Modeling the Historical Temperature in the Province of Laguna Using Ornstein-Uhlenbeck Process

The behavior of temperature is one of the major factors in the study of climate change which has already invited a lot of researchers and policymakers. These studies help in deciding the best adaptation and mitigation strategy. However, there are little studies on the progression of climate change in a local setting, such as in a municipal or provincial level. This study explored to model, using regression, the daily temperature in the province of Laguna. The daily maximum and minimum temperature from 1960 to 2018 were modeled using the classical Ornstein-Uhlenbeck (OU) process with additive seasonality. The model showed that the province saw an increase of $1.16^\circ$C (resp. $0.55^\circ$C) in the mean daily minimum (resp. maximum) temperature from 1960 to 2018. It was also found that minimum temperature showed a steadier increase than maximum temperature, which poses threats to agricultural activities. Consistent with other international predictions, there was a $0.02^\circ$C annual increase in 1960 to a $0.05^\circ$C starting in 2010. The proposed model can be used by authorities in designing and creating adaptive measures that would be more effective to the province of Laguna.

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Comparing precipitation and temperature trends between inland and coastal locations

ANZIAM Journal ◽

10.21914/anziamj.v60i0.13967 ◽

2019 ◽

Vol 60 ◽

pp. C109-C126 ◽

Cited By ~ 1

Author(s):

Joshua Hartigan ◽

Shev MacNamara ◽

Lance M Leslie

Keyword(s):

Climate Change ◽

Minimum Temperature ◽

Southern Oscillation ◽

Power Spectra ◽

Maximum Temperature ◽

P Value ◽

Wet Season ◽

Intergovernmental Panel ◽

The Past ◽

The Mean

Motivated by the Millennium Drought and the current drought over much of southern and eastern Australia, this detailed statistical study compares trends in annual wet season precipitation and temperature between a coastal site (Newcastle) and an inland site (Scone). Bootstrap permutation tests reveal Scone precipitation has decreased significantly over the past 40 years (p-value=0.070) whereas Newcastle has recorded little to no change (p-value=0.800). Mean maximum and minimum temperatures for Newcastle have increased over the past 40 years (p-values of 0.002 and 0.015, respectively) while the mean maximum temperature for Scone has increased (p-value = 0.058) and the mean minimum temperature has remained stable. This suggests mean temperatures during the wet season for both locations are increasing. Considering these trends along with those for precipitation, water resources in the Hunter region will be increasingly strained as a result of increased evaporation with either similar or less precipitation falling in the region. Wavelet analysis reveals that both sites have similar power spectra for precipitation and mean maximum temperature with a statistically significant signal in the two to seven year period, typically indicative of the El-Nino Southern Oscillation climate driver. The El-Nino Southern Oscillation also drives the Newcastle mean minimum temperature, whereas the Scone power spectra has no indication of a definitive driver for mean minimum temperature. References R. A., R. L. Kitching, F. Chiew, L. Hughes, P. C. D. Newton, S. S. Schuster, A. Tait, and P. Whetton. Climate change 2014: Impacts, adaptation, and vulnerability. Part B: Regional aspects. Contribution of Working Group II to the Fifth Assessment of the Intergovernmental Panel on Climate Change. Technical report, Intergovernmental Panel on Climate Change, 2014. URL https://www.ipcc.ch/report/ar5/wg2/. Bureau of Meteorology. Climate Glossary-Drought. URL http://www.bom.gov.au/climate/glossary/drought.shtml. K. M. Lau and H. Weng. Climate signal detection using wavelet transform: How to make a time series sing. B. Am. Meteorol. Soc., 76:23912402, 1995. doi:10.1175/1520-0477(1995)0762391:CSDUWT>2.0.CO;2. M. B. Richman and L. M. Leslie. Uniqueness and causes of the California drought. Procedia Comput. Sci., 61:428435, 2015. doi:10.1016/j.procs.2015.09.181. M. B. Richman and L. M. Leslie. The 20152017 Cape Town drought: Attribution and prediction using machine learning. Procedia Comput. Sci., 140:248257, 2018. doi:10.1016/j.procs.2018.10.323.

