SENSITIVITY ANALYSIS OF A FAO PENMAN MONTEITH FOR POTENTIAL EVAPOTRANSPIRATION TO CLIMATE CHANGE

2017 ◽  
Vol 79 (7) ◽  
Author(s):  
Nor Farah Atiqah Ahmad ◽  
Muhamad Askari ◽  
Sobri Harun ◽  
Abu Bakar Fadhil ◽  
Amat Sairin Demun
Keyword(s):  
Climate Change ◽  
Sensitivity Analysis ◽  
Wind Speed ◽  
Solar Radiation ◽  
Graphical Method ◽  
Potential Evapotranspiration ◽  
Peninsular Malaysia ◽  
Percentage Change ◽  
Cameron Highlands ◽  
Tropical Climates

Sensitivity of the FAO Penman-Monteith (FPM) potential evapotranspiration (PET) model under tropical climates has been studied in the present study. A total of 17 meteorological stations covering Peninsular Malaysia starting from 1987-2003 were used as model inputs. A sensitivity analysis (SA) was carried out using the graphical method for temperature, wind speed and solar radiation within the possible range of ±20% with increments of 5%. From the comparison done on the sensitivity of PET to climatic change, the Kuala Krai station gave the highest percentage change in terms of temperature (±6%). The highest percentage change for wind speed (±2%) and solar radiation (±17%) were shown at the Alor Setar and Kuala Krai stations, respectively. The Alor Setar station had the lowest percentage change for temperature (±0.3%) and solar radiation (±9.9). The lowest percentage change of wind speed (± 0.2%) was observed at the Kuala Krai station. PET percentage changes have a positive correlation to the percentage change of all climatic variables except for the Cameron Highlands station. Results revealed that solar radiation has the most significant effect on PET (±14%), followed by temperature (±4%) and wind speed (±1%). Taken together, these results suggest that solar radiation plays an important role in estimating PET in Peninsular Malaysia.

scholarly journals A Practical Approach to Developing Climate Change Scenarios for Water Quality Models

2019 ◽  
Vol 20 (6) ◽  
pp. 1197-1211 ◽  
Author(s):  
Rakesh K. Gelda ◽  
Rajith Mukundan ◽  
Emmet M. Owens ◽  
John T. Abatzoglou
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
New York ◽  
Wind Speed ◽  
Solar Radiation ◽  
Climate Change Scenarios ◽  
Quality Models ◽  
Hourly Data ◽  
Water Quality Models ◽  
The Impact

Abstract Climate model output is often downscaled to grids of moderately high spatial resolution (~4–6-km grid cells). Such projections have been used in numerous hydrological impact assessment studies at watershed scales. However, relatively few studies have been conducted to assess the impact of climate change on the hydrodynamics and water quality in lakes and reservoirs. A potential barrier to such assessments is the need for meteorological variables at subdaily time scales that are downscaled to in situ observations to which lake and reservoir water quality models have been calibrated and validated. In this study, we describe a generalizable procedure that utilizes gridded downscaled data; applies a secondary bias-correction procedure using equidistance quantile mapping to map projections to station-based observations; and implements temporal disaggregation models to generate point-scale hourly air and dewpoint temperature, wind speed, and solar radiation for use in water quality models. The proposed approach is demonstrated for six locations within New York State: four within watersheds of the New York City water supply system and two at nearby National Weather Service stations. Disaggregation models developed using observations reproduced hourly data well at all locations, with Nash–Sutcliffe efficiency greater than 0.9 for air temperature and dewpoint, 0.4–0.6 for wind speed, and 0.7–0.9 for solar radiation.

scholarly journals Using ERA-Interim Reanalysis output for creating datasets of energy-relevant climate variables

2017 ◽  
Author(s):  
Philip D. Jones ◽  
Colin Harpham ◽  
Alberto Troccoli ◽  
Benoit Gschwind ◽  
Thierry Ranchin ◽  
...  
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
Climate Variables ◽  
Climate Data ◽  
Near Surface ◽  
Bias Adjustment ◽  
Dewpoint Temperature ◽  
Data Store

Abstract. The construction of a bias-adjusted dataset of climate variables at the near surface using ERA-Interim Reanalysis is presented. A number of different bias-adjustment approaches have been proposed. Here we modify the parameters of different distributions (depending on the variable), adjusting those calculated from ERA-Interim to those based on gridded station or direct station observations. The variables are air temperature, dewpoint temperature, precipitation (daily only), solar radiation, wind speed and relative humidity, available at either 3 or 6 h timescales over the period 1979-2014. This dataset is available to anyone through the Climate Data Store (CDS) of the Copernicus Climate Change Data Store (C3S), and can be accessed at present from (ftp://ecem.climate.copernicus.eu). The benefit of performing bias-adjustment is demonstrated by comparing initial and bias-adjusted ERA-Interim data against observations.

