scholarly journals A spatial approach to rainfall in Sertão do Pajeú – Pernambuco

2021 ◽  
Vol 10 (11) ◽  
pp. e241101119614
Author(s):  
Gabriela Isabel Limoeiro Alves Nascimento ◽  
Guilherme Rocha Moreira ◽  
Victor Casimiro Piscoya ◽  
Raimundo Mainar de Medeiros ◽  
Renisson Neponuceno de Araújo Filho ◽  
...  

Changes in precipitation have implications for the hydrological cycle and water resources. Climate change is expected to alter average temperature and precipitation values, increasing the variability of these events, which could cause more intense and frequent floods and droughts. The objective of this study was to characterize the rainfall in the microregion of Pajeú, in Pernambuco, as well as to provide subsidies for public policies aimed at water scarcity. For this, rainfall data were used at stations belonging to the micro-region and its surroundings, for the period from January 1980 to December 2019. In addition, to mitigate the influences caused by temporal heterogeneity, stations with large discontinuity of information. The Inverse Weighted Distance was used to perform the interpolation of data and preparation of maps with isolines of rainfall. The results show the places with the highest annual rainfall during the study period were Serra Talhada and Triunfo, and the lowest rainfall occurred in the vicinity of Ingazeira and Tabira.

2021 ◽  
Author(s):  
Livia Serrao ◽  
Lorenzo Giovannini ◽  
Luz Elita Balcazar Terrones ◽  
Hugo Alfredo Huamaní Yupanqui ◽  
Dino Zardi

<p>Climatic characteristics and weather events have always conditioned the success of a harvest. Climate change and the associated increase in intense weather phenomena in recent years are making it clearer than ever that agriculture is among the sectors most at risk. Although problems in agriculture are found all over the world, the most vulnerable contexts are those where agriculture is low-tech and rainfed. Here, adaptation strategies are even more urgent to secure the food production. Assuming that the awareness of climate change is the basis for the adoption of adaptation and mitigation strategies, it is interesting to correlate the degree of perception of local inhabitants with their willingness to adopt bottom-up initiatives.</p><p>The current study focuses on banana producers’ perceptions of climate change in a tropical valley, and the initiatives that farmers adopt to cope with recent intense weather events. The banana plant (Musa Musacae) grows in tropical climates with annual rainfall around 2000 mm and average temperatures around 27°C. The species’ threadlike root system and the weak pseudostem make it particularly vulnerable to wind gusts, which, at speeds higher than 15 m/s, can bend and knock over entire plantations. The increased frequency of convective thunderstorms observed in connection with climate change has made downburst phenomena more frequent and caused greater crop loss.</p><p>The aim of the present work is to estimate the correlation between banana producers’ perceptions of climate change and their bottom-up initiatives for adaptation. To achieve this goal, the case study of the Upper Huallaga valley, which is located in the Peruvian Amazon region as shown in Figure 1, is analysed. The work was carried out at two levels: (i) we interviewed 73 banana producers in the valley, (ii) we estimated the alterations and trends in temperature and precipitation recorded by the only three available meteorological stations within the valley. Finally, we compared the two databases to evaluate if the perception of the population was confirmed by the data. Most of the surveyed population observed an increase in temperature, consistent with the results of the data analysis, and an increase in precipitation, which was not consistent with observations as these showed a cyclic variation without a clear trend. With regards to the adaptation measures, it was observed that, although a clear majority of the sample surveyed (around 82%) agreed with the existence of climate change, only 46% of them had taken any initiative to counteract adverse events in some way. However, it is important to note that the strategies implemented were all devised and implemented by the farmers themselves. Funding and coordinating the dissemination of these adaptation practices by the local authority through a rural development plan could certainly strengthen the population’s effort.</p><p><img src="https://contentmanager.copernicus.org/fileStorageProxy.php?f=gnp.34e8e7df2cff59382630161/sdaolpUECMynit/12UGE&app=m&a=0&c=59f620ca81f3a3bb7bb44139d499513c&ct=x&pn=gnp.elif&d=1" alt=""></p><p><em>Figure 1, On the left side: the Upper Huallaga basin. </em><em>On the right side: the study area</em></p>


