Performance of RegCM4.5 in Simulating the Regional Climate of Western Tianshan Mountains in Xinjiang, China

The western Tianshan Mountains region in China has a complex topography where basins, mountains and glaciers co-exist. It is of great significance to study the sensitivity of meteorological factors in this region to different parameterization schemes of climate models. In this paper, the regional climate model RegCM4.5 is used to simulate the meteorological factor (mean temperature, maximum temperature, minimum temperature, precipitation and wind speed) occurring in the western Tianshan Mountains region from 2012 to 2016, so as to investigate the effects of different cumulus convective schemes (Grell, Tiedtke and Emanuel), including land cumulus convective schemes (LCCs) and ocean convective schemes (OCCs) on annual and seasonal simulations of meteorological factor by using the schemes of RUN1 (Grell for LCC and Tiedtke for OCC), RUN2 (Tiedtke for LCC and Emanuel for OCC), RUN3 (Grell for LCC and Emanuel for OCC) and ENS (the ensemble of RUN1, RUN2 and RUN3). The results show that the simulations of annual and seasonal meteorological factors are not significantly sensitive to the combination of LCCs and OCCs. In the annual simulations, RUN2 scheme has the best simulation performance for the maximum, average and minimum temperatures. However, other schemes of precipitation simulation outperform RUN2 scheme, and there is no difference among the four schemes for wind speed simulation. In the seasonal simulations, RUN2 scheme still performs well in the simulation of the average, maximum and minimum temperatures for four seasons, except for the simulation of the average temperature in spring and summer. For the simulation of the maximum temperature in summer, RUN2 scheme performs the same as ENS. For the simulation of other seasons, different meteorological factors have different performances in four seasons. Overall, the results show that different combinations of cumulus convection schemes can improve the simulation performance of meteorological factors in the western Tianshan Mountains of Xinjiang.

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Estimation and Comparative Analysis of Daily Reference Evapotranspiration Based on Different Input Combinations and Different Models

10.21203/rs.3.rs-636505/v1 ◽

2021 ◽

Author(s):

Chaojie Niu ◽

Xiang Li ◽

Chengshuai Liu ◽

Shan-e-hyder Soomro ◽

Caihong Hu

Keyword(s):

Reference Evapotranspiration ◽

Meteorological Factors ◽

Meteorological Data ◽

Pearson Correlation ◽

Back Propagation ◽

Maximum Temperature ◽

Least Squares Regression ◽

Simulation Performance ◽

Bp Model ◽

Plsr Model

Abstract Daily reference evapotranspiration (ET0) is the most crucial link in estimating crop water demand. In this study, Levenberg-Marquardt (L-M), Genetic Algorithm-Back Propagation (GA-BP) and Partial Least Squares Regression (PLSR) models were introduced to calculate the ET0 values, Based on the Pearson Correlation analysis method, five meteorological factors were obtained, which were combined into six different input scenarios. Compared with the values that calculated by the the Penman Monteith (PM) formula. Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Nash-Sutcliffe Efficiency (NSE), and Scatter Index (SI) were used to evaluate the simulation performance of the models. The results showed that the simulation effect of the L-M model is better than that of the GA-BP model and PLSR model in all scenarios. PLSR model has the worst performance. The SI index of L-M6 was 46.69% lower than that of GA-BP6 and 65.78% lower than that of PLSR6. When the input factors are 3, the simulation effect of the input wind speed, the maximum temperature and the minimum temperature is the best. L-M model and GA-BP model can predict the ET0 in the region with a lack of meteorological data. This study provides an important reference for high-precision prediction of ET0 under different input combinations of meteorological factors.

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Exploring the Sensitivity of Subtropical Stand Aboveground Productivity to Local and Regional Climate Signals in South China

Forests ◽

10.3390/f10010071 ◽

2019 ◽

Vol 10 (1) ◽

pp. 71 ◽

Cited By ~ 1

Author(s):

Hua Zhou ◽

Yang Luo ◽

Guang Zhou ◽

Jian Yu ◽

Sher Shah ◽

...