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Analysis of Past and Projected Trends of Rainfall and Temperature Parameters in Eastern and Western Hararghe Zones, Ethiopia

Atmosphere ◽

10.3390/atmos13010067 ◽

2021 ◽

Vol 13 (1) ◽

pp. 67

Author(s):

Helen Teshome ◽

Kindie Tesfaye ◽

Nigussie Dechassa ◽

Tamado Tana ◽

Matthew Huber

Keyword(s):

Climate Change ◽

Minimum Temperature ◽

Annual Rainfall ◽

Maximum Temperature ◽

Climate Change And Variability ◽

Annual Minimum Temperature ◽

Increasing Trend ◽

Rcp 8.5 ◽

The Mean ◽

East And West

Smallholder farmers in East and West Hararghe zones, Ethiopia frequently face problems of climate extremes. Knowledge of past and projected climate change and variability at local and regional scales can help develop adaptation measures. A study was therefore conducted to investigate the spatio-temporal dynamics of rainfall and temperature in the past (1988–2017) and projected periods of 2030 and 2050 under two Representative Concentration Pathways (RCP4.5 and RCP8.5) at selected stations in East and West Hararghe zones, Ethiopia. To detect the trends and magnitude of change Mann–Kendall test and Sen’s slope estimator were employed, respectively. The result of the study indicated that for the last three decades annual and seasonal and monthly rainfall showed high variability but the changes are not statistically significant. On the other hand, the minimum temperature of the ‘Belg’ season showed a significant (p < 0.05) increment. The mean annual minimum temperature is projected to increase by 0.34 °C and 2.52 °C for 2030, and 0.41 °C and 4.15 °C for 2050 under RCP4.5 and RCP8.5, respectively. Additionally, the mean maximum temperature is projected to change by −0.02 °C and 1.14 °C for 2030, and 0.54 °C and 1.87 °C for 2050 under RCP4.5 and RCP 8.5, respectively. Annual rainfall amount is also projected to increase by 2.5% and 29% for 2030, and 12% and 32% for 2050 under RCP4.5 and RCP 8.5, respectively. Hence, it is concluded that there was an increasing trend in the Belg season minimum temperature. A significant increasing trend in rainfall and temperature are projected compared to the baseline period for most of the districts studied. This implies a need to design climate-smart crop and livestock production strategies, as well as an early warning system to counter the drastic effects of climate change and variability on agricultural production and farmers’ livelihood in the region.

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Evaluation of statistical downscaling methods for climate change projections over Spain: present conditions with perfect predictors.

10.5194/ems2021-46 ◽

2021 ◽

Author(s):

Alfonso Hernanz ◽

Juan-Andres García-Valero ◽

Marta Domínguez ◽

Petra Ramos-Calzado ◽

María-Asunción Pastor-Saavedra ◽

...

Keyword(s):

Climate Change ◽

Statistical Downscaling ◽

Precipitation Amount ◽

Maximum Temperature ◽

Support Vector ◽

Daily Maximum ◽

Climate Projections ◽

Total Precipitation ◽

The Mean ◽

Maximum Minimum

The Spanish Meteorological Agency (AEMET) is responsible for the elaboration of downscaled climate projections over Spain to feed the Second National Plan of Adaptation to Climate Change (PNACC-2). The main objective of this work is to establish a comparison among five statistical downscaling methods developed at AEMET: 1) Analog, 2) Regression, 3) Artificial Neural Networks, 4) Support Vector Machines and 5) Kernel Ridge Regression. All the five methods have been applied with a Perfect Prog approach to downscale daily maximum/minimum temperatures and daily precipitation on a high resolution observational grid (0.05o) over mainland Spain and the Balearic Islands, a region particularly challenging due to its large regional spatio-temporal variabilities. The comparison has been carried out under present conditions and with perfect predictors, based on the framework established by the VALUE network, in particular, on its perfect predictor experiment. The evaluation here performed is focused on marginal aspects, through an analysis of the four seasonal distributions of each variable. In order to enable a manageable comparison among all methods three indexes commonly used for climate change adaptation and impact studies have been used: the mean value and the 10th and 90th percentiles for daily maximum/minimum temperatures and the total precipitation amount (PRCPTOT), the total precipitation on very wet days (R95p) and the number of wet days (R01) for precipitation. For maximum/minimum temperatures, all methods display a similar behavior. They capture very satisfactorily the mean values although slight biases are detected on the extremes. In general, results for maximum temperature appear to be more accurate than for minimum temperature, and the non-linear methods display certain added value. For precipitation, remarkable differences are found among all methods: most of them are capable of reproducing the total precipitation amount quite satisfactorily, while other aspects such as intense precipitations and the precipitation occurrence are captured with more accuracy by the Analog method.&#160;