Climate ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 136
Author(s):  
Dol Raj Luitel ◽  
Pramod K. Jha ◽  
Mohan Siwakoti ◽  
Madan Lall Shrestha ◽  
Rangaswamy Munniappan

The Chitwan Annapurna Landscape (CHAL) is the central part of the Himalayas and covers all bioclimatic zones with major endemism of flora, unique agro-biodiversity, environmental, cultural and socio-economic importance. Not much is known about temperature and precipitation trends along the different bioclimatic zones nor how changes in these parameters might impact the whole natural process, including biodiversity and ecosystems, in the CHAL. Analysis of daily temperature and precipitation time series data (1970–2019) was carried out in seven bioclimatic zones extending from lowland Terai to the higher Himalayas. The non-parametric Mann-Kendall test was applied to determine the trends, which were quantified by Sen’s slope. Annual and decade interval average temperature, precipitation trends, and lapse rate were analyzed in each bioclimatic zone. In the seven bioclimatic zones, precipitation showed a mixed pattern of decreasing and increasing trends (four bioclimatic zones showed a decreasing and three bioclimatic zones an increasing trend). Precipitation did not show any particular trend at decade intervals but the pattern of rainfall decreases after 2000AD. The average annual temperature at different bioclimatic zones clearly indicates that temperature at higher elevations is increasing significantly more than at lower elevations. In lower tropical bioclimatic zone (LTBZ), upper tropical bioclimatic zone (UTBZ), lower subtropical bioclimatic zone (LSBZ), upper subtropical bioclimatic zone (USBZ), and temperate bioclimatic zone (TBZ), the average temperature increased by 0.022, 0.030, 0.036, 0.042 and 0.051 °C/year, respectively. The decade level temperature scenario revealed that the hottest decade was from 1999–2009 and average decade level increases of temperature at different bioclimatic zones ranges from 0.2 to 0.27 °C /decade. The average temperature and precipitation was found clearly different from one bioclimatic zone to other. This is the first time that bioclimatic zone level precipitation and temperature trends have been analyzed for the CHAL. The rate of additional temperature rise at higher altitudes compared to lower elevations meets the requirements to mitigate climate change in different bioclimatic zones in a different ways. This information would be fundamental to safeguarding vulnerable communities, ecosystem and relevant climate-sensitive sectors from the impact of climate change through formulation of sector-wise climate change adaptation strategies and improving the livelihood of rural communities.


2019 ◽  
Vol 19 (1) ◽  
pp. 15-37 ◽  
Author(s):  
Sumira Nazir Zaz ◽  
Shakil Ahmad Romshoo ◽  
Ramkumar Thokuluwa Krishnamoorthy ◽  
Yesubabu Viswanadhapalli

