Trend Analysis and ARIMA Modeling to Assess Meteorological and Surface Parameters In Ranchi, India During Pre-Monsoon Months

GIS Business ◽  
2020 ◽  
Vol 15 (2) ◽  
pp. 69-87
Author(s):  
Poulomi Chakravarty ◽  
Manoj Kumar
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
Land Surface ◽  
Regional Climate ◽  
Arima Model ◽  
Sensible Heat Flux ◽  
Shortwave Radiation ◽  
Maximum Temperature ◽  
Positive Temperature ◽  
Surface Parameters

The assessment of the human-induced climate change on a global level can be carried out only after the study of local and regional climate change patterns. This study was an attempt to establish a link between regional climate and the surface parameters. The study was carried out for Ranchi, India to assess the changes in climatic pattern over the years (1901-2016) and applied Mann-Kendall Trend analysis test. The pre-monsoon period was chosen due to high intensity and number of thunderstorms taking place in the study area. Maximum temperature (Tmax), minimum temperature (Tmin), rainfall (P) &diurnal temperature range (DTR) for the months (March, April & May) were studied, and a significant negative trend in Tmax and DTR was observed. Autoregressive Integrated Moving Average (ARIMA) model was applied to fit the datasets and predict 5 values for the meteorological parameters, and the model depicted positive temperature trends and negative rainfall and DTR trends in the future. Land surface process parameters such as sensible heat flux, momentum flux, frictional velocity, shortwave radiation, longwave radiation, and net radiation for Ranchi were also fit into the ARIMA model, and the fitness of the model and predictions were determined.

scholarly journals Effects of Forest Changes on Summer Surface Temperature in Changbai Mountain, China

Forests ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1551
Author(s):  
Jiaqi Zhang ◽  
Xiangjin Shen ◽  
Yanji Wang ◽  
Ming Jiang ◽  
Xianguo Lu
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Land Surface ◽  
Climate Models ◽  
Regional Climate ◽  
Changbai Mountain ◽  
Vegetation Coverage ◽  
Area Index ◽  
Forest Coverage ◽  
Cooling Effects

The area and vegetation coverage of forests in Changbai Mountain of China have changed significantly during the past decades. Understanding the effects of forests and forest coverage change on regional climate is important for predicting climate change in Changbai Mountain. Based on the satellite-derived land surface temperature (LST), albedo, evapotranspiration, leaf area index, and land-use data, this study analyzed the influences of forests and forest coverage changes on summer LST in Changbai Mountain. Results showed that the area and vegetation coverage of forests increased in Changbai Mountain from 2003 to 2017. Compared with open land, forests could decrease the summer daytime LST (LSTD) and nighttime LST (LSTN) by 1.10 °C and 0.07 °C, respectively. The increase in forest coverage could decrease the summer LSTD and LSTN by 0.66 °C and 0.04 °C, respectively. The forests and increasing forest coverage had cooling effects on summer temperature, mainly by decreasing daytime temperature in Changbai Mountain. The daytime cooling effect is mainly related to the increased latent heat flux caused by increasing evapotranspiration. Our results suggest that the effects of forest coverage change on climate should be considered in climate models for accurately simulating regional climate change in Changbai Mountain of China.

scholarly journals Effects of climate changes on phenological periods of apple, cherry and wheat in TurkeyTürkiye’de iklim değişikliğinin elma, kiraz ve buğdayın fenolojik dönemlerine etkileri

2016 ◽  
Vol 13 (1) ◽  
pp. 1036 ◽  
Author(s):  
Necla Türkoğlu ◽  
Serhat Şensoy ◽  
Olgu Aydın
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
Air Temperature ◽  
Climate Changes ◽  
Correlation Coefficients ◽  
Wheat Plant ◽  
Positive Temperature ◽  
Phenological Data ◽  
The World ◽  
Negative Relationships

