or accumulation of these parameters over longer time scales such as a week, month, or year. Seasonal (winter, spring, summer, and fall) and annual averages of temperature and accumulated precipitation describe the temporal variation of Flagstaff's climate, which is shown graphically with time series (figs. 2, 4, 6, 8-15). These plots show precipitation or temperature on the ordinate plotted against time on the abscissa, which is a year for annually repeating data or the year of a particular season. The plots reveal changing patterns of precipitation and temperature related to droughts, wet episodes, and rising temperatures.

Subtropical mouse-tailed bats use geothermally heated caves for winter hibernation

PubMed Central

Levin, Eran; Plotnik, Brit; Amichai, Eran; Braulke, Luzie J.; Landau, Shmulik; Yom-Tov, Yoram; Kronfeld-Schor, Noga

2015-01-01

We report that two species of mouse-tailed bats (Rhinopoma microphyllum and R. cystops) hibernate for five months during winter in geothermally heated caves with stable high temperature (20°C). While hibernating, these bats do not feed or drink, even on warm nights when other bat species are active. We used thermo-sensitive transmitters to measure the bats’ skin temperature in the natural hibernacula and open flow respirometry to measure torpid metabolic rate at different ambient temperatures (Ta, 16–35°C) and evaporative water loss (EWL) in the laboratory. Bats average skin temperature at the natural hibernacula was 21.7 ± 0.8°C, and no arousals were recorded. Both species reached the lowest metabolic rates around natural hibernacula temperatures (20°C, average of 0.14 ± 0.01 and 0.16 ± 0.04 ml O2 g−1 h−1 for R. microphyllum and R. cystops, respectively) and aroused from torpor when Ta fell below 16°C. During torpor the bats performed long apnoeas (14 ± 1.6 and 16 ± 1.5 min, respectively) and had a very low EWL. We hypothesize that the particular diet of these bats is an adaptation to hibernation at high temperatures and that caves featuring high temperature and humidity during winter enable these species to survive this season on the northern edge of their world distribution. PMID:25740890

Study of phase clustering method for analyzing large volumes of meteorological observation data

NASA Astrophysics Data System (ADS)

Volkov, Yu. V.; Krutikov, V. A.; Botygin, I. A.; Sherstnev, V. S.; Sherstneva, A. I.

2017-11-01

The article describes an iterative parallel phase grouping algorithm for temperature field classification. The algorithm is based on modified method of structure forming by using analytic signal. The developed method allows to solve tasks of climate classification as well as climatic zoning for any time or spatial scale. When used to surface temperature measurement series, the developed algorithm allows to find climatic structures with correlated changes of temperature field, to make conclusion on climate uniformity in a given area and to overview climate changes over time by analyzing offset in type groups. The information on climate type groups specific for selected geographical areas is expanded by genetic scheme of class distribution depending on change in mutual correlation level between ground temperature monthly average.

Breeding and mass scale rearing of clownfish Amphiprion percula: feeding and rearing in brackishwater

NASA Astrophysics Data System (ADS)

Dhaneesh, Kottila Veettil; Ajith Kumar, Thipramalai Thankappan; Swagat, Ghosh; Balasubramanian, Thangavel

2012-07-01

Breeding and mass scale larval rearing of clownfish Amphiprion percula is very limited in brackishwater. We designed an indoor program of A. percula culture in brackishwater with a salinity of 24±1, during which the impacts of feed type, water temperature, and light intensity, on the efficiency of its reproduction, were revealed. The fish were accommodated along with sea anemones in fibre glass tanks to determine the influence of brooder diet on breeding efficiency. Higher reproductive efficiency [number of eggs laid (276 ± 22.3 eggs)] was observed when fish were fed live Acetes sp. rather than clam (204 ± 16.4 eggs), trash fish (155 ± 12 eggs) and formulated feed (110 ± 10 eggs). The spawning rate was increased during September and October (water temperature, 28.74 ± 0.55°C) on average of 2.4 spawning per month; and low spawning rate was in January (water temperature, 24.55 ± 0.45°C) on average of 1 spawning per month. Among three light intensities (100, 500, and 900 lx) set to evaluate larval survival rate, larvae showed the highest survival rate (65.5%) at 900 lx. The breeding method specifically in brackishwater developed in the present study is a new approach, will help the people from the regions of estuary and backwater to enhance their livelihood and it will lead to reduce the exploitation from the wild habitat.

In situ thermal conductivity of gas-hydrate-bearing sediments of the Mallik 5L-38 well

NASA Astrophysics Data System (ADS)

Henninges, J.; Huenges, E.; Burkhardt, H.

2005-11-01

Detailed knowledge about thermal properties of rocks containing gas hydrate is required in order to quantify processes involving gas hydrate formation and decomposition in nature. In the framework of the Mallik 2002 program, three wells penetrating a continental gas hydrate occurrence under permafrost were successfully equipped with permanent fiber-optic distributed temperature sensing cables. Temperature data were collected over a 21-month period after completing the wells. Thermal conductivity profiles were calculated from the geothermal data as well as from a petrophysical model derived from the available logging data and application of mixing law models. Results indicate that thermal conductivity variations are mainly lithologically controlled with a minor influence from hydrate saturation. Average thermal conductivity values of the hydrate-bearing sediments range between 2.35 and 2.77 W m-1 K-1. Maximum gas hydrate saturations can reach up to about 90% at an average porosity of 0.3.

Correlation between asthma and climate in the European Community Respiratory Health Survey.

PubMed

Verlato, Giuseppe; Calabrese, Rolando; De Marco, Roberto

2002-01-01

The European Community Respiratory Health Survey, performed during 1991-1993, found a remarkable geographical variability in the prevalence of asthma and asthma-like symptoms in individuals aged 20-44 yr. The highest values occurred in the English-speaking centers. In the present investigation, the ecological relationship between climate and symptom prevalence was evaluated in the 48 centers of the European Community Respiratory Health Survey. Meteorological variables were derived from the Global Historical Climatology Network and were averaged over an 11-yr period (i.e., 1980-1990). Respiratory symptom prevalence was directly related to temperature in the coldest month and was related inversely to the temperature in the hottest month. Warm winters and cool summers are features of oceanic climate found in most English-speaking centers of the European Community Respiratory Health Survey (i.e., England, New Zealand, and Oregon). In conclusion, climate can account for significant geographic variability in respiratory symptom prevalence.

Spatial and Temporal Variations of Water Quality and Trophic Status in Sembrong Reservoir, Johor

NASA Astrophysics Data System (ADS)

Intan Najla Syed Hashim, Syarifah; Hidayah Abu Talib, Siti; Salleh Abustan, Muhammad

2018-03-01

A study of spatial and temporal variations on water quality and trophic status was conducted to determine the temporal (average reading by month) and spatial variations of water quality in Sembrong reservoir and to evaluate the trophic status of the reservoir. Water samples were collected once a month from November 2016 to June 2017 in seventeen (17) sampling stations at Sembrong Reservoir. Results obtained on the concentration of dissolved oxygen (DO), water temperature, pH and secchi depth had no significant differences compared to Total Phosphorus (TP) and chlorophyll-a. The water level has significantly decreased the value of the water temperature, pH and TP. The water quality of Sembrong reservoir is classified in Class II which is suitable for recreational uses and required conventional treatment while TSI indicates that sembrong reservoir was in lower boundary of classical eutrophic (TSI > 50).

Global atmospheric circulation statistics: Four year averages

NASA Technical Reports Server (NTRS)

Wu, M. F.; Geller, M. A.; Nash, E. R.; Gelman, M. E.

1987-01-01

Four year averages of the monthly mean global structure of the general circulation of the atmosphere are presented in the form of latitude-altitude, time-altitude, and time-latitude cross sections. The numerical values are given in tables. Basic parameters utilized include daily global maps of temperature and geopotential height for 18 pressure levels between 1000 and 0.4 mb for the period December 1, 1978 through November 30, 1982 supplied by NOAA/NMC. Geopotential heights and geostrophic winds are constructed using hydrostatic and geostrophic formulae. Meridional and vertical velocities are calculated using thermodynamic and continuity equations. Fields presented in this report are zonally averaged temperature, zonal, meridional, and vertical winds, and amplitude of the planetary waves in geopotential height with zonal wave numbers 1-3. The northward fluxes of sensible heat and eastward momentum by the standing and transient eddies along with their wavenumber decomposition and Eliassen-Palm flux propagation vectors and divergences by the standing and transient eddies along with their wavenumber decomposition are also given. Large interhemispheric differences and year-to-year variations are found to originate in the changes in the planetary wave activity.

Long-term growth rates and effects of bleaching in Acropora hyacinthus

NASA Astrophysics Data System (ADS)

Gold, Zachary; Palumbi, Stephen R.

2018-03-01

Understanding the response of coral growth to natural variation in the environment, as well as to acute temperature stress under current and future climate change conditions, is critical to predicting the future health of coral reef ecosystems. As such, ecological surveys are beginning to focus on corals that live in high thermal stress environments to understand how future coral populations may adapt to climate change. We investigated the relationship between coral growth, thermal microhabitat, symbionts type, and thermal acclimatization of four species of the Acropora hyacinthus complex in back-reef lagoons in American Samoa. Coral growth was measured from August 2010 to April 2016 using horizontal planar area of coral colonies derived from photographs and in situ maximum width measurements. Despite marked intraspecific variation, we found that planar colony growth rates were significantly different among cryptic species. The highly heat tolerant A. hyacinthus variant "HE" increased in area an average of 2.9% month-1 (0.03 cm average mean radial extension month-1). By contrast, the three less tolerant species averaged 6.1% (0.07 cm average mean radial extension month-1). Planar growth rates were 40% higher on average in corals harboring Clade C versus Clade D symbiont types, although marked inter-colony variation in growth rendered this difference nonsignificant. Planar growth rates for all four species dropped to near zero following a 2015 bleaching event, independent of the visually estimated percent area of bleaching. Within 1 yr, growth rates recovered to previous levels, confirming previous studies that found sublethal effects of thermal stress on coral growth. Long-term studies of individual coral colonies provide an important tool to measure impacts of environmental change and allow integration of coral physiology, genetics, symbionts, and microclimate on reef growth patterns.

Microclimate and actual evapotranspiration in a humid coastal-plain environment

USGS Publications Warehouse

Dennehy, K.F.; McMahon, P.B.

1987-01-01

Continuous hourly measurements of twelve meteorologic variables recorded during 1983 and 1984 were used to examine the microclimate and actual evapotranspiration at a low-level radioactive-waste burial site near Barnwell, South Carolina. The study area is in the Atlantic Coastal Plain of southwestern South Carolina. Monthly, daily, and hourly trends in net radiation, incoming and reflected short-wave radiation, incoming and emitted long-wave radiation, soil-heat flux, dry- and wet-bulb temperatures, soil temperatures, wind direction and speed, and precipitation were used to characterize the microclimate. Average daily air temperatures ranged from -9 to 32?? Celsius during the period of study. Net radiation varied from about -27 to 251 watts m-2 and was dominated by incoming short-wave radiation throughout the year. The peak net radiation during a summer day generally occurred 2-3h before the peak vapor pressure deficit. In the winter, these peaks occurred at about the same time of day. Monthly precipitation varied from 15 to 241 mm. The Bowen ratio method was used to estimate hourly evapotranspiration, which was summed to also give daily and monthly evapotranspiration. Actual evapotranspiration varied from 0.0 to 0.7 mm h-1, 0.8-5 mm d-1, and 20-140 mm month-1 during 1983 and 1984. The maximum rate of evapotranspiration generally occurred at the same time of day as maximum net radiation, suggesting net radiation was the main driving force for evapotranspiration. Precipitation exceeded evapotranspiration during 14 months of the 2yr study period. Late fall, winter, and early spring contained the majority of these months. The maximum excess precipitation was 115 mm in February 1983. ?? 1987.

Comparison of ground based indices (API and AQI) with satellite based aerosol products.

PubMed

Zheng, Sheng; Cao, Chun-Xiang; Singh, Ramesh P

2014-08-01

Air quality in mega cities is one of the major concerns due to serious health issues and its indirect impact to the climate. Among mega cities, Beijing city is considered as one of the densely populated cities with extremely poor air quality. The meteorological parameters (wind, surface temperature, air temperature and relative humidity) control the dynamics and dispersion of air pollution. China National Environmental Monitoring Centre (CNEMC) started air pollution index (API) as of 2000 to evaluate air quality, but over the years, it was felt that the air quality is not well represented by API. Recently, the Ministry of Environmental Protection (MEP) of the People's Republic of China (PRC) started using a new index "air quality index (AQI)" from January 2013. We have compared API and AQI with three different MODIS (MODIS - Moderate Resolution Imaging SpectroRadiometer, onboard the Terra/Aqua satellites) AOD (aerosol optical depth) products for ten months, January-October, 2013. The correlation between AQI and Aqua Deep Blue AOD was found to be reasonably good as compared with API, mainly due to inclusion of PM2.5 in the calculation of AQI. In addition, for every month, the correlation coefficient between AQI and Aqua Deep Blue AOD was found to be relatively higher in the month of February to May. According to the monthly average distribution of precipitation, temperature, and PM10, the air quality in the months of June-September was better as compared to those in the months of February-May. AQI and Aqua Deep Blue AOD show highly polluted days associated with dust event, representing true air quality of Beijing. Copyright © 2013 Elsevier B.V. All rights reserved.

Modeling and projection of dengue fever cases in Guangzhou based on variation of weather factors.

PubMed

Li, Chenlu; Wang, Xiaofeng; Wu, Xiaoxu; Liu, Jianing; Ji, Duoying; Du, Juan

2017-12-15

Dengue fever is one of the most serious vector-borne infectious diseases, especially in Guangzhou, China. Dengue viruses and their vectors Aedes albopictus are sensitive to climate change primarily in relation to weather factors. Previous research has mainly focused on identifying the relationship between climate factors and dengue cases, or developing dengue case models with some non-climate factors. However, there has been little research addressing the modeling and projection of dengue cases only from the perspective of climate change. This study considered this topic using long time series data (1998-2014). First, sensitive weather factors were identified through meta-analysis that included literature review screening, lagged analysis, and collinear analysis. Then, key factors that included monthly average temperature at a lag of two months, and monthly average relative humidity and monthly average precipitation at lags of three months were determined. Second, time series Poisson analysis was used with the generalized additive model approach to develop a dengue model based on key weather factors for January 1998 to December 2012. Data from January 2013 to July 2014 were used to validate that the model was reliable and reasonable. Finally, future weather data (January 2020 to December 2070) were input into the model to project the occurrence of dengue cases under different climate scenarios (RCP 2.6 and RCP 8.5). Longer time series analysis and scientifically selected weather variables were used to develop a dengue model to ensure reliability. The projections suggested that seasonal disease control (especially in summer and fall) and mitigation of greenhouse gas emissions could help reduce the incidence of dengue fever. The results of this study hope to provide a scientifically theoretical basis for the prevention and control of dengue fever in Guangzhou. Copyright © 2017 Elsevier B.V. All rights reserved.

Effects of climate change on residential infiltration and air pollution exposure.

PubMed

Ilacqua, Vito; Dawson, John; Breen, Michael; Singer, Sarany; Berg, Ashley

2017-01-01

Air exchange through infiltration is driven partly by indoor/outdoor temperature differences, and as climate change increases ambient temperatures, such differences could vary considerably even with small ambient temperature increments, altering patterns of exposures to both indoor and outdoor pollutants. We calculated changes in air fluxes through infiltration for prototypical detached homes in nine metropolitan areas in the United States (Atlanta, Boston, Chicago, Houston, Los Angeles, Minneapolis, New York, Phoenix, and Seattle) from 1970-2000 to 2040-2070. The Lawrence Berkeley National Laboratory model of infiltration was used in combination with climate data from eight regionally downscaled climate models from the North American Regional Climate Change Assessment Program. Averaged over all study locations, seasons, and climate models, air exchange through infiltration would decrease by ~5%. Localized increased infiltration is expected during the summer months, up to 20-30%. Seasonal and daily variability in infiltration are also expected to increase, particularly during the summer months. Diminished infiltration in future climate scenarios may be expected to increase exposure to indoor sources of air pollution, unless these ventilation reductions are otherwise compensated. Exposure to ambient air pollution, conversely, could be mitigated by lower infiltration, although peak exposure increases during summer months should be considered, as well as other mechanisms.

Spline models of contemporary, 2030, 2060, and 2090 climates for Mexico and their use in understanding climate-change impacts on the vegetation

Treesearch

Cuauhtemoc Saenz-Romero; Gerald E. Rehfeldt; Nicholas L. Crookston; Pierre Duval; Remi St-Amant; Jean Beaulieu; Bryce A. Richardson

2010-01-01

Spatial climate models were developed for Mexico and its periphery (southern USA, Cuba, Belize and Guatemala) for monthly normals (1961-1990) of average, maximum and minimum temperature and precipitation using thin plate smoothing splines of ANUSPLIN software on ca. 3,800 observations. The fit of the model was generally good: the signal was considerably less than one-...

Antarctica as a Model for the Human Exploration of Mars

DTIC Science & Technology

1987-07-19

that threaten the minds of men confined for several months with a small group of companions . Nevertheless, the strain exposed psychological weaknesses...continents. Winter temperatures average -60F and winds exceeding 150 miles per hour are not uncommon. Plant and animal life are largely confined to the... Immunoglobulin concentrations have also been found to undergo a significant decline during the Antarctic winter (Muchmore, Tatem, Worley, Shurley, and

The daily rhythm of body temperature, heart and respiratory rate in newborn dogs.

PubMed

Piccione, Giuseppe; Giudice, Elisabetta; Fazio, Francesco; Mortola, Jacopo P

2010-08-01

We asked whether, during the postnatal period, the daily patterns of body temperature (Tb), heart rate (HR) and breathing frequency (f) begin and develop in synchrony. To this end, measurements of HR, f and Tb were performed weekly, on two consecutive days, for the first two postnatal months on puppies of three breeds of dogs (Rottweiler, Cocker Spaniel and Carlino dogs) with very different birth weights and postnatal growth patterns. Ambient conditions and feeding habits were constant for all puppies. The results indicated that (1) the 24-h average Tb increased and average HR and f decreased with growth, (2) the daily rhythms in Tb were apparent by 4 weeks, irrespective of the puppy's growth pattern, (3) the daily rhythm of Tb in the puppy was not necessarily following that of the mother; in fact, it could anticipate it. (4) The daily rhythms in HR and f were not apparent for the whole study period. We conclude that in neonatal dogs the onset of the daily rhythms of Tb has no obvious relationship with body size or rate of growth and is not cued by the maternal Tb rhythm. The daily rhythms of HR and f do not appear before 2 months of age. Hence, they are not in synchrony with those of Tb.

Satellite monitoring of smoke from the Kuwait oil fires

NASA Astrophysics Data System (ADS)

Limaye, Sanjay S.; Ackerman, Steven A.; Fry, Patrick M.; Isa, Majeed; Ali, Habib; Ali, Ghulam; Wright, Allan; Rangno, Art

1992-09-01

The smoke from the oil fires in Kuwait was easily visible in observations from weather satellites in polar and geosynchronous orbits. A portable work station provided these data for planning the National Center for Atmospheric Research and University of Washington research aircraft flights out of Bahrain during the Kuwait Oil-Fire Smoke Experiment. Meteosat visible and infrared satellite observations indicate that the smoke often traveled southeast along the west shore of the Persian Gulf as far as Bahrain, at which point it typically turned west or continued south toward the Arabian coast. The smoke was difficult to detect from satellite observations as it moved over water and at large distances from the source during the night from infrared observations. Also notable among the daily satellite images were the frequent, intense dust storms that seemed to form in Syria and northern Iraq and transport dust southeastward over Kuwait, and often to northwestern Saudi Arabia. Clouds were virtually absent during the months of May and June within the first several hundred kilometers along the plume direction. Surface temperatures in Bahrain during April and August 1991 were lower than average by as much as 1°-3.2°C, and are significant compared to the climatological variability of average minimum and mean temperatures for the summer months.

Response to Comment on "Does the Earth Have an Adaptive Infrared Iris?"

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Chou, Ming-Dah; Lindzen, Richard S.; Hou, Arthur Y.

2001-01-01

In his comment on Lindzen et al., Harrison found that the amount of high-level clouds, A, and the sea-surface temperature beneath clouds, T, averaged over a large oceanic domain in the western Pacific have secular linear trends of opposite signs over a period of 20 months. He found that when the linear trends are subtracted from the data, the correlation between the residual A and T is much reduced. His estimates of the confidence levels for the correlation indicate, moreover, that this correlation is not statistically significant. The domain-averaged A and, to a lesser degree, T, have distinct intra-seasonal and seasonal variations. These variations are influenced by the large-scale wind and temperature distributions and by the seasonal variation of insolation. To separate the local effect from the effect of slowly changing large-scale conditions, rather than subtracting 20-month linear trends from the series, which has the potential to spuriously extrapolate intra-seasonal and seasonal variations to even longer time scales, we subtracted 30-day running means of A and T from each time series; in effect, the data were high-pass filtered. The number of points (days), N, is reduced by this process from the original value of 510 to 480.

Short and Long-Term Sunlight Radiation and Stroke Incidence

PubMed Central

McClure, Leslie A.; Judd, Suzanne E.; Howard, Virginia J.; Crosson, William L.; Al-Hamdan, Mohammad Z.; Wadley, Virginia G.; Peace, Fredrick; Kabagambe, Edmond K.

2012-01-01

OBJECTIVE Examine whether long and short-term sunlight radiation is related to stroke incidence. METHODS Fifteen-year residential histories merged with satellite, ground monitor, and model reanalysis data were used to determine sunlight radiation (insolation) and temperature exposure for a cohort of 16,606 stroke and coronary artery disease free black and white participants aged 45+ from the 48 contiguous United States. Fifteen, ten, five, two and one-year exposures were used to predict stroke incidence during follow-up in Cox proportional hazard models. Potential confounders and mediators were included during model-building. RESULTS Shorter exposure periods exhibited similar, but slightly stronger relationships than longer exposure periods. After adjustment for other covariates, the previous year’s monthly average insolation exposure below the median gave an HR=1.61 (95% CI: 1.15, 2.26) and the previous year’s highest compared to the second highest quartile of monthly average maximum temperature exposure gave an HR=1.92 (1.27, 2.92). INTERPRETATION These results indicate a relationship between lower levels of sunlight radiation and higher stroke incidence. The biological pathway of this relationship is not clear. Future research will show whether this finding stands, the pathway for this relationship, and if it is due to short or long-term exposures. PMID:23225379

Identification of climate-resilient integrated nutrient management practices for rice-rice cropping system--an empirical approach to uphold food security.

PubMed

Subash, N; Gangwar, B; Singh, Rajbir; Sikka, A K

2015-01-01

Yield datasets of long-term experiments on integrated nutrient management in rice-rice cropping systems were used to investigate the relationship of variability in rainfall, temperature, and integrated nutrient management (INM) practices in rice-rice cropping system in three different agroecological regions of India. Twelve treatments with different combinations of inorganic (chemical fertilizer) and organic (farmyard manure, green manure, and paddy straw) were compared with farmer's conventional practice. The intraseasonal variations in rice yields are largely driven by rainfall during kharif rice and by temperature during rabi rice. Half of the standard deviation from the average monthly as well as seasonal rainfall during kharif rice and 1 °C increase or decrease from the average maximum and minimum temperature during rabi rice has been taken as the classification of yield groups. The trends in the date of effective onset of monsoon indicate a 36-day delay during the 30-year period at Rajendranagar, which is statistically significant at 95 % confidence level. The mean annual maximum temperature shows an increasing trend in all the study sites. The length of monsoon also showed a shrinking trend in the rate of 40 days during the 30-year study period at Rajendranagar representing a semiarid region. At Bhubaneshwar, the application of 50 % recommended NPK through chemical fertilizers and 50 % N through green manure resulted in an overall average higher increase of 5.1 % in system productivity under both excess and deficit rainfall years and also during the years having seasonal mean maximum temperature ≥35 °C. However, at Jorhat, the application of 50 % recommended NPK through chemical fertilizers and 50 % N through straw resulted in an overall average higher increase of 7.4 % in system productivity, while at Rajendranagar, the application of 75 % NPK through chemical fertilizers and 25 % N through green manusre resulted in an overall average higher increase of 8.8 % in system productivity. This study highlights the adaptive capacity of different integrated nutrient management practices to rainfall and temperature variability under a rice-rice cropping system in humid, subhumid, and semiarid ecosystems.

A Bayesian approach for estimating under-reported dengue incidence with a focus on non-linear associations between climate and dengue in Dhaka, Bangladesh.

PubMed

Sharmin, Sifat; Glass, Kathryn; Viennet, Elvina; Harley, David

2018-04-01

Determining the relation between climate and dengue incidence is challenging due to under-reporting of disease and consequent biased incidence estimates. Non-linear associations between climate and incidence compound this. Here, we introduce a modelling framework to estimate dengue incidence from passive surveillance data while incorporating non-linear climate effects. We estimated the true number of cases per month using a Bayesian generalised linear model, developed in stages to adjust for under-reporting. A semi-parametric thin-plate spline approach was used to quantify non-linear climate effects. The approach was applied to data collected from the national dengue surveillance system of Bangladesh. The model estimated that only 2.8% (95% credible interval 2.7-2.8) of all cases in the capital Dhaka were reported through passive case reporting. The optimal mean monthly temperature for dengue transmission is 29℃ and average monthly rainfall above 15 mm decreases transmission. Our approach provides an estimate of true incidence and an understanding of the effects of temperature and rainfall on dengue transmission in Dhaka, Bangladesh.

Relationships between ten-year trends of tropospheric ozone and temperature over Taiwan.

PubMed

Hsu, Kuang-Jung

2007-03-01

The analyses of ten-year ozonesonde observations from 1993 till 2002, over Taipei, Taiwan show influences of climate change. Despite huge increases in its precursor emissions in this region, there were little variations in tropospheric ozone. Results indicate a warmer troposphere, a statistically insignificant rising tropopause, 79+/-206 m per decade, and decreasing tropopause temperature at -1.0+/-0.89 K per decade. The derived mean tropospheric ozone is 40.58+/-10.99 DU, and has a statistically insignificant small trend of -0.78+/-1.7 DU per decade. The derived ten-year vertical trends of temperature and ozone are inversely correlated with each other from the middle troposphere up to the lower stratosphere. The averaged monthly vertical temperature trends show a generally warmer middle troposphere. The tropospheric ozone monthly trend has small increases only in the lower troposphere during winter and spring. Strong decreases occur in summer, from the surface up into the stratosphere. For ozone variation, results suggest that influences of climate forcing are stronger than those from precursor increases. More frequent and/or intense convection in summer and other climate-induced effects may contribute to the less than expected ozone observed in the troposphere.

Effects of climate change on Salmonella infections.

PubMed

Akil, Luma; Ahmad, H Anwar; Reddy, Remata S

2014-12-01

Climate change and global warming have been reported to increase spread of foodborne pathogens. To understand these effects on Salmonella infections, modeling approaches such as regression analysis and neural network (NN) were used. Monthly data for Salmonella outbreaks in Mississippi (MS), Tennessee (TN), and Alabama (AL) were analyzed from 2002 to 2011 using analysis of variance and time series analysis. Meteorological data were collected and the correlation with salmonellosis was examined using regression analysis and NN. A seasonal trend in Salmonella infections was observed (p<0.001). Strong positive correlation was found between high temperature and Salmonella infections in MS and for the combined states (MS, TN, AL) models (R(2)=0.554; R(2)=0.415, respectively). NN models showed a strong effect of rise in temperature on the Salmonella outbreaks. In this study, an increase of 1°F was shown to result in four cases increase of Salmonella in MS. However, no correlation between monthly average precipitation rate and Salmonella infections was observed. There is consistent evidence that gastrointestinal infection with bacterial pathogens is positively correlated with ambient temperature, as warmer temperatures enable more rapid replication. Warming trends in the United States and specifically in the southern states may increase rates of Salmonella infections.

Connecting Atlantic temperature variability and biological cycling in two earth system models

NASA Astrophysics Data System (ADS)

Gnanadesikan, Anand; Dunne, John P.; Msadek, Rym

2014-05-01

Connections between the interdecadal variability in North Atlantic temperatures and biological cycling have been widely hypothesized. However, it is unclear whether such connections are due to small changes in basin-averaged temperatures indicated by the Atlantic Multidecadal Oscillation (AMO) Index, or whether both biological cycling and the AMO index are causally linked to changes in the Atlantic Meridional Overturning Circulation (AMOC). We examine interdecadal variability in the annual and month-by-month diatom biomass in two Earth System Models with the same formulations of atmospheric, land, sea ice and ocean biogeochemical dynamics but different formulations of ocean physics and thus different AMOC structures and variability. In the isopycnal-layered ESM2G, strong interdecadal changes in surface salinity associated with changes in AMOC produce spatially heterogeneous variability in convection, nutrient supply and thus diatom biomass. These changes also produce changes in ice cover, shortwave absorption and temperature and hence the AMO Index. Off West Greenland, these changes are consistent with observed changes in fisheries and support climate as a causal driver. In the level-coordinate ESM2M, nutrient supply is much higher and interdecadal changes in diatom biomass are much smaller in amplitude and not strongly linked to the AMO index.

Climate Assessment For 2001

NASA Astrophysics Data System (ADS)

Waple, A. M.; Lawrimore, J. H.; Lyon, B.; Halpert, M. S.; Gleason, K. L.; Menne, M. J.; Schnell, R. C.; Thiaw, W.; Wright, W. J.; Alexander, L.; Salinger, M. J.; Bell, G. D.; Higgins, R. W.; Stone, R. S.

2002-05-01

It is the twelfth year that the Climate Assessment has been written to summarize the state of the Earth's climate, and the second year that the National Climatic Data Center has taken the lead in its production. It is a cooperative effort that includes contributions from scientists around the country and the world. The long-running La Nina episode finally came to an end in 2001. The weak La Nina, which began in mid-1998 persisted through the first half of the year but gave way to neutral ENSO conditions for the latter half. Global temperatures in 2001 were 0.51C (0.92F) above the long-term (1880-2000) average, which places 2001 as the second warmest year on record. Land temperatures were 0.75C (1.35F) above average and ocean temperatures were 0.40C (0.72F) above the 1880-2000 mean. This ranks them as 2nd and 3rd warmest on record respectively. The Northern Hemisphere temperature continues to average near record levels in 2001 at 0.60C (1.08F) above the long-term average. The Southern Hemisphere also reflects the globally warmer conditions, with a positive anomaly of 0.43C (0.77F). Annual anomalies in excess of 1.0C (1.8F) were widespread across North America and much of Europe and the Middle East, while significantly cooler than average conditions were confined to Western Australia the Northeast and Northwest Pacific Ocean, and the far southeastern region of the Pacific, near coastal Chile. Although no hurricanes made landfall in the United States for the second consecutive year, it was nonetheless an extremely active Atlantic hurricane season, the fourth most active on record. Tropical Storm Allison became the costliest tropical storm on record when it caused around five billion US dollars worth of damage in southern and southeastern USA. The season was slow to start but quickly escalated in the last three months of the season and it was the first time in recorded history that three hurricanes have formed in the Atlantic in the month of November. Other notable events in 2001 include extreme cold and snow in Siberia during the 2000-2001 boreal winter; ongoing drought in the Middle East and central Asia; drought in Central America and Brazil; near-record flooding in central/eastern Europe; an extremely wet Austral spring in parts of Argentina; severe moisture deficits in parts of the USA; driest year on record in parts of western Australia.

Sea ice and oceanic processes on the Ross Sea continental shelf

NASA Technical Reports Server (NTRS)

Jacobs, S. S.; Comiso, J. C.

1989-01-01

The spatial and temporal variability of Antarctic sea ice concentrations on the Ross Sea continental shelf have been investigated in relation to oceanic and atmospheric forcing. Sea ice data were derived from Nimbus 7 scanning multichannel microwave radiometer (SMMR) brightness temperatures from 1979-1986. Ice cover over the shelf was persistently lower than above the adjacent deep ocean, averaging 86 percent during winter with little month-to-month of interannual variability. The large spring Ross Sea polynya on the western shelf results in a longer period of summer insolation, greater surface layer heat storage, and later ice formation in that region the following autumn.

One- to two-month oscillations in SSMI surface wind speed in western tropical Pacific Ocean

NASA Technical Reports Server (NTRS)

Collins, Michael L.; Stanford, John L.; Halpern, David

1994-01-01

The 10-m wind speed over the ocean can be estimated from microwave brightness temperature measurements recorded by the Special Sensor Microwave Imager (SSMI) instrument mounted on a polar-orbiting spacecraft. Four-year (1988-1991) time series of average daily 1 deg x 1 deg SSMI wind speeds were analyzed at selected sites in the western tropical Pacific Ocean. One- to two-month period wind speed oscillations with amplitudes statistically significant at the 95% confidence level were observed near Kanton, Eniwetok, Guam, and Truk. This is the first report of such an oscillation in SSMI wind speeds.

Evapotranspiration Estimation over Yangtze River Basin from GRACE satellite measurement and in situ data

NASA Astrophysics Data System (ADS)

Li, Qiong; Luo, Zhicai; Zhong, Bo; Wang, Haihong; Zhou, Zebing

2016-04-01

As the critical component of hydrologic cycle, evapotranspiration (ET) plays an important role in global water exchanges and energy flow across the hydrosphere, atmosphere and biosphere. Influenced by the Asian monsoon, the Yangtze River Basin (YRB) suffer from the several severe floods and droughts over the last decades due to the significant difference between temporal and spatial distribution terrestrial water storages. As an indispensable part, it is practically important to assessment ET in the YRB accompany with increased population and rapid economic and agriculture development. Average ET over the YRB is computed as the residual of terrestrial water budget using the Gravity Recovery and Climate Experiment (GRACE) satellite-based measurements and the ground-based observations. The GRACE-based ET were well coincidence with the ET from MODIS, with the correlation coefficient of 0.853, and the correlation coefficient is 0.696 while comparing with the ET ground-based observation. The mean monthly average of ET from these various estimates is 56.9 mm/month over the whole YRB, and peak between June and August. Monthly variations of ET reach a maximum in Wujiang with 69.11 mm/month and a minimum in Jinshajiang with 39.01 mm/month. Based on the correlation between ET and independent estimates of near-surface temperature and soil moisture, it is showed that as the temperature increased, the ET of the seven sub-catchment were rising except for the Poyang Lake and Donting Lake. And we also can infer that the midstream of YRB is significant correlated with ESON especially in the Hanjiang basin. The Surface Humidity Index over the YRB was gradually decreased and its variations in each sub-catchment showed a significant decreasing trend in Jinshajiang and Mingjiang. This research has important potential for use in large-scale water budget assessments and intercomparison studies. Acknowledgements: This research is supported by the National Natural Science Foundation of China (Grant No. 41504014; No.41474019).

