scholarly journals Mitigación de altas sensaciones térmicas del municipio Bosconia-Cesar a través de forestación con especies nativas.

2021 ◽  
Vol 17 (34) ◽  
pp. 110-130
Author(s):  
Angélica Patricia Vanegas Padilla ◽  
Oriana Carolina Jurado-Fuentes ◽  
Ronny Javier López-Hernández ◽  
Jorge Eduardo Gómez-González
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
Native Species ◽  
Thermal Sensation ◽  
Vehicular Pollution ◽  
Public And Private ◽  
Private Actors ◽  
Local Research

Las altas temperaturas o condiciones de sensación térmica revelan inestabilidad en la comunidad Bosconense debido a la presencia de elevados niveles en la zona urbana a causa de la contaminación vehicular, malas prácticas ambientales y topografía desventajosa, alcanzando niveles de “estrés térmico”. Se realizó análisis multitemporal de: humedad relativa, temperatura, velocidad del viento, puntos de calor y sensación térmica para los años 2000, 2010, 2015 y 2020. También una caracterización del suelo basada en bibliografías y ambientalistas locales, encontrando 20.694 ha’s deforestadas entre 2000-2020 en toda Bosconia. Se presentó metodología de forestación con especies nativas (Cañaguate, Mango, Puy y Roble) y metodología de monitoreo sobre las variables humedad relativa, radiación solar, temperatura y velocidad del viento para evaluar eficacia. Añadiendo monitoreo a la radiación solar para futuras investigaciones locales. Posteriormente, se implementó la forestación y socialización con actores públicos, privados y población aledaña sobre los beneficios y cuidados que deben tenerse, estableciendo los periodos e instrumentos para evaluar la mitigación. High temperatures or thermal sensation conditions reveal instability in the Bosconense community due to the presence of high levels in the urban area due to vehicular pollution, bad environmental practices and disadvantageous topography, reaching levels of “thermal stress”. Multitemporal analysis of: relative humidity, temperature, wind speed, hot spots and thermal sensation was carried out for the years 2000, 2010, 2015 and 2020. Also, a characterization of the soil based on bibliographies and local environmentalists, finding 20,694 ha's deforested between 2000 -2020 throughout Bosconia. Afforestation methodology with native species (Cañaguate, Mango, Puy and Roble) and monitoring methodology on the variables relative humidity, solar radiation, temperature and wind speed were presented to evaluate efficacy. Adding solar radiation monitoring for future local research. Subsequently, afforestation and socialization with public and private actors and the surrounding population about the benefits and care that should be taken was implemented, establishing the periods and instruments to evaluate mitigation.

scholarly journals Assessment of Spatiotemporal Variability and Trend Analysis of Reference Crop Evapotranspiration for the southern region of Peninsular India

2021 ◽  
Author(s):  
Jayashree Tenkila Ramachandra ◽  
Subba Reddy Nandanavana Veerappa ◽  
Dinesh Acharya Udupi
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
Water Resource Management ◽  
Spatiotemporal Variability ◽  
Trend Test ◽  
Accurate Estimation ◽  
Peninsular India ◽  
Climatic Zones ◽  
Statistical Measures

Abstract Accurate estimation of reference evapotranspiration (ET0) is an essential requirement for water resource management and scheduling agricultural activities. Several empirical methods have been employed in estimating ET0 across diverse climate regimes over the past decades. The Python implementation for estimation of daily and monthly ET0 values of representative stations of ten agro-climatic zones of Karnataka from 1979 through 2014 using the standard FAO Penman-Monteith method was carried out. The assessment of temporal and spatial variability of monthly ET0 values across the various agro-climatic zones done by the various statistical measures revealed that the variation in spatial ET0 values was higher than temporal indicating major differentiation of ET0 values was with respect to the stations rather than years under study. The non-parametric Mann-Kendall test conducted at 1% significance level on the annual ET0 values revealed that statistically significant increasing trend was observed for all the ten stations during the study period. The trend test conducted on the climate variables like mean air temperature, wind speed, relative humidity and solar radiation signify their influence the annual ET0 values. The magnitude changes in the trends detected by the Theil Sen’s slope indicated that increasing values of mean temperature, solar radiation and decreasing values of relative humidity predominantly contributed to the annual upward trend in ET0 values for the 10 stations. A trivial impact of wind speed on annual ET0 values was observed for the stations. Kalburgi and Udupi stations exhibited positive ET0 trend with the highest and lowest annual values among ten stations.

scholarly journals Using ERA-Interim Reanalysis output for creating datasets of energy-relevant climate variables