Abstract. The local weather and climate of the Himalayas are sensitive and interlinked with global-scale changes in climate, as the hydrology of this region is mainly governed by snow and glaciers. There are clear and strong indicators of climate change reported for the Himalayas, particularly the Jammu and Kashmir region situated in the western Himalayas. In this study, using observational data, detailed characteristics of long- and short-term as well as localized variations in temperature and precipitation are analyzed for these six meteorological stations, namely, Gulmarg, Pahalgam, Kokarnag, Qazigund, Kupwara and Srinagar during 1980–2016. All of these stations are located in Jammu and Kashmir, India. In addition to analysis of stations observations, we also utilized the dynamical downscaled simulations of WRF model and ERA-Interim (ERA-I) data for the study period. The annual and seasonal temperature and precipitation changes were analyzed by carrying out Mann–Kendall, linear regression, cumulative deviation and Student's t statistical tests. The results show an increase of 0.8 ∘C in average annual temperature over 37 years (from 1980 to 2016) with higher increase in maximum temperature (0.97 ∘C) compared to minimum temperature (0.76 ∘C). Analyses of annual mean temperature at all the stations reveal that the high-altitude stations of Pahalgam (1.13 ∘C) and Gulmarg (1.04 ∘C) exhibit a steep increase and statistically significant trends. The overall precipitation and temperature patterns in the valley show significant decreases and increases in the annual rainfall and temperature respectively. Seasonal analyses show significant increasing trends in the winter and spring temperatures at all stations, with prominent decreases in spring precipitation. In the present study, the observed long-term trends in temperature (∘Cyear-1) and precipitation (mm year−1) along with their respective standard errors during 1980–2016 are as follows: (i) 0.05 (0.01) and −16.7 (6.3) for Gulmarg, (ii) 0.04 (0.01) and −6.6 (2.9) for Srinagar, (iii) 0.04 (0.01) and −0.69 (4.79) for Kokarnag, (iv) 0.04 (0.01) and −0.13 (3.95) for Pahalgam, (v) 0.034 (0.01) and −5.5 (3.6) for Kupwara, and (vi) 0.01 (0.01) and −7.96 (4.5) for Qazigund. The present study also reveals that variation in temperature and precipitation during winter (December–March) has a close association with the North Atlantic Oscillation (NAO). Further, the observed temperature data (monthly averaged data for 1980–2016) at all the stations show a good correlation of 0.86 with the results of WRF and therefore the model downscaled simulations are considered a valid scientific tool for the studies of climate change in this region. Though the correlation between WRF model and observed precipitation is significantly strong, the WRF model significantly underestimates the rainfall amount, which necessitates the need for the sensitivity study of the model using the various microphysical parameterization schemes. The potential vorticities in the upper troposphere are obtained from ERA-I over the Jammu and Kashmir region and indicate that the extreme weather event of September 2014 occurred due to breaking of intense atmospheric Rossby wave activity over Kashmir. As the wave could transport a large amount of water vapor from both the Bay of Bengal and Arabian Sea and dump them over the Kashmir region through wave breaking, it probably resulted in the historical devastating flooding of the whole Kashmir valley in the first week of September 2014. This was accompanied by extreme rainfall events measuring more than 620 mm in some parts of the Pir Panjal range in the south Kashmir.


2017 ◽  

The effects of climate change have been observed on agricultural lands in the Caribbean. Climate change effects include shifts in temperature and precipitation, which can manifest as water scarcity or excess, above normal temperatures, sea level rise, as well as frequent tropical storms.


2021 ◽  
Author(s):  
Franco Catalano ◽  
Andrea Alessandri ◽  
Wilhelm May ◽  
Thomas Reerink

<p align="justify"><span>The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) aims at diagnosing systematic biases in the land models of CMIP6 Earth System Models and assessing the role of land-atmosphere feedbacks on climate change. Two components of experiments have been designed: the first is devoted to the assessment of the systematic land biases in offline mode (LMIP) while the second component is dedicated to the analysis of the land feedbacks in coupled mode (LFMIP). Here we focus on the LFMIP experiments. In the LFMIP protocol (van den Hurk et al. 2016), which builds upon the GLACE-CMIP configuration, two sets of climate-sensitivity projections have been carried out in amip mode: in the first set (amip-lfmip-pdLC) the land feedbacks to climate change have been disabled by prescribing the soil-moisture states from a climatology derived from “present climate conditions” (1980-2014) while in the second set (amip-lfmip-rmLC) 30-year running mean of land-surface state from the corresponding ScenarioMIP experiment (O’Neill et al., 2016) is prescribed. The two sensitivity simulations span the period 1980-2100 with sea surface temperature and sea-ice conditions prescribed from the first member of historical and ScenarioMIP experiments. Two different scenarios are considered: SSP1-2.6 (f1) and SSP5-8.5 (f2).</span></p><p align="justify"><span>In this analysis, we focus on the differences between amip-lfmip-rmLC and amip-lfmip-pdLC at the end of the 21st Century (2071–2100) in order to isolate the impact of the soil moisture changes on surface climate change. The (2071-2100) minus (1985-2014) temperature change is positive everywhere over land and the climate change signal of precipitation displays a clear intensification of the hydrological cycle in the Northern Hemisphere. Warming and hydrological cycle intensification are larger in SSP5-8.5 scenario. Results show large differences in the feedbacks between wet, transition and semi-arid climates. In particular, over the regions with negative soil moisture change, the 2m-temperature increases significantly while the cooling signal is not significant over all the regions getting wetter. In agreement with Catalano et al. (2016), the larger effects on precipitation due to soil moisture forcing occur mostly over transition zones between dry and wet climates, where evaporation is highly sensitive to soil moisture. The sensitivity of both 2m-temperature and precipitation to soil moisture change is much stronger in the SSP5-8.5 scenario.</span></p>