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Drought, Climate Change, and Dryland Wheat Yield Response: An Econometric Approach

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17145264 ◽

2020 ◽

Vol 17 (14) ◽

pp. 5264 ◽

Cited By ~ 1

Author(s):

Samira Shayanmehr ◽

Shida Rastegari Henneberry ◽

Mahmood Sabouhi Sabouni ◽

Naser Shahnoushi Foroushani

Keyword(s):

Climate Change ◽

Linear Model ◽

Climatic Change ◽

Minimum Temperature ◽

Wheat Yield ◽

Maximum Temperature ◽

Yield Variability ◽

Non Linear ◽

The Mean ◽

The Impact

Agriculture has been identified as one of the most vulnerable sectors affected by climate change. In the present study, we investigate the impact of climatic change on dryland wheat yield in the northwest of Iran for the future time horizon of 2041–2070. The Just and Pope production function is applied to assess the impact of climate change on dryland wheat yield and yield risk for the period of 1991–2016. The Statistical Downscaling Model (SDSM) is used to generate climate parameters from General Circulation Model (GCM) outputs. The results show that minimum temperature is negatively related to average yield in the linear model while the relationship is positive in the non-linear model. An increase in precipitation increases the mean yield in either model. The maximum temperature has a positive effect on the mean yield in the linear model, while this impact is negative in the non-linear model. Drought has an adverse impact on yield levels in both models. The results also indicate that maximum temperature, precipitation, and drought are positively related to yield variability, but minimum temperature is negatively associated with yield variability. The findings also reveal that yield variability is expected to increase in response to future climate scenarios. Given these impacts of temperature on rain-fed wheat crop and its increasing vulnerability to climatic change, policy-makers should support research into and development of wheat varieties that are resistant to temperature variations.

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Strong controls of daily minimum temperature on the autumn photosynthetic phenology of subtropical vegetation in China

Forest Ecosystems ◽

10.1186/s40663-021-00309-9 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Peixin Ren ◽

Zelin Liu ◽

Xiaolu Zhou ◽

Changhui Peng ◽

Jingfeng Xiao ◽

...

Keyword(s):

Climate Change ◽

Minimum Temperature ◽

Vegetation Index ◽

Climatic Factors ◽

Time Lag ◽

Evergreen Forest ◽

Maximum Temperature ◽

Daily Minimum Temperature ◽

Study Region ◽

Cumulative Precipitation

Abstract Background Vegetation phenology research has largely focused on temperate deciduous forests, thus limiting our understanding of the response of evergreen vegetation to climate change in tropical and subtropical regions. Results Using satellite solar-induced chlorophyll fluorescence (SIF) and MODIS enhanced vegetation index (EVI) data, we applied two methods to evaluate temporal and spatial patterns of the end of the growing season (EGS) in subtropical vegetation in China, and analyze the dependence of EGS on preseason maximum and minimum temperatures as well as cumulative precipitation. Our results indicated that the averaged EGS derived from the SIF and EVI based on the two methods (dynamic threshold method and derivative method) was later than that derived from gross primary productivity (GPP) based on the eddy covariance technique, and the time-lag for EGSsif and EGSevi was approximately 2 weeks and 4 weeks, respectively. We found that EGS was positively correlated with preseason minimum temperature and cumulative precipitation (accounting for more than 73% and 62% of the study areas, respectively), but negatively correlated with preseason maximum temperature (accounting for more than 59% of the study areas). In addition, EGS was more sensitive to the changes in the preseason minimum temperature than to other climatic factors, and an increase in the preseason minimum temperature significantly delayed the EGS in evergreen forests, shrub and grassland. Conclusions Our results indicated that the SIF outperformed traditional vegetation indices in capturing the autumn photosynthetic phenology of evergreen forest in the subtropical region of China. We found that minimum temperature plays a significant role in determining autumn photosynthetic phenology in the study region. These findings contribute to improving our understanding of the response of the EGS to climate change in subtropical vegetation of China, and provide a new perspective for accurately evaluating the role played by evergreen vegetation in the regional carbon budget.