scholarly journals Using ERA-Interim reanalysis for creating datasets of energy-relevant climate variables

2017 ◽  
Vol 9 (2) ◽  
pp. 471-495 ◽  
Author(s):  
Philip D. Jones ◽  
Colin Harpham ◽  
Alberto Troccoli ◽  
Benoit Gschwind ◽  
Thierry Ranchin ◽  
...  
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
Climate Variables ◽  
Climate Data ◽  
Near Surface ◽  
Bias Adjustment ◽  
Dewpoint Temperature ◽  
Data Store

Abstract. The construction of a bias-adjusted dataset of climate variables at the near surface using ERA-Interim reanalysis is presented. A number of different, variable-dependent, bias-adjustment approaches have been proposed. Here we modify the parameters of different distributions (depending on the variable), adjusting ERA-Interim based on gridded station or direct station observations. The variables are air temperature, dewpoint temperature, precipitation (daily only), solar radiation, wind speed, and relative humidity. These are available on either 3 or 6 h timescales over the period 1979–2016. The resulting bias-adjusted dataset is available through the Climate Data Store (CDS) of the Copernicus Climate Change Data Store (C3S) and can be accessed at present from ftp://ecem.climate.copernicus.eu. The benefit of performing bias adjustment is demonstrated by comparing initial and bias-adjusted ERA-Interim data against gridded observational fields.

scholarly journals Gulf Cooperation Council Countries’ Climate Change Mitigation Challenges and Exploration of Solar and Wind Energy Resource Potential

2021 ◽  
Vol 11 (6) ◽  
pp. 2648
Author(s):  
Fahad Radhi Alharbi ◽  
Denes Csala
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Solar Radiation ◽  
Wind Energy ◽  
Climate Change Mitigation ◽  
Energy Resource ◽  
Energy Resources ◽  
Speed Range ◽  
Wind Energy Resources ◽  
Change Mitigation

Climate change mitigation is one of the most critical challenges of this century. The unprecedented global effects of climate change are wide-ranging, including changing weather patterns that threaten food production, increased risk of catastrophic floods, and rising sea levels. Adapting to these impacts will be more difficult and costly in the future if radical changes are not made now. This review paper evaluates the Gulf Cooperation Council (GCC) countries’ potential for solar and wind energy resources to meet climate change mitigation requirements and assesses the ability of the GCC region to shift towards low-carbon technologies. The review demonstrates that the GCC region is characterized by abundant solar energy resources. The northwestern, southeastern, and western mountains of the region are highlighted as locations for solar energy application. Oman displays the highest onshore wind speed range, 3–6.3 m s⁻1, and has the highest annual solar radiation of up to 2500 kWh/m2. Kuwait has the second highest onshore wind speed range of 4.5–5.5 m s⁻1. The western mountains and northwestern Saudi Arabia have a wind speed range of 3–6 m s⁻1. The United Arab Emirates (UAE) has the second highest annual solar radiation, 2285 kWh/m2, while Saudi Arabia and the state of Kuwait have equal annual solar radiation at 2200 kWh/m2. This review demonstrates that abundant offshore wind energy resources were observed along the coastal areas of the Arabian Gulf, as well as a potential opportunity for wind energy resource development in the Red Sea, which was characterized by high performance. In addition, the GCC countries will not be able to control and address the interrelated issues of climate change in the future if they do not eliminate fossil fuel consumption, adhere to the Paris Agreement, and implement plans to utilize their natural resources to meet these challenges.

scholarly journals Influence of Meteorological Factors on the Potential Evapotranspiration in Yanhe River Basin, China

2021 ◽  
Author(s):  
yu luo ◽  
Peng Gao ◽  
Xingmin Mu
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
River Basin ◽  
Air Temperature ◽  
Hydrological Cycle ◽  
Meteorological Factors ◽  
Potential Evapotranspiration ◽  
Sensitivity Coefficients ◽  
The Impact

