Average Monthly Minimum Temperatures Research Articles

Minimum Temperature Forecasting Using Gated Recurrent Unit

Aim: To forecast the monthly average Minimum Temperature (ºC) in Coimbatore district.
 Study Design: Gated Recurrent Unit (GRU) has been employed to forecast the Minimum Temperature.
 Place and Duration of Study: Time series data for average month wise Minimum Temperature from January 1982 to September 2022 was collected from Agro Climate Research Centre, TNAU for Coimbatore District.
 Methodology: GRU which belongs to the field of deep learning has been employed to anticipate the average monthly Minimum Temperature by analyzing time series data from January 1982 to September 2022 in the district of Coimbatore. The model was trained using data from 1982 January to 2019 December and tested on data from 2020 January to 2022 September. After training and testing the algorithm was deployed to forecast Minimum Temperature for the lead time ahead.
 Results: The GRU model generated RMSE and MAE scores of 0.694ºC and 0.523ºC, respectively, for Minimum Temperature. GRU model had a Willmott’s Index of Agreement (WI) value as 0.943 that is very close to 1. This demonstrates the effectiveness of the model built to effectively predict the Minimum Temperature. The study's evaluation of the RMSE, MAE, and Willmott Index value made it readily evident that the GRU model performed quite accurately for forecasting Minimum Temperature. Gated Recurrent Unit algorithm was used to forecast the Minimum Temperature from October 2022 till December 2023 that is for the next 15 months.

Geographical Analysis of Repeat Cold Waves in Kurdistan Region for the Period 2000-2017

In this paper, we investigated changes in cold waves in Kurdistan region over the period 2000–2017. Cold waves it means decrease 5oc minimum temperature degree at least from the average monthly minimum temperature for this month and continues for 3 days consecutive at least. The study found 132 cold waves repeat in Kurdistan region, that is 112 waves were the type of shortwave it means %84.85 of them were shortwaves, 18 waves medium and only 2 waves were the type of long waves. About severity of the temperature of cold waves the study also, found different types, for example in all cold waves about %67.42 or 89 waves were from the type of moderate waves, 30 waves strong and 13 waves were extreme. About of the cold days over the period of time include 904 threshold cold waves, in this number 530 days were in the type of the cold day of cold waves, and 374 days were the Temperature fluctuation of cold days. As well as the paper found that the annual repetition cold waves vary from month to month, and the season to season, it was found that cold waves were highest in spring and lowest in summer. The most geographical distribution of system atmospheric pressure effect on the weather and cold waves in study area is The Siberian Heights.

Ten years of monitoring malaria trend and factors associated with malaria test positivity rates in Lower Moshi

BackgroundHigh altitude settings in Eastern Africa have been reported to experience increased malaria burden due to vector habitat expansion. This study explored possible associations between malaria test positivity rates and its predictors including malaria control measures and meteorological factors at a high-altitude, low malaria transmission setting, south of Mount Kilimanjaro.MethodsMalaria cases reported at the Tanganyika Plantation Company (TPC) hospital’s malaria registers, meteorological data recorded at TPC sugar factory and data on bed nets distributed in Lower Moshi from 2009 to 2018 were studied. Correlation between bed nets distributed and malaria test positivity rates were explored by using Pearson correlation analysis and the associations between malaria test positivity rates and demographic and meteorological variables were determined by logistic regression and negative binomial regression analyses, respectively.ResultsMalaria cases reported at TPC hospital ranged between 0.48 and 2.26% per year and increased slightly at the introduction of malaria rapid diagnostic tests. The risk of testing positive for malaria were significantly highest among individuals aged between 6 and 15 years (OR = 1.65; 1.65 CI = 1.28–2.13; p = 0.001) and 16–30 years (OR = 1.49; CI = 1.17–1.89; p = 0.001) and when adjusted for age, the risk were significantly higher among male individuals when compared to female individuals (OR = 1.54; 1.00–1.31; p = 0.044). Malaria test positivity rates were positively associated with average monthly minimum temperatures and negatively associated with average monthly maximum temperatures (incidence rate ratio (IRR) = 1.37, 95% confidence interval (CI) = 1.05–1.78, p = 0.019 and IRR = 0.72, 95% CI = 0.58–0.91, p = 0.005, respectively). When analysed with one month lag for predictor variables, malaria test positivity rates were still significantly associated with average monthly minimum and maximum temperatures (IRR = 1.67, 95% CI = 1.28–2.19, p = 0.001 and IRR = 0.68, 95% CI = 0.54–0.85, p = 0.001, respectively). Average monthly rainfall and relative humidity with or without a one month lag was not associated with malaria test positivity rates in the adjusted models. Explopring possible associations between distribution of long-lasting insecticidal nets, (LLINs) and malaria test positivity rates showed no apparent correlation between numbers of LLINs distributed in a particular year and malaria test positivity rates.ConclusionIn Lower Moshi, the risk of being tested positive for malaria was highest for older children and male individuals. Higher minimum and lower maximum temperatures were the strongest climatic predictors for malaria test positivity rates. In areas with extensive irrigation activity as in Lower Moshi, vector abundance and thus malaria transmission may be less dependent on rainfall patterns and humidity. Mass distribution of LLINs did not have an effect in this area with already very low malaria transmission.

