Average Minimum Temperature Research Articles

Spatio-Temporal Analysis of Climatic Variables in the Munneru River Basin, India, Using NEX-GDDP Data and the REA Approach

For effective management practices and decision-making, the uncertainty associated with Regional Climate Models (RCMs) and their scenarios need to be assessed in the context of climate change. The present study analyzes the various uncertainties in the precipitation and temperature datasets of NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) under Representative Concentrative Pathways (RCPs) 4.5 and 8.5 over the Munneru river basin, in India, using the Reliable Ensemble Averaging (REA) method. From the available 21 RCMs, the top five ranked are ensembled and bias-corrected at each grid using the non-parametric quantile mapping method for the precipitation and temperature datasets. The spatio-temporal variations in precipitation and temperature data for the future periods, i.e., 2021–2039 (near future), 2040–2069 (mid future) and 2070–2099 (far future) are analyzed. For the period 2021–2099, annual average precipitation increases by 233 mm and 287 mm, respectively, the in RCP 4.5 and RCP 8.5 scenarios when compared to the observed period (1951–2005). In both the RCP 4.5 and RCP 8.5 scenarios, the annual average maximum temperature rises by 1.8 °C and 1.9 °C, respectively. Similarly, the annual average minimum temperature rises by 1.8 °C and 2.5 °C for the RCP 4.5 and RCP 8.5 scenarios, respectively. The spatio-temporal climatic variations for future periods obtained from high-resolution climate model data aid in the preparation of water resource planning and management options in the study basin under the changing climate. The methodology developed in this study can be applied to any other basin to analyze the climatic variables suitable for climate change impact studies that require a finer scale, but the biases present in the historical simulations can be attributed to uncertainties in the estimation of climatic variable projections. The findings of the study indicate that NEX-GDDP datasets are in good agreement with IMD datasets on monthly scales but not on daily scales over the observed period, implying that these data should be scrutinized more closely on daily scales, especially when utilized in impact studies.

A Novel Mini-Channel Heat Sink Design with Arc-Type Design Domain by Topology Optimization.

Based on the advantages of the topology optimization method, a new mini-channel heat sink with arc-type design domain topology design is proposed in this work. This arc-type design domain is used to realize the flow distribution uniformity. Two dual objective optimization functions were selected to complete the topology design, and two topology optimization mini-channel models M1 and M2 were obtained. The aim of M1 is to achieve minimum average temperature and fluid dissipation of the heat source area. The fluid dissipation was used to characterize the pressure drop characteristics. The aim of M2 is to achieve minimum temperature difference and fluid dissipation of the heat source area. Then, the fluid and heat transfer characteristics of M1, M2, and the traditional straight heat sink M3 were analyzed by numerical simulation. Compared with straight mini-channel heat sink M3, the temperature differences of the mini-channel heat sink designed M1 and the mini-channel heat sink designed M2 were decreased by 31.6% and 42.48%, respectively. Compared with M3, the pressure drops of M1 and M2 were decreased by 22.7% and 30.9%, respectively. Moreover, the Nusselt number of the mini-channel heat sink designed M1 was increased by 34.43%. In comparison, that of the mini-channel heat sink-designed M2 increased by 15.86%. The thermal performance evaluation criteria (PEC) showed that the PEC value of M1 was greater than 1.4, while the PEC value of M2 was less than 1.14. Finally, experiments were conducted for M1 to verify the accuracy of the numerical simulation. It was found that the simulation results agreed well with the experimental results.

Highly-Scattering Cellulose-Based Films for Radiative Cooling.