The effect of cool water pack preparation on vaccine vial temperatures in refrigerators.

PubMed

Goldwood, Geneva; Diesburg, Steven

2018-01-02

Cool water packs are a useful alternative to ice packs for preventing unintentional freezing of vaccines during outreach in some situations. Current guidelines recommend the use of a separate refrigerator for cooling water packs from ambient temperatures to prevent possible heat degradation of adjacent vaccine vials. To investigate whether this additional equipment is necessary, we measured the temperatures that vaccine vials were exposed to when warm water packs were placed next to vials in a refrigerator. We then calculated the effect of repeated vial exposure to those temperatures on vaccine vial monitor status to estimate the impact to the vaccine. Vials were tested in a variety of configurations, varying the number and locations of vials and water packs in the refrigerator. The calculated average percentage life lost during a month of repeated warming ranged from 20.0% to 30.3% for a category 2 (least stable) vaccine vial monitor and from 3.8% to 6.0% for a category 7 (moderate stability) vaccine vial monitor, compared to 17.0% for category 2 vaccine vial monitors and 3.1% for category 7 vaccine vial monitors at a constant 5 °C. The number of vials, number of water packs, and locations of each impacted vial warming and therefore percentage life lost, but the vaccine vial monitor category had a higher impact on the average percentage life lost than any of the other parameters. The results suggest that damage to vaccines from repeated warming over the course of a month is not certain and that cooling water packs in a refrigerator where vaccines are being stored may be a useful practice if safe procedures are established. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

The effects of light, primary production, and temperature on bacterial production at Station ALOHA

NASA Astrophysics Data System (ADS)

Viviani, D. A.; Church, M. J.

2016-02-01

In the open oceans, bacterial metabolism is responsible for a large fraction of the movement of reduced carbon through these ecosystems. While broad meta-analyses suggest that factors such as temperature or primary production control rates of bacterial production over large geographic scales, to date little is known about how these factors influence variability in bacterial production in the open sea. Here we present two years of measurements of 3H-leucine incorporation, a proxy for bacterial production, at the open ocean field site of the Hawaii Ocean Time-series, Station ALOHA (22° 45'N, 158° 00'W). By examining 3H-leucine incorporation over monthly, daily, and hourly scales, this work provides insight into processes controlling bacterial growth in this persistently oligotrophic habitat. Rates of 3H-leucine incorporation were consistently 60% greater when measured in the light than in the dark, highlighting the importance of sunlight in fueling bacterial metabolism in this ecosystem. Over diel time scales, rates of 3H-leucine incorporation were quasi-sinusoidal, with rates in the light higher near midday, while rates in the dark were greatest after sunset. Depth-integrated (0 -125 m) rates of 3H-leucine incorporation in both light and dark were more variable ( 5- and 4-fold, respectively) than coincident measurements of primary production ( 2-fold). On average, rates of bacterial production averaged 2 and 4% of primary production (in the dark and light, respectively). At near-monthly time scales, rates of 3H-leucine incorporation in both light and dark were significantly related to temperature. Our results suggest that in the subtropical oligotrophic Pacific, bacterial production appears decoupled from primary production as a result of seasonal-scale variations in temperature and light.

Inverse relationship between ambient temperature and admissions for diabetic ketoacidosis and hyperglycemic hyperosmolar state: A 14-year time-series analysis.

PubMed

Lu, Chin-Li; Chang, Hsin-Hui; Chen, Hua-Fen; Ku, Li-Jung Elizabeth; Chang, Ya-Hui; Shen, Hsiu-Nien; Li, Chung-Yi

2016-09-01

This study aimed to investigate the association of admissions for diabetic ketoacidosis (DKA) and hyperglycemic hyperosmolar state (HHS) with ambient temperature and season, respectively in patients with diabetes mellitus (DM), after excluding known co-morbidities that predispose onset of acute hyperglycemia events. This was a time series correlation analysis based on medical claims of 40,084 and 33,947 episodes of admission for DKA and HHS, respectively over a 14-year period in Taiwan. These episodes were not accompanied by co-morbidities known to trigger incidence of DKA and HHS. Monthly temperature averaged from 19 meteorological stations across Taiwan was correlated with monthly rate of admission for DKA or HHS, respectively, using the 'seasonal Autoregressive Integrated Moving Average' (seasonal ARIMA) regression method. There was an inverse relationship between ambient temperature and rates of admission for DKA (β=-0.035, p<0.001) and HHS (β=-0.016, p<0.001), despite a clear decline in rates of DKA/HHS admission in the second half of the study period. We also noted that winter was significantly associated with increased rates of both DKA (β=0.364, p<0.001) and HHS (β=0.129, p<0.05) admissions, as compared with summer. On the other hand, fall was associated with a significantly lower rate of HHS admission (β=-0.016, p<0.05). Further stratified analyses according to sex and age yield essentially similar results. It is suggested that meteorological data can be used to raise the awareness of acute hyperglycemic complication risk for both patients with diabetes and clinicians to further avoid the occurrence of DKA and HHS. Copyright © 2016 Elsevier Ltd. All rights reserved.

Short-Term Forest Management Effects on a Long-Lived Ectotherm

PubMed Central

Currylow, Andrea F.; MacGowan, Brian J.; Williams, Rod N.

2012-01-01

Timber harvesting has been shown to have both positive and negative effects on forest dwelling species. We examined the immediate effects of timber harvests (clearcuts and group selection openings) on ectotherm behavior, using the eastern box turtle as a model. We monitored the movement and thermal ecology of 50 adult box turtles using radiotelemetry from May–October for two years prior to, and two years following scheduled timber harvests in the Central Hardwoods Region of the U.S. Annual home ranges (7.45 ha, 100% MCP) did not differ in any year or in response to timber harvests, but were 33% larger than previous estimates (range 0.47–187.67 ha). Distance of daily movements decreased post-harvest (from 22 m±1.2 m to 15 m±0.9 m) whereas thermal optima increased (from 23±1°C to 25±1°C). Microclimatic conditions varied by habitat type, but monthly average temperatures were warmer in harvested areas by as much as 13°C. Animals that used harvest openings were exposed to extreme monthly average temperatures (∼40°C). As a result, the animals made shorter and more frequent movements in and out of the harvest areas while maintaining 9% higher body temperatures. This experimental design coupled with radiotelemetry and behavioral observation of a wild ectotherm population prior to and in response to anthropogenic habitat alteration is the first of its kind. Our results indicate that even in a relatively contiguous forested landscape with small-scale timber harvests, there are local effects on the thermal ecology of ectotherms. Ultimately, the results of this research can benefit the conservation and management of temperature-dependent species by informing effects of timber management across landscapes amid changing climates. PMID:22792344

Utilizing Remote Sensing to Explore Hydrological and Climatic Factors of Visceral Leishmaniasis in South Sudan

NASA Astrophysics Data System (ADS)

Kruczkiewicz, A.; Sweeney, A.; Reid, C.; Seaman, J.; Abubakar, A.; Ritmeijer, K.; Jensen, K.; Schroeder, R.; McDonald, K. C.; Lessel, J.; Thomson, M. C.; Elnaiem, D.; Ceccato, P.

2014-12-01

Recent epidemics of visceral leishmaniasis (VL) in Sudan and South Sudan (locally known as Kala Azar) have caused an estimated 100,000 deaths and have renewed the impetus for defining the ecological boundaries of this vector borne disease. In the past 30 years outbreaks have occurred cyclically within this country, but recent shifts in endemicity have necessitated a more robust understanding of the drivers of the disease. Previous work (e.g. Gebre-Michael et al., 2004; Ashford & Thomson, 1991; Hoogstraal & Heyneman, 1969) has suggested that the primary biological vector in this region, the female sand fly Phlebotomus orientalis, exhibits sensitivities to environmental and climatic variables. Results of this study showed a relationship between precipitation and inundation during months of the transmission season (April-July) and the number of confirmed cases in the following September-January period. Particular months of the transmission season with below-average precipitation were better indicators of lagged reports of VL than others. During VL epidemics (2009, 2010, 2011) the month of June exhibited below average precipitation. The two largest epidemics (2010, 2011) were associated with years of below average precipitation in the month of April. Inundation during April-July (AMJJ) also exhibited a strong inverse relationship with reported VL cases in the following September- January (SONDJ). This relationship was best explored when comparing the VL case data of a specific medical center to the inundation anomalies. Results are typified by the Lankien Medical Center analysis where below average inundation during April displays an inverse relationship with VL cases in the following SONDJ. Drought may lead to below average inundation, which could allow for soils to maintain their fissures, thus maintaining the sand fly breeding habitat, resulting in a sustained breeding season for the sandflies (Quate, 1964). Above-average precipitation and inundation might have the inverse effect, eliminating their breeding sites within the soil. Land surface temperature (LST) Night, LST Day, and relative humidity did not show a particularly strong relationship with VL. Further research is needed, as these variables are known to exist across strong gradients within the northern states of South Sudan (Quate, 1964).

Reactions of Grape Rootstocks to Pratylenchus vulnus and Meloidogyne spp.

PubMed

Chitambar, J J; Raski, D J

1984-04-01

Five grape rootstocks were inoculated with 0, 100, 1,000, and 10,000 Pratylenchus vulnus. Dogridge and Saltcreek supported low average total numbers of P. vulnus, 136-705/pot, at 12 months after inoculation. Growth of both rootstocks was not affected. Harmony, Couderc 1613, and Ganzin 1 supported high average total numbers, 6-856 times the inoculum levels. Numbers in Harmony continued to increase at all levels but reduced root weight only at the 10,000 level after 12 months. Numbers in Couderc 1613 decreased by 15-30% after 12 months, and root weight was reduced at the 10,000 level. In Ganzin 1, total nematode numbers diminished after 12 months but were still at high levels; growth reduction was proportional to numbers of nematodes added. Meloidogyne incognita, M. javanica, and M. arenaria produced galls and egg masses in Harmony and Couderc 1613 only at 36 C. Galling in Ganzin 1 increased with increasing temperature. Galls in Ganzin 1 at 18 C supported mature females after 90 days. Harmony was resistant to M. incognita in single and concomitant inoculations of P. vulnus and M. incognita. At 250 days after inoculation, total numbers of P. vulnus increased above the inoculum level and the 150-day values; increase was greatest in P. vulnus added singly. Neither nematode species affected growth of Harmony.

Airborne fungi in child day care centers in Edirne City, Turkey.

PubMed

Aydogdu, Halide; Asan, Ahmet

2008-12-01

The purpose of this study was to determine the concentration, in terms of monthly and seasonal distribution and in relation to meteorological factors, of indoor and outdoor microfungi at selected sites in several child day care centers in the city of Edirne, Turkey. Samples were collected at one month intervals over a period of 12 months between January-December 2004, by exposing petri plates containing Peptone Dextrose Agar with Rose-Bengal and Streptomycin medium to the air for 10-15 min. A total of 2,071 microfungal colonies were counted on 192 petri plates. Thirty microfungal genera (Acremonium, Alternaria, Arthrinium, Aspergillus, Bahusakala, Beauveria, Ceuthospora, Chaetomium, Cladosporium, Curvularia, Drechslera, Epicoccum, Eurotium, Fusarium, Mycotypha, Myrotechium, Paecilomyces, Penicillium, Pestalotiopsis, Phoma, Ramichloridium, Rhizopus, Scopulariopsis, Stachybotrys, Stemphylium, Torula, Trichoderma, Trichothecium, Ulocladium, Verticillium) and 75 microfungal species were isolated from the air indoor and outdoor of the day care centers. The dominant microfungal genera were Cladosporium, Penicillium and Alternaria (44.11%, 18.94%, 14.67% of the total respectively), while the genus with the most species richness was Penicillium (26 species). Alternaria, Cladosporium, Penicillium and non-sporulating microfungi were found every month. Cladosporium was the dominant genus in both indoor and outdoor air. Although the predominant genus was the same in both indoor and outdoor air, Cladosporium was followed by Penicillium, Alternaria and Aspergillus genera in indoor air and by Alternaria, Penicillium and Aspergillus genera in outdoor air. While a positive correlation was found between the concentration of monthly outdoor microfungi and monthly average temperature, a negative correlation was found between the concentration of monthly outdoor microfungi and monthly average wind velocity. Also, some relationships were found between the monthly concentrations of the most predominant microfungal genera (Cladosporium, Penicillium and Alternaria) and various meteorological factors.

Improving representation of riparian vegetation shading in a regional stream temperature model using LiDAR data.

PubMed

Loicq, Pierre; Moatar, Florentina; Jullian, Yann; Dugdale, Stephen J; Hannah, David M

2018-05-15

Modelling river temperature at the catchment scale is needed to understand how aquatic communities may adapt to current and projected climate change. In small and medium rivers, riparian vegetation can greatly reduce maximum water temperature by providing shade. It is thus important that river temperature models are able to correctly characterise the impact of this riparian shading. In this study, we describe the use of a spatially-explicit method using LiDAR-derived data for computing the riparian shading on direct and diffuse solar radiation. The resulting data are used in the T-NET one-dimensional stream temperature model to simulate water temperature from August 2007 to July 2014 for 270km of the Loir River, an indirect tributary of the Loire River (France). Validation is achieved with 4 temperature monitoring stations spread along the Loir River. The vegetation characterised with the LiDAR approach provides a cooling effect on maximum daily temperature (T max ) ranging from 3.0°C (upstream) to 1.3°C (downstream) in late August 2009. Compared to two other riparian shading routines that are less computationally-intensive, the use of our LiDAR-based methodology improves the bias of T max simulated by the T-NET model by 0.62°C on average between April and September. However, difference between the shading routines reaches up to 2°C (monthly average) at the upstream-most station. Standard deviation of errors on T max is not improved. Computing the impact of riparian vegetation at the hourly timescale using reach-averaged parameters provides results close to the LiDAR-based approach, as long as it is supplied with accurate vegetation cover data. Improving the quality of riparian vegetation data should therefore be a priority to increase the accuracy of stream temperature modelling at the regional scale. Copyright © 2017 Elsevier B.V. All rights reserved.

A century of climate and ecosystem change in Western Montana: What do temperature trends portend?

USGS Publications Warehouse

Pederson, G.T.; Graumlich, L.J.; Fagre, D.B.; Kipfer, T.; Muhlfeld, C.C.

2010-01-01

The physical science linking human-induced increases in greenhouse gasses to the warming of the global climate system is well established, but the implications of this warming for ecosystem processes and services at regional scales is still poorly understood. Thus, the objectives of this work were to: (1) describe rates of change in temperature averages and extremes for western Montana, a region containing sensitive resources and ecosystems, (2) investigate associations between Montana temperature change to hemispheric and global temperature change, (3) provide climate analysis tools for land and resource managers responsible for researching and maintaining renewable resources, habitat, and threatened/endangered species and (4) integrate our findings into a more general assessment of climate impacts on ecosystem processes and services over the past century. Over 100 years of daily and monthly temperature data collected in western Montana, USA are analyzed for long-term changes in seasonal averages and daily extremes. In particular, variability and trends in temperature above or below ecologically and socially meaningful thresholds within this region (e.g., -17.8??C (0??F), 0??C (32??F), and 32.2??C (90??F)) are assessed. The daily temperature time series reveal extremely cold days (??? -17.8??C) terminate on average 20 days earlier and decline in number, whereas extremely hot days (???32??C) show a three-fold increase in number and a 24-day increase in seasonal window during which they occur. Results show that regionally important thresholds have been exceeded, the most recent of which include the timing and number of the 0??C freeze/thaw temperatures during spring and fall. Finally, we close with a discussion on the implications for Montana's ecosystems. Special attention is given to critical processes that respond non-linearly as temperatures exceed critical thresholds, and have positive feedbacks that amplify the changes. ?? Springer Science + Business Media B.V. 2009.

Rectal Diclofenac Versus Rectal Paracetamol: Comparison of Antipyretic Effectiveness in Children.

PubMed

Sharif, Mohammad Reza; Haji Rezaei, Mostafa; Aalinezhad, Marzieh; Sarami, Golbahareh; Rangraz, Masoud

2016-01-01

Fever is the most common complaint in pediatric medicine and its treatment is recommended in some situations. Paracetamol is the most common antipyretic drug, which has serious side effects such as toxicity along with its positive effects. Diclofenac is one of the strongest non-steroidal anti-inflammatory (NSAID) drugs, which has received little attention as an antipyretic drug. This study was designed to compare the antipyretic effectiveness of the rectal form of Paracetamol and Diclofenac. This double-blind controlled clinical trial was conducted on 80 children aged six months to six years old. One group was treated with rectal Paracetamol suppositories at 15 mg/kg dose and the other group received Diclofenac at 1 mg/kg by rectal administration (n = 40). Rectal temperature was measured before and one hour after the intervention. Temperature changes in the two groups were compared. The average rectal temperature in the Paracetamol group was 39.6 ± 1.13°C, and 39.82 ± 1.07°C in the Diclofenac group (P = 0.37). The average rectal temperature, one hour after the intervention, in the Paracetamol and the Diclofenac group was 38.39 ± 0.89°C and 38.95 ± 1.09°C, respectively (P = 0.02). Average temperature changes were 0.65 ± 0.17°C in the Paracetamol group and 1.73 ± 0.69°C in the Diclofenac group (P < 0.001). In the first one hour, Diclofenac suppository is able to control the fever more efficient than Paracetamol suppositories.

Reproducibility of Clathromorphum compactum coralline algal Mg/Ca ratios and comparison to high-resolution sea surface temperature data

NASA Astrophysics Data System (ADS)

Hetzinger, S.; Halfar, J.; Kronz, A.; Simon, K.; Adey, W. H.; Steneck, R. S.

2018-01-01

The potential of crustose coralline algae as high-resolution archives of past ocean variability in mid- to high-latitudes has only recently been recognized. Few comparisons of coralline algal proxies, such as temperature-dependent algal magnesium to calcium (Mg/Ca) ratios, with in situ-measured surface ocean data exist, even rarer are well replicated records from individual sites. We present Mg/Ca records from nine coralline algal specimens (Clathromorphum compactum) from a single site in the Gulf of Maine, North Atlantic. Sections from algal mounds were analyzed using Laser Ablation-Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS) yielding individual Mg/Ca records of up to 30 years in length. We first test intra- and intersample signal replication and show that algal Mg/Ca ratios are reproducible along several transects within individual sample specimens and between different samples from the same study site. In addition, LA-ICP-MS-derived Mg/Ca ratios are compared to electron microprobe (EMP) analyzed data on the longest-lived specimens and were found to be statistically commensurable. Second, we evaluate whether relationships between algal-based SST reconstructions and in situ temperature data can be improved by averaging Mg/Ca records from multiple algal specimens (intersample averages). We found that intersample averages yield stronger relationships to sea surface temperature (SST) data than Mg/Ca records derived from individual samples alone. Thus, Mg/Ca-based paleotemperature reconstructions from coralline algae can benefit from using multiple samples per site, and can expand temperature proxy precision from seasonal to monthly.

Study of the lower stratospheric thermal structure and total ozone from Nimbus-4 IRIS

NASA Technical Reports Server (NTRS)

Prabhakara, C.

1976-01-01

The global distribution of temperature in the stratosphere from 100 to 10 mbar and the total ozone in the atmosphere are remotely sensed from the Nimbus-4 IRIS measurements for a period of about one year. The temperature and ozone data are presented in the form of monthly mean global maps. The standard deviations of temperature and ozone with respect to zonal averages are calculated. The mean and the variable state of the stratosphere are discussed with the help of these observations. The lower stratosphere in the tropical regions reveals a significant wave number one pattern in the circulation. The Arctic and Antarctic stratospheric winter circulation regimes display a different behavior apparently due to the ocean and orographic differences.

Climatological observations in the Philip Smith Mountains of the North Slope, Alaska: Climatology report series No. 2

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

Kelley, J.J.; Foster, D.

1986-10-01

Climatological data from an automatic weather station (Aanderaa) located at the Alyeska Pipeline Service Company Material Site 117 (MS-117) are presented in this report. Data are listed for hourly averages daily. The data report covers the period 1 August 1985 to 31 May 1986. Observations in this report include wind speed and direction, temperature and barometric pressure. Descriptions of the instrumentation and estimates of reliability are included in the test. Various analyses of the data are presented in the appendices. A summary of the wind and temperature regime is presented through displays of cumulative frequencies of hourly temperatures and windmore » speeds for the 12-month period, June 1985 to May 1986.« less

Effects of vertical distribution of water vapor and temperature on total column water vapor retrieval error

NASA Technical Reports Server (NTRS)

Sun, Jielun

1993-01-01

Results are presented of a test of the physically based total column water vapor retrieval algorithm of Wentz (1992) for sensitivity to realistic vertical distributions of temperature and water vapor. The ECMWF monthly averaged temperature and humidity fields are used to simulate the spatial pattern of systematic retrieval error of total column water vapor due to this sensitivity. The estimated systematic error is within 0.1 g/sq cm over about 70 percent of the global ocean area; systematic errors greater than 0.3 g/sq cm are expected to exist only over a few well-defined regions, about 3 percent of the global oceans, assuming that the global mean value is unbiased.

Spatial and temporal variability in the trans-Pacific migration of Pacific bluefin tuna (Thunnus orientalis) revealed by archival tags

NASA Astrophysics Data System (ADS)

Fujioka, Ko; Fukuda, Hiromu; Tei, Yaoki; Okamoto, Suguru; Kiyofuji, Hidetada; Furukawa, Seishiro; Takagi, Junichi; Estess, Ethan; Farwell, Charles J.; Fuller, Daniel W.; Suzuki, Nobuaki; Ohshimo, Seiji; Kitagawa, Takashi

2018-03-01

Archival electronic tags were internally implanted in 713 age-0 Pacific bluefin tuna (PBF) caught in their nursery waters off the southern coast of Japan and in the East China Sea over an extended study period (1995-2015) to clarify the spatial and temporal variability of their trans-Pacific migration. Two hundred twenty-five of these tagged tuna were recaptured by fisheries (31.6%), and we successfully retrieved tag data from 14 of 21 individuals recovered in the Eastern pacific. Furthermore, one archival tag recovered in the Western Pacific revealed that the individual had performed a trans-Pacific migration, so in total 21 tagged PBF were shown to have migrated to the Eastern Pacific (2.9% of the total tags released). We successfully downloaded data from 15 of these 21 archival tags, which revealed that some age-1 PBF migrate rapidly (123.9 ± 82.8 km day-1) and directly from waters offshore of Japan to the eastern Pacific (160.0°E to 130.0°W), a journey that takes an average of 2.5 months (ranging from 1.2 to 5.5 months) through relatively cool waters (14.7 ± 2.0 °C). All juvenile PBF began their trans-Pacific migration shortly after exposure to cooler water temperatures (<14 °C), suggesting that sustained residence in lower water temperatures presents a physiological challenge for this age class. Three patterns were identified in the timing of the departure of juvenile PBF from the western Pacific: departing 12-14 months post-hatch (N = 7) in early summer (May-July), departing 17-19 months post-hatch (N = 7) in late autumn (October-December), and departing 21 months post-hatch (N = 1) in late winter (February). The PBF tagged along the southern coast of Japan (SCJ) arrived in the eastern Pacific earlier than those tagged in the East China Sea (ECS), most likely due to the shorter travel distance. Additionally, the PBF that began their trans-Pacific migration in the earlier period remained in an offshore foraging zone (the Kuroshio-Oyashio transition region) for shorter periods (2.8 months on average) and at lower latitudes (35.0°N) during the spring, while the PBF that delayed their migration spent more time (6.7 months on average) in the productive waters between 35.0 and 45.0°N during the spring-autumn months. The variability in the departure timing of the trans-Pacific migration of age-1 PBF may be related to geographic differences between nursery areas in addition to oceanographic conditions and foraging opportunities encountered by the tuna in the offshore waters of Japan during their first year.

Herbarium specimens can reveal impacts of climate change on plant phenology; a review of methods and applications.

PubMed

Jones, Casey A; Daehler, Curtis C

2018-01-01

Studies in plant phenology have provided some of the best evidence for large-scale responses to recent climate change. Over the last decade, more than thirty studies have used herbarium specimens to analyze changes in flowering phenology over time, although studies from tropical environments are thus far generally lacking. In this review, we summarize the approaches and applications used to date. Reproductive plant phenology has primarily been analyzed using two summary statistics, the mean flowering day of year and first-flowering day of year, but mean flowering day has proven to be a more robust statistic. Two types of regression models have been applied to test for associations between flowering, temperature and time: flowering day regressed on year and flowering day regressed on temperature. Most studies analyzed the effect of temperature by averaging temperatures from three months prior to the date of flowering. On average, published studies have used 55 herbarium specimens per species to characterize changes in phenology over time, but in many cases fewer specimens were used. Geospatial grid data are increasingly being used for determining average temperatures at herbarium specimen collection locations, allowing testing for finer scale correspondence between phenology and climate. Multiple studies have shown that inferences from herbarium specimen data are comparable to findings from systematically collected field observations. Understanding phenological responses to climate change is a crucial step towards recognizing implications for higher trophic levels and large-scale ecosystem processes. As herbaria are increasingly being digitized worldwide, more data are becoming available for future studies. As temperatures continue to rise globally, herbarium specimens are expected to become an increasingly important resource for analyzing plant responses to climate change.

Long-term patterns of air temperatures, daily temperature range, precipitation, grass-reference evapotranspiration and aridity index in the USA Great Plains: Part I. Spatial trends

NASA Astrophysics Data System (ADS)

Kukal, M.; Irmak, S.

2016-11-01

Due to their substantial spatio-temporal behavior, long-term quantification and analyses of important hydrological variables are essential for practical applications in water resources planning, evaluating the water use of agricultural crop production and quantifying crop evapotranspiration patterns and irrigation management vs. hydrologic balance relationships. Observed data at over 800 sites across the Great Plains of USA, comprising of 9 states and 2,307,410 km2 of surface area, which is about 30% of the terrestrial area of the USA, were used to quantify and map large-scale and long-term (1968-2013) spatial trends of air temperatures, daily temperature range (DTR), precipitation, grass-reference evapotranspiration (ETo) and aridity index (AI) at monthly, growing season and annual time steps. Air temperatures had a strong north to south increasing trend, with annual average varying from -1 to 24 °C, and growing season average temperature varying from 8 to 30 °C. DTR gradually decreased from western to eastern parts of the region, with a regional annual and growing season averages of 14.25 °C and 14.79 °C, respectively. Precipitation had a gradual shift towards higher magnitudes from west to east, with the average annual and growing season (May-September) precipitation ranging from 163 to 1486 mm and from 98 to 746 mm, respectively. ETo had a southwest-northeast decreasing trend, with regional annual and growing season averages of 1297 mm and 823 mm, respectively. AI increased from west to east, indicating higher humidity (less arid) towards the east, with regional annual and growing season averages of 0.49 and 0.44, respectively. The spatial datasets and maps for these important climate variables can serve as valuable background for climate change and hydrologic studies in the Great Plains region. Through identification of priority areas from the developed maps, efforts of the concerned personnel and agencies and resources can be diverted towards development of holistic strategies to address water supply and demand challenges under changing climate. These strategies can consist of, but not limited to, advancing water, crop and soil management, and genetic improvements and their relationships with the climatic variables on large scales.

Flowering phenological changes in relation to climate change in Hungary

NASA Astrophysics Data System (ADS)

Szabó, Barbara; Vincze, Enikő; Czúcz, Bálint

2016-09-01

The importance of long-term plant phenological time series is growing in monitoring of climate change impacts worldwide. To detect trends and assess possible influences of climate in Hungary, we studied flowering phenological records for six species ( Convallaria majalis, Taraxacum officinale, Syringa vulgaris, Sambucus nigra, Robinia pseudoacacia, Tilia cordata) based on phenological observations from the Hungarian Meteorological Service recorded between 1952 and 2000. Altogether, four from the six examined plant species showed significant advancement in flowering onset with an average rate of 1.9-4.4 days per decade. We found that it was the mean temperature of the 2-3 months immediately preceding the mean flowering date, which most prominently influenced its timing. In addition, several species were affected by the late winter (January-March) values of the North Atlantic Oscillation (NAO) index. We also detected sporadic long-term effects for all species, where climatic variables from earlier months exerted influence with varying sign and little recognizable pattern: the temperature/NAO of the previous autumn (August-December) seems to influence Convallaria, and the temperature/precipitation of the previous spring (February-April) has some effect on Tilia flowering.

Internal variability in European summer temperatures at 1.5 °C and 2 °C of global warming

NASA Astrophysics Data System (ADS)

Suarez-Gutierrez, Laura; Li, Chao; Müller, Wolfgang A.; Marotzke, Jochem

2018-06-01

We use the 100-member Grand Ensemble with the climate model MPI-ESM to evaluate the controllability of mean and extreme European summer temperatures with the global mean temperature targets in the Paris Agreement. We find that European summer temperatures at 2 °C of global warming are on average 1 °C higher than at 1.5 °C of global warming with respect to pre-industrial levels. In a 2 °C warmer world, one out of every two European summer months would be warmer than ever observed in our current climate. Daily maximum temperature anomalies for extreme events with return periods of up to 500 years reach return levels of 7 °C at 2 °C of global warming and 5.5 °C at 1.5 °C of global warming. The largest differences in return levels for shorter return periods of 20 years are over southern Europe, where we find the highest mean temperature increase. In contrast, for events with return periods of over 100 years these differences are largest over central Europe, where we find the largest changes in temperature variability. However, due to the large effect of internal variability, only four out of every ten summer months in a 2 °C warmer world present mean temperatures that could be distinguishable from those in a 1.5 °C world. The distinguishability between the two climates is largest over southern Europe, while decreasing to around 10% distinguishable months over eastern Europe. Furthermore, we find that 10% of the most extreme and severe summer maximum temperatures in a 2 °C world could be avoided by limiting global warming to 1.5 °C.

The Effect of Ocean Currents on Sea Surface Temperature Anomalies

NASA Technical Reports Server (NTRS)

Stammer, Detlef; Leeuwenburgh, Olwijn

2000-01-01

We investigate regional and global-scale correlations between observed anomalies in sea surface temperature and height. A strong agreement between the two fields is found over a broad range of latitudes for different ocean basins. Both time-longitude plots and wavenumber-frequency spectra suggest an advective forcing of SST anomalies by a first-mode baroclinic wave field on spatial scales down to 400 km and time scales as short as 1 month. Even though the magnitude of the mean background temperature gradient is determining for the effectiveness of the forcing, there is no obvious seasonality that can be detected in the amplitudes of SST anomalies. Instead, individual wave signatures in the SST can in some cases be followed over periods of two years. The phase relationship between SST and SSH anomalies is dependent upon frequency and wavenumber and displays a clear decrease of the phase lag toward higher latitudes where the two fields come into phase at low frequencies. Estimates of the damping coefficient are larger than generally obtained for a purely atmospheric feedback. From a global frequency spectrum a damping time scale of 2-3 month was found. Regionally results are very variable and range from 1 month near strong currents to 10 month at low latitudes and in the sub-polar North Atlantic. Strong agreement is found between the first global EOF modes of 10 day averaged and spatially smoothed SST and SSH grids. The accompanying time series display low frequency oscillations in both fields.

Spatial Patterns and Socioecological Drivers of Dengue Fever Transmission in Queensland, Australia

PubMed Central

Clements, Archie; Williams, Gail; Tong, Shilu; Mengersen, Kerrie

2011-01-01

Background: Understanding how socioecological factors affect the transmission of dengue fever (DF) may help to develop an early warning system of DF. Objectives: We examined the impact of socioecological factors on the transmission of DF and assessed potential predictors of locally acquired and overseas-acquired cases of DF in Queensland, Australia. Methods: We obtained data from Queensland Health on the numbers of notified DF cases by local government area (LGA) in Queensland for the period 1 January 2002 through 31 December 2005. Data on weather and the socioeconomic index were obtained from the Australian Bureau of Meteorology and the Australian Bureau of Statistics, respectively. A Bayesian spatial conditional autoregressive model was fitted at the LGA level to quantify the relationship between DF and socioecological factors. Results: Our estimates suggest an increase in locally acquired DF of 6% [95% credible interval (CI): 2%, 11%] and 61% (95% CI: 2%, 241%) in association with a 1-mm increase in average monthly rainfall and a 1°C increase in average monthly maximum temperature between 2002 and 2005, respectively. By contrast, overseas-acquired DF cases increased by 1% (95% CI: 0%, 3%) and by 1% (95% CI: 0%, 2%) in association with a 1-mm increase in average monthly rainfall and a 1-unit increase in average socioeconomic index, respectively. Conclusions: Socioecological factors appear to influence the transmission of DF in Queensland, but the drivers of locally acquired and overseas-acquired DF may differ. DF risk is spatially clustered with different patterns for locally acquired and overseas-acquired cases. PMID:22015625

Skill of real-time operational forecasts with the APCC multi-model ensemble prediction system during the period 2008-2015

NASA Astrophysics Data System (ADS)

Min, Young-Mi; Kryjov, Vladimir N.; Oh, Sang Myeong; Lee, Hyun-Ju

2017-12-01

This paper assesses the real-time 1-month lead forecasts of 3-month (seasonal) mean temperature and precipitation on a monthly basis issued by the Asia-Pacific Economic Cooperation Climate Center (APCC) for 2008-2015 (8 years, 96 forecasts). It shows the current level of the APCC operational multi-model prediction system performance. The skill of the APCC forecasts strongly depends on seasons and regions that it is higher for the tropics and boreal winter than for the extratropics and boreal summer due to direct effects and remote teleconnections from boundary forcings. There is a negative relationship between the forecast skill and its interseasonal variability for both variables and the forecast skill for precipitation is more seasonally and regionally dependent than that for temperature. The APCC operational probabilistic forecasts during this period show a cold bias (underforecasting of above-normal temperature and overforecasting of below-normal temperature) underestimating a long-term warming trend. A wet bias is evident for precipitation, particularly in the extratropical regions. The skill of both temperature and precipitation forecasts strongly depends upon the ENSO strength. Particularly, the highest forecast skill noted in 2015/2016 boreal winter is associated with the strong forcing of an extreme El Nino event. Meanwhile, the relatively low skill is associated with the transition and/or continuous ENSO-neutral phases of 2012-2014. As a result the skill of real-time forecast for boreal winter season is higher than that of hindcast. However, on average, the level of forecast skill during the period 2008-2015 is similar to that of hindcast.