It is known that the increase in air temperature from 1980 to present has dramatically changed the phenological periods of the plants in a large part of the world. In this study, the relationships between phenological periods of wheat plant, apple and cherry trees planted large areas in Turkey and climate change were investigated. In this study, the climate and phenological data for 1971-2012 period belonging to the General Directorate of Meteorology were used. The correlation coefficients between temperature and phenological data were calculated, and their trends were examined using Mann-Kendall trend analysis. In Turkey, positive temperature anomalies have been observed since 1994 until present days. Negative relationships were found between phenological periods of apple, cherry and wheat and the average temperatures of February-May period when the plants grow faster. This situation shows that the plants shift their phenological periods to the earlier times in response to the increasing temperatures. The trend calculated for harvest times of apple, cherry, and wheat are -25, -22, -40 days/100 years respectively. It was calculated that an increase of 1.0ºC in the temperatures of the February-May period will shift the harvest times of apple, cheery and wheat by 5, 4 and 8 days earlier respectively. Özet1980’lerden günümüze hava sıcaklıklarındaki artış, Dünya’nın büyük bir bölümünde bitkilerin fenolojik dönemlerini önemli ölçüde değiştirmiştir. Bu çalışmada Türkiye’de geniş alanlar kaplayan buğday, elma ve kiraz bitkilerinin fenolojik dönemleri ile iklim değişikliği arasındaki ilişkiler araştırılmıştır. Çalışmada Meteoroloji Genel Müdürlüğü’ne ait 1971-2012 döneminin iklim ve fenolojik verileri kullanılmıştır. Sıcaklık ile fenolojik veriler arasındaki korelasyon katsayıları hesaplanmış ve Mann- Kendall trend analizi ile eğilimlerine bakılmıştır. Türkiye’de 1994 yılından bu yana pozitif sıcaklık anomalileri bulunmuştur. Elma, kiraz ve buğdayın fenolojik dönemleri ile bitki gelişiminin fazla olduğu şubat-mayıs ortalama sıcaklıkları arasında negatif ilişki saptanmıştır. Bu durum bitkilerin artan sıcaklıklara tepki olarak fenolojik dönemlerini erkene kaydırdıklarını göstermektedir. Elma, kiraz ve buğdayın hasat tarihleri için hesaplanan trend sırasıyla-25, -22, -40 gün/100 yıl şeklindedir. Şubat-mayıs arası sıcaklıklarda 1.0°C’lik artışın anılan bitkilerin hasat tarihlerini sırasıyla 5, 4 ve 8 gün erkene kaydıracağı hesaplanmıştır.

scholarly journals Quantifying the Impacts of Climate Change and Vegetation Variation on Actual Evapotranspiration Based on the Budyko Hypothesis in North and South Panjiang Basin, China

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 508 ◽  
Author(s):  
Tiansheng Li ◽  
Jun Xia ◽  
Dunxian She ◽  
Lei Cheng ◽  
Lei Zou ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Surface ◽  
Climatic Factors ◽  
Actual Evapotranspiration ◽  
Maximum Temperature ◽  
Linear Regression Method ◽  
North And South ◽  
Average Contribution ◽  
Vegetation Variation ◽  
Impacts Of Climate Change

Actual evapotranspiration (Ea) plays a key role in the global water and energy cycles. The accurate quantification of the impacts of different factors on Ea change can help us better understand the driving mechanisms of Ea in a changing environment. Climate change and vegetation variations are well known as two main factors that have significant impacts on Ea change. Our study used three differential Budyko-type equations to quantify the contributions of climate change and vegetation variations to Ea change. First, in order to establish the relationship between the parameter n, which usually presents the land surface characteristics in the Budyko-type equations, with basic climatic variables and the Normalized Difference Vegetation Index (NDVI), the stepwise linear regression method has been used. Then, elasticity and contribution analyses were performed to quantify the contributions of different numbers of climatic factors and NDVI to Ea change. The North and South Panjiang basin in China was selected to investigate the efficiency of the modified Budyko-type equations and quantify the impacts of climate change and vegetation variations on Ea change. The empirical formal of the parameter n established in this study can be used to simulate the parameter n and Ea for the study area. The results of the elasticity and contribution analyses suggest that climate change contributed (whose average contribution is 149.6%) more to Ea change than vegetation variation (whose average contribution is −49.4%). Precipitation, NDVI and the maximum temperature are the major drivers of Ea change, while the minimum temperature and wind speed contribute the least to Ea change.