Passive radiative cooling (RC) enables the cooling of objects below ambient temperature during daytime without consuming energy, promising to be a game changer in terms of energy savings and CO2 reduction. However, so far most RC surfaces are obtained by energy‐intensive nanofabrication processes or make use of unsustainable materials. These limitations are overcome by developing cellulose films with unprecedentedly low absorption of solar irradiance and strong mid‐infrared (mid‐IR) emittance. In particular, a cellulose‐derivative (cellulose acetate) is exploited to produce porous scattering films of two different thicknesses, L ≈ 30 µm (thin) and L ≈ 300 µm (thick), making them adaptable to above and below‐ambient cooling applications. The thin and thick films absorb only ≈5% of the solar irradiance, which represents a net cooling power gain of at least 17 W m−2, compared to state‐of‐the‐art cellulose‐based radiative‐cooling materials. Field tests show that the films can reach up to ≈5 °C below ambient temperature, when solar absorption and conductive/convective losses are minimized. Under dryer conditions (water column = 1 mm), it is estimated that the films can reach average minimum temperatures of ≈7–8 °C below the ambient. The work presents an alternative cellulose‐based material for efficient radiative cooling that is simple to fabricate, cost‐efficient and avoids the use of polluting materials.

Assessment and Prediction of Heat Transfer Performance of Oscillating Heat Pipe using Acetone

Heat pipe is a device to enhance the performance of heat transfer, in particular to transition phase change process. The present investigation is carried out to measure the thermal performance of a closed loop acetone filled oscillating heat pipe with four turns is fabricated and tested. The test was carried out for the inner diameter of 1.7 mm copper tube by varying the acetone of 50%, 60%, 70% and 80% filler ratio with a heat input of 15 W to 40 W in steps of 5 W has been considered. The results shows that 80% acetone filled OHP provides the better thermal performance with an average minimum temperature difference between condenser and evaporator by 6.03%, heat transfer coefficient increased by 77% and the thermal resistance decrease by 43% respectively. The mathematical modelling was developed to predict the performance of the heat transfer. The model clearly shows that the independent variables are statistically significant with a p-value of 0.05 and the uncertainty analysis between the experimental and predicted values are less than 10%.

Spatiotemporal Evolution of the Carbon Fluxes from Bamboo Forests and their Response to Climate Change Based on a BEPS Model in China

Carbon flux is the main basis for judging the carbon source/sink of forest ecosystems. Bamboo forests have gained much attention because of their high carbon sequestration capacity. In this study, we used a boreal ecosystem productivity simulator (BEPS) model to simulate the gross primary productivity (GPP) and net primary productivity (NPP) of bamboo forests in China during 2001–2018, and then explored the spatiotemporal evolution of the carbon fluxes and their response to climatic factors. The results showed that: (1) The simulated and observed GPP values exhibited a good correlation with the determination coefficient (R2), root mean square error (RMSE), and absolute bias (aBIAS) of 0.58, 1.43 g C m−2 day−1, and 1.21 g C m−2 day−1, respectively. (2) During 2001–2018, GPP and NPP showed fluctuating increasing trends with growth rates of 5.20 g C m−2 yr−1 and 3.88 g C m−2 yr−1, respectively. The spatial distribution characteristics of GPP and NPP were stronger in the south and east than in the north and west. Additionally, the trend slope results showed that GPP and NPP mainly increased, and approximately 30% of the area showed a significant increasing trend. (3) Our study showed that more than half of the area exhibited the fact that the influence of the average annual precipitation had positive effects on GPP and NPP, while the average annual minimum and maximum temperatures had negative effects on GPP and NPP. On a monthly scale, our study also demonstrated that the influence of precipitation on GPP and NPP was higher than that of the influence of temperature on them.

Prediction of the global potential geographical distribution of Hylurgus ligniperda using a maximum entropy model

Hylurgus ligniperda (Fabricius) is native to Europe but has established populations in many countries and regions. H. ligniperda mainly infests Pinus species, and can cause severe weakness and even death of the host through its boring activity; it can also be a vector of various pathogenic fungi. This study was conducted to investigate the environmental variables limiting the distribution of H. ligniperda and the change trend of its suitable areas under climate change. We used a maximum entropy model to predict the potential geographical distribution of H. ligniperda on a global scale under near current and future climatic scenarios using its occurrence data and environmental variables. The result shows that the areas surrounding the Mediterranean region, the eastern coastal areas of Asia, and the southeastern part of Oceania are highly suitable for H. ligniperda . The environmental variables with the greatest effect on the distribution of H. ligniperda were determined using the jackknife method and Pearson's correlation analysis and included the monthly average maximum temperature in April, precipitation of driest quarter, the monthly average minimum temperature in December, precipitation of coldest quarter, mean temperature of driest quarter and mean diurnal range. Excessive precipitation in winter and low temperatures in spring had a great effect on the distribution of H. ligniperda . The potential geographical distribution of H. ligniperda was predicted to change under future climatic conditions compared with near current climate conditions. Highly suitable areas, moderately suitable areas and low suitable areas were predicted to increase by 59.99%, 44.43% and 22.92%, respectively, under the 2081–2100 ssp245 scenario.