Impacts of Future Climate Change on Ukraine Transportation System

NASA Astrophysics Data System (ADS)

Khomenko, Inna

2016-04-01

Transportation not only affects climate, but are strongly influenced with the climate conditions, and key hubs of the transportation sector are cities. Transportation decision makers have an opportunity now to prepare for projected climate changes owing to development of emission scenarios. In the study impact of climate change on operation of road transport along highways are analyzed on the basis of RCP 4.5 and RCP 8.5 scenarios. Data contains series of daily mean and maximum 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 8 cities (Dnipropetrovsk, Khmelnytskyi, Kirovohrad, Kharkiv, Odesa, Ternopil, Vinnytsia and Voznesensk) situated down the highways. The highways of 'Odesa-Voznesensk-Dnipropetrovsk-Kharkiv' and 'Dnipropetrovsk-Kirovohrad-Vinnytsia-Khmelnytskyi-Ternopil' are considered. The first highway goes across the Black Sea Lowland, the Dnieper Upland and Dnieper Lowland, the other passes through the Dnieper and Volhynia-Podillia Uplands. The both highways are situated in steppe and forest-steppe native zones. For both scenarios, significant climate warming is registered; it is revealed in significant increase of average monthly and yearly temperature by 2-3°C in all cities in questions, and also, in considerable increment of frequency of days with maximum temperature higher than +30 and 35°C, except Kharkiv, where decrease number of days with such temperatures is observed. On the contrary, number of days with daily mean temperature being equal to or below 0°C decreases in the south of steppe, is constant in the north of steppe and increases in the forest-steppe native zone. Extreme negative temperatures don't occur in the steppe zone, but takes place in the forest-steppe zone. Results obtained shows that road surface must hold in extreme maximum temperature, and in the forest-steppe zone hazards of extreme negative temperatures must be considered. Frequency of winter events that make road surface worse such as glaze-clear ice, frozen snow that had initially melted on a warm road surface, ice and snow slippery coats etc., are high enough, especially in the forest-steppe zone. In the Black Sea Lowland among winter events the frozen snow that had initially melted on a warm road surface is most commonly observed, that is connected with high occurrence of the thaws. Because of increase in frequency of shower precipitation in all cities wet road surface is observed most frequently, especially in May and June; it must be taken into account for construction of roads, too. Monthly mean wind speed shows that in Odesa and Kharkiv significant increase in average monthly and yearly wind speeds are observed, by 0,5-1 m/s in comparison with the period of 1961 to 1990. On the contrary, in Dnipropetrovsk, wind speed decreases by 0,7 m/s. Frequency distribution of maximum wind speed shows that high wind speeds are more frequent in the winter months.

Assessment of an aural infrared sensor for body temperature measurement in children.

PubMed

Rhoads, F A; Grandner, J

1990-02-01

A newly marketed device measures body temperature using an ear probe that detects infrared radiation from the tympanic membrane. It is simple to use and gives a reading in 1-2 seconds. Its accuracy was evaluated in a group of children, aged 1 month through 10 years, by comparing it with either rectal (n = 65), or oral (n = 48) temperatures obtained with a standard electronic thermometer, IVAC (San Diego, CA). The average elapsed time between readings was 11 minutes. Overall, 60 rectal and 40 oral temperatures (88.5%) were higher with IVAC than with the aural sensor. The difference ranged from -0.7 degrees C to +2.5 degrees C. The correlations between the infrared ear-probe values and the rectal and oral temperature readings were 0.77 and 0.75, respectively. Because the average reading using the aural sensor was lower than that using the IVAC, the sensitivity of the aural sensor for detecting clinically important levels of fever was low. None of seven patients with a rectal temperature of 39 degrees C or more and only 7 of 27 with a rectal temperature of 38 degrees C or more were identified by the aural sensor as having temperatures above these cutoff levels. Similarly, none of three patients with an oral temperature of 39 degrees C or more and only three of eight with an oral temperature of 38 degrees C or more were identified correctly by the aural sensor. The authors conclude that the aural sensor is unsatisfactory for detecting clinically significant fevers in a pediatric outpatient setting.

Comparison of Ozone Retrievals from the Pandora Spectrometer System and Dobson Spectrophotometer in Boulder, Colorado

NASA Technical Reports Server (NTRS)

Herman, J.; Evans, R.; Cede, A.; Abuhassan, N.; Petropavlovskikh, I.; McConville, G.

2015-01-01

A comparison of retrieved total column ozone (TCO) amounts between the Pandora #34 spectrometer system and the Dobson #061 spectrophotometer from direct-sun observations was performed on the roof of the Boulder, Colorado, NOAA building. This paper, part of an ongoing study, covers a 1-year period starting on 17 December 2013. Both the standard Dobson and Pandora TCO retrievals required a correction, TCO(sub corr) = TCO (1 + C(T)), using a monthly varying effective ozone temperature, T(sub E), derived from a temperature and ozone profile climatology. The correction is used to remove a seasonal difference caused by using a fixed temperature in each retrieval algorithm. The respective corrections C(T(sub E)) are C(sub Pandora) = 0.00333(T(sub E) - 225) and C(sub Dobson) = -0.0013(T(sub E) - 226.7) per degree K. After the applied corrections removed most of the seasonal retrieval dependence on ozone temperature, TCO agreement between the instruments was within 1% for clear-sky conditions. For clear-sky observations, both co-located instruments tracked the day-to-day variation in total column ozone amounts with a correlation of r(exp 2) = 0.97 and an average offset of 1.1 +/- 5.8 DU. In addition, the Pandora TCO data showed 0.3% annual average agreement with satellite overpass data from AURA/OMI (Ozone Monitoring Instrument) and 1% annual average offset with Suomi-NPP/OMPS (Suomi National Polar-orbiting Partnership, the nadir viewing portion of the Ozone Mapper Profiler Suite).

Comparison of ozone retrievals from the Pandora spectrometer system and Dobson spectrophotometer in Boulder, Colorado

NASA Astrophysics Data System (ADS)

Herman, J.; Evans, R.; Cede, A.; Abuhassan, N.; Petropavlovskikh, I.; McConville, G.

2015-08-01

A comparison of retrieved total column ozone (TCO) amounts between the Pandora #34 spectrometer system and the Dobson #061 spectrophotometer from direct-sun observations was performed on the roof of the Boulder, Colorado, NOAA building. This paper, part of an ongoing study, covers a 1-year period starting on 17 December 2013. Both the standard Dobson and Pandora TCO retrievals required a correction, TCOcorr = TCO (1 + C(T)), using a monthly varying effective ozone temperature, TE, derived from a temperature and ozone profile climatology. The correction is used to remove a seasonal difference caused by using a fixed temperature in each retrieval algorithm. The respective corrections C(TE) are CPandora = 0.00333(TE-225) and CDobson = -0.0013(TE-226.7) per degree K. After the applied corrections removed most of the seasonal retrieval dependence on ozone temperature, TCO agreement between the instruments was within 1 % for clear-sky conditions. For clear-sky observations, both co-located instruments tracked the day-to-day variation in total column ozone amounts with a correlation of r2 = 0.97 and an average offset of 1.1 ± 5.8 DU. In addition, the Pandora TCO data showed 0.3 % annual average agreement with satellite overpass data from AURA/OMI (Ozone Monitoring Instrument) and 1 % annual average offset with Suomi-NPP/OMPS (Suomi National Polar-orbiting Partnership, the nadir viewing portion of the Ozone Mapper Profiler Suite).

Polymerase chain reaction amplification of DNA from aged blood stains: quantitative evaluation of the "suitability for purpose" of four filter papers as archival media.

PubMed

Kline, Margaret C; Duewer, David L; Redman, Janette W; Butler, John M; Boyer, David A

2002-04-15

In collaboration with the Armed Forces Institute of Pathology's Department of Defense DNA Registry, the National Institute of Standards and Technology recently evaluated the performance of a short tandem repeat multiplex with dried whole blood stains on four different commercially available identification card matrixes. DNA from 70 stains that had been stored for 19 months at ambient temperature was extracted or directly amplified and then processed using routine methods. All four storage media provided fully typeable (qualitatively identical) samples. After standardization, the average among-locus fluorescence intensity (electropherographic peak height or area) provided a suitable metric for quantitative analysis of the relative amounts of amplifiable DNA in an archived sample. The amounts of DNA in Chelex extracts from stains on two untreated high-purity cotton linter pulp papers and a paper treated with a DNA-binding coating were essentially identical. Average intensities for the aqueous extracts from a paper treated with a DNA-releasing coating were somewhat lower but also somewhat less variable than for the Chelex extracts. Average intensities of directly amplified punches of the DNA-binding paper were much larger but somewhat more variable than the Chelex extracts. Approximately 25% of the observed variation among the intensity measurements is shared among the four media and thus can be attributed to intrinsic variation in white blood count among the donors. All of the evaluated media adequately "bank" forensically useful DNA in well-dried whole blood stains for at least 19 months at ambient temperature.

Evolution of record-breaking high and low monthly mean temperatures

NASA Astrophysics Data System (ADS)

Anderson, A. L.; Kostinski, A. B.

2011-12-01

We examine the ratio of record-breaking highs to record-breaking lows with respect to extent of time-series for monthly mean temperatures within the continental United States (1900-2006) and ask the following question. How are record-breaking high and low surface temperatures in the United States affected by time period? We find that the ratio of record-breaking highs to lows in 2006 increases as the time-series extend further into the past. For example: in 2006, the ratio of record-breaking highs to record-breaking lows is ≈ 13 : 1 with 1950 as the first year and ≈ 25 : 1 with 1900 as the first year; both ratios are an order of magnitude greater than 3-σ for stationary simulations. We also find record-breaking events are more sensitive to trends in time-series of monthly averages than time-series of corresponding daily values. When we consider the ratio as it evolves with respect to a fixed start year, we find it is strongly correlated with the ensemble mean. Correlation coefficients are 0.76 and 0.82 for 1900-2006 and 1950-2006 respectively; 3-σ = 0.3 for pairs of uncorrelated stationary time-series. We find similar values for globally distributed time-series: 0.87 and 0.92 for 1900-2006 and 1950-2006 respectively. However, the ratios evolve differently: global ratios increase throughout (1920-2006) while continental United States ratios decrease from about 1940 to 1970. (Based on Anderson and Kostinski (2011), Evolution and distribution of record-breaking high and low monthly mean temperatures. Journal of Applied Meteorology and Climatology. doi: 10.1175/JAMC-D-10-05025.1)

Potential solar radiation and land cover contributions to digital climate surface modeling

NASA Astrophysics Data System (ADS)

Puig, Pol; Batalla, Meritxell; Pesquer, Lluís; Ninyerola, Miquel

2016-04-01

Overview: We have designed a series of ad-hoc experiments to study the role of factors that a priori have a strong weight in developing digital models of temperature and precipitation, such as solar radiation and land cover. Empirical test beds have been designed to improve climate (mean air temperature and total precipitation) digital models using statistical general techniques (multiple regression) with residual correction (interpolated with inverse weighting distance). Aim: Understand what roles these two factors (solar radiation and land cover) play to incorporate them into the process of generating mapping of temperature and rainfall. Study area: The Iberian Peninsula and supported in this, Catalonia and the Catalan Pyrenees. Data: The dependent variables used in all experiments relate to data from meteorological stations precipitation (PL), mean temperature (MT), average temperature minimum (MN) and maximum average temperature (MX). These data were obtained monthly from the AEMET (Agencia Estatal de Meteorología). Data series of stations covers the period between 1950 to 2010. Methodology: The idea is to design ad hoc, based on a sample of more equitable space statistician, to detect the role of radiation. Based on the influence of solar radiation on the temperature of the air from a quantitative point of view, the difficulty in answering this lies in the fact that there are lots of weather stations located in areas where solar radiation is similar. This suggests that the role of the radiation variable remains "off" when, instead, we intuitively think that would strongly influence the temperature. We have developed a multiple regression analysis between these meteorological variables as the dependent ones (Temperature and rainfall), and some geographical variables: altitude (ALT), latitude (LAT), continentality (CON) and solar radiation (RAD) as the independent ones. In case of the experiment with land covers, we have used the NDVI index as a proxy of land covers and added this variable in to the independents to improve the models. Results: The role of solar radiation does not improve models only under certain conditions and areas, especially in the Pyrennes. The vegetation index NDVI and therefore the land cover on which the station is located, helps improve rainfall and temperature patterns, obtaining various degrees of improvement in terms of molded variables and months.

Naive vs. Sophisticated Methods of Forecasting Public Library Circulations.

ERIC Educational Resources Information Center

Brooks, Terrence A.

1984-01-01

Two sophisticated--autoregressive integrated moving average (ARIMA), straight-line regression--and two naive--simple average, monthly average--forecasting techniques were used to forecast monthly circulation totals of 34 public libraries. Comparisons of forecasts and actual totals revealed that ARIMA and monthly average methods had smallest mean…

Event-based stormwater management pond runoff temperature model

NASA Astrophysics Data System (ADS)

Sabouri, F.; Gharabaghi, B.; Sattar, A. M. A.; Thompson, A. M.

2016-09-01

Stormwater management wet ponds are generally very shallow and hence can significantly increase (about 5.4 °C on average in this study) runoff temperatures in summer months, which adversely affects receiving urban stream ecosystems. This study uses gene expression programming (GEP) and artificial neural networks (ANN) modeling techniques to advance our knowledge of the key factors governing thermal enrichment effects of stormwater ponds. The models developed in this study build upon and compliment the ANN model developed by Sabouri et al. (2013) that predicts the catchment event mean runoff temperature entering the pond as a function of event climatic and catchment characteristic parameters. The key factors that control pond outlet runoff temperature, include: (1) Upland Catchment Parameters (catchment drainage area and event mean runoff temperature inflow to the pond); (2) Climatic Parameters (rainfall depth, event mean air temperature, and pond initial water temperature); and (3) Pond Design Parameters (pond length-to-width ratio, pond surface area, pond average depth, and pond outlet depth). We used monitoring data for three summers from 2009 to 2011 in four stormwater management ponds, located in the cities of Guelph and Kitchener, Ontario, Canada to develop the models. The prediction uncertainties of the developed ANN and GEP models for the case study sites are around 0.4% and 1.7% of the median value. Sensitivity analysis of the trained models indicates that the thermal enrichment of the pond outlet runoff is inversely proportional to pond length-to-width ratio, pond outlet depth, and directly proportional to event runoff volume, event mean pond inflow runoff temperature, and pond initial water temperature.

Mapping Atmospheric Moisture Climatologies across the Conterminous United States

PubMed Central

Daly, Christopher; Smith, Joseph I.; Olson, Keith V.

2015-01-01

Spatial climate datasets of 1981–2010 long-term mean monthly average dew point and minimum and maximum vapor pressure deficit were developed for the conterminous United States at 30-arcsec (~800m) resolution. Interpolation of long-term averages (twelve monthly values per variable) was performed using PRISM (Parameter-elevation Relationships on Independent Slopes Model). Surface stations available for analysis numbered only 4,000 for dew point and 3,500 for vapor pressure deficit, compared to 16,000 for previously-developed grids of 1981–2010 long-term mean monthly minimum and maximum temperature. Therefore, a form of Climatologically-Aided Interpolation (CAI) was used, in which the 1981–2010 temperature grids were used as predictor grids. For each grid cell, PRISM calculated a local regression function between the interpolated climate variable and the predictor grid. Nearby stations entering the regression were assigned weights based on the physiographic similarity of the station to the grid cell that included the effects of distance, elevation, coastal proximity, vertical atmospheric layer, and topographic position. Interpolation uncertainties were estimated using cross-validation exercises. Given that CAI interpolation was used, a new method was developed to allow uncertainties in predictor grids to be accounted for in estimating the total interpolation error. Local land use/land cover properties had noticeable effects on the spatial patterns of atmospheric moisture content and deficit. An example of this was relatively high dew points and low vapor pressure deficits at stations located in or near irrigated fields. The new grids, in combination with existing temperature grids, enable the user to derive a full suite of atmospheric moisture variables, such as minimum and maximum relative humidity, vapor pressure, and dew point depression, with accompanying assumptions. All of these grids are available online at http://prism.oregonstate.edu, and include 800-m and 4-km resolution data, images, metadata, pedigree information, and station inventory files. PMID:26485026

Annual egg production rates of calanoid copepod species on the continental shelf of the Eastern Tropical Pacific off Mexico

NASA Astrophysics Data System (ADS)

Kozak, Eva R.; Franco-Gordo, Carmen; Palomares-García, Ricardo; Gómez-Gutiérrez, Jaime; Suárez-Morales, Eduardo

2017-01-01

We provide the first estimations of calanoid copepod egg production rates (EPR) in the Eastern Tropical Pacific over an annual cycle (January-December 2011). Gravid females were collected twice monthly and incubated for 12 h without food to estimate EPR, weight-specific fecundity (Gf), spawning success (SS, percentage of females to spawn out of the total species incubated per month and season) and egg hatching success (EHS). This study reports the average EPR of 10 species and the monthly EPR and Gf of four planktonic calanoid copepods (Centropages furcatus, Temora discaudata, Pontellina sobrina, and Nannocalanus minor) that spawned with enough frequency to infer their seasonal reproductive patterns. These species showed distinct seasonal reproductive strategies. Most copepod species spawned sporadically with large EPR variability, while three copepod species reproduced throughout the year (C. furcatus, T. discaudata and P. sobrina) and N. minor spawned only during the mixed period (Feb-May). The four species had relatively similar average EPR (C. furcatus 16, T. discaudata 18, P. sobrina 13, and N. minor 12 eggs fem-1 day-1). These are the first EPR estimations of P. sobrina and its previously known reproductive period is expanded. A Canonical Correspondence Analysis (CCA) was used to analyze EPR and species abundance of all calanoid copepods (40 spp.) collected throughout the time series in relation to temperature, salinity, mixed layer depth (MLD), dissolved oxygen, and chlorophyll a (Chl-a) concentrations to identify the variables that best explained the copepod abundance variability. Temperature, Chl-a, and salinity had the strongest effect on the biological variables, linked to seasonal and episodic upwelling-downwelling processes in the surveyed area. As a result of moderate upwelling events and seasonal variation of environmental conditions, it appears relatively few species are capable of maintaining continuous reproduction under the relatively higher temperatures and strong fluctuations of food availability that exist in this coastal habitat of the Eastern Tropical Pacific.

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.

Comparison of 15 evaporation methods applied to a small mountain lake in the northeastern USA

USGS Publications Warehouse

Rosenberry, D.O.; Winter, T.C.; Buso, D.C.; Likens, G.E.

2007-01-01

Few detailed evaporation studies exist for small lakes or reservoirs in mountainous settings. A detailed evaporation study was conducted at Mirror Lake, a 0.15 km2 lake in New Hampshire, northeastern USA, as part of a long-term investigation of lake hydrology. Evaporation was determined using 14 alternate evaporation methods during six open-water seasons and compared with values from the Bowen-ratio energy-budget (BREB) method, considered the standard. Values from the Priestley-Taylor, deBruin-Keijman, and Penman methods compared most favorably with BREB-determined values. Differences from BREB values averaged 0.19, 0.27, and 0.20 mm d-1, respectively, and results were within 20% of BREB values during more than 90% of the 37 monthly comparison periods. All three methods require measurement of net radiation, air temperature, change in heat stored in the lake, and vapor pressure, making them relatively data intensive. Several of the methods had substantial bias when compared with BREB values and were subsequently modified to eliminate bias. Methods that rely only on measurement of air temperature, or air temperature and solar radiation, were relatively cost-effective options for measuring evaporation at this small New England lake, outperforming some methods that require measurement of a greater number of variables. It is likely that the atmosphere above Mirror Lake was affected by occasional formation of separation eddies on the lee side of nearby high terrain, although those influences do not appear to be significant to measured evaporation from the lake when averaged over monthly periods. ?? 2007 Elsevier B.V. All rights reserved.

Hydrologic changes after logging in two small Oregon coastal watersheds

USGS Publications Warehouse

Harris, David Dell

1977-01-01

Effects of clearcut, cable logging on the hydrologic characteristics of a small coastal stream in Oregon indicate an average 181-percent increase in sediment yield over a 7-year postlogging period. Annual runoff and high-flow volumes increased 19 and 1.1 inches (480 and 28 mm), respectively, after logging in the watershed. Clearcutting in small, spaced patches in another watershed resulted in some increase in water and sediment yields, but the increase was not statistically significant. Average monthly April-October maximum water temperatures increased significantly in the principal stream of both the clearcut and 'patch-cut' watersheds. Hydrologic characteristics of both streams generally appear to be returning to prelogging conditions (19731.

Climate trends and projections for Guam

USGS Publications Warehouse

Gingerich, Stephen B.; Keener, Victoria; Finucane, Melissa L.

2015-01-01

The island of Guam experiences a tropical marine climate, which is warm and humid moderated by seasonal tradewinds and a wet and dry season. The dry season lasts from January to June, while the rainy months are from July to December. Annual rainfall totals 84-116 inches (2133-2946 mm), of which two-thirds fall during the rainy season. Seasonal temperatures and precipitation are also affected by the El-Niño Southern Oscillation (ENSO) and tropical cyclones, which cause the largest deviations from average precipitation. An average of three tropical storms and one typhoon pass within 80 nautical miles of Guam each year, and both flooding and drought can impact freshwater supply management and associated infrastructure. 

Assessing the social and environmental determinants of pertussis epidemics in Queensland, Australia: a Bayesian spatio-temporal analysis.

PubMed

Huang, X; Lambert, S; Lau, C; Soares Magalhaes, R J; Marquess, J; Rajmokan, M; Milinovich, G; Hu, W

2017-04-01

Pertussis epidemics have displayed substantial spatial heterogeneity in countries with high socioeconomic conditions and high vaccine coverage. This study aims to investigate the relationship between pertussis risk and socio-environmental factors on the spatio-temporal variation underlying pertussis infection. We obtained daily case numbers of pertussis notifications from Queensland Health, Australia by postal area, for the period January 2006 to December 2012. A Bayesian spatio-temporal model was used to quantify the relationship between monthly pertussis incidence and socio-environmental factors. The socio-environmental factors included monthly mean minimum temperature (MIT), monthly mean vapour pressure (VAP), Queensland school calendar pattern (SCP), and socioeconomic index for area (SEIFA). An increase in pertussis incidence was observed from 2006 to 2010 and a slight decrease from 2011 to 2012. Spatial analyses showed pertussis incidence across Queensland postal area to be low and more spatially homogeneous during 2006-2008; incidence was higher and more spatially heterogeneous after 2009. The results also showed that the average decrease in monthly pertussis incidence was 3·1% [95% credible interval (CrI) 1·3-4·8] for each 1 °C increase in monthly MIT, while average increase in monthly pertussis incidences were 6·2% (95% CrI 0·4-12·4) and 2% (95% CrI 1-3) for SCP periods and for each 10-unit increase in SEIFA, respectively. This study demonstrated that pertussis transmission is significantly associated with MIT, SEIFA, and SCP. Mapping derived from this work highlights the potential for future investigation and areas for focusing future control strategies.

Application of the Basin Characterization Model to Estimate In-Place Recharge and Runoff Potential in the Basin and Range Carbonate-Rock Aquifer System, White Pine County, Nevada, and Adjacent Areas in Nevada and Utah

USGS Publications Warehouse

Flint, Alan L.; Flint, Lorraine E.

2007-01-01

A regional-scale water-balance model was used to estimate recharge and runoff potential and support U.S. Geological Survey efforts to develop a better understanding of water availability for the Basin and Range carbonate-rock aquifer system (BARCAS) study in White Pine County, Nevada, and adjacent areas in Nevada and Utah. The water-balance model, or Basin Characterization Model (BCM), was used to estimate regional ground-water recharge for the 13 hydrographic areas in the study area. The BCM calculates recharge by using a distributed-parameter, water-balance method and monthly climatic boundary conditions. The BCM requires geographic information system coverages of soil, geology, and topographic information with monthly time-varying climatic conditions of air temperature and precipitation. Potential evapotranspiration, snow accumulation, and snowmelt are distributed spatially with process models. When combined with surface properties of soil-water storage and saturated hydraulic conductivity of bedrock and alluvium, the potential water available for in-place recharge and runoff is calculated using monthly time steps using a grid scale of 866 feet (270 meters). The BCM was used with monthly climatic inputs from 1970 to 2004, and results were averaged to provide an estimate of the average annual recharge for the BARCAS study area. The model estimates 526,000 acre-feet of potential in-place recharge and approximately 398,000 acre-feet of potential runoff. Assuming 15 percent of the runoff becomes recharge, the model estimates average annual ground-water recharge for the BARCAS area of about 586,000 acre-feet. When precipitation is extrapolated to the long-term climatic record (1895-2006), average annual recharge is estimated to be 530,000 acre-feet, or about 9 percent less than the recharge estimated for 1970-2004.

An atlas of upper tropospheric radiances observed in the 6 to 7-micrometer water vapor band using TOVS data from the NOAA weather satellites during 1979-1991

NASA Technical Reports Server (NTRS)

Chesters, Dennis; Sharma, OM

1992-01-01

This document is a pictorial atlas of the Earth's radiance emitted in the 6 to 7 micro-m water vapor band. At these wavelengths, the infrared brightness temperature corresponds to the layer-average temperature of the top few millimeters of water vapor in the atmosphere. At low altitudes, bright regions are dry slots in the upper troposphere. The satellite observations were obtained from NOAA's cloud and angle corrected measurements made by a series of polar orbiting TOVS (TIROS Operational Vertical Sounder) instruments flown from 1979 to 1991. TOVS 6.7 micro-m and 7.2 micro-m channels were converted to a single brightness temperature that simulates a high altitude channel near '6.5' micro-m. For climatological studies, the daily '6.5' micro-m overpass data were gridded to a cartesian projection with 5 by 5 degree horizontal resolution between 40 degrees N and 40 degrees S latitude. This atlas presents greyscale images of the '6.5' micro-m brightness fields for every day in every month for 13 years. The mean brightness for each of the 12 months for 13 years is presented to display interannual variability, and the annual cycle of 12 monthly means is summarized on a single page. Statistical summaries are presented from other investigations in progress.

Phenological research of climate changes in the north part of Lithuania by the phenological garden of Šiauliai University.

PubMed

Klimienė, Asta; Vainorienė, Rimanta; Klimas, Ramutis

2017-02-01

Šiauliai University Botanical Garden is a member of the International Phenological Garden network since 2005. It is the only one botanical garden in the East Europe that participated in the programme. In 2015, 18 species were observed. For research, data of 14 plants was used. The aim of this study is to estimate the responsiveness of the species of plants of the phenological garden to annual and monthly precipitation and temperature of the air. The main variables in this investigation were growing season length and the beginning of the growing season. In the period 2006-2015, the lowest annual air temperature was in 2010 (6.0 °C), and the highest was in 2015 (8.9 °C). The lowest precipitation was in 2015 (37.3 mm), and the highest was in 2012 (63.5 mm). The leanest regression among growing length, average annual precipitation, and air temperature showed that statistically significant correlation between growing length and average annual air temperature was found for nine plants, between growing length and precipitation was found for three plants, and between growing length and both factors was found for one plant, Salix smithiana, only. Due to the short evaluating period (2007-2015), consistent regression of the length of the growing season could not be found. The growing length of Betula pubescens sequentially increased. The average growing season of 14 plants starts on April 27 (±3), but for Corylus avellana, it is on April 26 (±3). Longevity of the growing season was the most related with precipitation for C. avellana in summer, autumn, and winter and with air temperature, Ribes alpinum and Salix acutifolia in summer and in autumn.

Water Use in Wetland Kalo Cultivation in Hawai`i

USGS Publications Warehouse

Gingerich, Stephen B.; Yeung, Chiu W.; Ibarra, Tracy-Joy N.; Engott, John A.

2007-01-01

Ten cultivation areas (8 windward, 2 leeward) were selected for a kalo water-use study, primarily on the basis of the diversity of environmental and agricultural conditions under which wetland kalo is grown and landowner permission and availability. Flow and water-temperature data were collected at the lo`i complex level and at the individual lo`i level. To ensure that flow and temperature data collected at different lo`i reflect similar irrigation conditions (continuous flooding of the mature crop), only lo`i with crops near the harvesting stage were selected for water-temperature data collection. The water need for kalo cultivation varies depending on the crop stage. In this study, data were collected during the dry season (June-October), when water requirements for cooling kalo approach upper limits. Flow measurements generally were made during the warmest part of the day, and temperature measurements were made every 15 minutes at each site for about a two-month period. Flow and temperature data were collected from kalo cultivation areas on four islands - Kaua`i, O`ahu, Maui, and Hawai`i. The average inflow value for the 19 lo`i complexes measured in this study is 260,000 gallons per acre per day, and the median inflow value is 150,000 gallons per acre per day. The average inflow value for the 17 windward sites is 270,000 gallons per acre per day, and the median inflow value is 150,000 gallons per acre per day. The average inflow value for the two leeward sites is 150,000 gallons per acre per day. The average inflow value measured for six individual lo`i is 350,000 gallons per acre per day, and the median inflow value is 270,000 gallons per acre per day. The average inflow value for the five windward lo`i is 370,000 gallons per acre per day, and the median inflow value is 320,000 gallons per acre per day. The inflow value for the one leeward lo`i is 210,000 gallons per acre per day. These inflow values are consistent with previously reported values for inflow and are significantly higher than values generally estimated for water consumption during kalo cultivation. These measurements of inflow are important for future considerations of water-use requirements for successful kalo cultivation. Of the 17 lo`i complexes where water inflow temperature was measured, only 3 had inflow temperatures that rose above 27 ?C, the threshold temperature above which wetland kalo is more susceptible to fungi and associated rotting diseases. The coldest mean inflow temperature was 20.0 ?C and the warmest inflow temperature was 24.9 ?C. All 15 of the sites where outflow temperatures were measured had some temperatures greater than 27 ?C. Outflow temperatures exceeded 27 ?C between 2.5 percent and about 40 percent of the time. Mean outflow temperatures ranged from 23.0 ?C to 26.7 ?C.

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.

Monitoring and Prediction of Precipitable Water Vapor using GPS data in Turkey

NASA Astrophysics Data System (ADS)

Ansari, Kutubuddin; Althuwaynee, Omar F.; Corumluoglu, Ozsen

2016-12-01

Although Global Positioning System (GPS) primarily provide accurate estimates of position, velocity and time of the receiver, as the signals pass through the atmoshphere carrying its signatures, thus offers opportunities for atmoshpheric applications. Precipitable water vapor (PWV) is a vital component of the atmosphere and significantly influences atmospheric processes like rainfall and atmospheric temperature. The developing networks of continuously operating GPS can be used to efficiently estimate PWV. The Turkish Permanent GPS Network (TPGN) is employed to monitor PWV information in Turkey. This work primarily aims to derive long-term data of PWV by using atmospheric path delays observed through continuously operating TPGN from November 2014 to October 2015. A least square mathematical approach was then applied to establish the relation of the observed PWV to rainfall and temperature. The modeled PWV was correlated with PWV estimated from GPS data, with an average correlation of 67.10 %-88.60 %. The estimated root mean square error (RMSE) varied from 2.840 to 6.380, with an average of 4.697. Finally, data of TPGN, rainfall, and temperature were obtained for less than 2 months (November 2015 to December 2015) and assessed to validate the mathematical model. This study provides a basis for determining PWV by using rainfall and temperature data.

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.

On statistical irregularity of stratospheric warming occurrence during northern winters

NASA Astrophysics Data System (ADS)

Savenkova, Elena N.; Gavrilov, Nikolai M.; Pogoreltsev, Alexander I.

2017-10-01

Statistical analysis of dates of warming events observed during the years 1981-2016 at different stratospheric altitudes reveals their non-uniform distributions during northern winter months with maxima at the beginning of January, at the end of January - beginning of February and at the end of February. Climatology of zonal-mean zonal wind, deviations of temperature from its winter-averaged values, and planetary wave (PW) characteristics at high and middle northern latitudes in the altitude range from the ground up to 60 km is studied using the database of meteorological reanalysis MERRA. Climatological temperature deviations averaged over the 60-90°N latitudinal bands reveal cooler and warmer layers descending due to seasonal changes during the polar night. PW amplitudes and upward Eliassen-Palm fluxes averaged over 36 years have periodical maxima with the main maximum at the beginning of January at altitudes 40-50 km. During the above-mentioned intervals of more frequent occurrence of stratospheric warming events, maxima of PW amplitudes and Eliassen-Palm fluxes, also minima of eastward winds in the high-latitude northern stratosphere have been found. Climatological intra-seasonal irregularities of stratospheric warming dates could indicate reiterating phases of stratospheric vacillations in different years.

Relationship Between Air Pollution, Weather, Traffic, and Traffic-Related Mortality

PubMed Central

Dastoorpoor, Maryam; Idani, Esmaeil; Khanjani, Narges; Goudarzi, Gholamreza; Bahrampour, Abbas

2016-01-01

Background Air pollution and weather are just two of many environmental factors contributing to traffic accidents (RTA). Objectives This study assessed the effects of these factors on traffic accidents and related mortalities in Ahvaz, Iran. Methods In this ecological study, data about RTA, traffic-related mortalities, air pollution (including NO, CO, NO2, NOx PM10, SO2, and O3 rates) and climate data from March 2008 until March 2015 was acquired from the Khuzestan State Police Force, the Environmental Protection Agency and the State Meteorological Department. Statistical analysis was performed with STATA 12 through both crude and adjusted negative binomial regression methods. Results There was a significant positive correlation between increase in the monthly average temperature, the number of rainy days, and the number of frost days with the number of RTA (P < 0.05). Increased monthly average relative humidity, evaporation, and number of sunny days were negatively correlated with the frequency of RTA (P < 0.05). We also observed an inverse significant correlation between monthly average relative humidity, evaporation, and wind speed with traffic accident mortality (P < 0.05). Some air pollutants were negatively associated with the incidence rate of RTA. Conclusions It appears that some weather variables were significantly associated with increased RTA. However, increased levels of air pollutants were not associated with increased rates of RTA and/or related mortalities. Additional studies are recommended to explore this topic in more detail. PMID:28180125

Effects of Climate Change on Salmonella Infections

PubMed Central

Akil, Luma; Reddy, Remata S.