scholarly journals Climate Extremes over the Arabian Peninsula Using RegCM4 for Present Conditions Forced by Several CMIP5 Models

Atmosphere ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 675 ◽  
Author(s):  
Almazroui
Keyword(s):  
Land Surface ◽  
Arabian Peninsula ◽  
Climate Model ◽  
Regional Climate ◽  
Coupled Model ◽  
Climate Extremes ◽  
Maximum Temperature ◽  
Cmip5 Models ◽  
Study Region ◽  
Temperature And Precipitation

This paper investigates the temperature and precipitation extremes over the Arabian Peninsula using data from the regional climate model RegCM4 forced by three Coupled Model Intercomparison Project Phase 5 (CMIP5) models and ERA–Interim reanalysis data. Indices of extremes are calculated using daily temperature and precipitation data at 27 meteorological stations located across Saudi Arabia in line with the suggested procedure from the Expert Team on Climate Change Detection and Indices (ETCCDI) for the present climate (1986–2005) using 1981–2000 as the reference period. The results show that RegCM4 accurately captures the main features of temperature extremes found in surface observations. The results also show that RegCM4 with the CLM land–surface scheme performs better in the simulation of precipitation and minimum temperature, while the BATS scheme is better than CLM in simulating maximum temperature. Among the three CMIP5 models, the two best performing models are found to accurately reproduce the observations in calculating the extreme indices, while the other is not so successful. The reason for the good performance by these two models is that they successfully capture the circulation patterns and the humidity fields, which in turn influence the temperature and precipitation patterns that determine the extremes over the study region.

scholarly journals An Analysis of Land Surface Temperature Trends in the Central Himalayan Region Based on MODIS Products

2019 ◽  
Vol 11 (8) ◽  
pp. 900 ◽  
Author(s):  
Wei Zhao ◽  
Juelin He ◽  
Yanhong Wu ◽  
Donghong Xiong ◽  
Fengping Wen ◽  
...  
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Thermal Environment ◽  
Himalayan Region ◽  
Maximum Temperature ◽  
Temperature Cycle ◽  
Increasing Trend ◽  
Nighttime Temperatures

The scientific community has widely reported the impacts of climate change on the Central Himalaya. To qualify and quantify these effects, long-term land surface temperature observations in both the daytime and nighttime, acquired by the Moderate Resolution Imaging Spectroradiometer from 2000 to 2017, were used in this study to investigate the spatiotemporal variations and their changing mechanism. Two periodic parameters, the mean annual surface temperature (MAST) and the annual maximum temperature (MAXT), were derived based on an annual temperature cycle model to reduce the influences from the cloud cover and were used to analyze their trend during the period. The general thermal environment represented by the average MAST indicated a significant spatial distribution pattern along with the elevation gradient. Behind the clear differences in the daytime and nighttime temperatures at different physiographical regions, the trend test conducted with the Mann-Kendall (MK) method showed that most of the areas with significant changes showed an increasing trend, and the nighttime temperatures exhibited a more significant increasing trend than the daytime temperatures, for both the MAST and MAXT, according to the changing areas. The nighttime changing areas were more widely distributed (more than 28%) than the daytime changing areas (around 10%). The average change rates of the MAST and MAXT in the daytime are 0.102 °C/yr and 0.190 °C/yr, and they are generally faster than those in the nighttime (0.048 °C/yr and 0.091 °C/yr, respectively). The driving force analysis suggested that urban expansion, shifts in the courses of lowland rivers, and the retreat of both the snow and glacier cover presented strong effects on the local thermal environment, in addition to the climatic warming effect. Moreover, the strong topographic gradient greatly influenced the change rate and evidenced a significant elevation-dependent warming effect, especially for the nighttime LST. Generally, this study suggested that the nighttime temperature was more sensitive to climate change than the daytime temperature, and this general warming trend clearly observed in the central Himalayan region could have important influences on local geophysical, hydrological, and ecological processes.