Characteristics of Climate Change in the Lake Basin Area of Gangcha County

This paper mainly was based on the average temperature, precipitation, humidity, and wind direction of Gangcha county from 1960 to 2013. By using wavelet analysis and Mann-Kendall (M-K) mutation analysis, specifically analyzed the climate change characteristics in the lake basin area of Gangcha county. The result showed that the climatic change in the lake basin area of Gangcha county is noticeable. The average temperature, average minimum temperature, average maximum temperature, and evaporation showed an increasing trend. But the evaporation in the study area was higher than precipitation. The average relative humidity showed a decreasing trend. And the sunshine and the average wind speed percentage showed a significant decreasing trend. Utilizing the Morelet wavelet, The time series of annual mean temperature, annual evaporation and annual sunshine percentage all have quasi3a and quasi4A periods, and the annual mean precipitation has quasi2–3A, quasi2–5A and quasi2–6A periods, which appear in 1996–2005, 1962–1978 and 1978–1996 respectively. The mean annual relative humidity has obvious quasi2–7A and quasi3A time series, which appear from 1960 to 1996, 1997 to 2005 and after 2008, respectively. The annual mean wind speed has quasi3–4A and quasi5A time series characteristics, which appear in 1964–1967, 1984–1995, after 2009 and 1971–1983, respectively. Through Mann-Kendall (M-K) mutation analysis, it is found that the mutations of evaporation and the average speed of wind are significant. The mutation of evaporation started in 2004, and the mutation of average started in 2003.

Assessment of the Contribution of Local and Regional Biomass Burning on PM2.5 in New York/New Jersey Metropolitan Area

The sources of fine particulate matter (PM2.5, particles with diameter < 2.5 μm) in four monitoring sites in the New York/New Jersey metropolitan statistical area from 2007 to 2017 was apportioned by positive matrix factorization (PMF) of chemical speciation data. Biomass burning, secondary inorganic (i.e., ammonium sulfate and nitrate) and primary traffic exhausts were the predominant PM2.5 sources. The declining trends of PM2.5 mass in all four sites were very well correlated with decreasing secondary sulfate levels due to SO2 emission reductions by coal-fired power plants. The contributions of secondary nitrate, primary traffic exhausts and diesel particles did not change (or slightly increased) over time except for the Queens site, where statistically significant declines were computed. Biomass burning contributions increased in the Queens and Chester sites but declined in the Division Str and Elizabeth Lab sites, although significant interannual variability was observed. Wintertime biomass burning aerosols were most likely due to combustion of contemporary biomass for industrial and domestic heating, and it was linked to the intensity (average minimum temperature) and duration (number of freezing days) of cold weather. The annual summertime biomass burning contributions were correlated with the number and area burnt by lightning-ignited wildfires. These results indicate that PM2.5 sources in urban environments is changing from anthropogenic secondary sulfate and nitrate to carbonaceous aerosol from local anthropogenic and regional climate-driven biomass burning. This trend may counterbalance emissions controls on anthropogenic activities and modify the biological and toxicological responses and resultant health effects.