2014-01-01

Abstract Background: Climate change and global warming have been reported to increase spread of foodborne pathogens. To understand these effects on Salmonella infections, modeling approaches such as regression analysis and neural network (NN) were used. Methods: Monthly data for Salmonella outbreaks in Mississippi (MS), Tennessee (TN), and Alabama (AL) were analyzed from 2002 to 2011 using analysis of variance and time series analysis. Meteorological data were collected and the correlation with salmonellosis was examined using regression analysis and NN. Results: A seasonal trend in Salmonella infections was observed (p<0.001). Strong positive correlation was found between high temperature and Salmonella infections in MS and for the combined states (MS, TN, AL) models (R2=0.554; R2=0.415, respectively). NN models showed a strong effect of rise in temperature on the Salmonella outbreaks. In this study, an increase of 1°F was shown to result in four cases increase of Salmonella in MS. However, no correlation between monthly average precipitation rate and Salmonella infections was observed. Conclusion: There is consistent evidence that gastrointestinal infection with bacterial pathogens is positively correlated with ambient temperature, as warmer temperatures enable more rapid replication. Warming trends in the United States and specifically in the southern states may increase rates of Salmonella infections. PMID:25496072

Impact of air temperature variation on the ixodid ticks habitat and tick-borne encephalitis incidence in the Russian Arctic: the case of the Komi Republic.

PubMed

Tokarevich, N; Tronin, A; Gnativ, B; Revich, B; Blinova, O; Evengard, B

2017-01-01

The causes of the recent rise of tick-borne encephalitis (TBE) incidence in Europe are discussed. Our objective was to estimate the impact of air temperature change on TBE incidence in the European part of the Russian Arctic. We analysed the TBE incidence in the Komi Republic (RK) over a 42-year period in relation to changes in local annual average air temperature, air temperature during the season of tick activity, tick abundance, TBE-prevalence in ticks, tick-bite incidence rate, and normalised difference vegetation index within the area under study. In 1998-2011 in RK a substantial growth of TBE virus (TBEV) prevalence both in questing and feeding ticks was observed. In 1992-2011 there was 23-fold growth of the tick-bite incidence rate in humans, a northward shift of the reported tick bites, and the season of tick bites increased from 4 to 6 months. In 1998-2011 there was more than 6-fold growth of average annual TBE incidence compared with 1970-1983 and 1984-1997 periods. This resulted both from the northward shift of TBE, and its growth in the south. In our view it was related to local climate change as both the average annual air temperature, and the air temperature during the tick activity season grew substantially. We revealed in RK a strong correlation between the change in the air temperature and that in TBE incidence. The satellite data showed NDVI growth within RK, i.e. alteration of the local ecosystem under the influence of climate change. The rise in TBE incidence in RK is related considerably to the expansion of the range of Ixodes persulcatus. The territory with reported TBE cases also expanded northward. Climate change is an important driver of TBE incidence rate growth.

Growth responses of Scots pine to climatic factors on reclaimed oil shale mined land.

PubMed

Metslaid, Sandra; Stanturf, John A; Hordo, Maris; Korjus, Henn; Laarmann, Diana; Kiviste, Andres

2016-07-01

Afforestation on reclaimed mining areas has high ecological and economic importance. However, ecosystems established on post-mining substrate can become vulnerable due to climate variability. We used tree-ring data and dendrochronological techniques to study the relationship between climate variables and annual growth of Scots pine (Pinus sylvestris L.) growing on reclaimed open cast oil shale mining areas in Northeast Estonia. Chronologies for trees of different age classes (50, 40, 30) were developed. Pearson's correlation analysis between radial growth indices and monthly climate variables revealed that precipitation in June-July and higher mean temperatures in spring season enhanced radial growth of pine plantations, while higher than average temperatures in summer months inhibited wood production. Sensitivity of radial increment to climatic factors on post-mining soils was not homogenous among the studied populations. Older trees growing on more developed soils were more sensitive to precipitation deficit in summer, while growth indices of two other stand groups (young and middle-aged) were highly correlated to temperature. High mean temperatures in August were negatively related to annual wood production in all trees, while trees in the youngest stands benefited from warmer temperatures in January. As a response to thinning, mean annual basal area increment increased up to 50 %. By managing tree competition in the closed-canopy stands, through the thinning activities, tree sensitivity and response to climate could be manipulated.

[Analysis on concentration variety characteristics of atmospheric ozone under the boundary layer in Beijing].

PubMed

Zong, Xue-Mei; Wang, Geng-Chen; Chen, Hong-Bin; Wang, Pu-Cai; Xuan, Yue-Jian

2007-11-01

Based on the atmospheric ozone sounding data, the average monthly and seasonal variety principles of atmospheric ozone concentration during six years are analyzed under the boundary layer in Beijing. The results show that the monthly variation of atmospheric ozone are obvious that the minimum values appear in January from less than 10 x 10(-9) on ground to less than 50 x 10(-9) on upper layer (2 km), but the maximum values appear in June from 85 x 10(-9) on ground to more than 90 x 10(-9) on upper layer. The seasonal variation is also clear that the least atmospheric ozone concentration is in winter and the most is in summer, but variety from ground to upper layer is largest in winter and least in summer. According to the type of outline, the outline of ozone concentration is composite of three types which are winter type, summer type and spring-autumn type. The monthly ozone concentration in different heights is quite different. After analyzing the relationship between ozone concentration and meteorological factors, such as temperature and humidity, we find ozone concentration on ground is linear with temperature and the correlation coefficient is more than 85 percent.

Construction and Analysis of Long-Term Surface Temperature Dataset in Fujian Province

NASA Astrophysics Data System (ADS)

Li, W. E.; Wang, X. Q.; Su, H.

2017-09-01

Land surface temperature (LST) is a key parameter of land surface physical processes on global and regional scales, linking the heat fluxes and interactions between the ground and atmosphere. Based on MODIS 8-day LST products (MOD11A2) from the split-window algorithms, we constructed and obtained the monthly and annual LST dataset of Fujian Province from 2000 to 2015. Then, we analyzed the monthly and yearly time series LST data and further investigated the LST distribution and its evolution features. The average LST of Fujian Province reached the highest in July, while the lowest in January. The monthly and annual LST time series present a significantly periodic features (annual and interannual) from 2000 to 2015. The spatial distribution showed that the LST in North and West was lower than South and East in Fujian Province. With the rapid development and urbanization of the coastal area in Fujian Province, the LST in coastal urban region was significantly higher than that in mountainous rural region. The LST distributions might affected by the climate, topography and land cover types. The spatio-temporal distribution characteristics of LST could provide good references for the agricultural layout and environment monitoring in Fujian Province.

Research on Dengue during World War II Revisited

PubMed Central

Snow, Grace E.; Haaland, Benjamin; Ooi, Eng Eong; Gubler, Duane J.

2014-01-01

Much of the basic clinical information about dengue infection comes from experimental human studies conducted in the 1920s and 1940s. Albert Sabin's original laboratory records from one such study were bequeathed to Duane J. Gubler. These records were reviewed and 150 experiments were included in our analyses. Persons were inoculated with dengue virus 1 (DENV-1) and DENV-2. Median fever duration was shorter in primary DENV-2 infections compared with DENV-1, although maximum temperature and severity of illness were comparable. At 1.5–9 months after primary infection, 20 persons were inoculated with the heterologous serotype. Only one person inoculated with a heterologous serotype at < 8 weeks showed development of a clinical infection with a maximum temperature of 38°C, and 7 (88%) of 8 persons inoculated with a heterologous serotype at 4–9 months post-primary infection showed development of fever. On average, persons had a shorter incubation period in secondary infection compared with primary infection. PMID:25311700

Use of Temperature, Humidity, and Slaughter Condemnation Data to Predict Increases in Transport Losses in Three Classes of Swine and Resulting Foregone Revenue.

PubMed

Peterson, Erik; Remmenga, Marta; Hagerman, Amy D; Akkina, Judy E

2017-01-01

The United States Department of Agriculture (USDA) Animal and Plant Health Inspection Service (APHIS) conducts weekly surveillance of slaughter condemnation rates to provide early warning for emerging diseases and to monitor health trends in swine. Swine deaths in-transit are an animal welfare concern and represent lost revenue for the swine industry. This retrospective observational study used ambient temperature and humidity data from weather stations near United States slaughter plants collected from 2010 to 2015 to predict the incidence and risk of death among swine in-transit and just prior to slaughter. The risk of death for market swine at a heat index (HI), which combines the effects of temperature and humidity, indicating moderately hot weather conditions between 85 and 92°F was 1.37 times greater than that of the baseline temperature range of 54-79°F. The risk of death for cull sows at an HI between 85 and 92°F was 1.93 times greater than that of average temperatures ranging from 54 to 79°F. Roaster swine (weigh < 220 lbs and often used for whole carcass roasting), however, had 0.80 times the risk when the HI was 85-92°F compared to a baseline temperature of 54-79°F. The risk of death for roaster swine at a minimum temperature between 40 and 50°F was 1.21 times greater than that of average temperatures ranging from 54 to 79°F. The risk of death for market swine at a minimum temperature range of 40-50°F was 0.97 times that of average temperatures ranging from 54 to 79°F. And for cull sows, the risk of death at a minimum temperature range of 40-50°F was 0.81 times the risk at the average temperature ranging from 54 to 79°F. Across the study period, cumulative foregone revenue, or revenue not realized due to swine condemnations, for all swine was $18.6 million and $4.3 million for cold temperatures and high HI ranges above the baseline, respectively. Marginal foregone revenue per hog in hotter months is higher due to seasonal peaks in swine prices. As a result of this study, the USDA-APHIS swine condemnation surveillance can incorporate weekly estimated HI values and ambient temperature data for slaughter establishments to provide additional information for analysts investigating signals (noteworthy increases above baseline) for "dead" condemnations. This study suggests that current mitigation measures are often not sufficient to prevent swine deaths due to ambient temperature extremes.

Climate relationships to fecal bacterial densities in Maryland shellfish harvest waters.

PubMed

Leight, A K; Hood, R; Wood, R; Brohawn, K

2016-02-01

Coastal states of the United States (US) routinely monitor shellfish harvest waters for types of bacteria that indicate the potential presence of fecal pollution. The densities of these indicator bacteria in natural waters may be related to climate in several ways, including through runoff from precipitation and survival related to water temperatures. The relationship between interannual precipitation and air temperature patterns and the densities of fecal indicator bacteria in shellfish harvest waters in Maryland's portion of the Chesapeake Bay was quantified using 34 years of data (1979-2013). Annual and seasonal precipitation totals had a strong positive relationship with average fecal coliform levels (R(2) = 0.69) and the proportion of samples with bacterial densities above the FDA regulatory criteria (R(2) = 0.77). Fecal coliform levels were also significantly and negatively related to average annual air temperature (R(2) = -0.43) and the average air temperature of the warmest month (R(2) = -0.57), while average seasonal air temperature was only significantly related to fecal coliform levels in the summer. River and regional fecal coliform levels displayed a wide range of relationships with precipitation and air temperature patterns, with stronger relationships in rural areas and mainstem Bay stations. Fecal coliform levels tended to be higher in years when the bulk of precipitation occurred throughout the summer and/or fall (August to September). Fecal coliform levels often peaked in late fall and winter, with precipitation peaking in summer and early fall. Continental-scale sea level pressure (SLP) analysis revealed an association between atmospheric patterns that influence both extratropical and tropical storm tracks and very high fecal coliform years, while regional precipitation was found to be significantly correlated with the Atlantic Multidecadal Oscillation and the Pacific North American Pattern. These findings indicate that management of shellfish harvest waters should account for changes in climate conditions and that SLP patterns may be particularly important for predicting years with extremely high levels of fecal coliforms. Published by Elsevier Ltd.

Relations between productivity, climate, and normalized difference vegetation index in the central Great Plains

NASA Astrophysics Data System (ADS)

Wang, Jue

Understanding the influences of climate on productivity remains a major challenge in landscape ecology. Satellite remote sensing of normalized difference vegetation index (NDVI) provides a useful tool to study landscape patterns, based on generalization of local measurements, and to examine relations between climate and variation in productivity. This dissertation examines temporal and spatial relations between NDVI, productivity, and climatic factors over the course of nine years in the central Great Plains. Two general findings emerge: (1) integrated NDVI is a reliable measure of production, as validated with ground-based productivity measurements; and (2) precipitation is the primary factor that determines spatial and temporal patterns of NDVI. NDVI, integrated over appropriate time intervals, is strongly correlated with ground productivity measurements in forests, grasslands, and croplands. Most tree productivity measurements (tree ring size, tree diameter growth, and seed production) are strongly correlated with NDVI integrated for a period during the early growing season; foliage production is most strongly correlated with NDVI integrated over the entire growing season; and tree height growth corresponds with NDVI integrate during the previous growing season. Similarly, productivity measurements for herbaceous plants (grassland biomass and crop yield) are strongly correlated with NDVI. Within the growing season, the temporal pattern of grassland biomass production covaries with NDVI, with a four-week lag time. Across years, grassland biomass production covaries with NDVI integrated from part to all of the current growing season. Corn and wheat yield are most strongly related to NDVI integrated from late June to early August and from late April to mid-May, respectively. Precipitation strongly influences both temporal and spatial patterns of NDVI, while temperature influences NDVI only during the early and late growing season. In terms of temporal patterns, NDVI integrated over the growing season is strongly correlated with precipitation received during the current growing season plus the seven preceding months (fifteen month period); NDVI within the growing season responds to changes in precipitation with a four to eight week lag time; and major precipitation events lead to changes in NDVI with a two to four week lag time. Temperature has a positive correlation with NDVI during the early and late growing season, and a weak negative correlation during the middle of the growing season. In terms of spatial patterns, average precipitation is a strong predictor of the major east-west gradient of NDVI. Deviation from average precipitation explains most of the year-to-year variation in spatial patterns. NDVI and precipitation deviations from average covary (both positive or both negative) for 60--95% of the total land area in Kansas. Minimum and average temperatures are positively correlated with NDVI, but temperature deviation from average is generally not correlated with NDVI deviation from average. The strong relationships between NDVI and productivity, and between precipitation and NDVI, along with detailed analysis of the temporal and spatial patterns for our study region, provides the basis for prediction of productivity at landscape scales under different climate regimes.

Facile and green synthesis of highly stable L-cysteine functionalized copper nanoparticles

NASA Astrophysics Data System (ADS)

Kumar, Nikhil; Upadhyay, Lata Sheo Bachan

2016-11-01

A simple eco-friendly method for L-cysteine capped copper nanoparticles (CCNPs) synthesis in aqueous solution has been developed. Glucose and L-cysteine were used as reducing agent and capping/functionalizing agent, respectively. Different parameters such as capping agent concentration, pH, reaction temperature, and reducing agent concentration were optimized during the synthesis. The L-cysteine capped copper nanoparticle were characterized by ultraviolet-visible spectroscopy, Fourier-transform infrared spectroscopy, X-ray diffraction, Particle size and zeta potential analyser, and high resolution transmission electron microscopy. Spherical shaped cysteine functionalized/capped copper nanoparticles with an average size of 40 nm were found to be highly stable at room temperature (RT) for a period of 1 month

HCMM/soil moisture experiment. [relationship between surface minus air temperature differential and available water according to crop type in Canada

NASA Technical Reports Server (NTRS)

Cihlar, J. (Principal Investigator)

1980-01-01

Progress in the compilation and analysis of airborne and ground data to determine the relationship between the maximum surface minus maximum air temperature differential (delta Tsa) and available water (PAW) is reported. Also, results of an analysis of HCMM images to determine the effect of cloud cover on the availability of HCMM-type data are presented. An inverse relationship between delta Tsa and PAW is indicated along with stable delta Tsa vs. PAW distributions for fully developed canopies. Large variations, both geographical and diurnal, in the cloud cover images are reported. The average monthly daytime cloud cover fluctuated between 40 and 60 percent.

The OceanFlux Greenhouse Gases methodology for deriving a sea surface climatology of CO2 fugacity in support of air-sea gas flux studies

NASA Astrophysics Data System (ADS)

Goddijn-Murphy, L. M.; Woolf, D. K.; Land, P. E.; Shutler, J. D.; Donlon, C.

2015-07-01

Climatologies, or long-term averages, of essential climate variables are useful for evaluating models and providing a baseline for studying anomalies. The Surface Ocean CO2 Atlas (SOCAT) has made millions of global underway sea surface measurements of CO2 publicly available, all in a uniform format and presented as fugacity, fCO2. As fCO2 is highly sensitive to temperature, the measurements are only valid for the instantaneous sea surface temperature (SST) that is measured concurrently with the in-water CO2 measurement. To create a climatology of fCO2 data suitable for calculating air-sea CO2 fluxes, it is therefore desirable to calculate fCO2 valid for a more consistent and averaged SST. This paper presents the OceanFlux Greenhouse Gases methodology for creating such a climatology. We recomputed SOCAT's fCO2 values for their respective measurement month and year using monthly composite SST data on a 1° × 1° grid from satellite Earth observation and then extrapolated the resulting fCO2 values to reference year 2010. The data were then spatially interpolated onto a 1° × 1° grid of the global oceans to produce 12 monthly fCO2 distributions for 2010, including the prediction errors of fCO2 produced by the spatial interpolation technique. The partial pressure of CO2 (pCO2) is also provided for those who prefer to use pCO2. The CO2 concentration difference between ocean and atmosphere is the thermodynamic driving force of the air-sea CO2 flux, and hence the presented fCO2 distributions can be used in air-sea gas flux calculations together with climatologies of other climate variables.

Passive monitoring using traffic noise recordings - case study on the Steinachtal Bridge

NASA Astrophysics Data System (ADS)

Salvermoser, Johannes; Stähler, Simon; Hadziioannou, Céline

2015-04-01

Civil structures age continuously. The early recognition of potentially critical damages is an important economical issue, but also one of public safety. Continuous tracking of small changes in the medium by using passive methods would offer an extension to established active non-destructive testing procedures at relatively low cost. Here we present a case study of structural monitoring using continuous recordings of traffic noise on a 200 meter long reinforced concrete highway bridge in Germany. Over two months of continuos geophone records are used in the frequency range of 2-8 Hz. Using passive image interferometry, evaluation of hourly cross-correlations between recordings at pairs of receivers yield velocity variations in the range of -1.5% to +2.1%. We were able to correlate our outcomes with temperature measurements of the same two month period. The measured velocity changes scale with the temperature variations with on average a dv/v of 0.064% per degree Celsius. This value is in accordance with other studies of concrete response to temperature, confirming that we are able to observe subtle changes with physical origin. It is shown that traffic noise is temporally homogenenous enough to fulfill the requirements of passive image interferometry.

Controlling the Degradation of Bioresorbable Polymers

NASA Astrophysics Data System (ADS)

Moritz, Istvan; Crowley, Brian; Brundage, Elizabeth; Rende, Deniz; Ozisik, Rahmi

Bioresorbable polymers play a vital role in the development of implantable materials that are used in surgical procedures, controlled drug delivery systems; and tissue engineering scaffolds. The half-life of common bioresorbable polymers ranges from 3 to over 12 months and slow bioresorption rates of these polymers restrict their use to a limited set of applications. The use of embedded enzymes was previously proposed to control the degradation rate of bioresorbable polymers, and was shown to decrease average degradation time to about 0.5 months. In this study, electromagnetic actuation of iron oxide magnetic nanoparticles embedded in an encapsulant polymer, poly(ethyleneoxide), PEO, was employed to initiate enzyme assisted degradation of bioresorbable polymer poly(caprolactone), PCL. Results indicate that the internal temperature of iron oxide magnetic nanoparticle doped PEO samples can be increased via an alternating magnetic field, and temperature increase depends strongly on nanoparticle concentration and magnetic field parameters. The temperature achieved is sufficient to relax the PEO matrix and to enable the diffusion of enzymes from PEO to a surrounding PCL matrix. Current studies are directed at measuring the degradation rate of PCL due to the diffused enzyme. This material is based upon work supported by the National Science Foundation under Grant No. CMMI-1538730.

Flowering phenological changes in relation to climate change in Hungary.

PubMed

Szabó, Barbara; Vincze, Enikő; Czúcz, Bálint

2016-09-01

The importance of long-term plant phenological time series is growing in monitoring of climate change impacts worldwide. To detect trends and assess possible influences of climate in Hungary, we studied flowering phenological records for six species (Convallaria majalis, Taraxacum officinale, Syringa vulgaris, Sambucus nigra, Robinia pseudoacacia, Tilia cordata) based on phenological observations from the Hungarian Meteorological Service recorded between 1952 and 2000. Altogether, four from the six examined plant species showed significant advancement in flowering onset with an average rate of 1.9-4.4 days per decade. We found that it was the mean temperature of the 2-3 months immediately preceding the mean flowering date, which most prominently influenced its timing. In addition, several species were affected by the late winter (January-March) values of the North Atlantic Oscillation (NAO) index. We also detected sporadic long-term effects for all species, where climatic variables from earlier months exerted influence with varying sign and little recognizable pattern: the temperature/NAO of the previous autumn (August-December) seems to influence Convallaria, and the temperature/precipitation of the previous spring (February-April) has some effect on Tilia flowering.

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.

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

NASA Astrophysics Data System (ADS)

Fipps, G.

2015-12-01

Municipalities, engineering consultants and State agencies use reference evapotranspiration (ETo) data (directly and indirectly) for long-term water planning, for designing hydraulic structures, and for establishing regulatory guidance and conservation programs intended to reduce water waste. The use ETo data for agricultural and landscape irrigation scheduling is becoming more common in Texas as ETo-based controllers and automation technologies become more affordable. Until recently, most ETo data has been available as monthly values averaged over many years. Today, automated weather stations and irrigation controllers equipped with specialized instrumentation allow for real-time ETo measurements. With the expected rise in global warming and increased frequency of extreme climate variability in the coming decades, conservation and efficient use of water resources is essential and must make use of the most accurate and representative data available. 2011 marked the driest year on record in the State of Texas. Compounding the lack of rainfall was record heat during the Summer of 2011. An analysis of real time ETo (reference evapotranspiration) data in Texas found that ET was 30 to 50% higher than historic averages during the 2011 Summer. The implications are quite serious, as most current water planning and drought contingency plans do not take into consideration increases in ET during such periods, and irrigation planning and capacity sizing are based on historic averages of consumptive use. This paper examines the relationship between ET and climate during this extreme climatic event. While the solar radiation was near normal levels, temperature and wind was much higher and dew points much lower than norms. The variability and statistical difference between average monthly ETo data and daily, monthly and seasonal ETo measurements (from 2006 to 2014) for selected weather stations of the Texas ET Network. This study will also examine the suitability of using average ETo rates for use in regional water planning and in irrigation scheduling.

Coping with a challenging environment

PubMed Central

Gesquiere, Laurence R.; Khan, Memuna; Shek, Lili; Wango, Tim L.; Wango, Emmanuel O.; Alberts, Susan C.; Altmann, Jeanne

2008-01-01

Environmental stressors impact physiology and behavior in many species of animals. These effects are partly mediated through changing concentrations of glucocorticoids, which also vary with reproductive state and social conditions. Prior research has focused largely on seasonal breeders, but the close temporal linkage between season and reproductive state in these species hinders ability to disentangle environmental effects from those of the animal’s reproductive status. Here we assessed the effects of environmental challenges on the fecal glucocorticoid (fGC) levels of non-seasonal breeders, female baboons (Papio cynocephalus) of Amboseli, Kenya. Amboseli is characterized by a long dry season, during which food and water become scarce, and by extreme temperatures above 40°C in the shade during some months of the year. We found that after accounting for female reproductive status and individual variability, females exhibited higher fGC levels during the dry season than during the wet season. Further, during the wet season, fGC levels were higher in months of high average daily maximum temperatures. During the dry season, fGC levels were elevated both in hotter months and in months during which the baboons spent a relatively high proportion of time feeding. In spite of these stressors, female baboons reproduce during all months of the year in Amboseli, unlike most other mammals in this environment. This may be attributable to their extreme adaptability, specifically their diversified diet, and their ability to modify their behavior, including their activity profiles. PMID:18514196

Estimation of evaporation from open water - A review of selected studies, summary of U.S. Army Corps of Engineers data collection and methods, and evaluation of two methods for estimation of evaporation from five reservoirs in Texas

USGS Publications Warehouse

Harwell, Glenn R.

2012-01-01

Organizations responsible for the management of water resources, such as the U.S. Army Corps of Engineers (USACE), are tasked with estimation of evaporation for water-budgeting and planning purposes. The USACE has historically used Class A pan evaporation data (pan data) to estimate evaporation from reservoirs but many USACE Districts have been experimenting with other techniques for an alternative to collecting pan data. The energy-budget method generally is considered the preferred method for accurate estimation of open-water evaporation from lakes and reservoirs. Complex equations to estimate evaporation, such as the Penman, DeBruin-Keijman, and Priestley-Taylor, perform well when compared with energy-budget method estimates when all of the important energy terms are included in the equations and ideal data are collected. However, sometimes nonideal data are collected and energy terms, such as the change in the amount of stored energy and advected energy, are not included in the equations. When this is done, the corresponding errors in evaporation estimates are not quantifiable. Much simpler methods, such as the Hamon method and a method developed by the U.S. Weather Bureau (USWB) (renamed the National Weather Service in 1970), have been shown to provide reasonable estimates of evaporation when compared to energy-budget method estimates. Data requirements for the Hamon and USWB methods are minimal and sometimes perform well with remotely collected data. The Hamon method requires average daily air temperature, and the USWB method requires daily averages of air temperature, relative humidity, wind speed, and solar radiation. Estimates of annual lake evaporation from pan data are frequently within 20 percent of energy-budget method estimates. Results of evaporation estimates from the Hamon method and the USWB method were compared against historical pan data at five selected reservoirs in Texas (Benbrook Lake, Canyon Lake, Granger Lake, Hords Creek Lake, and Sam Rayburn Lake) to evaluate their performance and to develop coefficients to minimize bias for the purpose of estimating reservoir evaporation with accuracies similar to estimates of evaporation obtained from pan data. The modified Hamon method estimates of reservoir evaporation were similar to estimates of reservoir evaporation from pan data for daily, monthly, and annual time periods. The modified Hamon method estimates of annual reservoir evaporation were always within 20 percent of annual reservoir evaporation from pan data. Unmodified and modified USWB method estimates of annual reservoir evaporation were within 20 percent of annual reservoir evaporation from pan data for about 91 percent of the years compared. Average daily differences between modified USWB method estimates and estimates from pan data as a percentage of the average amount of daily evaporation from pan data were within 20 percent for 98 percent of the months. Without any modification to the USWB method, average daily differences as a percentage of the average amount of daily evaporation from pan data were within 20 percent for 73 percent of the months. Use of the unmodified USWB method is appealing because it means estimates of average daily reservoir evaporation can be made from air temperature, relative humidity, wind speed, and solar radiation data collected from remote weather stations without the need to develop site-specific coefficients from historical pan data. Site-specific coefficients would need to be developed for the modified version of the Hamon method.

A long-term monitoring study of chlorophyll, microbial contaminants, and pesticides in a coastal residential stormwater pond and its adjacent tidal creek.

PubMed

DeLorenzo, Marie E; Thompson, Brian; Cooper, Emily; Moore, Janet; Fulton, Michael H

2012-01-01

Stormwater ponds are commonly used in residential and commercial areas to control flooding. The accumulation of urban contaminants in stormwater ponds can lead to water-quality problems including nutrient enrichment, chemical contamination, and bacterial contamination. This study presents 5 years of monitoring data assessing water quality of a residential subdivision pond and adjacent tidal creek in coastal South Carolina, USA. The stormwater pond is eutrophic, as described by elevated concentrations of chlorophyll and phosphorus, and experiences periodic cyanobacterial blooms. A maximum monthly average chlorophyll concentration of 318.75 μg/L was measured in the stormwater pond and 227.63 μg/L in the tidal creek. Fecal coliform bacteria (FCB) levels were measured in both the pond and the tidal creek that exceeded health and safety standards for safe recreational use. A maximum monthly average FCB level of 1,247 CFU/100 mL was measured in the stormwater pond and 12,850 CFU/100 mL in the tidal creek. In addition, the presence of antibiotic resistant bacteria and pathogenic bacteria were detected. Low concentrations of herbicides (atrazine and 2,4-D: ), a fungicide (chlorothalonil), and insecticides (pyrethroids and imidacloprid) were measured. Seasonal trends were identified, with the winter months having the lowest concentrations of chlorophyll and FCB. Statistical differences between the stormwater pond and the tidal creek were also noted within seasons. The tidal creek had higher FCB levels than the stormwater pond in the spring and summer, whereas the stormwater pond had higher chlorophyll levels than the tidal creek in the summer and fall seasons. Chlorophyll and FCB levels in the stormwater pond were significantly correlated with monthly average temperature and total rainfall. Pesticide concentrations were also significantly correlated with temperature and rainfall. Pesticide concentrations in the stormwater pond were significantly correlated with pesticide concentrations in the adjacent tidal creek. Chlorophyll and FCB levels in the tidal creek, however, were not significantly correlated with levels in the pond. While stormwater ponds are beneficial in controlling flooding, they may pose environmental and human health risks due to biological and chemical contamination. Management to reduce residential runoff may improve water quality in coastal stormwater ponds and their adjacent estuarine ecosystems.

Future hotspots of increasing temperature variability in tropical countries

NASA Astrophysics Data System (ADS)

Bathiany, S.; Dakos, V.; Scheffer, M.; Lenton, T. M.

2017-12-01

Resolving how climate variability will change in future is crucial to determining how challenging it will be for societies and ecosystems to adapt to climate change. We show that the largest increases in temperature variability - that are robust between state-of-the art climate models - are concentrated in tropical countries. On average, temperature variability increases by 15% per degree of global warming in Amazonia and Southern Africa during austral summer, and by up to 10% °C-1 in the Sahel, India and South East Asia. Southern hemisphere changes can be explained by drying soils, whereas shifts in atmospheric structure play a more important role in the Northern hemisphere. These robust regional changes in variability are associated with monthly timescale events, whereas uncertain changes in inter-annual modes of variability make the response of global temperature variability uncertain. Our results suggest that regional changes in temperature variability will create new inequalities in climate change impacts between rich and poor nations.

Dispersion of atmospheric air pollution in summer and winter season.

PubMed

Cichowicz, Robert; Wielgosiński, Grzegorz; Fetter, Wojciech

2017-11-04

Seasonal variation of air pollution is associated with variety of seasons and specificity of particular months which form the so-called summer and winter season also known as the "heating" season. The occurrence of higher values of air pollution in different months of a year is associated with the type of climate, and accordingly with different atmospheric conditions in particular months, changing state of weather on a given day, and anthropogenic activity. The appearance of these conditions results in different levels of air pollution characteristic for a given period. The study uses data collected during a seven-year period (2009-2015) in the automatic measuring station of immissions located in Eastern Wielkopolska. The analysis concerns the average and maximum values of air pollution (i.e., particulate matter PM10, sulfur dioxide, nitrogen dioxide, carbon monoxide, and ozone) from the perspective of their occurrence in particular seasons and months or in relation to meteorological actors such as temperature, humidity, and wind speed.

Methane emissions from tundra environments in the Yukon-Kuskokwin Delta, Alaska

NASA Technical Reports Server (NTRS)

Bartlett, Karen B.; Crill, Patrick M.; Sass, Ronald L.; Harriss, Robert C.; Dise, Nancy B.

1992-01-01

This paper reports CH4 flux to the atmosphere from a variety of tundra environments near Bethel, Alaska during the summer months of 1988. Emissions from wet meadow tundra averaged 144 +/- 31 mg/sq m/d and ranged from 15.6 to 426 mg/sq m/d varying with soil moisture and temperature. Flux from the drier upland tundra was about two orders of magnitude lower and averaged 2.3 +/- 1.1 mg/sq m/d. Tundra lakes emit CH4 from the open water surface as well as from fringing aquatic vegetation; the presence of vegetation significantly enhanced flux over open water rates. Calculated diffusive fluxes from open water varied with lake size, the large lakes emitting 3.8 mg/sq m/d and small lakes emitting an average of 77 mg/sq m/d. An updated estimate of global emissions from tundra indicates an annual fluxes of approximately 11 +/- 3 Tg CH4.

Effects of meteorological factors on incidence of scarlet fever during different periods in different districts of China.

PubMed

Duan, Yu; Yang, Li-Juan; Zhang, Yan-Jie; Huang, Xiao-Lei; Pan, Gui-Xia; Wang, Jing

2017-03-01

To reveal the difference of meteorological effect on scarlet fever in Beijing and Hong Kong, China, during different periods among 2004-2014. The data of monthly incidence of scarlet fever and meteorological variables from 2004 to 2014 in Beijing and Hong Kong were collected from Chinese science data center of public health, meteorological data website and Hong Kong observatory website. The whole study period was separated into two periods by the outbreak year 2011 (Jan 2004-Dec 2010 and Jan 2011-Dec 2014). A generalized additive Poisson model was conducted to estimate the effect of meteorological variables on monthly incidence of scarlet fever during two periods in Beijing and Hong Kong, China. Incidence of scarlet fever in two districts were compared and found the average incidence during period of 2004-2010 were significantly different (Z=203.973, P<0.001) while average incidence became generally equal during 2011-2014 (Z=2.125, P>0.05). There was also significant difference in meteorological variables between Beijing and Hong Kong during whole study period, except air pressure (Z=0.165, P=0.869). After fitting GAM model, it could be found monthly mean temperature showed a negative effect (RR=0.962, 95%CI: 0.933, 0.992) on scarlet fever in Hong Kong during the period of 2004-2010. By comparison, for data in Beijing during the period of 2011-2014, the RRs of monthly mean temperature range growing 1°C and monthly sunshine duration growing 1h was equal to 1.196(1.022, 1.399) and 1.006(1.001, 1.012), respectively. The changes of meteorological effect on scarlet fever over time were not significant both in Beijing and Hong Kong. This study suggests that meteorological variables were important factors for incidence of scarlet fever during different period in Beijing and Hong Kong. It also support that some meteorological effects were opposite in different period although these differences might not completely statistically significant. Copyright © 2017 Elsevier B.V. All rights reserved.