Potential evapotranspiration (ET) is an essential component of the hydrological cycle, and quantitative estimation of the influence of meteorological factors on ET can provide a scientific basis for studying the impact mechanisms of climate change. In the present research, the Penman-Monteith method was used to calculate ET. The Mann-Kendall statistical test with the inverse distance weighting were used to analyze the spatiotemporal characteristics of the sensitivity coefficients and contribution rates of meteorological factors to ET to identify the mechanisms underlying changing ET rates. The results showed that the average ET for the Yanhe River Basin, China from 1978–2017 was 935.92 mm. Save for a single location (Ganquan), ET increased over the study period. Generally, the sensitivity coefficients of air temperature (0.08), wind speed at 2 m (0.19), and solar radiation (0.42) were positive, while that of relative humidity was negative (-0.41), although significant spatiotemporal differences were observed. Increasing air temperature and solar radiation contributed 1.09% and 0.55% of the observed rising ET rates, respectively; whereas decreasing wind speed contributed -0.63%, and relative humidity accounted for -0.85%. Therefore, it was concluded that the decrease of relative humidity did not cause the observed ET increase in the basin. The predominant factor driving increasing ET was rising air temperatures, but this too varied significantly by location and time (intra- and interannually). Decreasing wind speed at Ganquan Station decreased ET by -9.16%, and was the primary factor underlying the observed, local “evaporation paradox.” Generally, increases in ET were driven by air temperature, wind speed and solar radiation, whereas decreases were derived from relative humidity.

scholarly journals Decomposition and Attribution Analysis of Runoff Alteration of the Dongting Lake in China

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2729
Author(s):  
Yuyun Huang ◽  
Minghui Yu ◽  
Haoyong Tian ◽  
Yujiao Liu
Keyword(s):  
Climate Change ◽  
Sensitivity Analysis ◽  
Human Activities ◽  
Potential Evapotranspiration ◽  
Dominant Role ◽  
Meteorological Data ◽  
Dongting Lake ◽  
Change Points ◽  
Runoff Change ◽  
Runoff Depth

The runoff process in the Dongting Lake has been influenced by climate change and human activities in recent decades. To manage the Dongting Lake efficiently and exploit water resources properly under the background of water shortage, it is desired to detect the factors of runoff change in the Dongting Lake. Hydro-meteorological data from 1961 to 2019 are analyzed to reveal the climate change and runoff alteration of the Dongting Lake comprehensively. Mutation test is used to detect the change points of runoff depth series, finding that 1984 and 2005 are change points and therefore 1961–1983, 1984–2004, and 2005–2019 are regarded as baseline period (BP), period 1 (P1), and period 2 (P2), respectively. Eight methods are used to quantitatively assess the relative contribution of human activities and climate change on runoff variation. It reveals that climate change especially precipitation change plays the dominant role (climate change makes runoff depth increase 70.14–121.51 mm, human activities make runoff depth decrease 51.98–103.35 mm) in runoff alteration in P1 while human activities play a prime role (account for 88.47–93.17%) in P2. Human activities such as reservoir construction, water consumption, and land-use (land-cover) change may be the main factors that influence the runoff in the Dongting Lake in P2. According to the sensitivity analysis, runoff in the Dongting Lake is more sensitive to climate change in P2 compared with that in P1, and no matter in P1 or P2, runoff is more sensitive to change in precipitation than the change in potential evapotranspiration. Combined with climate forecast, the results of sensitivity analysis can be used to estimate runoff change caused by climate change in the future.

scholarly journals Evaluation of Potential Evapotranspiration Based on CMADS Reanalysis Dataset over China

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1126 ◽  
Author(s):  
Ye Tian ◽  
Kejun Zhang ◽  
Yue-Ping Xu ◽  
Xichao Gao ◽  
Jie Wang
Keyword(s):  
Wind Speed ◽  
Solar Radiation ◽  
Potential Evapotranspiration ◽  
Swat Model ◽  
Western China ◽  
Reanalysis Dataset ◽  
The North ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Monteith Equation