Effects of Climate Change on Northern Bobwhite Nesting Chronology and Clutch Size

Widespread changes to breeding bird phenology in response to climate change have been apparent in North America for several decades. While the impact of an earlier breeding season may be minimal by itself, changes in community-level interactions can be greatly influenced because of varying responses to climate change in different trophic levels. Climate change has been shown to alter the onset of breeding season and chick survival, and lead to population declines for game birds in high latitudes, at high elevations, and on the periphery of their range. The topic of climate change in relation to northern bobwhite (Colinus virginianus; hereafter, bobwhite) populations has attracted interest in the past 2 decades. Some researchers have hypothesized that climate change has the potential to cause the breeding season to initiate sooner and have a shorter duration. Using a 29-year dataset (1992–2020) with 1,171 individual bobwhites, we analyzed how temperatures prior to the breeding season affected the timing of nest initiation and clutch size, and how the length of the breeding season varied over time. We determined that the average minimum daily temperatures 30 days prior to the breeding season warmed by 0.07° C/year from 1992–2020. For any given year, we found that nest initiation could occur 1.12 days earlier for every 1° C increase in temperature. Overall, we determined that the timing of the nesting season had not changed from 1992–2020. The overall average breeding season length (135 days) or last average initiation date (27 Aug) did not change over the course of our study. We did not find that clutch sizes have changed over time and they were not correlated to pre-laying temperature. We attribute the lack of significant change in nesting chronology to plasticity of populations within the core of the range and the intensity of bobwhite management on the landscape.

Analysis of the thermal performance of the novel assembled Chinese solar greenhouse with a modular soil wall in winter of Yinchuan, China

In order to improve the thermal insulation and storage performance of Chinese solar greenhouses in winter, a novel assembled Chinese solar greenhouse (ACSG) without energy supplement in cold climatic areas was designed to evaluate and compare its thermal performance with that of conventional Chinese solar greenhouse (CSG). The thermal properties of both greenhouses were tested in field on cold winter days in Ningxia, China. The results indicated that the land utilization rate of ACSG was 19.3% higher than that of CSG. On a typical sunny day (the lowest outdoor temperature was −22.0°C) and typical cloudy day (the lowest outdoor temperature was −19.7°C) during the experiment, the minimum indoor temperature of ACSG was respectively 1.7°C and 2.0°C higher than that of CSG. The results for 24 consecutive days (the average outdoor daily minimum air temperature was −19.0°C) showed that the average minimum indoor temperature of ACSG was 1.4°C higher than that of CSG (p<0.05). The modular soil wall attached with colored steel polystyrene boards would be exploited as the north wall of CSG in Yinchuan area. Keywords: thermal performance, solar greenhouse, north wall, composite wall structure, soil block DOI: 10.25165/j.ijabe.20221505.6759 Citation: Cao Y F, Xu H J, Shi M, Zhang X Y, Zhang Y H, Zou Z R. Analysis of the thermal performance of the novel assembled Chinese solar greenhouse with a modular soil wall in winter of Yinchuan, China. Int J Agric & Biol Eng, 2022; 15(5): 70–77.