Statistical downscaling of general-circulation-model- simulated average monthly air temperature to the beginning of flowering of the dandelion (Taraxacum officinale) in Slovenia

NASA Astrophysics Data System (ADS)

Bergant, Klemen; Kajfež-Bogataj, Lučka; Črepinšek, Zalika

2002-02-01

Phenological observations are a valuable source of information for investigating the relationship between climate variation and plant development. Potential climate change in the future will shift the occurrence of phenological phases. Information about future climate conditions is needed in order to estimate this shift. General circulation models (GCM) provide the best information about future climate change. They are able to simulate reliably the most important mean features on a large scale, but they fail on a regional scale because of their low spatial resolution. A common approach to bridging the scale gap is statistical downscaling, which was used to relate the beginning of flowering of Taraxacum officinale in Slovenia with the monthly mean near-surface air temperature for January, February and March in Central Europe. Statistical models were developed and tested with NCAR/NCEP Reanalysis predictor data and EARS predictand data for the period 1960-1999. Prior to developing statistical models, empirical orthogonal function (EOF) analysis was employed on the predictor data. Multiple linear regression was used to relate the beginning of flowering with expansion coefficients of the first three EOF for the Janauary, Febrauary and March air temperatures, and a strong correlation was found between them. Developed statistical models were employed on the results of two GCM (HadCM3 and ECHAM4/OPYC3) to estimate the potential shifts in the beginning of flowering for the periods 1990-2019 and 2020-2049 in comparison with the period 1960-1989. The HadCM3 model predicts, on average, 4 days earlier occurrence and ECHAM4/OPYC3 5 days earlier occurrence of flowering in the period 1990-2019. The analogous results for the period 2020-2049 are a 10- and 11-day earlier occurrence.

Seasonal and latitudinal variations of surface fluxes at two Arctic terrestrial sites

NASA Astrophysics Data System (ADS)

Grachev, Andrey A.; Persson, P. Ola G.; Uttal, Taneil; Akish, Elena A.; Cox, Christopher J.; Morris, Sara M.; Fairall, Christopher W.; Stone, Robert S.; Lesins, Glen; Makshtas, Alexander P.; Repina, Irina A.

2017-11-01

This observational study compares seasonal variations of surface fluxes (turbulent, radiative, and soil heat) and other ancillary atmospheric/surface/permafrost data based on in-situ measurements made at terrestrial research observatories located near the coast of the Arctic Ocean. Hourly-averaged multiyear data sets collected at Eureka (Nunavut, Canada) and Tiksi (East Siberia, Russia) are analyzed in more detail to elucidate similarities and differences in the seasonal cycles at these two Arctic stations, which are situated at significantly different latitudes (80.0°N and 71.6°N, respectively). While significant gross similarities exist in the annual cycles of various meteorological parameters and fluxes, the differences in latitude, local topography, cloud cover, snowfall, and soil characteristics produce noticeable differences in fluxes and in the structures of the atmospheric boundary layer and upper soil temperature profiles. An important factor is that even though higher latitude sites (in this case Eureka) generally receive less annual incoming solar radiation but more total daily incoming solar radiation throughout the summer months than lower latitude sites (in this case Tiksi). This leads to a counter-intuitive state where the average active layer (or thaw line) is deeper and the topsoil temperature in midsummer are higher in Eureka which is located almost 10° north of Tiksi. The study further highlights the differences in the seasonal and latitudinal variations of the incoming shortwave and net radiation as well as the moderating cloudiness effects that lead to temporal and spatial differences in the structure of the atmospheric boundary layer and the uppermost ground layer. Specifically the warm season (Arctic summer) is shorter and mid-summer amplitude of the surface fluxes near solar noon is generally less in Eureka than in Tiksi. During the dark Polar night and cold seasons (Arctic winter) when the ground is covered with snow and air temperatures are sufficiently below freezing, the near-surface environment is generally stably stratified and the hourly averaged turbulent fluxes are quite small and irregular with on average small downward sensible heat fluxes and upward latent heat and carbon dioxide fluxes. The magnitude of the turbulent fluxes increases rapidly when surface snow disappears and the air temperatures rise above freezing during spring melt and eventually reaches a summer maximum. Throughout the summer months strong upward sensible and latent heat fluxes and downward carbon dioxide (uptake by the surface) are typically observed indicating persistent unstable (convective) stratification. Due to the combined effects of day length and solar zenith angle, the convective boundary layer forms in the High Arctic (e.g., in Eureka) and can reach long-lived quasi-stationary states in summer. During late summer and early autumn all turbulent fluxes rapidly decrease in magnitude when the air temperature decreases and falls below freezing. Unlike Eureka, a pronounced zero-curtain effect consisting of a sustained surface temperature hiatus at the freezing point is observed in Tiksi during fall due to wetter and/or water saturated soils.

An annual quasidifference approach to water price elasticity

NASA Astrophysics Data System (ADS)

Bell, David R.; Griffin, Ronald C.

2008-08-01

The preferred price specification for retail water demand estimation has not been fully settled by prior literature. Empirical consistency of price indices is necessary to enable testing of competing specifications. Available methods of unbiasing the price index are summarized here. Using original rate information from several hundred Texas utilities, new indices of marginal and average price change are constructed. Marginal water price change is shown to explain consumption variation better than average water price change, based on standard information criteria. Annual change in quantity consumed per month is estimated with differences in climate variables and the new quasidifference marginal price index. As expected, the annual price elasticity of demand is found to vary with daily high and low temperatures and the frequency of precipitation.

Estimating solar radiation using NOAA/AVHRR and ground measurement data

NASA Astrophysics Data System (ADS)

Fallahi, Somayeh; Amanollahi, Jamil; Tzanis, Chris G.; Ramli, Mohammad Firuz

2018-01-01

Solar radiation (SR) data are commonly used in different areas of renewable energy research. Researchers are often compelled to predict SR at ground stations for areas with no proper equipment. The objective of this study was to test the accuracy of the artificial neural network (ANN) and multiple linear regression (MLR) models for estimating monthly average SR over Kurdistan Province, Iran. Input data of the models were two data series with similar longitude, latitude, altitude, and month (number of months) data, but there were differences between the monthly mean temperatures in the first data series obtained from AVHRR sensor of NOAA satellite (DS1) and in the second data series measured at ground stations (DS2). In order to retrieve land surface temperature (LST) from AVHRR sensor, emissivity of the area was considered and for that purpose normalized vegetation difference index (NDVI) calculated from channels 1 and 2 of AVHRR sensor was utilized. The acquired results showed that the ANN model with DS1 data input with R2 = 0.96, RMSE = 1.04, MAE = 1.1 in the training phase and R2 = 0.96, RMSE = 1.06, MAE = 1.15 in the testing phase achieved more satisfactory performance compared with MLR model. It can be concluded that ANN model with remote sensing data has the potential to predict SR in locations with no ground measurement stations.

No association between month of birth and biliary atresia in a country with tropical climate.

PubMed

Tanpowpong, Pornthep; Lertudomphonwanit, Chatmanee; Phuapradit, Pornpimol; Treepongkaruna, Suporn

2018-06-04

Children with biliary atresia (BA) born in countries with temperate climate showed month-of-birth (MoB) predilection during cooler months. To date, no study on the MoB-BA association has been performed in a tropical country. Our aim was to define MoB variation in children with BA in a tropical country. We studied 150 children diagnosed with BA between January 1996 and April 2015 at a teaching hospital. MoB was defined by two categories based on the precipitation: rain and dry, and three categories based on the air temperature: high, average and low. We applied the country's population data on the number of births in each period as the expected proportions of birth. A slightly higher proportion of BA children was born in the rainy months (52.7%); however, the difference was not significant compared to the general population's birth (P = 0.87). For the MoB based on the air temperature, no statistically significant difference was noted. Males with BA seemed to have a greater MoB variation compared to females, but this did not reach statistical significance. We could not find an association between MoB and BA in a tropical country. Multinational studies may aid in understanding the MoB-BA association in the tropical countries. © 2018 Paediatrics and Child Health Division (The Royal Australasian College of Physicians).

Temporal Changes in the Observed Relationship between Cloud Cover and Surface Air Temperature.

NASA Astrophysics Data System (ADS)

Sun, Bomin; Groisman, Pavel Ya.; Bradley, Raymond S.; Keimig, Frank T.

2000-12-01

The relationship between cloud cover and near-surface air temperature and its decadal changes are examined using the hourly synoptic data for the past four to six decades from five regions of the Northern Hemisphere: Canada, the United States, the former Soviet Union, China, and tropical islands of the western Pacific. The authors define the normalized cloud cover-surface air temperature relationship, NOCET or dT/dCL, as a temperature anomaly with a unit (one-tenth) deviation of total cloud cover from its average value. Then mean monthly NOCET time series (night- and daytime, separately) are area-averaged and parameterized as functions of surface air humidity and snow cover. The day- and nighttime NOCET variations are strongly anticorrelated with changes in surface humidity. Furthermore, the daytime NOCET changes are positively correlated to changes in snow cover extent. The regionally averaged nighttime NOCET varies from 0.05 K tenth1 in the wet Tropics to 1.0 K tenth1 at midlatitudes in winter. The daytime regional NOCET ranges from 0.4 K tenth1 in the Tropics to 0.7 K tenth1 at midlatitudes in winter.The authors found a general strengthening of a daytime surface cooling during the post-World War II period associated with cloud cover over the United States and China, but a minor reduction of this cooling in higher latitudes. Furthermore, since the 1970s, a prominent increase in atmospheric humidity has significantly weakened the effectiveness of the surface warming (best seen at nighttime) associated with cloud cover.The authors apportion the spatiotemporal field of interactions between total cloud cover and surface air temperature into a bivariate relationship (described by two equations, one for daytime and one for nighttime) with surface air humidity and snow cover and two constant factors. These factors are invariant in space and time domains. It is speculated that they may represent empirical estimates of the overall cloud cover effect on the surface air temperature.

The Differential Warming Response of Britain’s Rivers (1982–2011)

PubMed Central

Jonkers, Art R. T.; Sharkey, Kieran J.

2016-01-01

River water temperature is a hydrological feature primarily controlled by topographical, meteorological, climatological, and anthropogenic factors. For Britain, the study of freshwater temperatures has focussed mainly on observations made in England and Wales; similar comprehensive data sets for Scotland are currently unavailable. Here we present a model for the whole of mainland Britain over three recent decades (1982–2011) that incorporates geographical extrapolation to Scotland. The model estimates daily mean freshwater temperature for every river segment and for any day in the studied period, based upon physico-geographical features, daily mean air and sea temperatures, and available freshwater temperature measurements. We also extrapolate the model temporally to predict future warming of Britain’s rivers given current observed trends. Our results highlight the spatial and temporal diversity of British freshwater temperatures and warming rates. Over the studied period, Britain’s rivers had a mean temperature of 9.84°C and experienced a mean warming of +0.22°C per decade, with lower rates for segments near lakes and in coastal regions. Model results indicate April as the fastest-warming month (+0.63°C per decade on average), and show that most rivers spend on average ever more days of the year at temperatures exceeding 10°C, a critical threshold for several fish pathogens. Our results also identify exceptional warming in parts of the Scottish Highlands (in April and September) and pervasive cooling episodes, in December throughout Britain and in July in the southwest of England (in Wales, Cornwall, Devon, and Dorset). This regional heterogeneity in rates of change has ramifications for current and future water quality, aquatic ecosystems, as well as for the spread of waterborne diseases. PMID:27832108

The Differential Warming Response of Britain's Rivers (1982-2011).

PubMed

Jonkers, Art R T; Sharkey, Kieran J

2016-01-01

River water temperature is a hydrological feature primarily controlled by topographical, meteorological, climatological, and anthropogenic factors. For Britain, the study of freshwater temperatures has focussed mainly on observations made in England and Wales; similar comprehensive data sets for Scotland are currently unavailable. Here we present a model for the whole of mainland Britain over three recent decades (1982-2011) that incorporates geographical extrapolation to Scotland. The model estimates daily mean freshwater temperature for every river segment and for any day in the studied period, based upon physico-geographical features, daily mean air and sea temperatures, and available freshwater temperature measurements. We also extrapolate the model temporally to predict future warming of Britain's rivers given current observed trends. Our results highlight the spatial and temporal diversity of British freshwater temperatures and warming rates. Over the studied period, Britain's rivers had a mean temperature of 9.84°C and experienced a mean warming of +0.22°C per decade, with lower rates for segments near lakes and in coastal regions. Model results indicate April as the fastest-warming month (+0.63°C per decade on average), and show that most rivers spend on average ever more days of the year at temperatures exceeding 10°C, a critical threshold for several fish pathogens. Our results also identify exceptional warming in parts of the Scottish Highlands (in April and September) and pervasive cooling episodes, in December throughout Britain and in July in the southwest of England (in Wales, Cornwall, Devon, and Dorset). This regional heterogeneity in rates of change has ramifications for current and future water quality, aquatic ecosystems, as well as for the spread of waterborne diseases.

Variations in Withdrawal, Return Flow, and Consumptive Use of Water in Ohio and Indiana, with Selected Data from Wisconsin, 1999-2004

USGS Publications Warehouse

Shaffer, Kimberly H.

2009-01-01

This report contains an analysis of water withdrawal and return-flow data for Ohio and withdrawal data for Indiana and Wisconsin to compute consumptive-use coefficients and to describe monthly variability of withdrawals and consumptive use. Concurrent data were available for most water-use categories from 1999 through 2004. Average monthly water withdrawals are discussed for a variety of water-use categories, and average water use per month is depicted graphically for Ohio, Indiana, and Wisconsin (public supply only). For most water-use categories, the summer months were those of highest withdrawal and highest consumptive use. For public supply, average monthly withdrawals ranged from 1,380 million gallons per day (Mgal/d) (November) to 1,620 Mgal/d (July) in Ohio, 621 Mgal/d (December) to 816 Mgal/d (July) in Indiana, and 515 Mgal/d (December) to 694 Mgal/d (July) in Wisconsin. Ohio and Indiana thermoelectric facilities had large increases in average monthly withdrawals in the summer months (5,520 Mgal/d in March to 7,510 Mgal/d in August for Indiana; 7,380 Mgal/d in February to 10,040 Mgal/d in July for Ohio), possibly because of increased electricity production in the summer, a need for additional cooling-water withdrawals when intake-water temperature is high, or use of different types of cooling methods during different times of the year. Average industrial withdrawals ranged from 2,220 Mgal/d (December) to 2,620 Mgal/d (August) in Indiana and from 707 Mgal/d (January) to 787 Mgal/d (August) in Ohio. The Ohio and Indiana irrigation data showed that most withdrawals were in May through October for golf courses, nurseries, and crop irrigation. Commercial water withdrawals ranged from 30.4 Mgal/d (January) to 65.0 Mgal/d (September) in Indiana and from 23.2 Mgal/d (November) to 49.5 Mgal/d (August) in Ohio; commercial facilities that have high water demand in Ohio and Indiana are medical facilities, schools, amusement facilities, wildlife facilities, large stores, colleges, correctional institutions, and national security facilities. Monthly livestock withdrawals were constant for Ohio but were more variable in Indiana and depended on whether the livestock facility operated on a seasonal schedule. Aquaculture withdrawals appeared to correlate with growing seasons and with aeration of ponds during the winter months. Mining withdrawals - specifically, those for nonmetallic mining - tended to be highest in April and may be related to dewatering. Consumptive use and consumptive-use coefficients were computed by two principal methods in this study: the return-flow and withdrawal method (RW; Ohio only) and the winter-base-rate method (WBR; Ohio, Indiana and Wisconsin). The WBR method was not suitable for the thermoelectric, industrial, irrigation, livestock, aquaculture, and mining water-use categories. The RW method was not used for public-supply facilities. A third method, the Standard Industrial Classification code method (SIC), was used only for certain industrial facilities. The public-supply annual average consumptive-use coefficient derived by use of the WBR methods ranged from 6 to 8 percent among Ohio, Indiana, and Wisconsin; the summer average consumptive-use coefficient was considerably higher, ranging from 16 to 20 percent. The commercial annual consumptive-use coefficient for both Ohio and Indiana was 30 percent by the WBR method, which fell within the Ohio annual median (17 percent) and annual average (42 percent) by the RW method. Thermoelectric consumptive use differs greatly by the type of cooling the facility uses; the Ohio annual median consumptive-use coefficient (RW method) was 2 percent for all thermoelectric facilities and facilities with multiple types of cooling, but exclusively once-through-cooling facilities had a median of 0 percent and exclusively closed-loop-cooling facilities had a median of 25 percent. Industrial consumptive-use coefficients varied by type of industry, as reflected by SIC code

[The warning model and influence of climatic changes on hemorrhagic fever with renal syndrome in Changsha city].

PubMed

Xiao, Hong; Tian, Huai-yu; Zhang, Xi-xing; Zhao, Jian; Zhu, Pei-juan; Liu, Ru-chun; Chen, Tian-mu; Dai, Xiang-yu; Lin, Xiao-ling

2011-10-01

To realize the influence of climatic changes on the transmission of hemorrhagic fever with renal syndrome (HFRS), and to explore the adoption of climatic factors in warning HFRS. A total of 2171 cases of HFRS and the synchronous climatic data in Changsha from 2000 to 2009 were collected to a climate-based forecasting model for HFRS transmission. The Cochran-Armitage trend test was employed to explore the variation trend of the annual incidence of HFRS. Cross-correlations analysis was then adopted to assess the time-lag period between the climatic factors, including monthly average temperature, relative humidity, rainfall and Multivariate Elño-Southern Oscillation Index (MEI) and the monthly HFRS cases. Finally the time-series Poisson regression model was constructed to analyze the influence of different climatic factors on the HFRS transmission. The annual incidence of HFRS in Changsha between 2000 - 2009 was 13.09/100 000 (755 cases), 9.92/100 000 (578 cases), 5.02/100 000 (294 cases), 2.55/100 000 (150 cases), 1.13/100 000 (67 cases), 1.16/100 000 (70 cases), 0.95/100 000 (58 cases), 1.40/100 000 (87 cases), 0.75/100 000 (47 cases) and 1.02/100 000 (65 cases), respectively. The incidence showed a decline during these years (Z = -5.78, P < 0.01). The results of Poisson regression model indicated that the monthly average temperature (18.00°C, r = 0.26, P < 0.01, 1-month lag period; IRR = 1.02, 95%CI: 1.00 - 1.03, P < 0.01), relative humidity (75.50%, r = 0.62, P < 0.01, 3-month lag period; IRR = 1.03, 95%CI: 1.02 - 1.04, P < 0.01), rainfall (112.40 mm, r = 0.25, P < 0.01, 6-month lag period; IRR = 1.01, 95CI: 1.01 - 1.02, P = 0.02), and MEI (r = 0.31, P < 0.01, 3-month lag period; IRR = 0.77, 95CI: 0.67 - 0.88, P < 0.01) were closely associated with monthly HFRS cases (18.10 cases). Climate factors significantly influence the incidence of HFRS. If the influence of variable-autocorrelation, seasonality, and long-term trend were controlled, the accuracy of forecasting by the time-series Poisson regression model in Changsha would be comparatively high, and we could forecast the incidence of HFRS in advance.

Effects of elevated mean and extremely high temperatures on the physio-ecological characteristics of geographically distinctive populations of Cunninghamia lanceolata

NASA Astrophysics Data System (ADS)

Zhou, Ting; Jia, Xiaorong; Liao, Huixuan; Peng, Shijia; Peng, Shaolin

2016-12-01

Conventional models for predicting species distribution under global warming scenarios often treat one species as a homogeneous whole. In the present study, we selected Cunninghamia lanceolata (C. lanceolata), a widely distributed species in China, to investigate the physio-ecological responses of five populations under different temperature regimes. The results demonstrate that increased mean temperatures induce increased growth performance among northern populations, which exhibited the greatest germination capacity and largest increase in the overlap between the growth curve and the monthly average temperature. However,tolerance of the southern population to extremely high temperatures was stronger than among the population from the northern region,shown by the best growth and the most stable photosynthetic system of the southern population under extremely high temperature. This result indicates that the growth advantage among northern populations due to increased mean temperatures may be weakened by lower tolerance to extremely high temperatures. This finding is antithetical to the predicted results. The theoretical coupling model constructed here illustrates that the difference in growth between populations at high and low latitudes and altitudes under global warming will decrease because of the frequent occurrence of extremely high temperatures.

Recent SST trends and Flood Disasters in Brazil

NASA Astrophysics Data System (ADS)

Yamashiki, Y.; Behera, S. K.; Inoue, S.; Netrananda, S.; Silva, R. D.; Takara, K. T.; Yamagata, T.

2010-12-01

We analyzed recent variations in the sea surface temperature (SST) anomalies of Pacific and Atlantic Oceans to understand their roles in extreme discharge of Amazon River Basin. In general, higher than monthly average discharge appears when La Niña condition forms and lower than monthly average discharge appears when El Niño condition forms. We also investigated the relationship between SST anomalies and recent floods in Brazil during the period of 1980-2010. Most severe floods (e.g. 2003 and 2010 Rio de Janeiro-São Paulo Flood) in austral summer occurred when El Niño Modoki appears in the Pacific Ocean. In addition, warm waters in tropical South Atlantic Ocean between American and African Coast also helped the moisture convergence to the affected region. Floods in some other locations (for example, Itaipava flood occurred in Maranhao State in 2008) occurred when a La Niña Modoki appeared in Pacific Ocean. These flood disasters in Brazil associated with climate phenomena may increase due to warmer SST trend under the global warming stress.

Solar energy potential in the United Arab Emirates

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

Khalil, A.; Alnajjar, A.

1995-12-31

In the present study, the global, direct and diffuse components of solar radiation as well as temperature, relative humidity and wind speed have been continuously monitored and analyzed on hourly, daily and monthly basis. Experimental data is compared to the predictions of different theoretical models as functions of declination and hour angles. Correlations are obtained describing the variation of hourly, daily and monthly averages of total and diffuse solar radiation using polynomial expressions. Empirical correlations describing the dependence of the daily average diffuse to total radiation ratio on the clearness index are also obtained. Data of daily diffuse to totalmore » radiation ratio is compared to correlations obtained by other investigators. The comparison shows a reasonable agreement with some scatter due to the seasonal dependence of the correlation. Comparison of calculations with experimental measurements under clear sky conditions show excellent agreement with a maximum error of 8%. The measured ratio of hourly to daily insolation is in excellent agreement with the model of Hottel which is expressed as a function of the clearness index, hour and the sunset hour angles.« less

Using Seasonal Forecasts for medium-term Electricity Demand Forecasting on Italy

NASA Astrophysics Data System (ADS)

De Felice, M.; Alessandri, A.; Ruti, P.

2012-12-01

Electricity demand forecast is an essential tool for energy management and operation scheduling for electric utilities. In power engineering, medium-term forecasting is defined as the prediction up to 12 months ahead, and commonly is performed considering weather climatology and not actual forecasts. This work aims to analyze the predictability of electricity demand on seasonal time scale, considering seasonal samples, i.e. average on three months. Electricity demand data has been provided by Italian Transmission System Operator for eight different geographical areas, in Fig. 1 for each area is shown the average yearly demand anomaly for each season. This work uses data for each summer during 1990-2010 and all the datasets have been pre-processed to remove trends and reduce the influence of calendar and economic effects. The choice of focusing this research on the summer period is due to the critical peaks of demand that power grid is subject during hot days. Weather data have been included considering observations provided by ECMWF ERA-INTERIM reanalyses. Primitive variables (2-metres temperature, pressure, etc) and derived variables (cooling and heating degree days) have been averaged for summer months. A particular attention has been given to the influence of persistence of positive temperature anomaly and a derived variable which count the number of consecutive days of extreme-days has been used. Electricity demand forecast has been performed using linear and nonlinear regression methods and stepwise model selection procedures have been used to perform a variable selection with respect to performance measures. Significance tests on multiple linear regression showed the importance of cooling degree days during summer in the North-East and South of Italy with an increase of statistical significance after 2003, a result consistent with the diffusion of air condition and ventilation equipment in the last decade. Finally, using seasonal climate forecasts we evaluate the performances of electricity demand forecast performed with predicted variables on Italian regions with encouraging results on the South of Italy. This work gives an initial assessment on the predictability of electricity demand on seasonal time scale, evaluating the relevance of climate information provided by seasonal forecasts for electricity management during high-demand periods.;

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

40 CFR 421.265 - Pretreatment standards for existing sources.

Code of Federal Regulations, 2010 CFR

2010-07-01

... day Maximum for monthly average mg/troy ounce of precious metals, including silver, incinerated or... Pollutant or pollutant property Maximum for any 1 day Maximum for monthly average mg/troy ounce of precious... Maximum for any 1 day Maximum for monthly average mg/troy ounce of gold produced by cyanide stripping...

20 CFR 404.232 - Computing your average monthly wage under the guaranteed alternative.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Computing your average monthly wage under the... OLD-AGE, SURVIVORS AND DISABILITY INSURANCE (1950- ) Computing Primary Insurance Amounts Guaranteed Alternative for People Reaching Age 62 After 1978 But Before 1984 § 404.232 Computing your average monthly...

Long-term patterns of air temperatures, daily temperature range, precipitation, grass-reference evapotranspiration and aridity index in the USA great plains: Part II. Temporal trends

NASA Astrophysics Data System (ADS)

Kukal, M.; Irmak, S.

2016-11-01

Detection of long-term changes in climate variables over large spatial scales is a very important prerequisite to the development of effective mitigation and adaptation measures for the future potential climate change and for developing strategies for future hydrologic balance analyses under changing climate. Moreover, there is a need for effective approaches of providing information about these changes to decision makers, water managers and stakeholders to aid in efficient implementation of the developed strategies. This study involves computation, mapping and analyses of long-term (1968-2013) county-specific trends in annual, growing-season (1st May-30th September) and monthly air temperatures [(maximum (Tmax), minimum (Tmin) and average (Tavg)], daily temperature range (DTR), precipitation, grass reference evapotranspiration (ETo) and aridity index (AI) over the USA Great Plains region using datasets from over 800 weather station sites. Positive trends in annual Tavg, Tmax and Tmin, DTR, precipitation, ETo and AI were observed in 71%, 89%, 85%, 31%, 61%, 38% and 66% of the counties in the region, respectively, whereas these proportions were 48%, 89%, 62%, 20%, 57%, 28%, and 63%, respectively, for the growing-season averages of the same variables. On a regional average basis, the positive trends in growing-season Tavg, Tmax and Tmin, DTR, precipitation, ETo and AI were 0.18 °C decade-1, 0.19 °C decade-1, 0.17 °C decade-1, 0.09 °C decade-1, 1.12 mm yr-1, 0.4 mm yr-1 and 0.02 decade-1, respectively, and the negative trends were 0.21 °C decade-1, 0.06 °C decade-1, 0.09 °C decade-1, 0.22 °C decade-1, 1.16 mm yr-1, 0.76 mm yr-1 and 0.02 decade-1, respectively. The temporal trends were highly variable in space and were appropriately represented using monthly, annual and growing-season maps developed using Geographic Information System (GIS) techniques. The long-term and spatial and temporal information and data for a large region provided in this study can be used to analyze county-level trends in important climatic/hydrologic variables in context of climate change, water resources, agricultural and natural resources response to climate change.

Drought analysis and water resource availability using standardised precipitation evapotranspiration index

NASA Astrophysics Data System (ADS)

Hui-Mean, Foo; Yusop, Zulkifli; Yusof, Fadhilah

2018-03-01

Trend analysis for potential evapotranspiration (PET) and climatic water balance (CWB) is critical in identifying the wetness or dryness episodes with respect to the water surplus or deficit. The PET is computed based on the monthly average temperature for the entire Peninsular Malaysia using Thornthwaite parameterization. The trends and slope's magnitude for the PET and CWB were then investigated using Mann-Kendall, Spearman's rho tests and Thiel-Sen estimator. The 1-, 3-, 6- and 12-month standardised precipitation evapotranspiration index (SPEI) is applied to determine the drought episodes and the average recurrence interval are calculated based on the SPEI. The results indicate that most of the stations show an upward trend in annual and monthly PET while majority of the regions show an upward trend in annual CWB except for the Pahang state. The increasing trends detected in the CWB describe water is in excess especially during the northeast monsoons while the decreasing trends imply water insufficiency. The excess water is observed mostly in January especially in the west coast, east coast and southwest regions that suggest more water is available for crop requirement. The average recurrence interval for drought episodes is almost the same for the smaller severity with various time scale of SPEI and high probability of drought occurrence is observed for some regions. The findings are useful for policymakers and practitioners to improve water resources planning and management, in particular to minimise drought effects in the future. Future research shall address the influence of topography on drought behaviour using more meteorological stations and to include east Malaysia in the analysis.

One-year delayed effect of fog on malaria transmission: a time-series analysis in the rain forest area of Mengla County, south-west China

PubMed Central

Tian, Linwei; Bi, Yan; Ho, Suzanne C; Liu, Wenjie; Liang, Song; Goggins, William B; Chan, Emily YY; Zhou, Shuisen; Sung, Joseph JY

2008-01-01

Background Malaria is a major public health burden in the tropics with the potential to significantly increase in response to climate change. Analyses of data from the recent past can elucidate how short-term variations in weather factors affect malaria transmission. This study explored the impact of climate variability on the transmission of malaria in the tropical rain forest area of Mengla County, south-west China. Methods Ecological time-series analysis was performed on data collected between 1971 and 1999. Auto-regressive integrated moving average (ARIMA) models were used to evaluate the relationship between weather factors and malaria incidence. Results At the time scale of months, the predictors for malaria incidence included: minimum temperature, maximum temperature, and fog day frequency. The effect of minimum temperature on malaria incidence was greater in the cool months than in the hot months. The fog day frequency in October had a positive effect on malaria incidence in May of the following year. At the time scale of years, the annual fog day frequency was the only weather predictor of the annual incidence of malaria. Conclusion Fog day frequency was for the first time found to be a predictor of malaria incidence in a rain forest area. The one-year delayed effect of fog on malaria transmission may involve providing water input and maintaining aquatic breeding sites for mosquitoes in vulnerable times when there is little rainfall in the 6-month dry seasons. These findings should be considered in the prediction of future patterns of malaria for similar tropical rain forest areas worldwide. PMID:18565224

Globally Averaged Atmospheric CFC-11 Concentrations: Monthly and Annual Data for the Period 1975-1992 (DB1010)

DOE Data Explorer

Khalil, M. A.K. [Oregon Graduate Institute of Science and Technology Portland, Oregon (USA); Rasmussen, R. A. [Oregon Graduate Institute of Science and Technology Portland, Oregon

1996-01-01

This data set presents globally averaged atmospheric concentrations of chlorofluorocarbon 11, known also as CFC-11 or F-11 (chemical name: trichlorofluoromethane; formula: CCl3F). The monthly global average data are derived from flask air samples collected at eight sites in six locations over the period August 1980-July 1992. The sites are Barrow (Alaska), Cape Meares (Oregon), Cape Kumukahi and Mauna Loa (Hawaii), Cape Matatula (American Samoa), Cape Grim (Tasmania), Palmer Station, and the South Pole (Antarctica). At each collection site, monthly averages were obtained from three flask samples collected every week. In addition to the monthly global averages available for 1980-992, this data set also contains annual global average data for 1975-1985. These annual global averages were derived from January measurements at the South Pole and in the Pacific Northwest of the United States (specifically, Washington state and the Oregon coast).

Examination of snowmelt over Western Himalayas using remote sensing data

NASA Astrophysics Data System (ADS)

Tiwari, Sarita; Kar, Sarat C.; Bhatla, R.

2016-07-01

Snowmelt variability in the Western Himalayas has been examined using remotely sensed snow water equivalent (SWE) and snow-covered area (SCA) datasets. It is seen that climatological snowfall and snowmelt amount varies in the Himalayan region from west to east and from month to month. Maximum snowmelt occurs at the elevation zone between 4500 and 5000 m. As the spring and summer approach and snowmelt begins, a large amount of snow melts in May. Strength and weaknesses of temperature-based snowmelt models have been analyzed for this region by computing the snowmelt factor or the degree-day factor (DDF). It is seen that average DDF in the Himalayas is more in April and less in July. During spring and summer months, melting rate is higher in the areas that have height above 2500 m. The region that lies between 4500 and 5000 m elevation zones contributes toward more snowmelt with higher melting rate. Snowmelt models have been developed to estimate interannual variations of monthly snowmelt amount using the DDF, observed SWE, and surface air temperature from reanalysis datasets. In order to further improve the estimate snowmelt, regression between observed and modeled snowmelt has been carried out and revised DDF values have been computed. It is found that both the models do not capture the interannual variability of snowmelt in April. The skill of the model is moderate in May and June, but the skill is relatively better in July. In order to explain this skill, interannual variability (IAV) of surface air temperature has been examined. Compared to July, in April, the IAV of temperature is large indicating that a climatological value of DDF is not sufficient to explain the snowmelt rate in April. Snow area and snow amount depletion curves over Himalayas indicate that in a small area at high altitude, snow is still observed with large SWE whereas over most of the region, all the snow has melted.

Climatological Modeling of Monthly Air Temperature and Precipitation in Egypt through GIS Techniques

NASA Astrophysics Data System (ADS)

El Kenawy, A.

2009-09-01

This paper describes a method for modeling and mapping four climatic variables (maximum temperature, minimum temperature, mean temperature and total precipitation) in Egypt using a multiple regression approach implemented in a GIS environment. In this model, a set of variables including latitude, longitude, elevation within a distance of 5, 10 and 15 km, slope, aspect, distance to the Mediterranean Sea, distance to the Red Sea, distance to the Nile, ratio between land and water masses within a radius of 5, 10, 15 km, the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Water Index (NDWI), the Normalized Difference Temperature Index (NDTI) and reflectance are included as independent variables. These variables were integrated as raster layers in MiraMon software at a spatial resolution of 1 km. Climatic variables were considered as dependent variables and averaged from quality controlled and homogenized 39 series distributing across the entire country during the period of (1957-2006). For each climatic variable, digital and objective maps were finally obtained using the multiple regression coefficients at monthly, seasonal and annual timescale. The accuracy of these maps were assessed through cross-validation between predicted and observed values using a set of statistics including coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), mean bias Error (MBE) and D Willmott statistic. These maps are valuable in the sense of spatial resolution as well as the number of observatories involved in the current analysis.

