Application of SDSM and LARS-WG for simulating and downscaling of rainfall and temperature

Hassan, Zulkarnain; Shamsudin, Sarimah; Harun, Sobri

doi:10.1007/s00704-013-0951-8

Cited by 168 publications

(104 citation statements)

References 26 publications

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“…The findings of this work were in partial agreement with Agarwal et al [6], who also reported that LARS-WG underpredicted precipitation. In general, the current results are in agreement with other studies that reported lower performance of LARS-WG in predicting precipitation compared with its simulation of air temperature (Tmin and Tmax) [7,30]. It is also worth noting that other downscaling models (e.g., SDSM) exhibited lower performance in predicting precipitation compared with temperature [7,19].…”

Section: Performance Of the Lars-wg Modelsupporting

confidence: 92%

“…Projected increases in climate extremes (e.g., heat waves and severe snowstorms) are expected to result in serious health problems [1,4,5]. The hydrologic cycle is adversely affected by climate change, especially shifts in spatial and temporal rainfall distribution and intensity [6,7]. In addition, climate change and climate variability have been causing significant shifts in frequency and intensity of climate extremes, e.g., minimum and maximum temperatures [8,9] and droughts [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

“…Several studies have reported that the LARS-WG model fits observed air temperature (Tmin and Tmax) [7,23] very well, while its performance in predicting rainfall was reasonable [6]. The LARS-WG model fits the distribution of long-term observed climate data to develop the statistical parameters for the area of interest.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of Potential Future Climate and Climate Extremes in the Brazos Headwaters Basin, Texas

Awal

Bayabil

Fares

2016

Water

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Texas' fast-growing economy and population, coupled with cycles of droughts due to climate change, are creating an insatiable demand for water and an increasing need to understand the potential impacts of future climates and climate extremes on the state's water resources. The objective of this study was to determine potential future climates and climate extremes; and to assess spatial and temporal changes in precipitation (Prec), and minimum and maximum temperature (Tmin and Tmax, respectively), in the Brazos Headwaters Basin under three greenhouse gas emissions scenarios (A2, A1B, and B1) for three future periods: 2020s (2011-2030), 2055s (2046-2065), and 2090s (2080-2099). Daily gridded climate data obtained from Climate Forecast System Reanalysis (CFSR) were used to downscale outputs from 15 General Circulation Models (GCMs) using the Long Ashton Research Station-Weather Generator (LARS-WG) model. Results indicate that basin average Tmin and Tmax will increase; however, annual precipitation will decrease for all periods. Annual precipitation will decrease by up to 5.2% and 6.8% in the 2055s and 2090s, respectively. However, in some locations in the basin, up to a 14% decrease in precipitation is projected in the 2090s under the A2 (high) emissions scenario. Overall, the northwestern and southern part of the Brazos Headwaters Basin will experience greater decreases in precipitation. Moreover, precipitation indices of the number of wet days (prec ≥ 5 mm) and heavy precipitation days (prec ≥ 10 mm) are projected to slightly decrease for all future periods. On the other hand, Tmin and Tmax will increase by 2 and 3 • C on average in the 2055s and 2090s, respectively. Mostly, projected increases in Tmin and Tmax will be in the upper range in the southern and southeastern part of the basin. Temperature indices of frost (Tmin < 0 • C) and ice days (Tmax < 0 • C) are projected to decrease, while tropical nights (Tmin > 20 • C) and summer days (Tmax > 25 • C) are expected to increase. However, while the frequency distribution of meteorological drought shows slight shifts towards the dry range, there was no significant difference between the baseline and projected meteorological drought frequency and severity.

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Section: Performance Of the Lars-wg Modelsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

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Analysis of Potential Future Climate and Climate Extremes in the Brazos Headwaters Basin, Texas

Awal

Bayabil

Fares

2016

Water

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“…LARS-WG performed better in capturing the multimodal peaks seen in observed temperatures and was able to reproduce the observed data for both weather variables (temperature and precipitation) better than the other two generators as observed from the density plots [62]. LARS-WG also had very good representation of the dry and wet day sequences, consistent with [76], and performed well at simulating snow days and precipitation events, making it suitable for hydrologic studies. CLIGEN overestimated the dry sequences and snow days but had the added advantage of simulating a wide range of climate variables (nine, compared with three to four variables for LARS-WG and WeaGETS).…”

Section: Discussionmentioning

confidence: 81%

Comparative Study of Different Stochastic Weather Generators for Long-Term Climate Data Simulation