三江源国家公园植被净初级生产力变化趋势及影响因素

PDF HTML阅读 XML下载 导出引用 引用提醒 三江源国家公园植被净初级生产力变化趋势及影响因素 DOI: 10.5846/stxb202106131577 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 第二次青藏高原综合科学考察研究项目（2019QZKK0302）；中国科学院青海省人民政府三江源国家公园联合研究专项专项（LHZX-2020-07） Changes and influencing factors of vegetation net primary productivity in the Sanjiangyuan National Park Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:净初级生产力（NPP）是评估全球气候变化和人类活动下生态系统状况、过程和机制的重要指标之一。研究以中国首批国家公园之一的三江源国家公园为对象，利用GLOPEM-CEVSA耦合模型，以1981-2018年空间插值的气象数据和基于遥感反演的FPAR数据为输入，分别估算仅气候驱动的潜在NPP （NPPCL）和气候遥感共同驱动的现实NPP （NPPRS），以二者之差厘定人类活动影响的NPP （NPPHA），进而探究全球气候变化下人类活动的影响。结果表明：（1）三江源地区NPPRS多年均值为309.70 g C m-2 a-1，占NPPCL的61.65%。其中，黄河源、长江源和澜沧江源园区NPPRS分别为249.88 g C m-2 a-1、140.18 g C m-2 a-1和330.55 g C m-2 a-1。（2）全区NPPRS以2.00 g C m-2 a-1速率显著增加，高于NPPCL（1.74 g C m-2 a-1），其中黄河源、长江源和澜沧江源园区NPPRS增长速率分别占各自NPPCL增长速率的89.13%、90.23%和77.43%，澜沧江源园区整体受人类活动影响最大。（3）气候影响方面，年降水、年平均日最高气温和年平均日最低气温共同可解释全区NPPCL和NPPRS年际变化的51%和73%，可分别解释黄河源、长江源和澜沧江源园区的48%和58%、52%和69%、42%和50%，其中气温对NPP年际变化趋势影响更大。（4）人类活动在大部分区域呈负影响，存在西北向东南负面影响增强的空间分布特征，但2000年前后人类活动对生产力变化趋势呈负影响的面积从79.12%降低到56.34%，NPP变化量从-71.41 Tg C降低到-38.72 Tg C，作为主导因子的变化范围从18.73%增加至38.76%，三江源地区生态保护与恢复等措施促进了植被生产力增加，但需进一步实施生态保护与恢复措施，这是一项长期而艰巨的任务。 Abstract:The Net Primary Productivity (NPP) is an important indicator quantifying ecosystem status, process and undying mechanisms due to global climate change and human activities. The potential NPP (NPPCL) and actual NPP (NPPRS) were estimated through GLOPEM-CEVSA model driven by the only interpolated climate data, and both climate and remote sensing data, respectively, for the near 40 years from 1981 to 2018. The human activities dominated NPP (NPPHA) was defined as the difference between NPPRS and NPPCL. The method was applied in the Sanjiangyuan National Park, one of the first national parks in China, to explore the impacts of human activity under global climate change. The results showed that:(1) the average NPPRS was 309.70 g C m-2 a-1, accounting for 61.65% of the NPPCL for the whole region. For the three sub-parks, the NPPRS were 249.88 g C m-2 a-1, 140.18 g C m-2 a-1 and 330.55 g C m-2 a-1 in the Yellow River headwater, Yangtze River headwater and Lancang River headwater, respectively. (2) The NPPRS was increasing significantly by a speed of 2.00 g C m-2 a-1, which was faster than the NPPCL (1.74 g C m-2 a-1). The speed ratio of NPPRS to NPPCL were 89.13%, 90.23% and 77.43% for the three sub-parks by the above oder, respectively, which meant the Lancang Park was most impacted by human activities. (3) In the terms of climate impact, temperature had a stronger impact on the trend of NPP. Specifically, annual total precipitation, average annual maximum temperature and minimum temperature explained 51% and 73% of the interannual variation of NPPCL and NPPRS in the whole region, which can explain 48% and 58%, 52% and 69%, 42% and 50% of the interannual variability in the NPP timeseries in the Yellow River, Yangtze River and Lancang River sub-park, respectively. (4) Human activities had a negative influence over the most areas and became stronger to the southeast from the northwest. And the area showing a negative influence from human activities on the productivity changes decreased from 79.12% before 2000 to 56.34% after 2000. The total NPP over the whore negative area decreased from -71.41 Tg C to -38.72 Tg C, and the human activity as the dominant factor increased from 18.73% to 38.76% for the same two periods. It illustrated that the ecological protection and restoration of the Three-River Headwaters Region have contributed to an increasing vegetation productivity, but the protection and restoration measures should be further implemented. 参考文献 相似文献 引证文献

Impacts of weather abnormalities on to mental health problems related suicidal behaviours: an economic approach

This study aims to estimate the impacts of climate variation on suicide rates in the USA by using county-level data on temperature, and mental health-related suicides between 2011 and 2020. In addition to climate factors, several socio-economic factors such as uninsured population rate, access to mental health providers, and unemployment rate are included to estimate their impacts on suicides. The estimation is separately performed for female, male and overall groups. The results indicate that while there is limited evidence of the impact of precipitation on suicidal behaviours, the average daily minimum air temperature is an important determinant of the suicides in the US counties.