scholarly journals Impacts of projected maximum temperature extremes for C21 by an ensemble of regional climate models on cereal cropping systems in the Iberian Peninsula

2011 ◽  
Vol 11 (12) ◽  
pp. 3275-3291 ◽  
Author(s):  
M. Ruiz-Ramos ◽  
E. Sánchez ◽  
C. Gallardo ◽  
M. I. Mínguez
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
High Temperatures ◽  
Climate Models ◽  
Cropping Systems ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Grain Filling ◽  
Maximum Temperature ◽  
Climate Change Scenarios

Abstract. Crops growing in the Iberian Peninsula may be subjected to damagingly high temperatures during the sensitive development periods of flowering and grain filling. Such episodes are considered important hazards and farmers may take insurance to offset their impact. Increases in value and frequency of maximum temperature have been observed in the Iberian Peninsula during the 20th century, and studies on climate change indicate the possibility of further increase by the end of the 21st century. Here, impacts of current and future high temperatures on cereal cropping systems of the Iberian Peninsula are evaluated, focusing on vulnerable development periods of winter and summer crops. Climate change scenarios obtained from an ensemble of ten Regional Climate Models (multimodel ensemble) combined with crop simulation models were used for this purpose and related uncertainty was estimated. Results reveal that higher extremes of maximum temperature represent a threat to summer-grown but not to winter-grown crops in the Iberian Peninsula. The study highlights the different vulnerability of crops in the two growing seasons and the need to account for changes in extreme temperatures in developing adaptations in cereal cropping systems. Finally, this work contributes to clarifying the causes of high-uncertainty impact projections from previous studies.

scholarly journals Effects of Land Surface Schemes on WRF-Simulated Geopotential Heights over China in Summer 2003*

2016 ◽  
Vol 17 (3) ◽  
pp. 829-851 ◽  
Author(s):  
Xin-Min Zeng ◽  
B. Wang ◽  
Y. Zhang ◽  
Y. Zheng ◽  
N. Wang ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Regional Climate ◽  
Sensible Heat Flux ◽  
Wrf Model ◽  
Surface Fluxes ◽  
Forecast Errors ◽  
Large Area ◽  
Pressure Fields ◽  
Temperature And Pressure

Abstract To quantify and explain effects of different land surface schemes (LSSs) on simulated geopotential height (GPH) fields, we performed simulations over China for the summer of 2003 using 12-member ensembles with the Weather Research and Forecasting (WRF) Model, version 3. The results show that while the model can generally simulate the seasonal and monthly mean GPH patterns, the effects of the LSS choice on simulated GPH fields are substantial, with the LSS-induced differences exceeding 10 gpm over a large area (especially the northwest) of China, which is very large compared with climate anomalies and forecast errors. In terms of the assessment measures for the four LSS ensembles [namely, the five-layer thermal diffusion scheme (SLAB), the Noah LSS (NOAH), the Rapid Update Cycle LSS (RUC), and the Pleim–Xiu LSS (PLEX)] in the WRF, the PLEX ensemble is the best, followed by the NOAH, RUC, and SLAB ensembles. The sensitivity of the simulated 850-hPa GPH is more significant than that of the 500-hPa GPH, with the 500-hPa GPH difference fields generally characterized by two large areas with opposite signs due to the smoothly varying nature of GPHs. LSS-induced GPH sensitivity is found to be higher than the GPH sensitivity induced by atmospheric boundary layer schemes. Moreover, theoretical analyses show that the LSS-induced GPH sensitivity is mainly caused by changes in surface fluxes (in particular, sensible heat flux), which further modify atmospheric temperature and pressure fields. The temperature and pressure fields generally have opposite contributions to changes in the GPH. This study emphasizes the importance of choosing and improving LSSs for simulating seasonal and monthly GPHs using regional climate models.