2017 ◽  
Author(s):  
Philip D. Jones ◽  
Colin Harpham ◽  
Alberto Troccoli ◽  
Benoit Gschwind ◽  
Thierry Ranchin ◽  
...  
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
Climate Variables ◽  
Climate Data ◽  
Near Surface ◽  
Bias Adjustment ◽  
Dewpoint Temperature ◽  
Data Store

Abstract. The construction of a bias-adjusted dataset of climate variables at the near surface using ERA-Interim Reanalysis is presented. A number of different bias-adjustment approaches have been proposed. Here we modify the parameters of different distributions (depending on the variable), adjusting those calculated from ERA-Interim to those based on gridded station or direct station observations. The variables are air temperature, dewpoint temperature, precipitation (daily only), solar radiation, wind speed and relative humidity, available at either 3 or 6 h timescales over the period 1979-2014. This dataset is available to anyone through the Climate Data Store (CDS) of the Copernicus Climate Change Data Store (C3S), and can be accessed at present from (ftp://ecem.climate.copernicus.eu). The benefit of performing bias-adjustment is demonstrated by comparing initial and bias-adjusted ERA-Interim data against observations.

scholarly journals Future climate uncertainty and spatial variability over Tamilnadu State, India

2015 ◽  
Vol 17 (1) ◽  
pp. 175-185
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
Minimum Temperature ◽  
Climate Models ◽  
Regional Climate ◽  
Future Climate ◽  
Maximum Temperature ◽  
Projection Data ◽  
Climate Uncertainty

<div> <p>The present study analyses future climate uncertainty for the 21st century over Tamilnadu state for six weather parameters: solar radiation, maximum temperature, minimum temperature, relative humidity, wind speed and rainfall. The climate projection data was dynamically downscaled using high resolution regional climate models, PRECIS and RegCM4 at 0.22&deg;x0.22&deg; resolution. PRECIS RCM was driven by HadCM3Q ensembles (HQ0, HQ1, HQ3, HQ16) lateral boundary conditions (LBCs) and RegCM4 driven by ECHAM5 LBCs for 130 years (1971-2100). The deviations in weather variables between 2091-2100 decade and the base years (1971-2000) were calculated for all grids of Tamilnadu for ascertaining the uncertainty. These deviations indicated that all model members projected no appreciable difference in relative humidity, wind speed and solar radiation. The temperature (maximum and minimum) however showed a definite increasing trend with 1.8 to 4.0&deg;C and 2.0 to 4.8&deg;C, respectively. The model members for rainfall exhibited a high uncertainty as they projected high negative and positive deviations (-379 to 854 mm). The spatial representation of maximum and minimum temperature indicated a definite rhythm of increment from coastal area to inland. However, variability in projected rainfall was noticed.</p> </div> <p>&nbsp;</p>

scholarly journals Using ERA-Interim reanalysis for creating datasets of energy-relevant climate variables

2017 ◽  
Vol 9 (2) ◽  
pp. 471-495 ◽  
Author(s):  
Philip D. Jones ◽  
Colin Harpham ◽  
Alberto Troccoli ◽  
Benoit Gschwind ◽  
Thierry Ranchin ◽  
...  
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
Climate Variables ◽  
Climate Data ◽  
Near Surface ◽  
Bias Adjustment ◽  
Dewpoint Temperature ◽  
Data Store

Abstract. The construction of a bias-adjusted dataset of climate variables at the near surface using ERA-Interim reanalysis is presented. A number of different, variable-dependent, bias-adjustment approaches have been proposed. Here we modify the parameters of different distributions (depending on the variable), adjusting ERA-Interim based on gridded station or direct station observations. The variables are air temperature, dewpoint temperature, precipitation (daily only), solar radiation, wind speed, and relative humidity. These are available on either 3 or 6 h timescales over the period 1979–2016. The resulting bias-adjusted dataset is available through the Climate Data Store (CDS) of the Copernicus Climate Change Data Store (C3S) and can be accessed at present from ftp://ecem.climate.copernicus.eu. The benefit of performing bias adjustment is demonstrated by comparing initial and bias-adjusted ERA-Interim data against gridded observational fields.

scholarly journals A Study on Characteristics and Comparison of Evaporation Estimation Methods in Bandung

2021 ◽  
Vol 53 (2) ◽  
pp. 182-199
Author(s):  
Rusmawan Suwarman ◽  
Novitasari Novitasari ◽  
I Dewa Gede Agung Junnaedhi
Keyword(s):  
Regression Analysis ◽  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
Vapour Pressure ◽  
Vapour Pressure Deficit ◽  
Estimation Methods ◽  
Observation Data ◽  
Weather Factor ◽  
Better Than