STUDY OF CLIMATE CHANGE AND ITS IMPACTS ON WATER RESOURCE: A CASE STUDY FROM SIKLES VILLAGE OF ACAP REGION

Climate-induced water related problems are major challenge for mountain communities and little is known on changes and impacts to local people. This paper focuses on climate change issues and its water related consequences to people of Sikles village. Climatic data were collected and analyzed for trend and variability analysis. Water availability was analyzed based on discharge measurement through a volumetric approach and demand was estimated from total population and per capita daily water requirement as prescribed by WHO. Local perception was assessed from household questionnaire survey (n=60). The result showed that average annual maximum and minimum temperature is increasing at the rate of 0.049℃ and 0.006℃ annually. Similarly, annual precipitation is also slightly increasing but in unpredictable pattern whereas number of rainy days is decreasing at 1.123 days per year. Both hot and cold climate extremes and intense rainfall are seen frequently in recent years. Landslide is major water related problem in the area and has more risk due to intense rainfall. Locals perceived that water availability in the sources is decreasing, also current demand and supply analysis in dry period showed there is scarcity of water if collection time concentered only on morning and evening. Water source protection and plantation is most adopted practices to protect water and minimize landslide hazards. Local water use regulation for efficient use of water, development of water storage and distribution system and promotion of green interventions could be important future strategy to face the predicted water related problems in the village.

Validation and Projections of Climate Characteristics in the Saginaw Bay Watershed, MI, for Hydrologic Modeling Applications

Fundamental differences in the nature of climate and hydrologic models make coupling of future climate projections to models of watershed hydrology challenging. This study uses the NCAR Weather Research and Forecast model (WRF) to dynamically downscale climate simulations over the Saginaw Bay Watershed, MI and prepare the results for input into semi-distributed hydrologic models. One realization of the bias-corrected NCAR CESM1 model's RCP 8.5 climate scenario is dynamically downscaled at a spatial resolution of 3 km by 3 km for the end of the twenty-first century and validated based on a downscaled run for the end of the twentieth century in comparison to ASOS and NWS COOP stations. Bias-correction is conducted using Quantile Mapping to correct daily maximum and minimum temperature, precipitation, and relative humidity for use in future hydrologic model experiments. In the Saginaw Bay Watershed the end of the twenty-first century is projected to see maximum and minimum average daily temperatures warming by 5.7 and 6.3°C respectively. Precipitation characteristics over the watershed show an increase in mean annual precipitation (average of +14.3 mm over the watershed), mainly due to increases in precipitation intensity (average of +0.3 mm per precipitation day) despite a decrease in frequency of −10.7 days per year. The projected changes have substantial implications for watershed processes including flood prediction, erosion, mobilization of non-point source and legacy contaminants, and evapotranspirative demand, among others. We present these results in the context of usefulness of the downscaled and bias corrected data for semi-distributed hydrologic modeling.

Variability of thermohaline regime of see water of the Gulf of Mexico in 2005-2017

The Gulf of Mexico is a large, productive, marine and coastal ecosystem providing the coastal residents and neighbouring regions with goods and services. The Gulf of Mexico's water area plays a significant role in shaping the climate across the coastal zone and the thermal state of the region's water also has a major impact on development of atmospheric processes over the Atlantic and Europe. Long-term climate variability throughout the Gulf of Mexico may affect both the strength of the Gulf Stream and heat transfer patterns within the ocean and the economic activity and environmental stability of the entire Northwest Atlantic Region. This work aims at determining the characteristics of variability of temperature regime and salinity of the Gulf of Mexico over recent decades.&#x0D; The study was conducted based on the Gulf of Mexico Regional Climatology (GOM RC) data, version 2, available at the website of the NOAA's National Centers for Environmental Information (NCEI). It analyzes the temperature and salinity values at different depths for the period of 2005-2017. According to the analysis, over 2005-2017 the spatial distribution of the average annual water temperature on the Gulf of Mexico's surface demonstrates its decrease from south to north. Its highest value is observed next to the northwestern coast of Cuba and along the coastal area of the Bay of Campeche, and the lowest temperature is observed at Apalachee Bay located in the northeastern part of the Gulf of Mexico. Though significant horizontal temperature gradients are observed in winter, during the warm period the temperature field is more homogeneous. The minimum average monthly water temperature on the surface is observed in January, the maximum one – in September. The most distinct seasonal changes in temperature are observed in the water of the northern part of the Gulf of Mexico next to the United States' coast. The distribution of average annual salinity of the most of the Gulf of Mexico is homogeneous with the exception of its northern part, especially in the area where the Mississippi River water flows into it, where salinity decreases sharply. Graphs of water temperature and salinity distribution at different depths across different areas of the gulf were constructed in order to determine the water stratification.