Evaluation of the WRF Physics Ensemble using Multivariable Integrated Evaluation Approach over Haihe river basin in north China

2020 ◽  
Author(s):  
Danqiong Dai
Keyword(s):  
Vector Field ◽  
Observational Data ◽  
River Basin ◽  
Land Surface ◽  
Regional Climate ◽  
Field Evaluation ◽  
Shortwave Radiation ◽  
Haihe River Basin ◽  
Spatial Average ◽  
Haihe River

<p>  A crucial step of the application of WRF in regional climate research is selection of the proper combinations of physical parameterizations. In this study, we performed experiments in WRF to assess the predict skill of various parametrization schemes sets in simulating precipitation, temperature over the Haihe river basin. The experiments driven by ERA-INTERIM reanalysis data are performed for a period of summer (1 June to 31 August, 2016) in this domain with 13 km grid spacing. Fifty-eight members of physics combinations thoroughly covering five types of physics options are assessed against the available observational data by utilizing the multivariable integrated evaluation (MVIE) method. It is deduced that the best performing setup consists of CAM5.1 microphysics, MRF PBL, BMJ Cumulus, CAM Longwave/Shortwave radiation, and Noah Land Surface schemes. To identify the robustness of the optimal scheme set, the vector field evaluation (VFE) diagram for displaying all simulations reveals that the optimal one is distinguished from others by higher vector field similarity coefficient(Rν), smaller root mean square vector deviation(RMSVD). The model deviations spatially for the precipitation show a promising tendency that a strong overestimation about 5 mm/day for the default configuration evolves small biases of the optimal setup with a range between -1 and 1 mm/day, and the surface temperature forecasts have improved to some extent although not significant as that of precipitation. The temporally analysis of the spatial average of all simulations exhibits that for temperature the optimal setup is more approaching to the observational data, but for precipitation no remarkable difference between all simulation and the observations. Further analysis of the sensitivities of model output to different types of physics option suggests that, microphysics, PBL, and Cumulus schemes have more significant impact on the model performances measured by a multivariable integrated evaluation index (MIEI) than radiation scheme and Land Surface schemes.</p>

scholarly journals A Statistical Adjustment of Regional Climate Model Outputs to Local Scales: Application to Platja de Palma, Spain

2012 ◽  
Vol 25 (3) ◽  
pp. 939-957 ◽  
Author(s):  
A. Amengual ◽  
V. Homar ◽  
R. Romero ◽  
S. Alonso ◽  
C. Ramis
Keyword(s):  
Climate Change ◽  
Regional Climate ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Climate Change Signal ◽  
Daily Maximum ◽  
Climate Projections ◽  
Recent Past

Abstract Projections of climate change effects for the System of Platja de Palma (SPdP) are derived using a novel statistical technique. Socioeconomic activities developed in this settlement are very closely linked to its climate. Any planning for socioeconomic opportunities in the mid- and long term must take into account the possible effects of climate change. To this aim, daily observed series of minimum and maximum temperatures, precipitation, relative humidity, cloud cover, and wind speed have been analyzed. For the climate projections, daily data generated by an ensemble of regional climate models (RCMs) have been used. To properly use RCM data at local scale, a quantile–quantile adjustment has been applied to the simulated regional projections. The method is based on detecting changes in the cumulative distribution functions between the recent past and successive time slices of the simulated climate and applying these, after calibration, to the recent past (observed) series. Results show an overall improvement in reproducing the present climate baseline when using calibrated series instead of raw RCM outputs, although the correction does not result in such clear improvement when dealing with very extreme rainfalls. Next, the corrected series are analyzed to quantify the climate change signal. An increase of the annual means for temperatures together with a decrease for the remaining variables is projected throughout the twenty-first century. Increases in weak and intense daily rainfalls and in high extremes for daily maximum temperature can also be expected. With this information at hand, the experts planning the future of SPdP can respond more effectively to the problem of local adaptation to climate change.

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