Assessment of regional weather and climatic conditions as health risk factors according to the wind-cold index

Determined the cold periods of the year in different weather and climatic conditions of the Krasnoyarsk Territory. We assessed the health risk of the population under the influence of temperature and wind speed in an open area according to the wind-cold index (which determines the comfort and discomfort of the weather). The average monthly daily, average monthly minimum temperatures and wind speeds were estimated for 10 years (2010–2019). Wind speed was assessed using the Bothford scale. In terms of ambient temperature, the cold period lasted: subarctic zone (Norilsk) — 5, moderate continental (Krasnoyarsk and Minusinsk) — 3 months. According to the wind-cold index (in terms of average temperature and wind speed), the period of severe weather in the subarctic zone lasted from 6 to 7 months a year. Three months of the year, the meteorological perception was assessed as «very» and 1 month — as «extremely cold». In the region of Krasnoyarsk, as well as in Minusinsk, the cold «uncomfortable period» was lengthened by 1 month. The health risk under the combined influence of the minimum temperature and maximum wind increased in the subarctic zone up to 8, moderate continental up to 5 (Krasnoyarsk) — 5–6 (Minusinsk) months. In the area of Norilsk, the period, assessed as «extremely cold, exposed parts of the body can be supercooled by 10 minutes,» extended by 4 months, in Krasnoyarsk such a period was possible in January, Minusinsk was recorded in January and February. In the conditions of one climatic zone (Krasnoyarsk, Minusinsk), regional features of weather and climatic characteristics (duration of cold and warm periods, temperature, wind speed, severity and duration of periods of severe weather), which can affect the well-being and state of health of the population, have been identified.

Air temperature and precipitation regime in Ukraine in 2021-2050 by CORDEX model ensemble

Global temperatures over the period of 2081–2100 are expected to rise by 0.3–4.8 °C compared to the period of 1986–2005. According to the previous studies, the average annual air temperature in all regions of Ukraine will keep increasing in the near future and the maximum increase in precipitation is expected mainly in the western and northern regions during winter and spring, whereas the decrease in precipitation will be registered in the central, eastern and southern regions during summer and autumn. This article aims to identify the features of changes in air temperature and precipitation for different regions of Ukraine in 2021–2050 based on the modelling results of the ensemble of CORDEX models as per the RCP4.5 scenario. 16 simulation runs for 7 regional climate models were selected for the analysis and the results were presented for five regional centers of Ukraine: Kyiv, Lviv, Kropyvnytskyi, Kharkiv and Odesa.
 It is shown that future monthly precipitation in all regions tends to increase by an average of 20–40 mm during autumn, winter and spring, whereas the decrease is expected to occur in summer. According to some models, the monthly precipitation will be close to zero in the Southern Ukraine in July and August, which is typical for the Mediterranean climate. Compared to the period of 1961–1990, the average monthly temperature will undergo small changes (up to 1 °C) in spring and autumn, while the temperature in summer and winter will increase by 2.5–3.5 °C. In Odesa, in contrast to the present-day situation, a positive average monthly air temperature will be expected to be recorded throughout the whole year, and only 25% of the runs show negative average monthly minimum temperatures. In the Northern Ukraine, the average monthly minimum and maximum temperatures in winter will increase by 2.0–2.5 °C, and in summer only the maximum air temperature will increase significantly.
 Thus, we can assume a change in the regime of moisture supply in Ukraine over the next thirty years. One can also assume a high probability of snow cover absence throughout the whole winter in the Southern Ukraine as a result of positive temperatures.