Author(s):  
Mai Van Khiem

Abstract: This article presents the results of constructing climate change scenarios for Ho Chi Minh City (HCMC)based on the climate change scenarios of Vietnam published in 2016 by the Ministry of Natural Resources and Environment. Four high- resolution regional climate models include CCAM, clWRF, PRECIS, RegCM were used to downscale results of global climate models. The results show that the annual average temperature in HCMC tends to increase in the future compared to the baseline period 1986-2005, the increase depends on each RCP scenario. By the end of the century, the annual average temperature in HCMC had an increase of about 1.7÷1.9°C under the RCP4.5 scenario and 3.2÷3.6°C under RCP8.5.Meanwhile, annual rainfall in HCMC tends to increase in most periods under both of RCP scenarios. By the end of the century, annual rainfall in HCMC increases from 15% to 25% in the RCP4.5 scenario and 20-25% in the RCP8.5 scenario. Annual rainfall in coastal areas increases more than inland areas. Keyword: Climate change scenarios, Ho Chi Minh city


2020 ◽  
Vol 9 (3) ◽  
pp. 6
Author(s):  
Adamu Mulu Ketema ◽  
Kasahun Dubale Negeso

Currently climate change is known as the major environmental problem the world face. Its effect is openly reduces agricultural output in particular and economic growth in general. The aim of the study was to examine the long run and short run effect of climate change on agricultural output in Ethiopia over a period of 1980-2016. The ARDL approach to co integration was applied to examine the long run and short run effect of climate change on agricultural output. ADF test was used for Unit root test. The finding of bound test shows that there is stable long run relationship between RAGDP, labour force, Mean annual rainfall, Average temperature, agriculture land, and fertilizer input import. The estimated long run model reveals that climate changes have an important effect on agricultural output which is the main contributor of overall GDP of the country. The coefficient of error correction term is -0.738 suggesting about 73.8% percent annual adjustment towards long run equilibrium. The estimate coefficients of short run show that mean annual rainfall have significant effect but average temperature is insignificant effect on output. In the long run both main variable of interest have significant effect on agricultural output with a positive effect from mean annual rainfall and negative effect from average temperature. To reduce the effect of climate change the study recommends government and stakeholders needs to create a specific policies to reduce the effect of climate change especially focus on technological innovation that avert effect of increase in temperature that would result increase on the output and adopting technology at macro and micro level.. 


2021 ◽  
Author(s):  
Beatrix Izsák ◽  
Tamás Szentimrey ◽  
Mónika Lakatos ◽  
Rita Pongrácz

<p>To study climate change, it is essential to analyze extremes as well. The study of extremes can be done on the one hand by examining the time series of extreme climatic events and on the other hand by examining the extremes of climatic time series. In the latter case, if we analyze a single element, the extreme is the maximum or minimum of the given time series. In the present study, we determine the extreme values of climatic time series by examining several meteorological elements together and thus determining the extremes. In general, the main difficulties are connected with the different probability distribution of the variables and the handling of the stochastic connection between them. The first issue can be solved by the standardization procedures, i.e. to transform the variables into standard normal ones. For example, the Standardized Precipitation Index (SPI) uses precipitation sums assuming gamma distribution, or the standardization of temperature series assumes normal distribution. In case of more variables, the problem of stochastic connection can be solved on the basis of the vector norm of the variables defined by their covariance matrix. According to this methodology we have developed a new index in order to examine the precipitation and temperature variables jointly. We present the new index with the mathematical background, furthermore some examples for spatio-temporal examination of these indices using our software MASH (Multiple Analysis of Series for Homogenization; Szentimrey) and MISH (Meteorological Interpolation based on Surface Homogenized Data Basis; Szentimrey, Bihari). For our study, we used the daily average temperature and precipitation time series in Hungary for the period 1870-2020. First of all, our analyses indicate that even though some years may not be considered extreme if only either precipitation or average temperature is taken in to account, but examining the two elements together these years were extreme years indeed. Based on these, therefore, the study of the extremes of multidimensional climate time series complements and thus makes the study of climate change more efficient compared to examining only one-dimensional time series.</p>