Keyword(s):

Regional Climate ◽

Mixed Forest ◽

Single Species ◽

Forest Productivity ◽

Maximum Temperature ◽

Forest Types ◽

Monthly Average ◽

Aboveground Productivity ◽

Average Maximum ◽

Average Maximum Temperature

Subtropical forest productivity is significantly affected by both natural disturbances (local and regional climate changes) and anthropogenic activities (harvesting and planting). Monthly measures of forest aboveground productivity from natural forests (primary and secondary forests) and plantations (mixed and single-species forests) were developed to explore the sensitivity of subtropical mountain productivity to the fluctuating characteristics of climate change in South China, spanning the 35-year period from 1981 to 2015. Statistical analysis showed that climate regulation differed across different forest types. The monthly average maximum temperature, precipitation, and streamflow were positively correlated with primary and mixed-forest aboveground net primary productivity (ANPP) and its components: Wood productivity (WP) and canopy productivity (CP). However, the monthly average maximum temperature, precipitation, and streamflow were negatively correlated with secondary and single-species forest ANPP and its components. The number of dry days and minimum temperature were positively associated with secondary and single-species forest productivity, but inversely associated with primary and mixed forest productivity. The multivariate ENSO (EI Niño-Southern Oscillation) index (MEI), computed based on sea level pressure, surface temperature, surface air temperature, and cloudiness over the tropical Pacific Ocean, was significantly correlated with local monthly maximum and minimum temperatures (Tmax and Tmin), precipitation (PRE), streamflow (FLO), and the number of dry days (DD), as well as the monthly means of primary and mixed forest aboveground productivity. In particular, the mean maximum temperature increased by 2.5, 0.9, 6.5, and 0.9 °C, and the total forest aboveground productivity decreased by an average of 5.7%, 3.0%, 2.4%, and 7.8% in response to the increased extreme high temperatures and drought events during the 1986/1988, 1997/1998, 2006/2007, and 2009/2010 EI Niño periods, respectively. Subsequently, the total aboveground productivity values increased by an average of 1.1%, 3.0%, 0.3%, and 8.6% because of lagged effects after the wet La Niña periods. The main conclusions of this study demonstrated that the influence of local and regional climatic fluctuations on subtropical forest productivity significantly differed across different forests, and community position and plant diversity differences among different forest types may prevent the uniform response of subtropical mountain aboveground productivity to regional climate anomalies. Therefore, these findings may be useful for forecasting climate-induced variation in forest aboveground productivity as well as for selecting tree species for planting in reforestation practices.

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Spatiotemporal Variability of Potential Evaporation in Heihe River Basin Influenced by Irrigation

10.5194/egusphere-egu2020-12520 ◽

2020 ◽

Author(s):

Congying Han

Keyword(s):

Wind Speed ◽

Relative Humidity ◽

Spatial Pattern ◽

River Basin ◽

Meteorological Factors ◽

Heihe River Basin ◽

Spatiotemporal Variability ◽

Maximum Temperature ◽

Heihe River ◽

Potential Evaporation

Spatiotemporal Variability of Potential Evaporation in Heihe River Basin Influenced by Irrigation Congying Han1,2, Baozhong Zhang1,2, Songjun Han1,21 State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China.2 National Center of Efficient Irrigation Engineering and Technology Research-Beijing, Beijing 100048, China.Corresponding author: Baozhong Zhang ([email protected])Abstract: Potential evaporation is a key factor in crop water requirement estimation and agricultural water resource planning. The spatial pattern and temporal changes of potential evaporation calculated by Penman equation (EPen) (1970-2017) in Heihe River Basin (HRB), Northwest China were evaluated by using data from 10 meteorological stations, with a serious consideration of the influences of irrigation development. Results indicated that the spatial pattern of annual EPen in HRB was significantly different, among which the EPen of agricultural sites (average between 1154 mm and 1333 mm) was significantly higher than that of natural sites (average between 794 mm and 899 mm). Besides, the coefficient of spatial variation of the aerodynamic term (Eaero) was 0.4, while that of the radiation term (Erad) was 0.09. The agricultural irrigation water withdrawal increased annually before 2000, but decreased significantly after 2000 which was influenced by the agricultural development and the water policy. Coincidentally, the annual variation of Epen in agricultural sites decreased at -40 mm/decade in 1970-2000 but increased at 60 mm/decade in 2001-2017, while that in natural sites with little influence of irrigation, only decreased at -0.5mm/decade in 1970-2000 but increased at 11 mm/decade in 2001-2017. So it was obvious that irrigation influenced Epen significantly and the change of Epen was mainly caused by the aerodynamic term. The analysis of the main meteorological factors that affect Epen showed that wind speed had the greatest impact on Epen of agricultural sites, followed by relative humidity and average temperature, while the meteorological factors that had the greatest impact on Epen of natural sites were maximum temperature, followed by wind speed and relative humidity.