Sensitivity of vegetation to climate variability and its implications for malaria risk in Baringo, Kenya.

The global increase in vector borne diseases has been linked to climate change. Seasonal vegetation changes are known to influence disease vector population. However, the relationship is more theoretical than quantitatively defined. There is a growing demand for understanding and prediction of climate sensitive vector borne disease risks especially in regions where meteorological data are lacking. This study aimed at analyzing and quantitatively assessing the seasonal and year-to-year association between climatic factors (rainfall and temperature) and vegetation cover, and its implications for malaria risks in Baringo County, Kenya. Remotely sensed temperature, rainfall, and vegetation data for the period 2004–2015 were used. Poisson regression was used to model the association between malaria cases and climatic and environmental factors for the period 2009–2012, this being the period for which all datasets overlapped. A strong positive relationship was observed between the Normalized Difference Vegetation Index (NDVI) and monthly total precipitation. There was a strong negative relationship between NDVI and minimum temperature. The total monthly rainfall (between 94 -181mm), average monthly minimum temperatures (between 16–21°C) and mean monthly NDVI values lower than 0.35 were significantly associated with malaria incidence rates. Results suggests that a combination of climatic and vegetation greenness thresholds need to be met for malaria incidence to be significantly increased in the county. Planning for malaria control can therefore be enhanced by incorporating these factors in malaria risk mapping.

Changes in selected physical water quality characteristics after thinning in a forested watershed

Climate change is a natural phenomenon with far-reaching impacts. Due to global warming, forest vegetation patterns in the Mediterranean region can be affected and the extent of forested areas can be altered. The purpose of this study was to investigate the impact of slightly decreased forest density on physical water quality parameters by employing 18% thinning with a paired watershed methodology in a broadleaf forest ecosystem. After a 70-month monitoring period that started in December 2005, calibration equations were established between control and treatment watersheds for streamwater parameters including pH, color, turbidity, electrical conductivity (EC), suspended sediment concentration (SSC), water and air temperatures. After 18% standing timber volume was harvested from the treatment watershed, streamwater was also sampled for the same parameters in both watersheds during the 46-month treatment period between January 2012 and October 2015. Changes in the mean monthly values of streamwater parameters were determined as the differences between measured and estimated values derived from the calibration equations. Results showed that 18% forest thinning caused 7.3 μS cm−1 increase in the overall average monthly EC, 2.8 NTU in turbidity, 15.1 mg L−1 in SSC, 0.3 °C increase in the air temperature, and 1.2 °C in the maximum air temperature, whereas it caused 0.5 °C decrease in overall average monthly minimum temperature and 1.3C.P·U in overall mean monthly color. In contrast, forest harvest did not have significant impact on overall average monthly pH and streamwater temperature values. Results of 18% forest harvest indicated that even a small decrease in the forest cover can significantly affect selected physical water quality parameters and hence aquatic life in the forested watersheds.

한국 남부지방 난온대성 상록활엽수의 동해피해 -전라남도 광양시 중마동의 후박나무를 중심으로-

This study was carried out to clarify the climatic factors of the freezing injury for the judgement on the adaptation areas of evergreen broad-leaved trees. We surveyed and analyzed the climatic factors of the freezing injury to Machilus thunbergii Siebold & Zucc. on the streets with the analyzation of planting grounds, soil conditions and the surrounding buildings. This study showed that only the minimum air temperature factor out of the other climate elements, which were the annual precipitation; the average annual temperature; the average monthly temperature of january; the average monthly minimum temperature of January; the average temperature of the coldest month; the warmth index and the coldness index, was matched up with the previous theories and reports on the freezing damages on the evergreen broad leaved trees and Machilus thunbergii Siebold & Zucc. The freezing injury of Machilus thunbergii Siebold & Zucc was occurred when the mean minimum temperature of the coldest month(TMC) in winter season fell down below <TEX>$-4.1^{\circ}C$</TEX> and the temperature fell down below <TEX>$-9.2^{\circ}C$</TEX>. The freezing damage on Machilus thunbergii Siebold & Zucc surrounded by high buildings were less than those surrounded by low buildings or at non buildings.