2020 ◽  
Vol 8 (3) ◽  
pp. 195-208
Author(s):  
Adamu Mulu Ketema ◽  
Kasahun Dubale Negeso

Currently change in climate is known as the main environmental difficult that the world face. Its effect is openly reduces agricultural output in particular and economic growth in general. The main objective of the study was to examine the long run and short run effect of climate change on agricultural output in Ethiopia over a period of 1980-2016. The Auto Regresive Distributive Lag approach to co integration was applied to examine the long run and short run effect of climate change on agricultural output. ADF test was used for Unit root test. Result of bound test reveals that there is stable long run relationship between RAGDP, labour force, Mean annual rainfall, Average temperature, agriculture land, and fertilizer input import. The estimated long run model reveals that climate changes have an important effect on agricultural output which is the main contributor of overall GDP of the country. The coefficient of error correction term is -0.738 suggesting about 73.8% annual adjustment towards long run equilibrium. The estimate coefficients of short run show that mean annual rainfall have significant effect whereas average temperature has insignificant effect on output. In the long run both main variable of interest have significant effect on agricultural output with a positive effect from mean annual rainfall and negative effect from average temperature. In order to lessen the effects the study recommends concerned body needs to create a specific policies especially focus on technological adoption that avert effect of increase in temperature and that would result increase on the output by adopting technology at macro and micro level, additionally information regarding climate should be available for producers and consumer.


2021 ◽  
Author(s):  
Eshrat Fatima ◽  
Akif Rahim ◽  
Shabeh ul Hasson ◽  
Mujtaba Hassan ◽  
Farhan Aziz ◽  
...  

<p>The hydrological cycle is generally known as a recurring result of various forms of water movement and changes in its physical state in nature over a specific area of ​​the earth (river or Lake Basin, a continent, or the whole earth). It is most likely that the increase in global warming will intensively affect the hydrological cycle regionally and globally which will ultimately affect the ecosystem, public health, and municipal water demand. Therefore, the resiliency of watershed to extreme events play a vital role to understand the health of the watershed. This study aims to quantify the resiliency of the Hunza watershed, which lies in the Western Karakoram, to dry conditions under the climate change projections i.e. RCPs 2.6, 4.5, and 8.5. We used a fully distributed hydrological model SPHY to simulate the impact of climate change on future water availability. The SPHY Model was calibration and validation for the time periods (1994-2000) and (2001-2006) respectively. The performance of the model was tested through statistical analysis such as Nash-Sutcliffe efficiency (NSE), coefficient of determination (R<sup>2</sup>), percentage of bias (PBIAS), and root mean square error (RMSE).To develop future water scenarios, the daily temperature, and precipitation data were obtained from the CORDEX South Asia domain under three Representative Concentration Pathways (RCPs). The empirical quantile mapping method was used for the correction of the daily temperature and precipitation biases under the regional scale. The model was run for near (2007-2036), mid (2037-2066), and far-future (2067-2096) climate projections i.e. RCP2.6, RCP4.5, and RCP8.5. The resilience of watershed defined as the speed of recovery from dry conditions. The monthly Streamflow Drought Index (SDI) was used as an indicator of the dry condition. The resiliency of the watershed determines with the threshold levels of -0.5 and -1.0. The analysis indicates that the resiliency of the watershed has increased from 0.3 to 0.5 in the future under the RCP of 2.6. The value of resilience under the RCP of 4.5 is 0.29, 0.45, and 0.52 for near, mid, and far futures respectively. Under extreme climate conditions RCP 8.5, the watershed resilience is 0.2 in the near future and 0.3 in the mid-future, and 0.6 for the far future. Therefore, it can be concluded that the health of the reservoirs will be very good in the future to stabilize the drought.  </p>


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