This study aims to understand the characteristic of evaporation and to evaluate the evaporation estimation methods to be employed in Bandung by using observation data at three different land cover characteristics sites, namely, densely vegetated area (Baleendah), densely built-up area (Ujung Berung), and mix of buildings and vegetation area (ITB). Observation data used are hourly evaporation, vapour pressure deficit, temperature, relative humidity, wind speed, and radiation. The analysis was done mostly by using statistical methods such as regression analysis and error comparison. The result shows the dominant weather factor affecting the evaporation in ITB and Ujung Berung is vapour pressure deficit, and in Baleendah is solar radiation. The methods of evaporation estimations used in this study are Trabert, Schendel, Turc, and CIMIS-Penman methods. The result shows that the original constant values of those methods are significantly correlated. However, the Schendel is found the most overestimated, and the second is Turc. The best estimated evaporation in Baleendah, ITB, and Ujung Berung is calculated using CIMIS-Penman with one hour lag of radiation, Trabert, and Calibrated Schendel, respectively. The improvement of constant value was applied to Schendel and the result is better than the original constants.

scholarly journals Long-term weather, hydrometric, and water chemistry datasets in high-temporal resolution at the La Salle River watershed in Manitoba, Canada

2017 ◽  
Author(s):  
Marcos R. C. Cordeiro ◽  
Jason A. Vanrobaeys ◽  
Henry F. Wilson
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
Water Chemistry ◽  
Temporal Resolution ◽  
Time Step ◽  
Canadian Prairies ◽  
River Watershed ◽  
Stream Discharge

Abstract. Lack of long-term datasets in fine temporal resolution hinders environmental studies and modelling efforts; to address this issue in the La Salle River watershed, in Canada, long-term weather (1990–2013), hydrometric (1990–2013 except years with no or poor data), and water chemistry (2009–2013) datasets were developed. The weather variables consisted of temperature, relative humidity, wind speed, solar radiation, and precipitation in an hourly time-step, which is required for physically-based modelling. The only hydrometric variable included in the dataset was stream discharge in a daily time-step, which is the usual time-frame for summarizing the results of long-term studies. The water chemistry data consisted of total nitrogen (TN), total dissolved nitrogen (TDN), total phosphorus (TP) and total dissolved phosphorus (TDP). Samples were collected weekly during the open water season at the same site as they hydrometric gauging station (05OG008) starting in August 2009 until October 2012 with some gaps (i.e. Fall 2011, Spring 2012, September 2012). In 2013 the frequency of sampling was increased to daily or sub-daily during high stream discharge and weekly during low stream discharge. An overview of the data indicates that values and trends are within ranges reported in the literature for the region. Mean annual, winter, and summer temperatures were 3.5 °C–10.7 °C and 17.2 °C, respectively. Annual relative humidity averaged 73.1 % but tended to be higher and more homogenous in cold seasons. Wind speed was very similar over the different seasons with annual average of 4.3 m/s. Solar radiation followed the typical curve reported for western Canada, with peak daily average values around 250 W/m2 in July. The precipitation records were mostly comprised of dry hours and the characteristic precipitation pattern of the Canadian Prairies with high frequency of small precipitation events as observed, with 75.3 % of the hourly precipitation being equal or less than 2 mm/h. The hydrometric characteristics of the dataset were also typical of the Canadian Prairies; the average peak discharge over the entire period was larger in April (2.3 m3/s) due to large amounts of snowmelt runoff. The average concentrations of TN, TDN, TP and TDP of 1.54, 1.35, 0.56, and 0.49 mg/L, respectively, were in agreement with values found in previous studies at the same location. The datasets for weather (https://doi.org/10.23684/ODI-2017-00957), discharge (https://doi.org/10.23684/ODI-2017-00959) and water chemistry (https://doi.org/10.23684/ODI-2017-00958) are accessible through the Government of Canada's Open Data portal (http://open.canada.ca).

scholarly journals Investigation on the Temperature Distribution of Asphalt Overlay on the Existing Cement Concrete Pavement in Hot-Humid Climate in Southern China

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Zuzhong Li ◽  
Yayun Zhang ◽  
Chunguang Fa ◽  
Xiaoming Zou ◽  
Haiwei Xie ◽  
...  
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
Prediction Model ◽  
Air Temperature ◽  
Concrete Pavement ◽  
Humid Climate ◽  
Temperature Prediction ◽  
Asphalt Overlay ◽  
Hot Humid Climate