Predicting the distribution of the air pollution sensitive lichen species Usnea hirta

AbstractUsnea hirta, an important member of the lichen family Parmeliaceae, has long been used as a bio-monitor of air pollution, particularly of sulphur dioxide in North America. Although U. hirta has a wide geographical distribution, it is important to be able to identify accurately the optimal habitat conditions for air pollution-sensitive species, thus making it possible to more effectively and efficiently establish air quality bio-monitoring stations. We modelled the distribution of U. hirta as a function of nine variables, five macroclimatic variables: average monthly precipitation, average monthly minimum temperature, average monthly maximum temperature, solar radiation, and integrated moisture index, and four topographic variables: elevation, slope, aspect, and land forms and uses for the White River National Forest, Colorado. The response variable was developed based on the presence or absence of U. hirta at each of 72 bio-monitoring baseline sites established in selected portions of four intermountain area states. Our model was developed using Non-Parametric Multiplicative Regression (NPMR) analysis, a modelling approach that analyzes environmental gradients, or predictor variables, against known locations for individuals of the model species. Finally, we evaluated our model on the basis of log β values and overall improvement over a naïve model and the Monte Carlo Permutation Test with 1000 randomized runs. The best model for U. hirta included four variables – solar radiation, average monthly precipitation, and average monthly minimum and maximum temperatures (log β=3·68). Among these four variables, average monthly maximum temperature was the most influential predictor (sensitivity=0·71) for the distribution of U. hirta. The occurrence rate for U. hirta, based on field validation, was 45·5%, 65·4%, and 70·4% for low, medium, and high probability areas, respectively. This study showed that our model was successful in predicting the distribution of U. hirta in the White River National Forest. Based on these results, the north-eastern and western portions of the forest appear to offer the most favourable conditions for the installation of future air quality bio-monitoring baseline sites.

Ridge regression technique to determine the environmental influences on tef (Eragrostis tef) grain yield

Tef grain yield is dependent on a number of component characters such as plant height and panicle length. These characters and consequently yield are governed by a large number of factors including environmental factors. The objective of this paper was to determine the environmental influences on tef grain yield. The effects of eleven environmental variables on tef yield were studied using least squares and ridge regression analyses. The results revealed that the least squares estimates of regression coefficients for seven environmental variables did not give a correct indication of the influence of the variables on tef yield but that the estimates from ridge regression were stable. In addition, the ridge regression model has a lower mean square error. Tef grain yield is positively correlated to rainfall, average monthly minimum temperatures, soils dominated by silt with adequate quantities of available nitrogen while it is negatively influenced by average monthly maximum temperatures and clay soils. The results obtained from this study are in accordance with previous literature about the effects of environmental factors on yield of tef cultivars.

Treeline dynamics in relation to climatic variability in the central Tianshan Mountains, northwestern China