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Effects of Cropland Expansion on Temperature Extremes in Western India from 1982 to 2015

Land ◽

10.3390/land10050489 ◽

2021 ◽

Vol 10 (5) ◽

pp. 489

Author(s):

Jinxiu Liu ◽

Weihao Shen ◽

Yaqian He

Keyword(s):

Land Use ◽

Heat Flux ◽

Land Cover ◽

Minimum Temperature ◽

Negative Impact ◽

Maximum Temperature ◽

Daily Minimum Temperature ◽

Daily Maximum ◽

Temperature Extremes ◽

Western India

India has experienced extensive land cover and land use change (LCLUC). However, there is still limited empirical research regarding the impact of LCLUC on climate extremes in India. Here, we applied statistical methods to assess how cropland expansion has influenced temperature extremes in India from 1982 to 2015 using a new land cover and land use dataset and ECMWF Reanalysis V5 (ERA5) climate data. Our results show that during the last 34 years, croplands in western India increased by ~33.7 percentage points. This cropland expansion shows a significantly negative impact on the maxima of daily maximum temperature (TXx), while its impacts on the maxima of daily minimum temperature and the minima of daily maximum and minimum temperature are limited. It is estimated that if cropland expansion had not taken place in western India over the 1982 to 2015 period, TXx would likely have increased by 0.74 (±0.64) °C. The negative impact of croplands on reducing the TXx extreme is likely due to evaporative cooling from intensified evapotranspiration associated with croplands, resulting in increased latent heat flux and decreased sensible heat flux. This study underscores the important influences of cropland expansion on temperature extremes and can be applicable to other geographic regions experiencing LCLUC.

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Observations on 287 thunder-storms made at highfield house, near Nottingham, during the last nine years

Abstracts of the Papers Communicated to the Royal Society of London ◽

10.1098/rspl.1843.0247 ◽

1851 ◽

Vol 5 ◽

pp. 957-957

Keyword(s):

Minimum Temperature ◽

Maximum Temperature ◽

Tabular Form ◽

The Hours ◽

The Mean ◽

Atmospheric Phenomena ◽

Rotatory Motion

The thunder-storms referred to in this communication are recorded in a tabular form., arranged according to their dates. In this table are given the date; the hour of the commencement of the storm; the mean height of the barometer to tenths of an inch; whether it is rising, stationary, or falling; the direction of the wind before the storm, during its continuance, and after its cessation; the maximum temperature on the day of the storm and on the day after; the minimum temperature on the night before and on the night after; and general remarks on the storms. This table is followed by remarks on particular storms recorded in it. In conclusion the author gives the results of his observations with reference to the number of storms in each year; the number in each month, with the hours at which they mostly occur in particular months; the number that have occurred with a rising, stationary, or falling barometer; the number in respect to the direction of the wind and of the current in which the storms moved; the number of storms that have occurred at the various heights of the maximum, and also of the minimum thermometer; the number in which the peculiar breeze that suddenly springs up on the commencement of thunder-storms has been well marked; the change in the direction of some of these storms, and indications of rotatory motion; and finally, the different atmospheric phenomena which have accompanied these storms.

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Observed Trends in Indices of Daily Temperature Extremes in South America 1960–2000

Journal of Climate ◽

10.1175/jcli3589.1 ◽

2005 ◽

Vol 18 (23) ◽

pp. 5011-5023 ◽

Cited By ~ 294

Author(s):

L. A. Vincent ◽

T. C. Peterson ◽

V. R. Barros ◽

M. B. Marino ◽

M. Rusticucci ◽

...