Temperature is known to be one of the most important factors affecting the design and performance of asphalt concrete pavement. The distresses of asphalt overlay are closely related to its temperature, particularly in Guangxi, a hot-humid-climate region in China. This research is to analyze the impact of meteorological factors on temperature at 2 cm depth in asphalt overlay by ReliefF algorithm and also obtain the temperature prediction model using MATLAB. Two test sites were installed to monitor the temperatures at different pavement depths from 2014 to 2016; meanwhile, the meteorological data (including air temperature, solar radiation, wind speed, and relative humidity) were collected from the two meteorological stations. It has been found that the temperature at 2 cm depth experiences greater temperature variation, and the maximum and minimum temperatures of asphalt overlay, respectively, occur at 2 cm depth and on the surface. Besides, the results of ReliefF algorithm have also shown that the temperature at 2 cm depth is affected significantly by solar radiation, air temperature, wind speed, and the relative humidity. Based on these analyses, the prediction model of maximum temperature at 2 cm depth is developed using statistical regression. Moreover, the data collected in 2017 are used to validate the accuracy of the model. Compared with the existing models, the developed model was confirmed to be more effective for temperature prediction in hot-humid region. In addition, the analysis of rutting depth and overlay deformation for the two test sections with different materials is done, and the results have shown that reasonable structure and materials of asphalt overlay are vital to promote the high-temperature antideforming capability of pavement.

scholarly journals Enhanced Prediction of Solar Radiation Using NARX Models with Corrected Input Vectors

Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2576 ◽  
Author(s):  
Eduardo Rangel ◽  
Erasmo Cadenas ◽  
Rafael Campos-Amezcua ◽  
Jorge L. Tena
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
Mean Squared Error ◽  
Absolute Error ◽  
Relevant Information ◽  
Causality Tests ◽  
Narx Models ◽  
Persistence Model ◽  
Narx Model

The main objective of this work is to analyze and configure appropriately the input vectors to enhance the performance of NARX models to forecast solar radiation one hour ahead. For this study, Engle–Granger causality tests were implemented. Additionally, collinearity among the meteorological variables of the databases was examined. Different databases were used to test the contribution of these analyses in the improvement of the input vectors. For that, databases from three cities of Mexico with different climates were obtained, namely: Chihuahua, Temixco, and Zacatecas. These databases consisted of hourly measurements of the following variables: solar radiation (SR), wind speed (WS), relative humidity (RH), pressure (P), and temperature (T). Results showed that, in all three cases, proper NARX models were produced even when using input vectors formed only with solar radiation and temperature data. Consequently, it was inferred that pressure, wind speed, and relative humidity could be excluded from the input vectors of the forecasting models since, according to the causality tests, they did not provide relevant information to improve the solar radiation forecast in the studied cases. Conversely, these variables could generate spurious results. Forecasting results obtained with the NARX model were compared to the smart persistence model, commonly used to validate SR prediction. Error measures, such as mean absolute error (MAE) and root mean squared error (RMSE), were used to compare prediction results obtained from different models. In all cases, results obtained from the enhanced NARX model surpassed the results of the smart persistence, namely: in Chihuahua up to 11.5 % , in Temixco up to 15.7 % , and in Zacatecas up to 27.2 % .

Relationship between meteorological conditions and respiratory syncytial virus in a tropical country

2015 ◽  
Vol 143 (12) ◽  
pp. 2679-2686 ◽  
Author(s):  
C. E. RODRIGUEZ-MARTINEZ ◽  
M. P. SOSSA-BRICEÑO ◽  
R. ACUÑA-CORDERO
Keyword(s):  
Respiratory Syncytial Virus ◽  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
Latin American ◽  
Meteorological Conditions ◽  
Acute Lower Respiratory Infection ◽  
Average Temperature ◽  
Monthly Average ◽  
Syncytial Virus

SUMMARYThis study aimed to determine which meteorological conditions are associated with respiratory syncytial virus (RSV) isolates in a population of children hospitalized with acute lower respiratory infection (ALRI) in Bogota, Colombia. In an analytical cross-sectional study, links were examined between the number of monthly RSV infections and monthly average climatic variation (temperature, relative humidity, rainfall, wind speed, solar radiation) between 1 January 2010 and 30 April 2011 in a population of hospitalized children aged <3 years with ALRI caused by RSV. Out of a total of 1548 children included in the study (mean age 9·2 ± 8·5 months), 1194 (77·1%) presented RSV infection during the 3-month period from March to May. In the multivariate analysis, after controlling for wind speed, relative humidity, and solar radiation, monthly average temperature [incident rate ratio (IRR) 3·14, 95% confidence interval (CI) 1·56–6·30,P= 0·001] and rainfall (IRR 1·008, 95% CI 1·00–1·01,P= 0·048) were independently associated with the monthly number of RSV infections. In conclusion, in Bogota, a tropical Latin American city, average temperature and rainfall are the meteorological variables most strongly associated with RSV isolation in children hospitalized with ALRI in the city.

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