Climate variation and incidence of Ross river virus in Cairns, Australia: a time-series analysis.

PubMed Central

Tong, S; Hu, W

2001-01-01

In this study we assessed the impact of climate variability on the Ross River virus (RRv) transmission and validated an epidemic-forecasting model in Cairns, Australia. Data on the RRv cases recorded between 1985 and 1996 were obtained from the Queensland Department of Health. Climate and population data were supplied by the Australian Bureau of Meteorology and the Australian Bureau of Statistics, respectively. The cross-correlation function (CCF) showed that maximum temperature in the current month and rainfall and relative humidity at a lag of 2 months were positively and significantly associated with the monthly incidence of RRv, whereas relative humidity at a lag of 5 months was inversely associated with the RRv transmission. We developed autoregressive integrated moving average (ARIMA) models on the data collected between 1985 to 1994, and then validated the models using the data collected between 1995 and 1996. The results show that the relative humidity at a lag of 5 months (p < 0.001) and the rainfall at a lag of 2 months (p < 0.05) appeared to play significant roles in the transmission of RRv disease in Cairns. Furthermore, the regressive forecast curves were consistent with the pattern of actual values. PMID:11748035

High Frequency Data Acquisition System for Modelling the Impact of Visitors on the Thermo-Hygrometric Conditions of Archaeological Sites: A Casa di Diana (Ostia Antica, Italy) Case Study.

PubMed

Merello, Paloma; García-Diego, Fernando-Juan; Beltrán, Pedro; Scatigno, Claudia

2018-01-25

The characterization of the microclimatic conditions is fundamental for the preventive conservation of archaeological sites. In this context, the identification of the factors that influence the thermo-hygrometric equilibrium is key to determine the causes of cultural heritage deterioration. In this work, a characterization of the thermo-hygrometric conditions of Casa di Diana (Ostia Antica, Italy) is carried out analyzing the data of temperature and relative humidity recorded by a system of sensors with high monitoring frequency. Sensors are installed in parallel, calibrated and synchronized with a microcontroller. A data set of 793,620 data, arranged in a matrix with 66,135 rows and 12 columns, was used. Furthermore, the influence of human impact (visitors) is evaluated through a multiple linear regression model and a logistic regression model. The visitors do not affect the environmental humidity as it is very high and constant all the year. The results show a significant influence of the visitors in the upset of the thermal balance. When a tourist guide takes place, the probability that the hourly temperature variation reaches values higher than its monthly average is 10.64 times higher than it remains equal or less to its monthly average. The analysis of the regression residuals shows the influence of outdoor climatic variables in the thermal balance, such as solar radiation or ventilation.

Towards custom made seasonal/decadal forecasting

NASA Astrophysics Data System (ADS)

Mahlstein, Irina; Spirig, Christoph; Liniger, Mark

2014-05-01

Climate indices offer the possibility to deliver information to the end user that can be easily applied to their field of work. For instance, a 3-monthly mean average temperature does not say much about the Heating Degree Days of a season, or how many frost days there are to be expected. Hence, delivering aggregated climate information can be more useful to the consumer than just raw data. In order to ensure that the end-users actually get what they need, the providers need to know what exactly they need to deliver. Hence, the specific user-needs have to be identified. In the framework of EUPORIAS, interviews with the end-user were conducted in order to learn more about the types of information that are needed. But also to investigate what knowledge exists among the users about seasonal/decadal forecasting and in what way uncertainties are taken into account. It is important that we gain better knowledge of how forecasts/predictions are applied by the end-user to their specific situation and business. EUPORIAS, which is embedded in the framework of EU FP7, aims exactly to improve that knowledge and deliver very specific forecasts that are custom made. Here we present examples of seasonal forecasts and their skill of several climate impact indices with direct relevance for specific economic sectors, such as energy. The results are compared to the visualization of conventional depiction of seasonal forecasts, such as 3 monthly average temperature tercile probabilities and the differences are highlighted.

High Frequency Data Acquisition System for Modelling the Impact of Visitors on the Thermo-Hygrometric Conditions of Archaeological Sites: A Casa di Diana (Ostia Antica, Italy) Case Study

PubMed Central

Merello, Paloma; García-Diego, Fernando-Juan; Beltrán, Pedro; Scatigno, Claudia

2018-01-01

The characterization of the microclimatic conditions is fundamental for the preventive conservation of archaeological sites. In this context, the identification of the factors that influence the thermo-hygrometric equilibrium is key to determine the causes of cultural heritage deterioration. In this work, a characterization of the thermo-hygrometric conditions of Casa di Diana (Ostia Antica, Italy) is carried out analyzing the data of temperature and relative humidity recorded by a system of sensors with high monitoring frequency. Sensors are installed in parallel, calibrated and synchronized with a microcontroller. A data set of 793,620 data, arranged in a matrix with 66,135 rows and 12 columns, was used. Furthermore, the influence of human impact (visitors) is evaluated through a multiple linear regression model and a logistic regression model. The visitors do not affect the environmental humidity as it is very high and constant all the year. The results show a significant influence of the visitors in the upset of the thermal balance. When a tourist guide takes place, the probability that the hourly temperature variation reaches values higher than its monthly average is 10.64 times higher than it remains equal or less to its monthly average. The analysis of the regression residuals shows the influence of outdoor climatic variables in the thermal balance, such as solar radiation or ventilation. PMID:29370142

Prevalence rates of health and welfare conditions in broiler chickens change with weather in a temperate climate.

PubMed

Part, Chérie E; Edwards, Phil; Hajat, Shakoor; Collins, Lisa M

2016-09-01

Climate change impact assessment and adaptation research in agriculture has focused primarily on crop production, with less known about the potential impacts on livestock. We investigated how the prevalence of health and welfare conditions in broiler (meat) chickens changes with weather (temperature, rainfall, air frost) in a temperate climate. Cases of 16 conditions were recorded at approved slaughterhouses in Great Britain. National prevalence rates and distribution mapping were based on data from more than 2.4 billion individuals, collected between January 2011 and December 2013. Analysis of temporal distribution and associations with national weather were based on monthly data from more than 6.8 billion individuals, collected between January 2003 and December 2013. Ascites, bruising/fractures, hepatitis and abnormal colour/fever were most common, at annual average rates of 29.95, 28.00, 23.76 and 22.29 per 10 000, respectively. Ascites and abnormal colour/fever demonstrated clear annual cycles, with higher rates in winter than in summer. Ascites prevalence correlated strongly with maximum temperature at 0 and -1 month lags. Abnormal colour/fever correlated strongly with temperature at 0 lag. Maximum temperatures of approximately 8°C and approximately 19°C marked the turning points of curve in a U-shaped relationship with mortality during transportation and lairage. Future climate change research on broilers should focus on preslaughter mortality.

Prevalence rates of health and welfare conditions in broiler chickens change with weather in a temperate climate

PubMed Central

Edwards, Phil; Hajat, Shakoor

2016-01-01

Climate change impact assessment and adaptation research in agriculture has focused primarily on crop production, with less known about the potential impacts on livestock. We investigated how the prevalence of health and welfare conditions in broiler (meat) chickens changes with weather (temperature, rainfall, air frost) in a temperate climate. Cases of 16 conditions were recorded at approved slaughterhouses in Great Britain. National prevalence rates and distribution mapping were based on data from more than 2.4 billion individuals, collected between January 2011 and December 2013. Analysis of temporal distribution and associations with national weather were based on monthly data from more than 6.8 billion individuals, collected between January 2003 and December 2013. Ascites, bruising/fractures, hepatitis and abnormal colour/fever were most common, at annual average rates of 29.95, 28.00, 23.76 and 22.29 per 10 000, respectively. Ascites and abnormal colour/fever demonstrated clear annual cycles, with higher rates in winter than in summer. Ascites prevalence correlated strongly with maximum temperature at 0 and −1 month lags. Abnormal colour/fever correlated strongly with temperature at 0 lag. Maximum temperatures of approximately 8°C and approximately 19°C marked the turning points of curve in a U-shaped relationship with mortality during transportation and lairage. Future climate change research on broilers should focus on preslaughter mortality. PMID:27703686

High-resolution spatial databases of monthly climate variables (1961-2010) over a complex terrain region in southwestern China

NASA Astrophysics Data System (ADS)

Wu, Wei; Xu, An-Ding; Liu, Hong-Bin

2015-01-01

Climate data in gridded format are critical for understanding climate change and its impact on eco-environment. The aim of the current study is to develop spatial databases for three climate variables (maximum, minimum temperatures, and relative humidity) over a large region with complex topography in southwestern China. Five widely used approaches including inverse distance weighting, ordinary kriging, universal kriging, co-kriging, and thin-plate smoothing spline were tested. Root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) showed that thin-plate smoothing spline with latitude, longitude, and elevation outperformed other models. Average RMSE, MAE, and MAPE of the best models were 1.16 °C, 0.74 °C, and 7.38 % for maximum temperature; 0.826 °C, 0.58 °C, and 6.41 % for minimum temperature; and 3.44, 2.28, and 3.21 % for relative humidity, respectively. Spatial datasets of annual and monthly climate variables with 1-km resolution covering the period 1961-2010 were then obtained using the best performance methods. Comparative study showed that the current outcomes were in well agreement with public datasets. Based on the gridded datasets, changes in temperature variables were investigated across the study area. Future study might be needed to capture the uncertainty induced by environmental conditions through remote sensing and knowledge-based methods.

Climate Change and ENSO Effects on Southeastern US Climate Patterns and Maize Yield.

PubMed

Mourtzinis, Spyridon; Ortiz, Brenda V; Damianidis, Damianos

2016-07-19

Climate change has a strong influence on weather patterns and significantly affects crop yields globally. El Niño Southern Oscillation (ENSO) has a strong influence on the U.S. climate and is related to agricultural production variability. ENSO effects are location-specific and in southeastern U.S. strongly connect with climate variability. When combined with climate change, the effects on growing season climate patterns and crop yields might be greater than expected. In our study, historical monthly precipitation and temperature data were coupled with non-irrigated maize yield data (33-43 years depending on the location) to show a potential yield suppression of ~15% for one °C increase in southeastern U.S. growing season maximum temperature. Yield suppression ranged between -25 and -2% among locations suppressing the southeastern U.S. average yield trend since 1981 by 17 kg ha(-1)year(-1) (~25%), mainly due to year-to-year June temperature anomalies. Yields varied among ENSO phases from 1971-2013, with greater yields observed during El Niño phase. During La Niña years, maximum June temperatures were higher than Neutral and El Niño, whereas June precipitation was lower than El Niño years. Our data highlight the importance of developing location-specific adaptation strategies quantifying both, climate change and ENSO effects on month-specific growing season climate conditions.

Climate variables as predictors for seasonal forecast of dengue occurrence in Chennai, Tamil Nadu

NASA Astrophysics Data System (ADS)

Subash Kumar, D. D.; Andimuthu, R.

2013-12-01

Background Dengue is a recently emerging vector borne diseases in Chennai. As per the WHO report in 2011 dengue is one of eight climate sensitive disease of this century. Objective Therefore an attempt has been made to explore the influence of climate parameters on dengue occurrence and use for forecasting. Methodology Time series analysis has been applied to predict the number of dengue cases in Chennai, a metropolitan city which is the capital of Tamil Nadu, India. Cross correlation of the climate variables with dengue cases revealed that the most influential parameters were monthly relative humidity, minimum temperature at 4 months lag and rainfall at one month lag (Table 1). However due to intercorrelation of relative humidity and rainfall was high and therefore for predictive purpose the rainfall at one month lag was used for the model development. Autoregressive Integrated Moving Average (ARIMA) models have been applied to forecast the occurrence of dengue. Results and Discussion The best fit model was ARIMA (1,0,1). It was seen that the monthly minimum temperature at four months lag (β= 3.612, p = 0.02) and rainfall at one month lag (β= 0.032, p = 0.017) were associated with dengue occurrence and they had a very significant effect. Mean Relative Humidity had a directly significant positive correlation at 99% confidence level, but the lagged effect was not prominent. The model predicted dengue cases showed significantly high correlation of 0.814(Figure 1) with the observed cases. The RMSE of the model was 18.564 and MAE was 12.114. The model is limited by the scarcity of the dataset. Inclusion of socioeconomic conditions and population offset are further needed to be incorporated for effective results. Conclusion Thus it could be claimed that the change in climatic parameters is definitely influential in increasing the number of dengue occurrence in Chennai. The climate variables therefore can be used for seasonal forecasting of dengue with rise in minimum temperature and rainfall at a city level. Table 1. Cross correlation of climate variables with dengue cases in Chennai ** p<0.01,*p<0.05

[Size-based classification of choroidal melanoma and its role in treatment decision-making].

PubMed

Brovkina, A F; Stoyukhina, A S; Chesalin, I P

2016-01-01

To specify indications for brachytherapy (BT) in large choroidal melanoma (CM) so that tumor size and vital prognosis were considered. We retrospectively analyzed data from 161 CM patients who were treated with BT and followed-up at either the Ophthalmological Clinical Hospital or some other Moscow medical facility and also registered by the City Cancer Registry. Patient age at the time of starting the treatment lied within the range of 17 to 84 years and averaged 56.89±1.93 years. During the follow-up period (12-275 months, 95.65±8.4 months on average) hematogenous metastases were found in 23 (14.29%) patients. Liver involvement was diagnosed in 8 patients within the average of 23.13 months after treatment. Their average survival time was 11 months. A total of 142 patients were followed up for more than 36 months (104.87 months on average). Of them, 15 patients were diagnosed with metastatic CM within 37-167 months after BT (80.27 months on average). Despite metastatic disease they generally survived 2.8 time longer than the aforementioned patients (30.8 months). The cases were then divided into 3 groups according to J. Shields classification of CM. Small melanoma patients did not develop metastases within 99.96±12.47 months of follow-up. In medium melanomas, as many as 13.35% of cases were metastatic (with the average survival time of 20.66 months); in large melanomas - 19.51% (with the average survival time of 13.5 months). Treatment modality and follow-up periods being the same (7-8 years after BT), larger choroidal melanomas has been shown to be associated with higher risk of hematogenous metastases. For local treatment to be successive, the maximal diameter of the tumor should not exceed 10 mm. Every fifth patient of those with CM larger than 15 mm is likely to develop hematogenous metastases. The results obtained indicate the necessity of decreasing the size thresholds for choroidal melanomas, small and medium in the first place.

The effect of ambient temperature on infrared thermographic images of joints in the distal forelimbs of healthy racehorses.

PubMed

Soroko, Maria; Howell, Kevin; Dudek, Krzysztof

2017-05-01

The aim of the study was to describe the dependence on ambient temperature of distal joint temperature at the forelimbs of racehorses. The study also investigated the influence of differing ambient temperatures on the temperature difference between joints: this was measured ipsilaterally (i.e. between the carpal and fetlock joints along each forelimb) and contralaterally (i.e. between the same joints of the left and right forelimbs). Sixty-four healthy racehorses were monitored over 10 months. At each session, three thermographic images were taken of the dorsal, lateral and medial aspects of the distal forelimbs. Temperature measurements were made from regions of interest (ROIs) covering the carpal and fetlock joints. There was a strong correlation between ambient temperature and absolute joint temperature at all ROIs. The study also observed a moderate correlation between ambient temperature and the ipsilateral temperature differences between joints when measured from the medial and lateral aspects. No significant correlation was noted when measured dorsally. The mean contralateral temperature differences between joints were all close to 0°C. The data support previous reports that the temperature distribution between the forelimbs of the healthy equine is generally symmetric, although some horses differ markedly from the average findings. Copyright © 2017 Elsevier Ltd. All rights reserved.

Selected meteorological data for an arid site near Beatty, Nye County, Nevada, calendar year 1988

USGS Publications Warehouse

Wood, James L.; Hill, Kevin J.; Andraski, Brian J.

1992-01-01

Selected meteorological data were collected at a study site adjacent to a low-level radioactive-waste burial facility near Beatty/ Nevada, for calendar year 1988. Data were collected in support of ongoing studies to estimate the potential for downward movement of radionuclides into the unsaturated sediments beneath waste-burial trenches at the facility. The data include air temperature, relative humidity, vapor pressure, incident solar radiation, windspeed, wind direction, and precipitation. The data are summarized in tables and graphs.Instrumentation used at the site is discussed. The discussion includes the type, reported accuracy, and mounting height of each sensor.In 1988, the average hourly air temperatures ranged from -10.2 degrees Celsius, in December, to 45.3 degrees Celsius, in July. Hourly averaged relative humidity ranged from about 12 percent to over 80 percent. Hourly vapor pressures ranged from 0.09 to 2.22 kilopascals. Daily values for maximum incident solar radiation ranged from 63 to 1,064 watts per square meter. Daily mean windspeed ranged from 1.2 to 7.8 meters per second. Monthly wind-direction patterns are shown in a series of diagrams in which wind direction is summed over 10-degree arcs from hourly averaged data. Total precipitation for 1988 was 104.5 millimeters, with over 70 percent occurring from January through May.

Thermal Performance of LANDSAT-7 ETM+ Instruments During First Year in Flight

NASA Technical Reports Server (NTRS)

Choi, Michael K.

2000-01-01

Landsat-7 was successfully launched into orbit on April 15, 1999. After devoting three months to the t bakeout and cool-down of the radiative cooler, and on- t orbit checkout, the Enhanced Thematic Mapper Plus (ETM+) began the normal imaging phase of the mission in mid-July 1999. This paper presents the thermal performance of the ETM+ from mid-July 1999 to mid-May 2000. The flight temperatures are compared to the yellow temperature limits, and worst cold case and worst hot case flight temperature predictions in the 15-orbit mission design profile. The flight temperature predictions were generated by a thermal model, which was correlated to the observatory thermal balance test data. The yellow temperature limits were derived from the flight temperature predictions, plus some margins. The yellow limits work well in flight, so that only several minor changes to them were needed. Overall, the flight temperatures and flight temperature predictions have good agreement. Based on the ETM+ thermal vacuum qualification test, new limits on the imaging time are proposed to increase the average duty cycle, and to resolve the problems experienced by the Mission Operation Team.

Monthly and Seasonal Cloud Cover Patterns at the Manila Observatory (14.64°N, 121.08°E)

NASA Astrophysics Data System (ADS)

Antioquia, C. T.; Lagrosas, N.; Caballa, K.

2014-12-01

A ground based sky imaging system was developed at the Manila Observatory in 2012 to measure cloud occurrence and to analyse seasonal variation of cloud cover over Metro Manila. Ground-based cloud occurrence measurements provide more reliable results compared to satellite observations. Also, cloud occurrence data aid in the analysis of radiation budget in the atmosphere. In this study, a GoPro Hero 2 with almost 180o field of view is employed to take pictures of the atmosphere. These pictures are taken continuously, having a temporal resolution of 1min. Atmospheric images from April 2012 to June 2013 (excluding the months of September, October, and November 2012) were processed to determine cloud cover. Cloud cover in an image is measured as the ratio of the number of pixels with clouds present in them to the total number of pixels. The cloud cover values were then averaged over each month to know its monthly and seasonal variation. In Metro Manila, the dry season occurs in the months of November to May of the next year, while the wet season occurs in the months of June to October of the same year. Fig 1 shows the measured monthly variation of cloud cover. No data was collected during the months of September (wherein the camera was used for the 7SEAS field campaign), October, and November 2012 (due to maintenance and repairs). Results show that there is high cloud cover during the wet season months (80% on average) while there is low cloud cover during the dry season months (62% on average). The lowest average cloud cover for a wet season month occurred in June 2012 (73%) while the highest average cloud cover for a wet season month occurred in June 2013 (86%). The variations in cloud cover average in this season is relatively smaller compared to that of the dry season wherein the lowest average cloud cover in a month was during April 2012 (38%) while the highest average cloud cover in a month was during January 2013 (77%); minimum and maximum averages being 39% apart. During the wet season, the cloud occurrence is mainly due to tropical storms, Southwest Monsoon, and local convection processes. In the dry season, less cloud is formed because of cold dry air from Northeast Monsoon (December to February) and generally dry and hot weather (March to May). Regular data collection has been implemented for further long term data analysis.

One Hundred Years of New York City's "Urban Heat Island": Temperature Trends and Public Health Impacts

NASA Astrophysics Data System (ADS)

Rosenthal, J. E.; Knowlton, K. M.; Rosenzweig, C.; Goldberg, R.; Kinney, P. L.

2003-12-01

In this paper, we examine the relationship between the historical development of New York City and its effect on the urban climate. Urban "heat islands" (UHI) are created principally by man-made surfaces, including concrete, dark roofs, asphalt lots and roads, which absorb most of the sunlight falling on them and reradiate that energy as heat. Many urban streets have fewer trees and other vegetation to shade buildings, block solar radiation and cool the air by evapotranspiration. The historical development of the NYC heat island effect was assessed in terms of average temperature differences of the city center relative to its surrounding 31-county metropolitan region, comprised of parts of New York State, New Jersey, and Connecticut. Monthly maximum and minimum temperatures for 1900-1997 were obtained from NOAA's National Climatic Data Center, the NASA-Goddard Institute for Space Studies, and the Lamont-Doherty Earth Observatory of Columbia University for 24 weather stations within the region that are part of the U.S. Historical Climatology Network. Analysis of annual mean temperatures shows an increasing difference between NYC (Central Park weather station) and its surrounding region over the twentieth century. Analysis of the temperature differences over time between NY Central Park (NYCP) station and 23 regional weather stations classified according to distance and level of urbanization show a heat island effect existing in NYC, with mean temperatures in the NYCP Station generally higher than the surrounding stations, ranging from 1.20\\deg C to 3.02\\deg C. A difference of at least 1\\deg C already existed at the beginning of the 20th century between the mean temperature in NYC and its surrounding rural areas, and this difference increased over the twentieth century. There was a significant decrease in the monthly and seasonal variability of the UHI effect over the century. Temperature extremes and summertime heat can create heat stress and other health consequences for urban residents. Public health impacts are assessed as the proportion of heat-related regional mortality estimated to be attributable to New York City's heat island effect during an average 1990's summer. Concentration-response functions describing the temperature-mortality relationship in NYC derived from the epidemiological literature are used to estimate numbers of deaths in a typical 1990s summer and those attributable to the city's heat island effect. The techniques and potential public health benefits of a pilot project to mitigate the heat island effect in NYC will be discussed.

Effect of Climate Factors on the Childhood Pneumonia in Papua New Guinea: A Time-Series Analysis.

PubMed

Kim, Jinseob; Kim, Jong-Hun; Cheong, Hae-Kwan; Kim, Ho; Honda, Yasushi; Ha, Mina; Hashizume, Masahiro; Kolam, Joel; Inape, Kasis

2016-02-15

This study aimed to assess the association between climate factors and the incidence of childhood pneumonia in Papua New Guinea quantitatively and to evaluate the variability of the effect size according to their geographic properties. The pneumonia incidence in children under five-year and meteorological factors were obtained from six areas, including monthly rainfall and the monthly average daily maximum temperatures during the period from 1997 to 2006 from national health surveillance data. A generalized linear model was applied to measure the effect size of local and regional climate factor. The pooled risk of pneumonia in children per every 10 mm increase of rainfall was 0.24% (95% confidence interval: -0.01%-0.50%), and risk per every 1 °C increase of the monthly mean of the maximum daily temperatures was 4.88% (95% CI: 1.57-8.30). Southern oscillation index and dipole mode index showed an overall negative effect on childhood pneumonia incidence, -0.57% and -4.30%, respectively, and the risk of pneumonia was higher in the dry season than in the rainy season (pooled effect: 12.08%). There was a variability in the relationship between climate factors and pneumonia which is assumed to reflect distribution of the determinants of and vulnerability to pneumonia in the community.

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.

Changes in winter air temperatures near Lake Michigan, 1851-1993, as determined from regional lake-ice records

USGS Publications Warehouse

Assel, R.A.; Robertson, Dale M.

1995-01-01

Records of freezeup and breakup dates for Grand Traverse Bay, Michigan, and Lake Mendota, Wisconsin, are among the longest ice records available near the Great Lakes, beginning in 185 1 and 1855, respectively. The timing of freezeup and breakup results from an integration of meteorological conditions (primarily air temperature) that occur before these events. Changes in the average timing of these ice-events are translated into changes in air temperature by the use of empirical and process-driven models. The timing of freezeup and breakup at the two locations represents an integration of air temperatures over slightly different seasons (months). Records from both locations indicate that the early winter period before about 1890 was - 15°C cooler than the early winter period after that time; the mean temperature has, however, remained relatively constant since about 1890. Changes in breakup dates demonstrate a similar 1.0-1 .5”C increase in late winter and early spring air temperatures about 1890. More recent average breakup dates at both locations have been earlier than during 1890-1940, indicating an additional warming of 1.2”C in March since about 1940 and a warming of 1 . 1°C in January-March since about 1980. Ice records at these sites will continue to provide an early indication of the anticipated climatic warming, not only because of the large response of ice cover to small changes in air temperature but also because these records integrate climatic conditions during the seasons (winter-spring) when most warming is forecast to occur. Future reductions in ice cover may strongly affect the winter ecology of the Great Lakes by reducing the stable environment required by various levels of the food chain. 

Measuring the global distribution of intense convection over land with passive microwave radiometry

NASA Technical Reports Server (NTRS)

Spencer, R. W.; Santek, D. A.

1985-01-01

The global distribution of intense convective activity over land is shown to be measurable with satellite passive-microwave methods through a comparison of an empirical rain rate algorithm with a climatology of thunderstorm days for the months of June-August. With the 18 and 37 GHz channels of the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR), the strong volume scattering effects of precipitation can be measured. Even though a single frequency (37 GHz) is responsive to the scattering signature, two frequencies are needed to remove most of the effect that variations in thermometric temperatures and soil moisture have on the brightness temperatures. Because snow cover is also a volume scatterer of microwave energy at these microwavelengths, a discrimination procedure involving four of the SMMR channels is employed to separate the rain and snow classes, based upon their differences in average thermometric temperature.

Global Average Brightness Temperature for April 2003

NASA Image and Video Library

2003-06-02

This image shows average temperatures in April, 2003, observed by AIRS at an infrared wavelength that senses either the Earth's surface or any intervening cloud. Similar to a photograph of the planet taken with the camera shutter held open for a month, stationary features are captured while those obscured by moving clouds are blurred. Many continental features stand out boldly, such as our planet's vast deserts, and India, now at the end of its long, clear dry season. Also obvious are the high, cold Tibetan plateau to the north of India, and the mountains of North America. The band of yellow encircling the planet's equator is the Intertropical Convergence Zone (ITCZ), a region of persistent thunderstorms and associated high, cold clouds. The ITCZ merges with the monsoon systems of Africa and South America. Higher latitudes are increasingly obscured by clouds, though some features like the Great Lakes, the British Isles and Korea are apparent. The highest latitudes of Europe and Eurasia are completely obscured by clouds, while Antarctica stands out cold and clear at the bottom of the image. http://photojournal.jpl.nasa.gov/catalog/PIA00427

Using Bayesian Model Averaging (BMA) to calibrate probabilistic surface temperature forecasts over Iran

NASA Astrophysics Data System (ADS)

Soltanzadeh, I.; Azadi, M.; Vakili, G. A.

2011-07-01

Using Bayesian Model Averaging (BMA), an attempt was made to obtain calibrated probabilistic numerical forecasts of 2-m temperature over Iran. The ensemble employs three limited area models (WRF, MM5 and HRM), with WRF used with five different configurations. Initial and boundary conditions for MM5 and WRF are obtained from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) and for HRM the initial and boundary conditions come from analysis of Global Model Europe (GME) of the German Weather Service. The resulting ensemble of seven members was run for a period of 6 months (from December 2008 to May 2009) over Iran. The 48-h raw ensemble outputs were calibrated using BMA technique for 120 days using a 40 days training sample of forecasts and relative verification data. The calibrated probabilistic forecasts were assessed using rank histogram and attribute diagrams. Results showed that application of BMA improved the reliability of the raw ensemble. Using the weighted ensemble mean forecast as a deterministic forecast it was found that the deterministic-style BMA forecasts performed usually better than the best member's deterministic forecast.

Surface-Wind Anomalies in North-Atlantic and North Pacific from SSM/I Observations: Influence on Temperature of Adjoining Land Regions

NASA Technical Reports Server (NTRS)

Otterman, Joseph; Atlas, R.; Ingraham, J.; Ardizzone, J.; Starr, D.; Terry, J.

1998-01-01

Surface winds over the oceans are derived from Special Sensor Microwave Imager (SSM/I) measurements, assigning direction by Variational Analysis Method (VAM). Validations by comparison with other measurements indicate highly-satisfactory data quality. Providing global coverage from 1988, the dataset is a convenient source for surface-wind climatology. In this study, the interannual variability of zonal winds is analyzed concentrating on the westerlies in North Atlantic and North Pacific, above 30 N. Interannual differences in the westerlies exceeding 10 m sec (exp -1) are observed over large regions, often accompanied by changes of the same magnitude in the easterlies below 30 N. We concentrate on February/March, since elevated temperatures, by advancing snow-melt, can produce early spring. The extremely strong westerlies in 1997 observed in these months over North Atlantic (and also North Pacific) apparently contributed to large surface-temperature anomalies in western Europe, on the order of +3 C above the climatic monthly average for England and France. At these latitudes strong positive anomalies extended in a ring around the globe. We formulated an Index of South westerlies for the North Atlantic, which can serve as an indicator for day-by-day advection effects into Europe. In comparing 1997 and 1998 with the previous years, we establish significant correlations with the temperature anomalies (one to five days later, depending on the region, and on the season). This variability of the ocean-surface winds and of the temperature anomalies on land may be related to the El Nino/La Nina oscillations. Such large temperature fluctuations over large areas, whatever the cause, can be regarded as noise in attempts to assess long-term trends in global temperature.

On the occurrence of the coldest region in the stratosphere and tropical tropopause stability: A study using COSMIC/FORMOSAT-3 satellite measurements

NASA Astrophysics Data System (ADS)

Kumar, V.; Dhaka, S. K.; Choudhary, R. K.; Ho, Shu-Peng; Yoden, S.; Reddy, K. K.

2014-12-01

The occurrence of coldest region in the lower and middle stratosphere has been investigated using COSMIC/FORMASAT-3 radio occultation measurements. Observations from January 2007 to December 2011, comprising of 2,871,811 numbers of occultations uniformly spread over land and sea, have been used in this study. Using vertical profiles of temperature upto 40 km altitude, zonally averaged at each 5° latitude band between 90°N and 90°S, it is shown that the coldest region in the upper atmosphere occurs during winter in high latitude stratosphere (latitudes >45°) in both the hemispheres with southern hemisphere (temperature less than <-85 °C) cooler than northern hemisphere (temperature ~-75 °C). The spatial extent of the region of low temperature region found between 10 km and 30 km altitude, indicating a 20 km vertical thick layer of cold temperature. In the southern hemisphere, such a region of coldest temperature remains for more than six months (April-October), in the Northern hemispheric polar region (~-75 °C) it is seen mostly during four winter months between October and January. Using NCEP-DOE reanalysis data, we show that cold temperature in the stratospheric region coexists with the jet streams prevalent in those regions. Strong wind jet is surmised to make stratosphere colder. The absence of sunlight in the coldest region is known to cause jet streams. Impact of stratospheric quasi-biennial oscillation (QBO) on the sharpness of tropical tropopause (stability) has also been investigated. Observations suggest that during westerly phase of QBO, the stability of the tropopause increases.

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 Validity of Two Neuromotor Assessments for Predicting Motor Performance at 12 Months in Preterm Infants.

PubMed

Song, You Hong; Chang, Hyun Jung; Shin, Yong Beom; Park, Young Sook; Park, Yun Hee; Cho, Eun Sol

2018-04-01

To evaluate the validity of the Test of Infant Motor Performance (TIMP) and general movements (GMs) assessment for predicting Alberta Infant Motor Scale (AIMS) score at 12 months in preterm infants. A total of 44 preterm infants who underwent the GMs and TIMP at 1 month and 3 months of corrected age (CA) and whose motor performance was evaluated using AIMS at 12 months CA were included. GMs were judged as abnormal on basis of poor repertoire or cramped-synchronized movements at 1 month CA and abnormal or absent fidgety movement at 3 months CA. TIMP and AIMS scores were categorized as normal (average and low average and >5th percentile, respectively) or abnormal (below average and far below average or <5th percentile, respectively). Correlations between GMs and TIMP scores at 1 month and 3 months CA and the AIMS classification at 12 months CA were examined. The TIMP score at 3 months CA and GMs at 1 month and 3 months CA were significantly correlated with the motor performance at 12 months CA. However, the TIMP score at 1 month CA did not correlate with the AIMS classification at 12 months CA. For infants with normal GMs at 3 months CA, the TIMP score at 3 months CA correlated significantly with the AIMS classification at 12 months CA. Our findings suggest that neuromotor assessment using GMs and TIMP could be useful to identify preterm infants who are likely to benefit from intervention.

Interannual Rainfall Variability in North-East Brazil: Observation and Model Simulation

NASA Astrophysics Data System (ADS)

Harzallah, A.; Rocha de Aragão, J. O.; Sadourny, R.

1996-08-01

The relationship between interannual variability of rainfall in north-east Brazil and tropical sea-surface temperature is studied using observations and model simulations. The simulated precipitation is the average of seven independent realizations performed using the Laboratoire de Météorologie Dynamique atmospheric general model forced by the 1970-1988 observed sea-surface temperature. The model reproduces very well the rainfall anomalies (correlation of 091 between observed and modelled anomalies). The study confirms that precipitation in north-east Brazil is highly correlated to the sea-surface temperature in the tropical Atlantic and Pacific oceans. Using the singular value decomposition method, we find that Nordeste rainfall is modulated by two independent oscillations, both governed by the Atlantic dipole, but one involving only the Pacific, the other one having a period of about 10 years. Correlations between precipitation in north-east Brazil during February-May and the sea-surface temperature 6 months earlier indicate that both modes are essential to estimate the quality of the rainy season.

Comparison of tropospheric NO2 vertical columns in an urban environment using satellite, multi-axis differential optical absorption spectroscopy, and in situ measurements

NASA Astrophysics Data System (ADS)

Mendolia, D.; D'Souza, R. J. C.; Evans, G. J.; Brook, J.