Potential evapotranspiration (PET) is used in many hydrological models to estimate actual evapotranspiration. The calculation of PET by the Food and Agriculture Organization of the United Nations (FAO) Penman–Monteith method requires data for several meteorological variables that are often unavailable in remote areas. The China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) reanalysis datasets provide an alternative to the use of observed data. This study evaluates the use of CMADS reanalysis datasets in estimating PET across China by the Penman–Monteith equation. PET estimates from CMADS data (PET_cma) during the period 2008–2016 were compared with those from observed data (PET_obs) from 836 weather stations in China. Results show that despite PET_cma overestimating average annual PET and average seasonal in some areas (in comparison to PET_obs), PET_cma well matches PET_obs overall. Overestimation of average annual PET occurs mainly for western inland China. There are more meteorological stations in southeastern China for which PET_cma is a large overestimate, with percentage bias ranging from 15% to 25% for spring but a larger overestimate in the south and underestimate in the north for the winter. Wind speed and solar radiation are the climate variables that contribute most to the error in PET_cma. Wind speed causes PET to be underestimated with percentage bias in the range −15% to −5% for central and western China whereas solar radiation causes PET to be overestimated with percentage bias in the range 15% to 30%. The underestimation of PET due to wind speed is offset by the overestimation due to solar radiation, resulting in a lower overestimation overall.

Weibull and Hargreaves Methods to Determine the Wind and Solar Energy – Case Study

2011 ◽  
Vol 110-116 ◽  
pp. 2030-2033 ◽  
Author(s):  
A.N. Syafawati ◽  
I. Daut ◽  
Muhamad Irwanto ◽  
S.S. Shema ◽  
Z. Farhana ◽  
...  
Keyword(s):  
Wind Speed ◽  
Solar Radiation ◽  
Solar Energy ◽  
Radiation Pattern ◽  
Peninsular Malaysia ◽  
Weather Station ◽  
Speed Characteristic

This paper presents a case study of Weibull and Hargreaves methods used to determine the wind speed characteristic and solar radiation pattern in Perlis the northern part of Peninsular Malaysia. These two methods are then used to analyze the data of wind and solar that recorded using Davis Vantage Pro2 Weather Station. This paper also discusses the correlation of these two methods in determining the wind and solar energy. Through this case study, this paper conclude that these methods is highly recommended to determine and analyze the potential of wind and solar energy.

scholarly journals Attribute Analysis of Aridity Variability in North Xinjiang, China

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Yanfeng Wu ◽  
Guangxin Zhang ◽  
Hong Shen ◽  
Y. Jun Xu ◽  
Batur Bake
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Meteorological Factors ◽  
Potential Evapotranspiration ◽  
Aridity Index ◽  
Northwest China ◽  
Future Trend ◽  
Sunshine Hours ◽  
Recent Climate ◽  
North Xinjiang

Identifying the dominant meteorological factors affecting aridity variability can improve our understanding of climate change and its future trend in arid and semiarid regions. This study investigated the spatiotemporal aridity variability in North Xinjiang, China, from 1961 to 2013, based on the UNESCO aridity index (precipitation/potential evapotranspiration), and analyzed its association with meteorological factors. The results suggest that North Xinjiang is becoming more humid with an increasing trend in aridity index. Precipitation, temperature, and relative humidity have positive correlation with aridity, and evapotranspiration, sunshine hours, and wind speed have negative correlation with aridity. Wind speed and sunshine hours have a higher sensitivity and more contribution to aridity. This study provides an understanding of the effect of recent climate change on drought in northwest China.

scholarly journals Impact of Climate Change on the Water Requirements of Oat in Northeast and North China

Water ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 91 ◽  
Author(s):  
Hao Jia ◽  
Ting Zhang ◽  
Xiaogang Yin ◽  
Mengfei Shang ◽  
Fu Chen ◽  
...  
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Solar Radiation ◽  
Climatic Change ◽  
Climatic Factors ◽  
Water Requirement ◽  
Effective Rainfall ◽  
Crop Water ◽  
Water Requirements ◽  
Impact Of Climate Change

Crop water requirements are directly affected by climatic variability, especially for crops grown in the areas which are sensitive to climatic change. Based on the SIMETAW model and a long-term meteorological dataset, we evaluated the spatiotemporal variations of climatic change impacts on water requirement of oat in North and Northeast China. The results indicated that effective rainfall showed an increasing trend, while the crop water requirement and irrigation demand presented decreasing trends over the past decades. The water requirement of oat showed significant longitudinal and latitudinal spatial variations, with a downtrend from north to south and uptrend from east to west. Climatic factors have obviously changed in the growth season of oat, with upward trends in the average temperature and precipitation, and downward trends in the average wind speed, sunshine hours, relative humidity, and solar radiation. Declines in solar radiation and wind speed, accompanied with the increase in effective rainfall, have contributed to the reduced crop water requirement over these decades. Given the complex dynamic of climate change, when studying the impact of climate change on crop water requirements, we should not only consider single factors such as temperature or rainfall, we need to analyze the comprehensive effects of various climatic factors.

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