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Future climate uncertainty and spatial variability over Tamilnadu State, India

Global NEST Journal ◽

10.30955/gnj.001516 ◽

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> 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°x0.22° 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°C and 2.0 to 4.8°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. </div>

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Environmental and Genetic Regulation of Plant Height in Soybean

10.21203/rs.2.20549/v2 ◽

2020 ◽

Author(s):

Qing Yang ◽

Gaoming Lin ◽

Huiyong Lv ◽

Cunhu Wang ◽

Yongqing Yang ◽

...

Keyword(s):

Environmental Factors ◽

Soil Properties ◽

Plant Height ◽

Meteorological Factors ◽

Day Length ◽

Maximum Temperature ◽

Soybean Plant ◽

Environment Interaction ◽

Shoot Architecture ◽

Average Maximum

Abstract Background: Shoot architecture is fundamentally crucial to crop growth and productivity. As a key component of shoot architecture, plant height is known to be controlled by both genetic and environmental factors, though specific details remain scarce.Results: In this study, 308 representative soybean lines from a core collection and 168 F9 soybean progeny were planted at distinct field sites. The results demonstrated the presence of significant genotype × environment interaction (G × E) effects on traits associated with plant height in a natural soybean population. In total, 19 loci containing 51 QTLs (quantitative trait locus) for plant height were identified across four environments, with 23, 13 and 15 being QTLs for SH (shoot height), SNN (stem node number) and AIL (average internode length), respectively. Significant LOD ranging from 2.50 to 16.46 explained 2.80% - 26.10% of phenotypic variation. Intriguingly, only two loci, Loc11 and Loc19-1, containing 20 QTLs, were simultaneously detected across all environments. Results from Pearson correlation analysis and PCA (principal component analysis) revealed that each of the five agro-meteorological factors and four soil properties significantly affected soybean plant height traits, and that the corresponding QTLs had additive effects. Among significant environmental factors, AD (average day-length), AMaT (average maximum temperature), pH, and AN (available nitrogen) had the largest impacts on soybean plant height. Therefore, in spite of uncontrollable agro-meteorological factors, soybean shoot architecture might be remolded through combined efforts to produce superior soybean genetic materials while also optimizing soil properties.Conclusions: Overall, the comprehensive set of relationships outlined herein among environment factors, soybean genotypes and QTLs in effects on plant height opens new avenues to explore in work aiming to increase soybean yield through improvements in shoot architecture.

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Environmental and Genetic Regulation of Plant Height in Soybean

10.21203/rs.2.20549/v3 ◽

2021 ◽

Author(s):

Qing Yang ◽

Gaoming Lin ◽

Huiyong Lv ◽

Cunhu Wang ◽

Yongqing Yang ◽

...

Keyword(s):

Environmental Factors ◽

Soil Properties ◽

Plant Height ◽

Meteorological Factors ◽

Day Length ◽

Maximum Temperature ◽

Soybean Plant ◽

Environment Interaction ◽

Shoot Architecture ◽

Average Maximum

Abstract Background:Shoot architecture is fundamentally crucial to crop growth and productivity. As a key component of shoot architecture, plant height is known to be controlled by both genetic and environmental factors, though specific details remain scarce.Results:In this study, 308 representative soybean lines from a core collection and 168 F9 soybean progeny were planted at distinct field sites. The results demonstrated the presence of significant genotype × environment interaction (G × E) effects on traits associated with plant height in a natural soybean population. In total, 19 loci containing 51 QTLs (quantitative trait locus) for plant height were identified across four environments, with 23, 13 and 15 being QTLs for SH (shoot height), SNN (stem node number) and AIL (average internode length), respectively. Significant LOD ranging from 2.50 to 16.46 explained 2.80% - 26.10% of phenotypic variation. Intriguingly, only two loci, Loc11 and Loc19-1, containing 20 QTLs, were simultaneously detected across all environments. Results from Pearson correlation analysis and PCA (principal component analysis) revealed that each of the five agro-meteorological factors and four soil properties significantly affected soybean plant height traits, and that the corresponding QTLs had additive effects. Among significant environmental factors, AD (average day-length), AMaT (average maximum temperature), pH, and AN (available nitrogen) had the largest impacts on soybean plant height. Therefore, in spite of uncontrollable agro-meteorological factors, soybean shoot architecture might be remolded through combined efforts to produce superior soybean genetic materials while also optimizing soil properties.Conclusions:Overall, the comprehensive set of relationships outlined herein among environment factors, soybean genotypes and QTLs in effects on plant height opens new avenues to explore in work aiming to increase soybean yield through improvements in shoot architecture.