2013-10-01

Tropospheric NO2 vertical column densities have been retrieved and compared for the first time in Toronto, Canada, using three methods of differing spatial scales. Remotely sensed NO2 vertical column densities, retrieved from multi-axis differential optical absorption spectroscopy and satellite remote sensing, were evaluated by comparison with in situ vertical column densities estimated using a pair of chemiluminescence monitors situated 0.01 and 0.5 km a.g.l. (above ground level). The chemiluminescence measurements were corrected for the influence of NOz, which reduced the NO2 concentrations at 0.01 and 0.5 km by an average of 8 ± 1% and 12 ± 1%, respectively. The average absolute decrease in the chemiluminescence NO2 measurement as a result of this correction was less than 1 ppb. The monthly averaged ratio of the NO2 concentration at 0.5 to 0.01 km varied seasonally, and exhibited a negative linear dependence on the monthly average temperature, with Pearson's R = 0.83. During the coldest month, February, this ratio was 0.52 ± 0.04, while during the warmest month, July, this ratio was 0.34 ± 0.04, illustrating that NO2 is not well mixed within 0.5 km above ground level. Good correlation was observed between the remotely sensed and in situ NO2 vertical column densities (Pearson's R value ranging from 0.72 to 0.81), but the in situ vertical column densities were 52 to 58% greater than the remotely sensed columns. These results indicate that NO2 horizontal heterogeneity strongly impacted the magnitude of the remotely sensed columns. The in situ columns reflected an urban environment with major traffic sources, while the remotely sensed NO2 vertical column densities were representative of the region, which included spatial heterogeneity introduced by residential neighbourhoods and Lake Ontario. Despite the difference in absolute values, the reasonable correlation between the vertical column densities determined by three distinct methods increased confidence in the validity of the values provided by each measurement technique.

Survey on air pollution and cardiopulmonary mortality in shiraz from 2011 to 2012: an analytical-descriptive study.

PubMed

Dehghani, Mansooreh; Anushiravani, Amir; Hashemi, Hassan; Shamsedini, Narges

2014-06-01

Expanding cities with rapid economic development has resulted in increased energy consumption leading to numerous environmental problems for their residents. The aim of this study was to investigate the correlation between air pollution and mortality rate due to cardiovascular and respiratory diseases in Shiraz. This is an analytical cross-sectional study in which the correlation between major air pollutants (including carbon monoxide [CO], sulfur dioxide [SO2], nitrogen dioxide [NO2] and particle matter with a diameter of less than 10 μ [PM10]) and climatic parameters (temperature and relative humidity) with the number of those whom expired from cardiopulmonary disease in Shiraz from March 2011 to January 2012 was investigated. Data regarding the concentration of air pollutants were determined by Shiraz Environmental Organization. Information about climatic parameters was collected from the database of Iran's Meteorological Organization. The number of those expired from cardiopulmonary disease in Shiraz were provided by the Department of Health, Shiraz University of Medical Sciences. We used non-parametric correlation test to analyze the relationship between these parameters. The results demonstrated that in all the recorded data, the average monthly pollutants standard index (PSI) values of PM10 were higher than standard limits, while the average monthly PSI value of NO2 were lower than standard. There was no significant relationship between the number of those expired from cardiopulmonary disease and the air pollutant (P > 0.05). Air pollution can aggravate chronic cardiopulmonary disease. In the current study, one of the most important air pollutants in Shiraz was the PM10 component. Mechanical processes, such as wind blowing from neighboring countries, is the most important parameter increasing PM10 in Shiraz to alarming conditions. The average monthly variation in PSI values of air pollutants such as NO2, CO, and SO2 were lower than standard limits. Moreover, there was no significant correlation between the average monthly variation in PSI of NO2, CO, PM10, and SO2 and the number of those expired from cardiopulmonary disease in Shiraz.

40 CFR 421.256 - Pretreatment standards for new sources.

Code of Federal Regulations, 2011 CFR

2011-07-01

... for any 1 day Maximum for monthly average mg/troy ounce of gold refined electrolytically Lead 5.544 2... Maximum for monthly average mg/troy ounce of gold and silver smelted Lead 0.364 0.169 Mercury 0.195 0.078... Maximum for monthly average mg/troy ounce of silver reduced in solution Lead 0.112 0.052 Mercury 0.060 0...

40 CFR 421.256 - Pretreatment standards for new sources.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Maximum for monthly average mg/troy ounce of gold and silver smelted Lead 0.364 0.169 Mercury 0.195 0.078... Maximum for monthly average mg/troy ounce of silver reduced in solution Lead 0.112 0.052 Mercury 0.060 0... for any 1 day Maximum for monthly average mg/troy ounce of gold refined electrolytically Lead 5.544 2...

40 CFR 421.262 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2010 CFR

2010-07-01

... pollutant property Maximum for any 1 day Maximum for monthly average mg/troy ounce of precious metals... day Maximum for monthly average mg/troy ounce of precious metal in the granulated raw material Copper... monthly average mg/troy ounce of gold produced by cyanide stripping Copper 7.030 3.700 Cyanide (total) 1...

40 CFR 421.253 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2010 CFR

2010-07-01

... pollutant property Maximum for any 1 day Maximum for monthly average mg/troy ounce of gold and silver... Pollutant or pollutant property Maximum for any 1 day Maximum for monthly average mg/troy ounce of silver... Subcategory Pollutant or pollutant property Maximum for any 1 day Maximum for monthly average mg/troy ounce of...

20 CFR 404.222 - Use of benefit table in finding your primary insurance amount from your average monthly wage.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 20 Employees' Benefits 2 2013-04-01 2013-04-01 false Use of benefit table in finding your primary insurance amount from your average monthly wage. 404.222 Section 404.222 Employees' Benefits SOCIAL SECURITY... Average-Monthly-Wage Method of Computing Primary Insurance Amounts § 404.222 Use of benefit table in...

20 CFR 404.222 - Use of benefit table in finding your primary insurance amount from your average monthly wage.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Use of benefit table in finding your primary insurance amount from your average monthly wage. 404.222 Section 404.222 Employees' Benefits SOCIAL SECURITY... Average-Monthly-Wage Method of Computing Primary Insurance Amounts § 404.222 Use of benefit table in...

20 CFR 404.222 - Use of benefit table in finding your primary insurance amount from your average monthly wage.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 20 Employees' Benefits 2 2014-04-01 2014-04-01 false Use of benefit table in finding your primary insurance amount from your average monthly wage. 404.222 Section 404.222 Employees' Benefits SOCIAL SECURITY... Average-Monthly-Wage Method of Computing Primary Insurance Amounts § 404.222 Use of benefit table in...

20 CFR 404.222 - Use of benefit table in finding your primary insurance amount from your average monthly wage.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 20 Employees' Benefits 2 2012-04-01 2012-04-01 false Use of benefit table in finding your primary insurance amount from your average monthly wage. 404.222 Section 404.222 Employees' Benefits SOCIAL SECURITY... Average-Monthly-Wage Method of Computing Primary Insurance Amounts § 404.222 Use of benefit table in...

20 CFR 404.222 - Use of benefit table in finding your primary insurance amount from your average monthly wage.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 20 Employees' Benefits 2 2011-04-01 2011-04-01 false Use of benefit table in finding your primary insurance amount from your average monthly wage. 404.222 Section 404.222 Employees' Benefits SOCIAL SECURITY... Average-Monthly-Wage Method of Computing Primary Insurance Amounts § 404.222 Use of benefit table in...

40 CFR 421.113 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2010 CFR

2010-07-01

... Maximum for monthly average mg/kg (pounds per million pounds) of concentrate digested Lead .174 .081 Zinc... monthly average mg/Kg (pounds per million pounds) of concentrate digested Lead 2.592 1.203 Zinc 9.442 3... Maximum for monthly average mg/kg (pounds per million pounds) of concentrate digested Lead .069 .032 Zinc...

40 CFR 421.113 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2011 CFR

2011-07-01

... Maximum for monthly average mg/kg (pounds per million pounds) of concentrate digested Lead .174 .081 Zinc... monthly average mg/Kg (pounds per million pounds) of concentrate digested Lead 2.592 1.203 Zinc 9.442 3... Maximum for monthly average mg/kg (pounds per million pounds) of concentrate digested Lead .069 .032 Zinc...

40 CFR 467.36 - Pretreatment standards for new sources.

Code of Federal Regulations, 2011 CFR

2011-07-01

... day Maximum for monthly average mg/off-kg (lb/million off-lbs) of extruded Chromium 0.13 0.05 Cyanide... monthly average mg/off-kg (lb/million off-lbs) of hard alloy aluminum extruded Chromium 0.11 0.05 Cyanide... day Maximum for monthly average mg/off-kg (lb/million off-lbs) of aluminum cast Chromium 0.49 0.20...

Apparent temperature and cause-specific emergency hospital admissions in Greater Copenhagen, Denmark.

PubMed

Wichmann, Janine; Andersen, Zorana; Ketzel, Matthias; Ellermann, Thomas; Loft, Steffen

2011-01-01

One of the key climate change factors, temperature, has potentially grave implications for human health. We report the first attempt to investigate the association between the daily 3-hour maximum apparent temperature (Tapp(max)) and respiratory (RD), cardiovascular (CVD), and cerebrovascular (CBD) emergency hospital admissions in Copenhagen, controlling for air pollution. The study period covered 1 January 2002-31 December 2006, stratified in warm and cold periods. A case-crossover design was applied. Susceptibility (effect modification) by age, sex, and socio-economic status was investigated. For an IQR (8°C) increase in the 5-day cumulative average of Tapp(max), a 7% (95% CI: 1%, 13%) increase in the RD admission rate was observed in the warm period whereas an inverse association was found with CVD (-8%, 95% CI: -13%, -4%), and none with CBD. There was no association between the 5-day cumulative average of Tapp(max) during the cold period and any of the cause-specific admissions, except in some susceptible groups: a negative association for RD in the oldest age group and a positive association for CVD in men and the second highest SES group. In conclusion, an increase in Tapp(max) is associated with a slight increase in RD and decrease in CVD admissions during the warmer months.

Meteorologic and Geographic Barriers to Physical Activity in a Workplace Wellness Program.

PubMed

Smith, Karen C; Michl, Griffin L; Katz, Jeffrey N; Losina, Elena

2018-02-01

Inclement weather and home environment can act as barriers to physical activity. However, it is unclear if they reduce the activity of persons participating in activity-promoting programs. Data from a 6-month workplace financial incentives program were used to establish the association between meteorologic (temperature, rain, snow, and wind) and geographic factors (urban/nonurban home location and distance between home and work) and moderate to vigorous physical activity (MVPA). Multivariable models were built to estimate mean weekly minutes of MVPA adjusting for demographic factors, clinical factors, and impulsivity. The 292 participants had a mean age of 38 (SD = 11) years. Eighty-three percent were female and 62% were white. Twenty-nine percent lived within 3 miles of work, and 35% lived in urban areas. Participants who lived more than 3 miles from work averaged 75 [95% confidence interval (CI), 65-84] minutes of weekly MVPA compared with 105 (95% CI, 88-122) minutes for those who lived within 3 miles of work. Urban participants averaged 70 (95% CI, 57-83) minutes of MVPA compared with 91 (95% CI, 80-102) minutes for nonurban participants. Colder temperatures were associated with decreased MVPA, and impulsivity modified the effect. Colder temperatures, greater distance from work, and an urban residence are associated with fewer minutes of MVPA.

Simulated effects of dam removal on water temperatures along the Klamath River, Oregon and California, using 2010 Biological Opinion flow requirements

USGS Publications Warehouse

Risley, John C.; Brewer, Scott J.; Perry, Russell W.

2012-01-01

Computer model simulations were run to determine the effects of dam removal on water temperatures along the Klamath River, located in south-central Oregon and northern California, using flow requirements defined in the 2010 Biological Opinion of the National Marine Fisheries Service. A one-dimensional, daily averaged water temperature model (River Basin Model-10) developed by the U.S. Environmental Protection Agency Region 10, Seattle, Washington, was used in the analysis. This model had earlier been configured and calibrated for the Klamath River by the U.S. Geological Survey for the U.S. Department of the Interior, Klamath Secretarial Determination to simulate the effects of dam removal on water temperatures for current (2011) and future climate change scenarios. The analysis for this report was performed outside of the scope of the Klamath Secretarial Determination process at the request of the Bureau of Reclamation Technical Services Office, Denver, Colorado.For this analysis, two dam scenarios were simulated: “dams in” and “dams out.” In the “dams in” scenario, existing dams in the Klamath River were kept in place. In the “dams out” scenario, the river was modeled as a natural stream, without the J.C. Boyle, Copco1, Copco2, and Iron Gate Dams, for the entire simulation period. Output from the two dam scenario simulations included daily water temperatures simulated at 29 locations for a 50-year period along the Klamath River between river mile 253 (downstream of Link River Dam) and the Pacific Ocean. Both simulations used identical flow requirements, formulated in the 2010 Biological Opinion, and identical climate conditions based on the period 1961–2009.Simulated water temperatures from January through June at almost all locations between J.C. Boyle Reservoir and the Pacific Ocean were higher for the “dams out” scenario than for the “dams in” scenario. The simulated mean monthly water temperature increase was highest [1.7–2.2 degrees Celsius (°C)] in May downstream of Iron Gate Dam. However, from August to December, dam removal generally cooled water temperatures. During these months, water temperatures decreased 1°C or more between Copco Lake and locations 50 miles or more downstream. The greatest mean monthly temperature decrease was 4°C in October just downstream of Iron Gate Dam. Near the ocean, the effects of dam removal were small (less than 0.2°C) for most months. However, the mean November temperature near the ocean was almost 0.5°C cooler with dam removal.

Modeling the seasonal circulation in Massachusetts Bay

USGS Publications Warehouse

Signell, Richard P.; Jenter, Harry L.; Blumberg, Alan F.; ,

1994-01-01

An 18 month simulation of circulation was conducted in Massachusetts Bay, a roughly 35 m deep, 100??50 km embayment on the northeastern shelf of the United States. Using a variant of the Blumberg-Mellor (1987) model, it was found that a continuous 18 month run was only possible if the velocity field was Shapiro filtered to remove two grid length energy that developed along the open boundary due to mismatch in locally generated and climatologically forced water properties. The seasonal development of temperature and salinity stratification was well-represented by the model once ??-coordinate errors were reduced by subtracting domain averaged vertical profiles of temperature, salinity and density before horizontal differencing was performed. Comparison of modeled and observed subtidal currents at fixed locations revealed that the model performance varies strongly with season and distance from the open boundaries. The model performs best during unstratified conditions, and in the interior of the bay. The model performs poorest during stratified conditions and in the regions where the bay is driven predominantly by remote fluctuations from the Gulf of Maine.

Detection of geothermal anomalies in Tengchong, Yunnan Province, China from MODIS multi-temporal night LST imagery

NASA Astrophysics Data System (ADS)

Li, H.; Kusky, T. M.; Peng, S.; Zhu, M.

2012-12-01

Thermal infrared (TIR) remote sensing is an important technique in the exploration of geothermal resources. In this study, a geothermal survey is conducted in Tengchong area of Yunnan province in China using multi-temporal MODIS LST (Land Surface Temperature). The monthly night MODIS LST data from Mar. 2000 to Mar. 2011 of the study area were collected and analyzed. The 132 month average LST map was derived and three geothermal anomalies were identified. The findings of this study agree well with the results from relative geothermal gradient measurements. Finally, we conclude that TIR remote sensing is a cost-effective technique to detect geothermal anomalies. Combining TIR remote sensing with geological analysis and the understanding of geothermal mechanism is an accurate and efficient approach to geothermal area detection.

What climate changes could be observed by two generations of Poles?

NASA Astrophysics Data System (ADS)

Szwed, M.

2010-09-01

For many years, numerous scientific papers in different disciplines have been published on different aspects of the global warming. The issue of climate change and its impacts has become certainly a "fashionable" research area. In Poland, for example, the issue was tackled by one of the greatest hydro-climatological research projects, namely: "Extreme meteorological and hydrological events in Poland (the evaluation of forecasting events and their effects on human environment)". However, for several years, and certainly since 2007, when Al Gore, former U.S. vice-president, and the Intergovernmental Panel on Climate Change (IPCC) won the Nobel Peace Prize, this topic has started to be increasingly more frequently raised by the Polish media. The average Polish citizen increasingly more often learns from the press, radio and television about the global warming. There are also those skeptical of the climate change who loudly express their opinions in the media. Can the average Pole not get lost in the thicket of information? Can they refer to their own memory or the memory of their parents or grandparents on issues of climate change? How is the typical summer or winter perceived the previous generations? Is it possible to observe such changes without reference to extreme events? This article is to try to answer the question whether the average Pole could see climate change, most simply understood as changes in the thermal conditions and precipitations. If yes, then what seasons or months see the biggest changes. Which parts of the country witness the biggest changes? The starting point of the analysis are the 58-years time series of real monthly temperature and precipitation in the period of 1951-2008 for 20 stations across Poland. However, they will not be analyzed in more detail. In order to smooth the data sequences and thus to reject the short-term fluctuations, the long-term moving averages in different sequences (individual months, seasons and years) will be analyzed. The analysis of moving averages will help to find potential longer-term trends or cycles in the test time series. Trends will be detected based on parametric and nonparametric tests, such as linear regression and Mann-Kendall test. Finally, the current temperature and precipitation will be compared to the climate projections at the end of the 21st century. To this end, the climate models from the ENSEMBLES research project will be used. In the case of temperature, these will be C41RCA3 from Rossby Centre (Norrköping, Sweden); CLM from ETH (Zurich, Switzerland), KNMI-RACMO2 from the Royal National Meteorological Institute (De Bilt, the Netherlands), MPI-M-REMO from the Max Planck Institute (Hamburg, Germany); METO-HC from the Met Office's Hadley Centre (Exeter, UK), and RCA from the SMHI Swedish Meteorological and Hydrological Institute (Norrköping, Sweden). In the case of precipitation, only the MPI-M-REMO model will be used. The reason is the outcome of the validation of models for the territory of Poland (previously made by the author) which indicated that this model was the best fit for the Polish precipitation conditions.

Phytoremediation of arsenic- and molybdenum-contaminated alkaline wastewater by Eleocharis acicularis in winter in Japan

NASA Astrophysics Data System (ADS)

Yamazaki, Shusaku; Okazaki, Kenji; Kurahashi, Toshiyuki; Sakakibara, Masayuki

2017-06-01

Phytoremediation using aquatic plants is a sustainable, low-cost measure for remediating water contaminated by toxic heavy metals. In this study, we conducted a channel experiment using Eleocharis acicularis in heavy metal-contaminated mildly alkaline wastewater under unfavorable plant habitat conditions in winter in northeastern Japan. The wastewater from an embankment consisting of Neogene marine sediments had a temperature of 10-15 °C and a pH of about 9, and it contained ∼0.02 mg/L of As and ∼ 0.23 mg/L of Mo. About 16 kg (fresh weight) of E. acicularis was laid in a plastic channel measuring 30 cm in width by 20 m in length, and the channel was enclosed in a tunnel greenhouse. The experiment was conducted for the 3 months from November 2015 at an average flow rate of 0.3 L/min and an air temperature of -4 to 19 °C. No reductions in As or Mo concentrations in the outflow were detected. However, at 3 months, the E. acicularis showed accumulations of ∼7 mg/kg As and ∼18 mg/kg Mo as dry weight, indicating that this remediation method is workable in an unfavorable low-temperature, mildly alkaline environment.

Examination of the Armagh Observatory Annual Mean Temperature Record, 1844-2004

NASA Technical Reports Server (NTRS)

Wilson, Robert M.; Hathaway, David H.

2006-01-01

The long-term annual mean temperature record (1844-2004) of the Armagh Observatory (Armagh, Northern Ireland, United Kingdom) is examined for evidence of systematic variation, in particular, as related to solar/geomagnetic forcing and secular variation. Indeed, both are apparent in the temperature record. Moving averages for 10 years of temperature are found to highly correlate against both 10-year moving averages of the aa-geomagnetic index and sunspot number, having correlation coefficients of approx. 0.7, inferring that nearly half the variance in the 10-year moving average of temperature can be explained by solar/geomagnetic forcing. The residuals appear episodic in nature, with cooling seen in the 1880s and again near 1980. Seven of the last 10 years of the temperature record has exceeded 10 C, unprecedented in the overall record. Variation of sunspot cyclic averages and 2-cycle moving averages of temperature strongly associate with similar averages for the solar/geomagnetic cycle, with the residuals displaying an apparent 9-cycle variation and a steep rise in temperature associated with cycle 23. Hale cycle averages of temperature for even-odd pairs of sunspot cycles correlate against similar averages for the solar/geomagnetic cycle and, especially, against the length of the Hale cycle. Indications are that annual mean temperature will likely exceed 10 C over the next decade.

[Evaluation of the influence of humidity and temperature on the drug stability by initial average rate experiment].

PubMed

He, Ning; Sun, Hechun; Dai, Miaomiao

2014-05-01

To evaluate the influence of temperature and humidity on the drug stability by initial average rate experiment, and to obtained the kinetic parameters. The effect of concentration error, drug degradation extent, humidity and temperature numbers, humidity and temperature range, and average humidity and temperature on the accuracy and precision of kinetic parameters in the initial average rate experiment was explored. The stability of vitamin C, as a solid state model, was investigated by an initial average rate experiment. Under the same experimental conditions, the kinetic parameters obtained from this proposed method were comparable to those from classical isothermal experiment at constant humidity. The estimates were more accurate and precise by controlling the extent of drug degradation, changing humidity and temperature range, or by setting the average temperature closer to room temperature. Compared with isothermal experiments at constant humidity, our proposed method saves time, labor, and materials.

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.

Projections of Seasonal Patterns in Temperature- Related Deaths for Manhattan, New York

NASA Technical Reports Server (NTRS)

Li, Tiantian; Horton, Radley M.; Kinney, Patrick L.

2013-01-01

Global average temperatures have been rising for the past half-century, and the warming trend has accelerated in recent decades. Further warming is expected over the next few decades, with significant regional variations. These warming trends will probably result in more frequent, intense and persistent periods of hot temperatures in summer, and generally higher temperatures in winter. Daily death counts in cities increase markedly when temperatures reach levels that are very high relative to what is normal in a given location. Relatively cold temperatures also seem to carry risk. Rising temperatures may result in more heat-related mortality but may also reduce cold-related mortality, and the net impact on annual mortality remains uncertain. Here we use 16 downscaled global climate models and two emissions scenarios to estimate present and future seasonal patterns in temperature-related mortality in Manhattan, New York. All 32 projections yielded warm-season increases and cold-season decreases in temperature-related mortality, with positive net annual temperature-related deaths in all cases. Monthly analyses showed that the largest percentage increases may occur in May and September. These results suggest that, over a range of models and scenarios of future greenhouse gas emissions, increases in heat-related mortality could outweigh reductions in cold-related mortality, with shifting seasonal patterns.

Effect of tillage and crop residue on soil temperature following planting for a Black soil in Northeast China.

PubMed

Shen, Yan; McLaughlin, Neil; Zhang, Xiaoping; Xu, Minggang; Liang, Aizhen

2018-03-14

Crop residue return is imperative to maintain soil health and productivity but some farmers resist adopting conservation tillage systems with residue return fearing reduced soil temperature following planting and crop yield. Soil temperatures were measured at 10 cm depth for one month following planting from 2004 to 2007 in a field experiment in Northeast China. Tillage treatments included mouldboard plough (MP), no till (NT), and ridge till (RT) with maize (Zea mays L.) and soybean (Glycine max Merr.) crops. Tillage had significant effects on soil temperature in 10 of 15 weekly periods. Weekly average NT soil temperature was 0-1.5 °C lower than MP, but the difference was significant (P < 0.05) only in 2007 when residue was not returned in MP the previous autumn. RT showed no clear advantage over NT in increasing soil temperature. Higher residue coverage caused lower soil temperature; the effect was greater for maize than soybean residue. Residue type had significant effect on soil temperature in 9 of 15 weekly periods with 0-1.9 °C lower soil temperature under maize than soybean residue. Both tillage and residue had small but inconsistent effect on soil temperature following planting in Northeast China representative of a cool to temperate zone.

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.

Predicting alpine headwater stream intermittency: a case study in the northern Rocky Mountains

USGS Publications Warehouse

Sando, Thomas R.; Blasch, Kyle W.

2015-01-01

This investigation used climatic, geological, and environmental data coupled with observational stream intermittency data to predict alpine headwater stream intermittency. Prediction was made using a random forest classification model. Results showed that the most important variables in the prediction model were snowpack persistence, represented by average snow extent from March through July, mean annual mean monthly minimum temperature, and surface geology types. For stream catchments with intermittent headwater streams, snowpack, on average, persisted until early June, whereas for stream catchments with perennial headwater streams, snowpack, on average, persisted until early July. Additionally, on average, stream catchments with intermittent headwater streams were about 0.7 °C warmer than stream catchments with perennial headwater streams. Finally, headwater stream catchments primarily underlain by coarse, permeable sediment are significantly more likely to have intermittent headwater streams than those primarily underlain by impermeable bedrock. Comparison of the predicted streamflow classification with observed stream status indicated a four percent classification error for first-order streams and a 21 percent classification error for all stream orders in the study area.

Simulating the effect of climate change on stream temperature in the Trout Lake Watershed, Wisconsin

USGS Publications Warehouse

Selbig, William R.

2015-01-01

The potential for increases in stream temperature across many spatial and temporal scales as a result of climate change can pose a difficult challenge for environmental managers, especially when addressing thermal requirements for sensitive aquatic species. This study evaluates simulated changes to the thermal regime of three northern Wisconsin streams in response to a projected changing climate using a modeling framework and considers implications of thermal stresses to the fish community. The Stream Network Temperature Model (SNTEMP) was used in combination with a coupled groundwater and surface water flow model to assess forecasts in climate from six global circulation models and three emission scenarios. Model results suggest that annual average stream temperature will steadily increase approximately 1.1 to 3.2 °C (varying by stream) by the year 2100 with differences in magnitude between emission scenarios. Daily mean stream temperature during the months of July and August, a period when cold-water fish communities are most sensitive, showed excursions from optimal temperatures with increased frequency compared to current conditions. Projections of daily mean stream temperature, in some cases, were no longer in the range necessary to sustain a cold water fishery.

Simulating the effect of climate change on stream temperature in the Trout Lake Watershed, Wisconsin.

PubMed

Selbig, William R

2015-07-15

The potential for increases in stream temperature across many spatial and temporal scales as a result of climate change can pose a difficult challenge for environmental managers, especially when addressing thermal requirements for sensitive aquatic species. This study evaluates simulated changes to the thermal regime of three northern Wisconsin streams in response to a projected changing climate using a modeling framework and considers implications of thermal stresses to the fish community. The Stream Network Temperature Model (SNTEMP) was used in combination with a coupled groundwater and surface water flow model to assess forecasts in climate from six global circulation models and three emission scenarios. Model results suggest that annual average stream temperature will steadily increase approximately 1.1 to 3.2°C (varying by stream) by the year 2100 with differences in magnitude between emission scenarios. Daily mean stream temperature during the months of July and August, a period when cold-water fish communities are most sensitive, showed excursions from optimal temperatures with increased frequency compared to current conditions. Projections of daily mean stream temperature, in some cases, were no longer in the range necessary to sustain a cold water fishery. Published by Elsevier B.V.

Pattern of resolution of tachypnoea and fever in childhood pneumonia.

PubMed

Muhe, L

1998-02-01

Acute lower respiratory infections (ALRI) account for one fifth of deaths among children below five years of age and pneumonia is responsible for about 70% of all ALRI deaths. Interventions with antibiotics have shown reduction in pneumonia case-fatality rates. However, there is room for further reduction of deaths from pneumonia through improved monitoring and follow up system. We studied the pattern of resolution of tachypnoea and fever among 108 children who presented to our outpatient clinic with non-severe pneumonia and among 102 children who were admitted for severe pneumonia. We found that tachypnoea was present in 18% and 23% after 72 hours of initiation of antibiotics and fever resolved completely after 48 hours and 72 hours of initiation of therapy in non-severe cases of pneumonia among children two to 11 months and 12 to 59 months of age respectively. Conversely, among cases of severe pneumonia on day 5 of initiation of treatment, tachypnoea and fever were present in 65% and 51% respectively in children two to 11 months old and in 53% and 60% respectively in children 12 to 59 months old. Respiratory rate increased with increase in body temperature at an average rate of four breaths per minute for every 1 degree C rise. Our study suggests that body temperature and respiratory rate can be used to monitor the clinical course of non-severe pneumonia. Further research is needed to identify other clinical signs that will help the health worker to decide improvement in attacks of severe pneumonia.

Analysis of variability of tropical Pacific sea surface temperatures

NASA Astrophysics Data System (ADS)

Davies, Georgina; Cressie, Noel

2016-11-01

Sea surface temperature (SST) in the Pacific Ocean is a key component of many global climate models and the El Niño-Southern Oscillation (ENSO) phenomenon. We shall analyse SST for the period November 1981-December 2014. To study the temporal variability of the ENSO phenomenon, we have selected a subregion of the tropical Pacific Ocean, namely the Niño 3.4 region, as it is thought to be the area where SST anomalies indicate most clearly ENSO's influence on the global atmosphere. SST anomalies, obtained by subtracting the appropriate monthly averages from the data, are the focus of the majority of previous analyses of the Pacific and other oceans' SSTs. Preliminary data analysis showed that not only Niño 3.4 spatial means but also Niño 3.4 spatial variances varied with month of the year. In this article, we conduct an analysis of the raw SST data and introduce diagnostic plots (here, plots of variability vs. central tendency). These plots show strong negative dependence between the spatial standard deviation and the spatial mean. Outliers are present, so we consider robust regression to obtain intercept and slope estimates for the 12 individual months and for all-months-combined. Based on this mean-standard deviation relationship, we define a variance-stabilizing transformation. On the transformed scale, we describe the Niño 3.4 SST time series with a statistical model that is linear, heteroskedastic, and dynamical.

40 CFR 421.252 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2010 CFR

2010-07-01

... Pollutant or pollutant property Maximum for any 1 day Maximum for monthly average mg/troy ounce of gold and... monthly average mg/troy ounce of silver reduced in solution Lead 0.168 0.080 Mercury 0.100 0.040 Silver 0... property Maximum for any 1 day Maximum for monthly average mg/troy ounce of gold refined electrolytically...

Assessing variability of evapotranspiration over the Ganga river basin using water balance computations

NASA Astrophysics Data System (ADS)

Syed, Tajdarul H.; Webster, Peter J.; Famiglietti, James S.

2014-03-01

A thorough assessment of evapotranspiration (ET) pervades several important issues of the 21st century including climate change, food-security, land-management, flood and drought prediction, and water resources assessment and management. Such a proper assessment is of particular importance in the Ganga river basin (GRB) with its backdrop of a rapidly increasing population pressure and unregulated use of water resources. Spatially averaged ET over the GRB is computed as the residual of atmospheric and terrestrial water budget computations using a combination of model simulations and satellite and ground-based observations. The best estimate of monthly ET is obtained as the monthly mean of atmospheric and terrestrial water balance computations for the period 1980-2007. The mean monthly average of ET from these various estimates is 72.3 ± 18.8 mm month-1. Monthly variations of ET peak between July and August and reach a minimum in February. For the entire study period, the rate of change of ET across the GRB is -11 mm yr-2 (i.e., mm/yr/yr). Alongside a notable influence of the 1997-1998 El Niño, results allude to the existence of interim periods during which ET trends varied significantly. More specifically, during the period of 1998-2002, the rate of decline increased to -55.8 mm yr-2, which is almost 5 times the overall trend. Based on the correlation between ET and independent estimates of near-surface temperature and soil moisture, we can infer that the ET over the GRB is primarily limited by moisture availability. The analysis has important potential for use in large-scale water budget assessments and intercomparison studies. The analysis also emphasizes the importance of synergistic use of mutliplatform hydrologic information.

High Resolution Monthly Oceanic Rainfall Based on Microwave Brightness Temperature Histograms

NASA Astrophysics Data System (ADS)

Shin, D.; Chiu, L. S.

2005-12-01

A statistical emission-based passive microwave retrieval algorithm has been developed by Wilheit, Chang and Chiu (1991) to estimate space/time oceanic rainfall. The algorithm has been applied to Special Sensor Microwave Imager (SSM/I) data taken on board the Defense Meteorological Satellite Program (DMSP) satellites to provide monthly oceanic rainfall over 2.5ox2.5o and 5ox5o latitude-longitude boxes by the Global Precipitation Climatology Project-Polar Satellite Precipitation Data Center (GPCP-PSPDC, URL: http://gpcp-pspdc.gmu.edu/) as part of NASA's contribution to the GPCP. The algorithm has been modified and applied to the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) data to produce a TRMM Level 3 standard product (3A11) over 5ox5o latitude/longitude boxes. In this study, the algorithm code is modified to retrieve rain rates at 2.5ox2.5o and 1ox1o resolutions for TMI. Two months of TMI data have been tested and the results compared with the monthly mean rain rates derived from TRMM Level 2 TMI rain profile algorithm (2A12) and the original 5ox5o data from 3A11. The rainfall pattern is very similar to the monthly average of 2A12, although the intensity is slightly higher. Details in the rain pattern, such as rain shadow due to island blocking, which were not discernible from the low resolution products, are now easily discernible. The spatial average of the higher resolution rain rates are in general slightly higher than lower resolution rain rates, although a Student-t test shows no significant difference. This high resolution product will be useful for the calibration of IR rain estimates for the production of the GPCP merge rain product.

Modern calibration of Tussac grass (Poa flabellata) as a new paleoclimate proxy in the Falkland Islands

NASA Astrophysics Data System (ADS)

Groff, D. V.; Williams, D. G.; Gill, J. L.