Mehan

Guo

Gitau

et al. 2017

Climate

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Abstract:Climate is one of the single most important factors affecting watershed ecosystems and water resources. The effect of climate variability and change has been studied extensively in some places; in many places, however, assessments are hampered by limited availability of long-term continuous climate data. Weather generators provide a means of synthesizing long-term climate data that can then be used in natural resource assessments. Given their potential, there is the need to evaluate the performance of the generators; in this study, three commonly used weather generators-CLImate GENerator (CLIGEN), Long Ashton Research Station Weather Generator (LARS-WG), and Weather Generators (WeaGETS) were compared with regard to their ability to capture the essential statistical characteristics of observed data (distribution, occurrence of wet and dry spells, number of snow days, growing season temperatures, and growing degree days). The study was based on observed 1966-2015 weather station data from the Western Lake Erie Basin (WLEB), from which 50 different realizations were generated, each spanning 50 years. Both CLIGEN and LARS-WG performed fairly well with respect to representing the statistical characteristics of observed precipitation and minimum and maximum temperatures, although CLIGEN tended to overestimate values at the extremes. This generator also overestimated dry sequences by 18%-30% and snow-day counts by 12%-19% when considered over the entire WLEB. It (CLIGEN) was, however, well able to simulate parameters specific to crop growth such as growing degree days and had an added advantage over the other generators in that it simulates a larger number of weather variables. LARS-WG overestimated wet sequence counts across the basin by 15%-38%. In addition, the optimal growth period simulated by LARS-WG also exceeded that obtained from observed data by 16%-29% basin-wide. Preliminary results with WeaGETS indicated that additional evaluation is needed to better define its parameters. Results provided insights into the suitability of both CLIGEN and LARS-WG for use with water resource applications.

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“…However, GCMs have relatively coarse space resolution and cannot represent the fine-scale detail that characterises the climate in many regions of the world, especially in regions with complex orography or heterogeneous land surface cover or coastlines. This can makes their climate simulations of limited use in impact studies of climate change on biodiversity, ecosystem services, agricultural systems, species distributions and other landscape and environment related matters (Villegas and Jarvis 2010, Daniels et al 2012, Hassan et al 2013, Xiaoduo et al 2012. These types of impact and adaptation studies require data with much finer spatial resolution.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the performance of CORDEX regional climate models in simulating present climate conditions of Tanzania

Luhunga¹,

Botai²,

Kahimba³

2016

JSHESS

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Regional climate models (RCMs) are widely used in regional assessment of climate change impacts. However, the reliability of individual models needs to be assessed before using their output for impact assessment. In this study, we evaluate the performance of RCMs from the Coordinated Regional Climate Downscaling Experiment program (CORDEX) to simulate minimum air temperature (TN), maximum air temperature (TX) and rainfall over Tanzania. Output from four RCMs driven by boundary conditions from three General Circulation Models (GCMs) and ERA-Interim data are evaluated against observed data from 22 weather stations. The evaluation is based on determining how well the RCMs reproduce climatological trends, interannual, and annual cycles of TN, TX and rainfall. Statistical measures of model performance that include the bias, root mean square error, correlation and trend analysis are used. It is found that RCMs capture the annual cycle of TN, TX and rainfall well, however underestimate and overestimate the amount of rainfall in March-April-May (MAM) and October-November-December (OND) seasons respectively. Most RCMs reproduce interannual variations of TN, TX and rainfall. The source of uncertainties can be analysed when the same RCM is driven by different GCMs and different RCMs driven by same GCM simulate TN, TX and rainfall differently. It is found that the biases and errors from the RCMs and driving GCMs contribute roughly equally. Overall, the evaluation finds reasonable (although variable) model skill in representing mean climate, interannual variability and temperature trends, suggesting the potential use of CORDEX RCMs in simulating TN, TX and rainfall over Tanzania.

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Application of SDSM and LARS-WG for simulating and downscaling of rainfall and temperature

Cited by 168 publications

References 26 publications

Analysis of Potential Future Climate and Climate Extremes in the Brazos Headwaters Basin, Texas

Analysis of Potential Future Climate and Climate Extremes in the Brazos Headwaters Basin, Texas

Comparative Study of Different Stochastic Weather Generators for Long-Term Climate Data Simulation

Evaluation of the performance of CORDEX regional climate models in simulating present climate conditions of Tanzania

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