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Environmental and Genetic Regulation of Plant Height in Soybean

10.21203/rs.2.20549/v4 ◽

2021 ◽

Author(s):

Qing Yang ◽

Gaoming Lin ◽

Huiyong Lv ◽

Cunhu Wang ◽

Yongqing Yang ◽

...

Keyword(s):

Environmental Factors ◽

Soil Properties ◽

Plant Height ◽

Meteorological Factors ◽

Day Length ◽

Maximum Temperature ◽

Soybean Plant ◽

Environment Interaction ◽

Shoot Architecture ◽

Average Maximum

Abstract Background:Shoot architecture is fundamentally crucial to crop growth and productivity. As a key component of shoot architecture, plant height is known to be controlled by both genetic and environmental factors, though specific details remain scarce.Results:In this study, 308 representative soybean lines from a core collection and 168 F9 soybean progeny were planted at distinct field sites. The results demonstrated the presence of significant genotype × environment interaction (G × E) effects on traits associated with plant height in a natural soybean population. In total, 19 loci containing 51 QTLs (quantitative trait locus) for plant height were identified across four environments, with 23, 13 and 15 being QTLs for SH (shoot height), SNN (stem node number) and AIL (average internode length), respectively. Significant LOD ranging from 2.50 to 16.46 explained 2.80% - 26.10% of phenotypic variation. Intriguingly, only two loci, Loc11 and Loc19-1, containing 20 QTLs, were simultaneously detected across all environments. Results from Pearson correlation analysis and PCA (principal component analysis) revealed that each of the five agro-meteorological factors and four soil properties significantly affected soybean plant height traits, and that the corresponding QTLs had additive effects. Among significant environmental factors, AD (average day-length), AMaT (average maximum temperature), pH, and AN (available nitrogen) had the largest impacts on soybean plant height. Therefore, in spite of uncontrollable agro-meteorological factors, soybean shoot architecture might be remolded through combined efforts to produce superior soybean genetic materials while also optimizing soil properties.Conclusions:Overall, the comprehensive set of relationships outlined herein among environment factors, soybean genotypes and QTLs in effects on plant height opens new avenues to explore in work aiming to increase soybean yield through improvements in shoot architecture.

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Characteristics of thunderstorms and squalls over Indira Gandhi International (IGI) airport, New Delhi - Impact on environment especially on summer’s day temperatures and use in forecasting

MAUSAM ◽

10.54302/mausam.v60i4.1115 ◽

2021 ◽

Vol 60 (4) ◽

pp. 461-474

Author(s):

R. K. JENAMANI ◽

R. C. VASHISTH ◽

S. C. BHAN

Keyword(s):

Wind Speed ◽

Environmental Changes ◽

Maximum Wind Speed ◽

Maximum Temperature ◽

Daily Maximum Temperature ◽

Daily Maximum ◽

Peak Time ◽

New Delhi ◽

Maximum Wind ◽

Average Maximum

In the present study, commencement timings and duration of thunderstorms (TS) and squalls at IGI airport, Palam, New Delhi have been analysed critically based on most recent eleven years data of 1995-2005 to find their favourable time of occurrences. Then utility of such data base in the aviation warning has been demonstrated. Environmental changes associated with these squalls have also been further analysed to understand their impact. Being recent May 2007 a very cool month over Delhi, the role of TS on controlling the day’s soaring temperature has also been studied from their data. Results show TS are maximum in June followed by July whereas squalls are maximum in May followed by June. It shows more than 80% of TS in each season are of duration less than 3 hours with remaining are mostly 3 to 6 hours. The peak time period of commencement of both TS and squalls in the day differ with the progress of the months. For pre monsoon months, the most favourable timing of TS and squalls are 1200-1500 UTC while for monsoon, it starts earlier. Around 37% of the total TS during the period were associated with squalls. The average maximum wind speed in squall at IGI airport is about 68 kmph with highest maximum wind speed 139 kmph. On an average the environmental temperature falls by 5.6° C, humidity levels rises by 17.8% and mean sea level pressure rises by 1.6 hPa due to the occurrences of squalls. Study also shows daily maximum temperature rise is highly controlled by TS occurrences and May 2007, being a month of highest TS occurrences at the airport since 1995, became one of the coolest month in May over Delhi. The comparison of TS frequencies shows 12% increase in their annual activities since 1950-1980 with very high unusual increase of 51% in June and 26% in May. Since analysis of data from 1995 shows occurrences of TS are reversely but strongly correlated with summer temperatures and longer period temperature data since 1975 also confirms absence of significant trend in maximum temperature and higher temperature days in peak summer months of May and June till recent as expected due to high pollution, global warming and fast urbanization in the city, so it is the higher number of TS occurrences over the region from time to time which might have been main factor for controlling its significant rise.