2017-12-01

Monospecific stands of Tussac grasses (Poa flabellata) are a peat forming community found along coastal fringes of the Falkland Islands, and other sub-Antarctic islands in the South Atlantic region. Vegetation in peatlands record variation in regional precipitation and temperature in the cellulose of root and leaf plant tissues. A modern proof-of-concept study has determined how modern living P. flabellata records temperature, relative humidity, and precipitation using carbon (δ13C) and oxygen (δ18O) stable isotopes of leaf and root cellulose. At four locations in the Falkland Islands, P. flabellata plants were collected monthly and temperature (°C) and relative humidity (%) were measured continuously between September 1, 2015 to September 1, 2016. Monthly composite precipitation at each location was used to construct a local meteoric water line using δ2H and δ18O. Measurements of δ13C in leaf cellulose positively correlated with monthly average temperature (Pearson's r=0.82) and negatively correlated with relative humidity (Pearson's r = -0.76) across all sites, but not δ13C of root cellulose. Across all sites, the mean summer δ13C of leaf cellulose (-24.28‰) was significantly greater than winter (-26.80‰; t=8.91, df=73, p<0.001), and mean seasonal temperatures range from 9.32°C to 3.68°C for summer and winter, respectively. Measurements of δ18O in precipitation and leaf cellulose indicate a weak negative correlation (Pearson's r = -0.20), as well as δ18O in root cellulose (Pearson's r= -0.30). The δ13C isotope composition in leaf cellulose, along with the abundance of macrofossil P. flabellata leaves in peat deposits spanning the Holocene, supports the use of coastal grasslands formed by P. flabellata in the Falkland Islands as a paleoclimate proxy in the South Atlantic region.

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.

Monthly monsoon rainfall forecasting using artificial neural networks

NASA Astrophysics Data System (ADS)

Ganti, Ravikumar

2014-10-01

Indian agriculture sector heavily depends on monsoon rainfall for successful harvesting. In the past, prediction of rainfall was mainly performed using regression models, which provide reasonable accuracy in the modelling and forecasting of complex physical systems. Recently, Artificial Neural Networks (ANNs) have been proposed as efficient tools for modelling and forecasting. A feed-forward multi-layer perceptron type of ANN architecture trained using the popular back-propagation algorithm was employed in this study. Other techniques investigated for modeling monthly monsoon rainfall include linear and non-linear regression models for comparison purposes. The data employed in this study include monthly rainfall and monthly average of the daily maximum temperature in the North Central region in India. Specifically, four regression models and two ANN model's were developed. The performance of various models was evaluated using a wide variety of standard statistical parameters and scatter plots. The results obtained in this study for forecasting monsoon rainfalls using ANNs have been encouraging. India's economy and agricultural activities can be effectively managed with the help of the availability of the accurate monsoon rainfall forecasts.

[Multi-month dynamics of the functional condition of organism of normal male northeners of Russia].

PubMed

Solonin, Iu G; Markov, A L; Boĭko, E R

2012-01-01

In conjunction with the Mars-500 project, 17 male residents (25-46 y.o.) of the North of Russia (62 degrees 40'N) were examined monthly using hard- and software EKOSAN-2007. In the period of June, 2010 through to November, 2011 they visited a standard laboratory to go through comprehensive anthropophysiometric, psychophysiological and physiological investigations at rest and combined with exercise, standing and cold tests aimed at tracking the seasonal responses of the body functional parameters. The larger part of group-average psychomotor, breathing and circulation measurements as well as heart rate variability did not exhibit statistically significant differences between months or seasons. Reliable seasonal variations were documented in the life index, body and cutaneous temperature, myocardium index and regulatory systems activity. A correlation between environmental and some body functional parameters was established. In the course of the multi-month monitoring there were periods when essentially healthy people were diagnosed as prenosologic and even premorbid. Some findings in the functioning of male northerner's organism are clearly attributable to living in the high-altitude area.

Temporal and spatial variation in temperature experienced by macrofauna at Main Endeavour hydrothermal vent field

NASA Astrophysics Data System (ADS)

Lee, Raymond W.; Robert, Katleen; Matabos, Marjolaine; Bates, Amanda E.; Juniper, S. Kim

2015-12-01

A significant focus of hydrothermal vent ecological studies has been to understand how species cope with various stressors through physiological tolerance and biochemical resistance. Yet, the environmental conditions experienced by vent species have not been well characterized. This objective requires continuous observations over time intervals that can capture environmental variability at scales that are relevant to animals. We used autonomous temperature logger arrays (four roughly parallel linear arrays of 12 loggers spaced every 10-12 cm) to study spatial and temporal variations in the thermal regime experienced by hydrothermal vent macrofauna at a diffuse flow vent. Hourly temperatures were recorded over eight months from 2010 to 2011 at Grotto vent in the Main Endeavour vent field on the Juan de Fuca Ridge, a focus area of the Ocean Networks Canada cabled observatory. The conspicuous animal assemblages in video footage contained Ridgeia piscesae tubeworms, gastropods (primarily Lepetodrilus fucensis), and polychaetes (polynoid scaleworms and the palm worm Paralvinella palmiformis). Two dimensional spatial gradients in temperature were generally stable over the deployment period. The average temperature recorded by all arrays, and in some individual loggers, revealed distinctive fluctuations in temperature that often corresponded with the tidal cycle. We postulate that this may be related to changes in bottom currents or fluctuations in vent discharge. A marked transient temperature increase lasting over a period of days was observed in April 2011. While the distributions and behavior of Juan de Fuca Ridge vent invertebrates may be partially constrained by environmental temperature and temperature tolerance, except for the one transient high-temperature event, observed fluid temperatures were generally similar to the thermal preferences for some species, and typically well below lethal temperatures for all species. Average temperatures of the four arrays ranged from 4.1 to 11.0 °C during the deployment, indicating that on an hourly timescale the temperature conditions in this tubeworm community were fairly moderate and stable. The generality of these findings and behavioral responses of vent organisms to predictable rhythmicity and non-periodic temperature shifts are areas for further investigation.

Effects of Land Use Changes on the Water and Energy Balance Over South America

NASA Astrophysics Data System (ADS)

Nascimento, M.; Herdies, D. L.; Angelis, C.

2013-05-01

With the objective of analyzing the effects of land use changes in the Amazon and its consequences on the main components of the water and energy balance over South America, with emphasis on the Amazon and La Plata Basin, two experiments were carried for 10-year period (1999-2008), in which the land use conditions were modified, representing conditions for the 90s (CONTROL Experiment) and current conditions over land use in the Amazon region (Experiment 1). Changes in land use were observed mainly in the Amazon region and southern Brazil. The numerical model used to perform the simulations was the ETA in its climate version, using as an initial and boundary condition the CFSR/NCEP reanalysis datasets. The results show for the analyzed period that there was a reduction of 3.3 mm/month in average rainfall rates in the La Plata Basin and 4.2 mm/month in the Amazon region, with some places where this reduction was more pronounced. Seasonally was observed that during the summer there is an average reduction of 3.9 mm/month in the Amazon region. Already on the La Plata Basin was observed an average increase of 11.7 mm/month in the La Plata Basin during the summer and an reduction in winter season. Through the overall result was also possible to conclude that the changes in land use for more realistic conditions, there were significant reductions in evapotranspiration and latent heat fluxes, as well as an increase in sensible heat fluxes, especially over the regions where the changes were more pronounced. Through the analyzes it can be observed that in general the La Plata Basin is sensitive to changes in land use over the Amazon and adjacent regions, allowing to conclude that such changes can influence the amount of rainfall, the intensity of the major meteorological systems, as well as temperature trends on the regions analyzed.

MOnthly TEmperature DAtabase of Spain 1951-2010: MOTEDAS (2): The Correlation Decay Distance (CDD) and the spatial variability of maximum and minimum monthly temperature in Spain during (1981-2010).

NASA Astrophysics Data System (ADS)

Cortesi, Nicola; Peña-Angulo, Dhais; Simolo, Claudia; Stepanek, Peter; Brunetti, Michele; Gonzalez-Hidalgo, José Carlos

2014-05-01

One of the key point in the develop of the MOTEDAS dataset (see Poster 1 MOTEDAS) in the framework of the HIDROCAES Project (Impactos Hidrológicos del Calentamiento Global en España, Spanish Ministery of Research CGL2011-27574-C02-01) is the reference series for which no generalized metadata exist. In this poster we present an analysis of spatial variability of monthly minimum and maximum temperatures in the conterminous land of Spain (Iberian Peninsula, IP), by using the Correlation Decay Distance function (CDD), with the aim of evaluating, at sub-regional level, the optimal threshold distance between neighbouring stations for producing the set of reference series used in the quality control (see MOTEDAS Poster 1) and the reconstruction (see MOREDAS Poster 3). The CDD analysis for Tmax and Tmin was performed calculating a correlation matrix at monthly scale between 1981-2010 among monthly mean values of maximum (Tmax) and minimum (Tmin) temperature series (with at least 90% of data), free of anomalous data and homogenized (see MOTEDAS Poster 1), obtained from AEMEt archives (National Spanish Meteorological Agency). Monthly anomalies (difference between data and mean 1981-2010) were used to prevent the dominant effect of annual cycle in the CDD annual estimation. For each station, and time scale, the common variance r2 (using the square of Pearson's correlation coefficient) was calculated between all neighbouring temperature series and the relation between r2 and distance was modelled according to the following equation (1): Log (r2ij) = b*°dij (1) being Log(rij2) the common variance between target (i) and neighbouring series (j), dij the distance between them and b the slope of the ordinary least-squares linear regression model applied taking into account only the surrounding stations within a starting radius of 50 km and with a minimum of 5 stations required. Finally, monthly, seasonal and annual CDD values were interpolated using the Ordinary Kriging with a spherical variogram over conterminous land of Spain, and converted on a regular 10 km2 grid (resolution similar to the mean distance between stations) to map the results. In the conterminous land of Spain the distance at which couples of stations have a common variance in temperature (both maximum Tmax, and minimum Tmin) above the selected threshold (50%, r Pearson ~0.70) on average does not exceed 400 km, with relevant spatial and temporal differences. The spatial distribution of the CDD shows a clear coastland-to-inland gradient at annual, seasonal and monthly scale, with highest spatial variability along the coastland areas and lower variability inland. The highest spatial variability coincide particularly with coastland areas surrounded by mountain chains and suggests that the orography is one of the most driving factor causing higher interstation variability. Moreover, there are some differences between the behaviour of Tmax and Tmin, being Tmin spatially more homogeneous than Tmax, but its lower CDD values indicate that night-time temperature is more variable than diurnal one. The results suggest that in general local factors affects the spatial variability of monthly Tmin more than Tmax and then higher network density would be necessary to capture the higher spatial variability highlighted for Tmin respect to Tmax. The results suggest that in general local factors affects the spatial variability of Tmin more than Tmax and then higher network density would be necessary to capture the higher spatial variability highlighted for minimum temperature respect to maximum temperature. A conservative distance for reference series could be evaluated in 200 km, that we propose for continental land of Spain and use in the development of MOTEDAS.

Interannual and intra-annual variability of rainfall in Haiti (1905-2005)

NASA Astrophysics Data System (ADS)

Moron, Vincent; Frelat, Romain; Jean-Jeune, Pierre Karly; Gaucherel, Cédric

2015-08-01

The interannual variability of annual and monthly rainfall in Haiti is examined from a database of 78 rain gauges in 1905-2005. The spatial coherence of annual rainfall is rather low, which is partly due to Haiti's rugged landscape, complex shoreline, and surrounding warm waters (mean sea surface temperatures >27 °C from May to December). The interannual variation of monthly rainfall is mostly shaped by the intensity of the low-level winds across the Caribbean Sea, leading to a drier- (or wetter-) than-average rainy season associated with easterly (or westerly) anomalies, increasing (or decreasing) winds. The varying speed of low-level easterlies across the Caribbean basin may reflect at least four different processes during the year: (1) an anomalous trough/ridge over the western edge of the Azores high from December to February, peaking in January; (2) a zonal pressure gradient between Eastern Pacific and the tropical Northern Atlantic from May/June to September, with a peak in August (i.e. lower-than-average rainfall in Haiti is associated with positive sea level pressure anomalies over the tropical North Atlantic and negative sea level pressure anomalies over the Eastern Pacific); (3) a local ocean-atmosphere coupling between the speed of the Caribbean Low Level Jet and the meridional sea surface temperature (SST) gradient across the Caribbean basin (i.e. colder-than-average SST in the southern Caribbean sea is associated with increased easterlies and below-average rainfall in Haiti). This coupling is triggered when the warmest Caribbean waters move northward toward the Gulf of Mexico; (4) in October/November, a drier- (or wetter-) than-usual rainy season is related to an almost closed anticyclonic (or cyclonic) anomaly located ENE of Haiti on the SW edge of the Azores high. This suggests a main control of the interannual variations of rainfall by intensity, track and/or recurrence of tropical depressions traveling northeast of Haiti. During this period, the teleconnection of Haitian rainfall with synchronous Atlantic and Eastern Pacific SST is at a minimum.

Coral disease following massive bleaching in 2005 causes 60% decline in coral cover on reefs in the US Virgin Islands

USGS Publications Warehouse

Miller, J.; Muller, E.; Rogers, C.; Waara, R.; Atkinson, A.; Whelan, K.R.T.; Patterson, M.; Witcher, B.

2009-01-01

In the northeast Caribbean, doldrum-like conditions combined with elevated water temperatures in the summer/fall 2005 created the most severe coral bleaching event ever documented within this region. Video monitoring of 100 randomly chosen, permanent transects at five study sites in the US Virgin Islands revealed over 90% of the scleractinian coral cover showed signs of thermal stress by paling or becoming completely white. Lower water temperatures in October allowed some re-coloring of corals; however, a subsequent unprecedented regional outbreak of coral disease affected all sites. Five known diseases or syndromes were recorded; however, most lesions showed signs similar to white plague. Nineteen scleractinian species were affected by disease, with >90% of the disease-induced lesions occurring on the genus Montastraea. The disease outbreak peaked several months after the onset of bleaching at all sites but did not occur at the same time. The mean number of disease-induced lesions increased 51-fold and the mean area of disease-associated mortality increased 13-fold when compared with pre-bleaching disease levels. In the 12 months following the onset of bleaching, coral cover declined at all sites (average loss: 51.5%, range: 42.4-61.8%) reducing the five-site average from 21.4% before bleaching to 10.3% with most mortality caused by white plague disease, not bleaching. Continued losses through October 2007 reduced the average coral cover of the five sites to 8.3% (average 2-year loss: 61.1%, range: 53.0-79.3%). Mean cover by M. annularis (complex) decreased 51%, Colpophyllia natans 78% and Agaricia agaricites 87%. Isolated disease outbreaks have been documented before in the Virgin Islands, but never as widespread or devastating as the one that occurred after the 2005 Caribbean coral-bleaching event. This study provides insight into the effects of continued seawater warming and subsequent coral bleaching events in the Caribbean and highlights the need to understand links between coral bleaching and disease. ?? The Author(s) 2009.

PREDICTING CLINICALLY DIAGNOSED DYSENTERY INCIDENCE OBTAINED FROM MONTHLY CASE REPORTING BASED ON METEOROLOGICAL VARIABLES IN DALIAN, LIAONING PROVINCE, CHINA, 2005-2011 USING A DEVELOPED MODEL.

PubMed

An, Qingyu; Yao, Wei; Wu, Jun

2015-03-01

This study describes our development of a model to predict the incidence of clinically diagnosed dysentery in Dalian, Liaoning Province, China, using time series analysis. The model was developed using the seasonal autoregressive integrated moving average (SARIMA). Spearman correlation analysis was conducted to explore the relationship between meteorological variables and the incidence of clinically diagnosed dysentery. The meteorological variables which significantly correlated with the incidence of clinically diagnosed dysentery were then used as covariables in the model, which incorporated the monthly incidence of clinically diagnosed dysentery from 2005 to 2010 in Dalian. After model development, a simulation was conducted for the year 2011 and the results of this prediction were compared with the real observed values. The model performed best when the temperature data for the preceding month was used to predict clinically diagnosed dysentery during the following month. The developed model was effective and reliable in predicting the incidence of clinically diagnosed dysentery for most but not all months, and may be a useful tool for dysentery disease control and prevention, but further studies are needed to fine tune the model.

Depth, Salinity and Temperature Variability in the Maryland Coastal Lagoons

NASA Astrophysics Data System (ADS)

Chigbu, P.; Malagon, H.; Doctor, S.

2016-02-01

Alterations in temperature, precipitation, and sea level associated with global climate change will likely affect the hydrology and bathymetry of Maryland Coastal Bays (MCBs). This will in turn have effects on the abundance, distribution and diversity of the inhabiting biota, as well as the biogeochemistry and food web dynamics of the system. Depth, salinity and temperature data collected monthly (April to October) each year (1990 to 2012) from 20 sites in the MCBs were analyzed. Mean depth at most sites increased significantly with year (p<0.02). The rate of change in depth ranged from -0.02m/yr to 0.043m/yr (mean = 0.021m/yr), which is about seven times higher than the global rate of sea level rise. At the predicted mean rate of change in depth, the MCBs would have risen by 0.78m by the year 2050. Salinity varied between years of below average (e.g. 1990, 2003 and 2009), and above average (e.g. 1991, 1999, 2002 and 2007) levels. Inter-annual variability in salinity at most sites was significantly accounted for by variations in freshwater discharge, although the strength of the relationship decreased with proximity of the sites to the inlets. Measurements taken in April of each year since 1990 showed that temperature has increased significantly in the northern bays (Assawoman and Isle of Wight) and Chincoteague Bay, but not in Sinepuxent and Newport Bays. The observed changes in depth, salinity and temperature have important implications with regard to the functioning of the MCBs, and serve as a basis for evaluating future responses of the lagoons to climatic changes.

Quantifying uncertainty in future floods and drought conditions in the Northeastern United States using regionally downscaled climate projections

NASA Astrophysics Data System (ADS)

Siddique, R.; Wu, C.; Karmalkar, A.; Bradley, R. S.; Palmer, R. N.

2017-12-01

Northeastern region (NER) of the United States (US) has been projected to be a place where climate change can have the most severe impacts. These impacts include, but are not limited to, increases in the following: extreme precipitation events, temperature, flood magnitudes, flood frequencies, droughts, and sea level rise. In this study, we estimate the frequency of hydrological extremes under different climate change scenarios using regionally downscaled climate projections from a limited number of selected models from the fifth phase of Coupled Model Intercomparison Project (CMIP5). The models are chosen to minimize the loss of key climate information relevant to the NER. Precipitation and temperature from the selected models are forced into a distributed hydrological model called Hydrology Laboratory - Research Distributed Hydrological Model (HL-RDHM) to obtain streamflows for two different time regimes, near-term (20-50 years out) and long-term (50-80 years out). For this, two climate emission scenarios will be considered: RCP 4.5 and RCP 8.5. The impacts of the climate projections on the streamflows are then evaluated across different watershed scales in the NER. Among different metrics, we employ: 1) Flood Events - return period of 1 year, 10 year, 20 year, 50 year, and 100 year flood events and 2) Drought Events -low flow events associated with the 7-day 10 year low flow, number of days per month that will be below the historic monthly average, number of days per month that will be below the 25 percentile monthly historic average, changes in the 30-day and 60-day cumulative summer flows, and the timing and magnitude of spring run-off. For estimates of the climate impacts on low and high flows, only the unregulated watersheds are taken into consideration. Ensembles of streamflows obtained by forcing different climate projections are used to quantify and account for the associated uncertainties. Thus, the outcomes of this study are expected to guide regional decision makers on potential impacts of climate change on hydrological extreme events and water resources across different spatial scales within NER of the US.

[Research on accidents in a tire-producing plant].

PubMed

Mete, R; Sabatucci, A

1989-09-30

In the autumn of 1987 the U.S.L. health service (prevention, hygiene and occupational safety section) began a study about the accidents in a firm manufacturing tyres, placed in its own area. The retrospective enquiry starts from the analysis of typology, diffusion and seriousness of occupational accidents. The firm's accident register has been analyzed and integrated with other necessary information provided by the firm, by I.N.A.I.L. and by the air force metereological service. The study has been carried out on data concerning the following years: 1984-1985-1986. The accidents considered, implied absence from work and were divided as follows: for absence up till 3 days (in franchise), and more than 3 days (indemnified), applying the average value calculated on one year of the three analyzed. Every accident has been analyzed per year, month, day, hour of event. According to the classes: circumstances, kind of lesion, site of lesion, period of absence from work. The indices of: frequency, seriousness, incidence, mean duration have been calculated. The average monthly values of temperature: max and min. of the area and to the average monthly amount of processed elastomer (rate of production). The statistics we obtained, justified the study and showed the operative solution. The aspect of sanitary education and the general psychological aspect regarding the accident have been considered. Moreover the general operative solutions for the firm and specific ones for every department and for every position have been shown and faced up to. In this way, according to the risks that have emerged from the enquiries on previous accidents and thanks to direct inspection. it was possible to prevent accidents.

The influence of climate variables on dengue in Singapore.

PubMed

Pinto, Edna; Coelho, Micheline; Oliver, Leuda; Massad, Eduardo

2011-12-01

In this work we correlated dengue cases with climatic variables for the city of Singapore. This was done through a Poisson Regression Model (PRM) that considers dengue cases as the dependent variable and the climatic variables (rainfall, maximum and minimum temperature and relative humidity) as independent variables. We also used Principal Components Analysis (PCA) to choose the variables that influence in the increase of the number of dengue cases in Singapore, where PC₁ (Principal component 1) is represented by temperature and rainfall and PC₂ (Principal component 2) is represented by relative humidity. We calculated the probability of occurrence of new cases of dengue and the relative risk of occurrence of dengue cases influenced by climatic variable. The months from July to September showed the highest probabilities of the occurrence of new cases of the disease throughout the year. This was based on an analysis of time series of maximum and minimum temperature. An interesting result was that for every 2-10°C of variation of the maximum temperature, there was an average increase of 22.2-184.6% in the number of dengue cases. For the minimum temperature, we observed that for the same variation, there was an average increase of 26.1-230.3% in the number of the dengue cases from April to August. The precipitation and the relative humidity, after analysis of correlation, were discarded in the use of Poisson Regression Model because they did not present good correlation with the dengue cases. Additionally, the relative risk of the occurrence of the cases of the disease under the influence of the variation of temperature was from 1.2-2.8 for maximum temperature and increased from 1.3-3.3 for minimum temperature. Therefore, the variable temperature (maximum and minimum) was the best predictor for the increased number of dengue cases in Singapore.

Incidence and seasonality of hypothermia among newborns in southern Nepal.

PubMed

Mullany, Luke C; Katz, Joanne; Khatry, Subarna K; Leclerq, Steven C; Darmstadt, Gary L; Tielsch, James M

2010-01-01

To quantify incidence, age distribution, and seasonality of neonatal hypothermia among a large population cohort. Longitudinal cohort study. Sarlahi, Nepal. A total of 23 240 newborns born between September 2, 2002, and February 1, 2006. Main Exposures Community-based workers recorded axillary temperature on days 1 through 4, 6, 8, 10, 12, 14, 21, and 28 (213 636 total measurements). Regression smoothing was used to describe axillary temperature patterns during the newborn period. Hypothermia incidence in the first day, week, and month were estimated using standard cutoffs. Ambient temperatures allowed comparison of mild hypothermia (36.0 degrees C to <36.5 degrees C) and moderate or severe hypothermia (<36.0 degrees C) incidence over mean ambient temperature quintiles. Measurements lower than 36.5 degrees C were observed in 21 459 babies (92.3%); half (48.6%) had moderate or severe hypothermia, and risk peaked in the first 24 to 72 hours of life. Risk of moderate or severe hypothermia increased by 41.3% (95% confidence interval, 40.0%-42.7%) for every 5 degrees C decrease in average ambient temperature. Relative to the highest quintile, risk was 4.03 (95% confidence interval, 3.77-4.30) times higher among babies exposed to the lowest quintile of average ambient temperature. In the hot season, one-fifth of the babies (18.2%) were observed below the moderate hypothermia cutoff. Mild or moderate hypothermia was nearly universal, with substantially higher risk in the cold season. However, incidence in the hot season was also high; thus, year-round thermal care promotion is required. Research on community, household, and caretaker practices associated with hypothermia can guide behavioral interventions to reduce risk.

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.

A remarkable climate warming hiatus over Northeast China since 1998

NASA Astrophysics Data System (ADS)

Sun, Xiubao; Ren, Guoyu; Ren, Yuyu; Fang, Yihe; Liu, Yulian; Xue, Xiaoying; Zhang, Panfeng

2017-07-01

Characteristics and causes of global warming hiatus (GWH) phenomenon have received much attention in recent years. Monthly mean data of land surface air maximum temperature (Tmax), minimum temperature (Tmin), and mean temperature (Tmean) of 118 national stations since 1951 in Northeast China are used in this paper to analyze the changes of land surface air temperature in recent 64 years with an emphasis on the GWH period. The results show that (1) from 1951 to 2014, the warming trends of Tmax, Tmin, and Tmean are 0.20, 0.42, and 0.34 °C/decade respectively for the whole area, with the warming rate of Tmin about two times of Tmax, and the upward trend of Tmean obviously higher than mainland China and global averages; (2) in the period 1998-2014, the annual mean temperature consistently exhibits a cooling phenomenon in Northeast China, and the trends of Tmax, Tmin, and Tmean are -0.36, -0.14, and -0.28 °C/decade respectively; (3) in the GWH period, seasonal mean cooling mainly occurs in northern winter (DJF) and spring (MAM), but northern summer (JJA) and autumn (SON) still experience a warming, implying that the annual mean temperature decrease is controlled by the remarkable cooling of winter and spring; (4) compared to the global and mainland China averages, the hiatus phenomenon is more evident in Northeast China, and the cooling trends are more obvious in the cold season; (5) the Northeast China cooling trend occurs under the circulation background of the negative phase Arctic Oscillation (AO), and it is also closely related to strengthening of the Siberia High (SH) and the East Asian Trough (EAT), and the stronger East Asian winter monsoon (EAWM) over the GWH period.

The influence of intra- and inter-annual meteorological variability on dengue transmission: a multi-level modeling analysis

NASA Astrophysics Data System (ADS)

Wen, Tzai-Hung; Chen, Tzu-Hsin

2017-04-01

Dengue fever is one of potentially life-threatening mosquito-borne diseases and IPCC Fifth Assessment Report (AR5) has confirmed that dengue incidence is sensitive to the critical weather conditions, such as effects of temperature. However, previous literature focused on the effects of monthly or weekly average temperature or accumulative precipitation on dengue incidence. The influence of intra- and inter-annual meteorological variability on dengue outbreak is under investigated. The purpose of the study focuses on measuring the effect of the intra- and inter-annual variations of temperature and precipitation on dengue outbreaks. We developed the indices of intra-annual temperature variability are maximum continuity, intermittent, and accumulation of most suitable temperature (MST) for dengue vectors; and also the indices of intra-annual precipitation variability, including the measure of continuity of wetness or dryness during a pre-epidemic period; and rainfall intensity during an epidemic period. We used multi-level modeling to investigate the intra- and inter-annual meteorological variations on dengue outbreaks in southern Taiwan from 1998-2015. Our results indicate that accumulation and maximum continuity of MST are more significant than average temperature on dengue outbreaks. The effect of continuity of wetness during the pre-epidemic period is significantly more positive on promoting dengue outbreaks than the rainfall effect during the epidemic period. Meanwhile, extremely high or low rainfall density during an epidemic period do not promote the spread of dengue epidemics. Our study differentiates the effects of intra- and inter-annual meteorological variations on dengue outbreaks and also provides policy implications for further dengue control under the threats of climate change. Keywords: dengue fever, meteorological variations, multi-level model

Influence of temperature, precipitation, and cultivar characteristics on changes in the spectrum of pathogenic fungi in winter wheat.

PubMed

Hýsek, Josef; Vavera, Radek; Růžek, Pavel

2017-06-01

In view of the threat posed by climate change, we studied the influence of temperature, precipitation, cultivar characteristics, and technical management measures on the occurrence of phytopathogenic fungi in wheat during 2009-2013. This work involved experiments at two sites differing in average temperatures and precipitation. Temperature and precipitation appear to influence differences in the spectrum of phytopathogenic fungi at the individual sites. In 2009 (the warmest year), Alternaria triticina was dominant. In 2010 (having the smallest deviations from the average for individual years), Septoria tritici dominated. In 2011, Puccinia triticina was most prominent, while in 2012, the genus Drechslera (Pyrenophora) and in 2013, S. tritici and Drechslera tritici-repentis (DTR) dominated. Temperature and precipitation levels in the individual spring months (warmer March to May) played a large role, especially for the leaf rust P. triticina in 2011. A change of only 1 °C with different precipitation during a year played a significant role in changing wheat's fungal spectrum. Cluster analysis showed the differences between single pathogenic fungi on wheat in a single year due to temperature and precipitation. Alternaria abundance was strongly influenced by year (p < 0.001) while locality was significant only in certain years (2012, 2013; p = 0.004 and 0.015, respectively). The same factors were revealed to be significant in the case of Puccinia, but locality played a role (p < 0.001) in different years (2011, 2013). The abundance of S. tritici and Pyrenophora tritici-repentis (Drechslera tritici-repentis) was influenced only by year (p < 0.001).

Epidemiology of Toxocara vitulorum in cattle around Bursa, Turkey.

PubMed

Akyol, C V

1993-03-01

The prevalence of Toxocara vitulorum in cattle around Bursa, Turkey, was surveyed by faecal examination of eggs. The average infection rate among 11 towns was 5.1% in calves younger than 6-months-old, and 2.2% in all ages of animals. T. vitulorum was found to be prevalent in two different areas of Bursa. Third stage larvae were found in one milk sample and therefore galactogenic transmission was suggested. Experimental incubation of eggs showed that the optimum temperature for development was 20 to 30 degrees C and eggs could survive under low temperature, indicating that grazing in the contaminated pasture may accelerate the transmission of eggs to cows. Mode of farming, therefore, affects the infection rate of T. vitulorum and may explain the difference in the rate between the two areas.

Climate risks on potato yield in Europe

NASA Astrophysics Data System (ADS)

Sun, Xun; Lall, Upmanu

2016-04-01

The yield of potatoes is affected by water and temperature during the growing season. We study the impact of a suite of climate variables on potato yield at country level. More than ten climate variables related to the growth of potato are considered, including the seasonal rainfall and temperature, but also extreme conditions at different averaging periods from daily to monthly. A Bayesian hierarchical model is developed to jointly consider the risk of heat stress, cold stress, wet and drought. Future climate risks are investigated through the projection of future climate data. This study contributes to assess the risks of present and future climate risks on potatoes yield, especially the risks of extreme events, which could be used to guide better sourcing strategy and ensure food security in the future.

Seasonal variation of meteor decay times observed at King Sejong Station (62.22°S, 58.78°W), Antarctica

NASA Astrophysics Data System (ADS)

Kim, Jeong-Han; Kim, Yong Ha; Lee, Chang-Sup; Jee, Geonhwa

2010-07-01

We analyzed meteor decay times measured by a VHF radar at King Sejong Station by classifying strong and weak meteors according to their estimated electron line densities. The height profiles of monthly averaged decay times show a peak whose altitude varies with season at altitudes of 80-85 km. The higher peak during summer is consistent with colder temperatures that cause faster chemical reactions of electron removal. By adopting temperature dependent empirical recombination rates from rocket experiments and meteor electron densities of 2×105-2×106 cm-3 in a decay time model, we are able to account for decreasing decay times below the peak for all seasons without invoking meteor electron removal by hypothetical icy particles.

A high-spin and durable polyradical: poly(4-diphenylaminium-1,2-phenylenevinylene).

PubMed

Murata, Hidenori; Takahashi, Masahiro; Namba, Kazuaki; Takahashi, Naoki; Nishide, Hiroyuki

2004-02-06

A purely organic, high-spin, and durable polyradical molecule was synthesized: It is based on the non-Kekulé- and non-disjoint design of a pi-conjugated poly(1,2-phenylenevinylene) backbone pendantly 4-substituted with multiple robust arylaminium radicals. 4-N,N-Bis(4-methoxy- and -tert-butylphenyl)amino-2-bromostyrene 5 were synthesized and polymerized with a palladium-phosphine catalyst to afford the head-to-tail-linked polyradical precursors (1). Oxidation of 1 with the nitrosonium ion solubilized with a crown ether gave the aminium polyradicals (1(+)()) which were durable (half-life > 1 month) at room temperature in air. A high-spin ground state with an average S = (4.5)/2 for 1a(+) was proved even at room temperature by magnetic susceptibility, magnetization, ESR, and NMR measurements.

Hydrothermal synthesis of histidine-functionalized single-crystalline gold nanoparticles and their pH-dependent UV absorption characteristic.

PubMed

Liu, Zhiguo; Zu, Yuangang; Fu, Yujie; Meng, Ronghua; Guo, Songling; Xing, Zhimin; Tan, Shengnan

2010-03-01

L-Histidine capped single-crystalline gold nanoparticles have been synthesized by a hydrothermal process under a basic condition at temperature between 65 and 150 degrees C. The produced gold nanoparticles were spherical with average diameter of 11.5+/-2.9nm. The synthesized gold colloidal solution was very stable and can be stored at room temperature for more than 6 months. The color of the colloidal solution can change from wine red to mauve, purple and blue during the acidifying process. This color changing phenomenon is attributed to the aggregation of gold nanoparticles resulted from hydrogen bond formation between the histidines adsorbed on the gold nanoparticles surfaces. This hydrothermal synthetic method is expected to be used for synthesizing some other amino acid functionalized gold nanomaterials.

40 CFR Table 21 to Subpart G of... - Average Storage Temperature (Ts) as a Function of Tank Paint Color

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 10 2012-07-01 2012-07-01 false Average Storage Temperature (Ts) as a..., and Wastewater Pt. 63, Subpt. G, Table 21 Table 21 to Subpart G of Part 63—Average Storage Temperature (Ts) as a Function of Tank Paint Color Tank Color Average Storage Temperature (Ts) White TA a = 0...

40 CFR Table 21 to Subpart G of... - Average Storage Temperature (Ts) as a Function of Tank Paint Color

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 9 2010-07-01 2010-07-01 false Average Storage Temperature (Ts) as a..., and Wastewater Pt. 63, Subpt. G, Table 21 Table 21 to Subpart G of Part 63—Average Storage Temperature (Ts) as a Function of Tank Paint Color Tank Color Average Storage Temperature (Ts) White TA a = 0...

40 CFR Table 21 to Subpart G of... - Average Storage Temperature (Ts) as a Function of Tank Paint Color

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 10 2013-07-01 2013-07-01 false Average Storage Temperature (Ts) as a..., and Wastewater Pt. 63, Subpt. G, Table 21 Table 21 to Subpart G of Part 63—Average Storage Temperature (Ts) as a Function of Tank Paint Color Tank Color Average Storage Temperature (Ts) White TA a = 0...