Development of Statistically Downscaled Regional Climate Model based on Representative Concentration Pathways for Ipoh, Subang and KLIA Sepang in Peninsular Malaysia

Climate change is one of the challenging global issues that our world is facing and it is intensely debated on the international agenda. It is a fact that climate change has brought about many disastrous events on a global scale which affect our livelihoods. Climate models are commonly used by researchers to study the magnitude of the changing climate and to simulate future climate projections. Most climate models are developed based on various interactions among the Earth’s climate components such as the land surface, oceans, atmosphere and sea-ice. In this study, the second-generation Canadian Earth System Model (CanESM2) was statistically downscaled to develop a regional climate model (RCM) based on three representative concentration pathways (RCPs): RCP2.6, RCP4.5 and RCP8.5. The RCM will be used to simulate the average minimum and maximum temperatures and average precipitation for Ipoh, Subang and KLIA Sepang in Peninsular Malaysia for the years 2006 to 2100. The simulated data were bias corrected using the historical observation data of monthly average minimum and maximum temperatures and monthly average rainfall retrieved from the Malaysian Meteorological Department (MMD). The different trends of the simulated data for all the three locations based on the RCP2.6, RCP4.5 and RCP8.5 were evaluated for future climate projection.

IMPACT OF TEMPERATURE AND RAINFALL ALTERATIONS ON SPAWNING BEHAVIOUR OF INDIAN MAJOR CARPS AND CONSEQUENCE ON FISHERS’ INCOME IN ODISHA

The present communication assessed the impact of the changes in climatic variables, viz. temperature and rainfall on the spawning of Indian Major Carps (IMC) in the river Mahanadi, in the fish hatcheries in its plains and on the fishers’ income in five districts of Odisha. The average minimum and maximum temperature throughout the state has increased in the range of 0.1 °C to 0.9 oC. The annual rainfall in Cuttack and Puri districts have increased by 27.78 mm and 13.20 mm respectively and decreased by 18.73 mm, 16.25 mm, 7.4 mm, 86.88 mm and 11.25 mm in Angul, Balasore, Khurda, Sambalpur and Bolangir districts, respectively during 1981-2010. The fish spawn availability has decreased drastically in river Mahanadi in three decades from 30-43 ml net-1day-1 to the present level of 6 ml net-1day-1. The study revealed that the onset of the breeding period of the Indian major carps has advanced by one month in the hatcheries, compared to the previous two decades. The advancement in breeding period of IMC in the fish seed hatcheries in Balasore, Khordha, Puri and Mayurbhanj districts can be attributed primarily to the effect of increased water temperature and shifting of the rainfall pattern facilitating early maturation and spawning. The respondents in the fish seed hatcheries surveyed also perceived temperature and rainfall as the most important factors responsible for advancement of the onset of breeding of IMC. Key words : Climate change, breeding season, Indian major carps, hatchery, Mahanadi river basin, Odisha, India

Multi-objective optimization design for a double-direction liquid heating system-based Cell-to-Chassis battery module