ABSTRACTAim Climate variability may be an important mediating agent of ecosystem dynamics in cold, arid regions such as the central Tianshan Mountains, north‐western China. Tree‐ring chronologies and the age structure of a Schrenk spruce (Picea schrenkiana) forest were developed to examine treeline dynamics in recent decades in relation to climatic variability. Of particular interest was whether tree‐ring growth and population recruitment patterns responded similarly to climate warming.Location The study was conducted in eight stands that ranged from 2500 m to 2750 m a.s.l. near the treeline in the Tianchi Nature Reserve (43°45′−43°59′ N, 88°00′−88°20′ E) in the central Xinjiang Uygur Autonomous Region, northwestern China.Methods Tree‐ring cores were collected and used to develop tree‐ring chronologies. The age of sampled trees was determined from basal cores sampled as close as possible to the ground. Population age structure and recruitment information were obtained using an age–d.b.h. (diameter at breast height) regression from the sampled cores and the d.b.h. measured on all trees in the plots. Ring‐width chronologies and tree age structure were both used to investigate the relationship between treeline dynamics and climate change.Results Comparisons with the climatic records showed that both the radial growth of trees and tree recruitment were influenced positively by temperature and precipitation in the cold high treeline zone, but the patterns of their responses differed. The annual variation in tree rings could be explained largely by the average monthly minimum temperatures during February and August of the current year and by the monthly precipitation of the previous August and January, which had a significant and positive effect on tree radial growth. P. schrenkiana recruitment was influenced mainly by consecutive years of high minimum summer temperatures and high precipitation during spring. Over the last several decades, the treeline did not show an obvious upward shift and new recruitment was rare. Some trees had established at the treeline at least 200 years ago. Recruitment increased until the early 20th century (1910s) but then decreased with poor recruitment over the past several decades (1950–2000).Main conclusions There were strong associations between climatic change and ring‐width patterns, and with recruitments in Schrenk spruce. Average minimum temperatures in February and August, and total precipitation in the previous August and January, had a positive effect on tree‐ring width, and several consecutive years of high minimum summer temperature and spring precipitation was a main factor favouring the establishment of P. schrenkiana following germination within the treeline ecotone. Both dendroclimatology and recruitment analysis were useful and compatible to understand and reconstruct treeline dynamics in the central Tianshan Mountains.

Koeleria macrantha (Ledeb.) Schultes (K. alpigena Domin, K. cristata (L.) Pers. pro parte, K. gracilis Pers., K. albescens auct. non DC.)

<i>Koeleria macrantha</i> (Ledeb.) Schultes (<i>K. alpigena</i> Domin, <i>K. cristata</i> (L.) Pers. pro parte, <i>K. gracilis</i> Pers., <i>K. albescens</i> auct. non DC.)

Climatic Assessment of the Arid Southwestern United States for Use in Predicting Evapotranspiration of Turfgrass

Climatic conditions were assessed at three locations in the arid southwestern United States over a two year period. The three locations were Las Vegas, NV, Tucson, AZ and Palm Desert, CA. Automated weather stations monitored maximum and minimum temperature, relative humidity, solar radiation, wind run and rainfall. Data were input into the empirical based Penman combination equation to predict potential evapotranspiration (ETo). Surveys were conducted at all three locations to evaluate the soil conditions, water availability, turfgrass management and crop coefficients used. Only slight differences existed beween average monthly minimum temperatures, maximum temperatures and solar radiation at the three sites. However, differences in average monthly wind run and relative humidity at the three sites led to greater separation in the ETo estimates during summer months. These differences resulted in a 7% and 13% error in estimating monthly ETo at the Palm Desert and Tucson sites respectively, based on using th...

Wintering Biology of Ruby-Crowned Kinglets in the Lower Colorado River Valley

The Ruby-crowned Kinglet (Regulus calendula) was studied from October-April during four years, 1975-1979, among six major plant communities in the riparian corridor of the lower Colorado River valley. Kinglets were most abundant in cottonwood-willow and least abundant in arrowweed. Within each community, the greatest density of kinglets generally occurred in areas of tall, dense vegetation. Density differed significantly among the four years in November, the month of peak abundance, and in February, winter's end. Populations decreased significantly through the winter in each year and decreases were not uniform among plant communities. Differences in relative abundances and winter population decreases were related to winter weather conditions. During the study period, kinglets were subject to marked seasonality as determined by decreases in average monthly minimum temperatures, changes in tree phenology, and changes in insect abundance and biomass. Kinglet responses to seasonality were most apparent in population dynamics, distribution among plant communities, foraging substrate utilization and choice of prey. Analysis of these data emphasizes the selective importance of the nonbreeding season ecology to kinglets and implies that these birds may be winter-limited.

The effect of low temperatures on banana yields

Banana yields from four regions in Israel have been correlated with low temperatures over a period of eleven years. It was found that the average monthly minimum temperatures during the winter season affect primarily the yield of the current year, while the "quantity of cold" i.e. a measure of temperatures below 5°C affects the yield of the following year. Mild cold weather during November and March have a beneficial effect. The model used fitted the data fairly well, explaining 98% to 61% of the total variation in yield, depending on the climatic region.