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DINAMIKA KUALITAS UDARA AMBIEN SELAMA MASA PANDEMI COVID-19 DI KAWASAN INDONESIA TOURISM DEVELOPMENT CORPORATION NUSA DUA BALI

ECOTROPHIC Jurnal Ilmu Lingkungan (Journal of Environmental Science) ◽

10.24843/ejes.2021.v15.i01.p11 ◽

2021 ◽

Vol 15 (1) ◽

pp. 124

Author(s):

Ika Sulistiani ◽

I GD Yudha Partama ◽

Sang Putu Kaler Surata ◽

I Ketut Sumantra

Keyword(s):

Air Quality ◽

Wind Speed ◽

Meteorological Factors ◽

Ambient Air ◽

Meteorological Factor ◽

Ambient Air Quality ◽

Air Concentration ◽

Direct Reading ◽

New Normal ◽

Normal Period

The Covid-19 pandemic has increased the improvement of air quality in various countries in the world, such as China, Italy, New York, India, Spain and Korea. This study aims to compare ambient air quality during the Covid-19 pandemic with new normal and normal periods, assess the effect of meteorological factors on ambient air quality, and map the spatial distribution of ambient air quality during the normal, Covid-19 pandemic and new normal in the ITDC Nusa Dua area. Air concentration parameter data and meteorological factors were collected using the midget impinger and direct reading method in 2019 (normal period), March and May 2020 (Covid-19 pandemic period) and July, September, and November 2020 (new normal period). Furthermore, comparing air quality using the Anova test, assessing the effect of meteorological factors on air quality using a linear regression test, and mapping the distribution of ambient air using the ArcGis 10.8 application. The analysis showed that the air quality during the Covid-19 pandemic and the new normal was significantly different from the normal period. The concentrations of SO2, NO2, NH3, CO, TSP and H2S during the Covid-19 pandemic and normal just decreased while the O3 concentration increased compared to the normal period. The meteorological factor that affects air quality is the wind speed, the higher the wind speed the lower the O3 concentration. Map of the distribution of spatial concentrations of SO2, NO2, NH3, CO, O3 and H2S in the normal, Covid-19 pandemic and new normal, lowest at the coast point of the peninsula and the highest distribution at the ITDC roundabout, bima statue or influence TSP is the highest spatial concentration of normal distribution at the ITDC roundabout and the bima statue, while the Covid-19 pandemic and normal are only at the coast point of the peninsula beach.Keywords: ambient air quality; Covid-19; pandemic; tourism.

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Application of the Principal Component Analysis (PCA) Method to Assess the Impact of Meteorological Elements on Concentrations of Particulate Matter (PM10): A Case Study of the Mountain Valley (the Sącz Basin, Poland)

Sustainability ◽

10.3390/su11236740 ◽

2019 ◽

Vol 11 (23) ◽

pp. 6740 ◽

Cited By ~ 5

Author(s):

Zuśka ◽

Kopcińska ◽

EwaDacewicz ◽

Skowera ◽

Wojkowski ◽

...

Keyword(s):

Wind Speed ◽

Principal Component ◽

Pm10 Concentration ◽

Maximum Temperature ◽

Mountain Valley ◽

Average Maximum ◽

Pca Method ◽

Autumn And Winter ◽

Meteorological Elements ◽

The Impact

The aim of this study was to determine, by use PCA analysis, the impact of meteorological elements on the PM10 concentration on the example of the mountain valley. Daily values of selected meteorological elements, measured during a ten-year period in the spring, summer, autumn and winter, obtained from the meteorological station in Nowy Sącz, were adopted as variables explaining PM10 concentration. The level of PM10 was significantly affected by the maximum, minimum and average temperature in autumn, winter and spring. In summer the average and maximum temperature was significant. In winter, the first principle component mainly consisted of the combination of the average and maximum wind speed. The second principal component in spring, summer and autumn was the combination of the wind speed (average and maximum), but in winter humidity and atmospheric pressure seemed to be significant. The third principal component, in terms of strength of impact, was humidity in spring, the combination of humidity and minimum temperature in summer, and precipitation in autumn. In winter, the highest PM10 concentrations were observed during the non-directional, anticyclonic wedge conditions. Three principal components were distinguished in this situation: temperature (average, maximum and minimum); the combination of humidity and wind speed and precipitation.

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