Sub-zero temperature causes performance degradation, lifespan shortage, and even some safety issues of Li-ion battery cells, such as the internal short circuit. Preheating has become a critical issue for electric vehicle (EV) promotion in the high-latitude area or cold temperatures. To address this issue, a double-direction liquid heating-based Cell-to-Chassis (CTC) battery module is proposed for an extreme low-temperature environment (-40°C). Two cooling plates and the battery module are embedded in the chassis to reduce the component number. Besides, the volume energy density gets increased by 26.3%. The numerical calculation indicates that the proposed system is more efficient than the commonly utilized battery thermal management system (BTMS) in EVs. Moreover, the preheating effect with different heating intervals is compared; eight-minutes-preheating is proved to be more effective in preheating the battery module to 0°C with less energy consumption. Furthermore, a multi-objective optimization design is further carried out considering the heating rate, thermal safety, thermal uniformity, and energy cost. The impact of the mass flow rate in the mini-channels and the PTC heating film power are analysed through sensitivity analysis. Finally, the optimal design scheme is selected. The minimum, maximum, and volume average temperatures of the battery module are 273.2K, 296.7K, and 286.9K, respectively. Moreover, the temperature standard deviation is further reduced to 8.8K without much energy cost increment. This study guides for combing the efficient BTMS with the EV chassis for all-climate applications, especially with integrated preheating/cooling functions, which is feasible for the fast charging and cold environment applications, both the thermal management efficiency and the volume energy density can be effectively enhanced.

Influence of prevailing weather parameters on population dynamics of spotted stem borer, Chilo partellus (Swinhoe) and its natural enemies on maize in Haryana

&#x0D; The experiment was conducted at CCS Haryana Agricultural University Regional Research Station, Karnal to ascertain the influence of prevailing meteorological parameters on population dynamics of Chilo partellus and its natural enemies on maize during Kharif, 2017. Maximum oviposition (0.75 egg masses per plant) was recorded during 28th standard meteorological week (SMW) whereas larval population was at peak during 31st SMW (3.8 larvae per plant). Cumulative (47.5%) and fresh plant infestation (11.5%) were maximum during 34th and 28th SMW, respectively. Maximum egg parasitisation (6.53%) by Trichogramma sp. and larval parasitisation (31.64%) by Cotesia flavipes was recorded during 28th and 33rd SMW, respectively. Changes in pest population were correlated and regressed with weather parameters. Egg and larval populations of C. partellus and parasitisation by Trichogramma sp. exhibited significant positive correlation with average minimum temperature whereas C. flavipes exhibited significant negative correlation with average maximum temperature (r = -0.741) and highly significant positive correlation with evening relative humidity (r = 0.695). Plant infestation and dead heart formation were significantly correlated with average minimum temperature and non-significantly correlated with all other weather parameters. The multiple linear regression analysis explained the variability due to various weather parameters. This information can be utilised while formulating integrated management tactics against this pest.&#x0D;

Modeling of climate change in cold arid regions of north western Himalayas using multiple linear regression (MLR)

&#x0D; The present study aimed at modeling the impacts of climate change on precipitation and temperature and its trend in the context of changing climate in cold arid regions of north western Himalayas using multiple linear regression (MLR) model. The study was carried out in three different time slices viz., near future (2017-2045), mid future (2046-2072) and far future (2073-2099). The study includes the calibration of the observed climate data (maximum temperature, minimum temperature and precipitation) for fourteen years (2002-2015) and the outputs of downscaled scenario A2 of the Global Climate Model (GCM) data of Hadley Centre Coupled Model, (HadCM3) was used for validation, for the future. Daily climate (maximum temperature, minimum temperature and precipitation) scenarios were generated from 1961 to 2099 under A2 defined by Intergovernmental Panel on Climate Change (IPCC). During calibration, the maximum temperature, minimum temperature and precipitation showed decreasing trend. During validation, the maximum temperature showed an increasing trend in near future (2017- 2045) and decreasing trend in mid (2046-2072) and far future (2073-2099). While as, the minimum temperature and precipitation showed an increasing trend and decreasing trend respectively, in three futuristic phases. After validation, on comparison with the measured data, the variation in maximum temperature was found -2.59 oC in near future, -3.17 oC in mid future and -3.41 oC in far future. Similarly, for minimum temperature and precipitation, the variations with observed data were found 0.91 oC and -32.2 mm, respectively in near future, 2.01 oC and -34.6 mm, respectively in mid future, 4.08 oC and -3.4 mm, respectively in far future. These changes may be found due to global warming which lead to decrease in average annual precipitation and increase in average minimum temperatures causing the melting of glaciers.&#x0D;