Keyword(s):

Climate Change ◽

South America ◽

Climate Extremes ◽

Daily Temperature ◽

Maximum Temperature ◽

Daily Minimum Temperature ◽

Daily Maximum Temperature ◽

Daily Maximum ◽

Temperature Extremes ◽

Increasing Trends

Abstract A workshop on enhancing climate change indices in South America was held in Maceió, Brazil, in August 2004. Scientists from eight southern countries brought daily climatological data from their region for a meticulous assessment of data quality and homogeneity, and for the preparation of climate change indices that can be used for analyses of changes in climate extremes. This study presents an examination of the trends over 1960–2000 in the indices of daily temperature extremes. The results indicate no consistent changes in the indices based on daily maximum temperature while significant trends were found in the indices based on daily minimum temperature. Significant increasing trends in the percentage of warm nights and decreasing trends in the percentage of cold nights were observed at many stations. It seems that this warming is mostly due to more warm nights and fewer cold nights during the summer (December–February) and fall (March–May). The stations with significant trends appear to be located closer to the west and east coasts of South America.

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Assessing the contribution of multiple forcings to changes in temperature extremes 1981–2020 using CMIP6 climate models

10.5194/egusphere-egu21-7137 ◽

2021 ◽

Author(s):

Mastawesha Misganaw Engdaw ◽

Andrew Ballinger ◽

Gabriele Hegerl ◽

Andrea Steiner

Keyword(s):

Climate Change ◽

Greenhouse Gases ◽

Climate Models ◽

Temporal Trends ◽

Maximum Temperature ◽

Daily Minimum Temperature ◽

Daily Maximum Temperature ◽

Daily Maximum ◽

Temperature Extremes ◽

Cold Temperatures

In this study, we aim at quantifying the contribution of different forcings to changes in temperature extremes over 1981&#8211;2020 using CMIP6 climate model simulations. We first assess the changes in extreme hot and cold temperatures defined as days below 10% and above 90% of daily minimum temperature (TN10 and TN90) and daily maximum temperature (TX10 and TX90). We compute the change in percentage of extreme days per season for October-March (ONDJFM) and April-September (AMJJAS). Spatial and temporal trends are quantified using multi-model mean of all-forcings simulations. The same indices will be computed from aerosols-, greenhouse gases- and natural-only forcing simulations. The trends estimated from all-forcings simulations are then attributed to different forcings (aerosols-, greenhouse gases-, and natural-only) by considering uncertainties not only in amplitude but also in response patterns of climate models. The new statistical approach to climate change detection and attribution method by Ribes et al. (2017) is used to quantify the contribution of human-induced climate change. Preliminary results of the attribution analysis show that anthropogenic climate change has the largest contribution to the changes in temperature extremes in different regions of the world.Keywords: climate change, temperature, extreme events, attribution, CMIP6&#160;Acknowledgement: This work was funded by the Austrian Science Fund (FWF) under Research Grant W1256 (Doctoral Programme Climate Change: Uncertainties, Thresholds and Coping Strategies)

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Assessing runoff sensitivities to precipitation and temperature changes under global climate-change scenarios

Hydrology Research ◽

10.2166/nh.2018.192 ◽

2018 ◽

Vol 50 (1) ◽

pp. 24-42 ◽

Cited By ~ 10

Author(s):

Lei Chen ◽

Jianxia Chang ◽

Yimin Wang ◽

Yuelu Zhu

Keyword(s):

Climate Change ◽

Minimum Temperature ◽

Yellow River ◽

Control Variable ◽

Maximum Temperature ◽

Future Climate Change ◽

Climate Change Scenarios ◽

Temperature Changes ◽

Runoff Change ◽

Precipitation And Temperature

Abstract An accurate grasp of the influence of precipitation and temperature changes on the variation in both the magnitude and temporal patterns of runoff is crucial to the prevention of floods and droughts. However, there is a general lack of understanding of the ways in which runoff sensitivities to precipitation and temperature changes are associated with the CMIP5 scenarios. This paper investigates the hydrological response to future climate change under CMIP5 RCP scenarios by using the Variable Infiltration Capacity (VIC) model and then quantitatively assesses runoff sensitivities to precipitation and temperature changes under different scenarios by using a set of simulations with the control variable method. The source region of the Yellow River (SRYR) is an ideal area to study this problem. The results demonstrated that the precipitation effect was the dominant element influencing runoff change (the degree of influence approaching 23%), followed by maximum temperature (approaching 12%). The weakest element was minimum temperature (approaching 3%), despite the fact that the increases in minimum temperature were higher than the increases in maximum temperature. The results also indicated that the degree of runoff sensitivity to precipitation and temperature changes was subject to changing external climatic conditions.

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