Regional mean and variability characteristics of temperature and precipitation over Thailand in 1961–2000 by a regional climate model and their evaluation

Torsri, Kritanai; Octaviani, Mega; Manomaiphiboon, Kasemsan; Towprayoon, Sirintornthep

doi:10.1007/s00704-012-0782-z

Cited by 19 publications

(23 citation statements)

References 33 publications

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“…Previous regional climate downscaling simulations over Thailand have used a single GCM and single RCM; hence the outcomes provided limited use for climate change impact assessments (e.g., Chotamonsak et al, 2011;Champathong et al, 2013;Manomaiphiboon et al, 2013;Torsri et al, 2013;Masud et al, 2016). While some impact assessments at the basin scale have relied on coarse GCM products (e.g., Supharatid, 2016;Supharatid et al, 2016), these studies would be constrained by the limited ability of GCMs to resolve local and basin scale climate processes (e.g., Troin et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Projected future changes in mean precipitation over Thailand based on multi‐model regional climate simulations of CORDEX Southeast Asia

Tangang

Juneng

Salimun

et al. 2019

Intl Journal of Climatology

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This paper highlights detailed projected changes in rainfall over Thailand for the early (2011–2040), middle (2041–2070) and late (2071–2099) periods of the 21st century under the representative concentration pathways (RCP) 4.5 and RCP 8.5 using the high‐resolution multi‐model simulations of the Coordinated Regional Climate Downscaling Experiment (CORDEX) Southeast Asia. The ensemble mean is calculated based on seven members consisting of six general circulation models (GCMs) and three regional climate models (RCMs). Generally, the ensemble mean precipitation agrees reasonably well with observations, best represented by the Global Precipitation Climatology Center (GPCC) data, over Thailand during the historical period (1976–2005). However, inter‐model variations can be large among ensemble members especially during dry months (December to March) for northern‐central‐eastern parts, and throughout the year for the southern parts of Thailand. Similarly for future projection periods, inter‐model variations in the sign and magnitude of changes exist. The ensemble means of projected changes in rainfall for both RCPs during dry months show distinct contrast between the northern‐central‐eastern parts and the southern parts of Thailand with generally wetter and drier conditions, respectively. The magnitude of change can be as high as 15% of the historical period, which varies depending on the sub‐region, season, projection period, and RCP scenario. In contrast, generally drier conditions are projected during the wet season (June to September) throughout the country for both RCPs where the rainfall reduction can be as high as 10% in some areas. However, the magnitude of projected rainfall changes of some individual models can be much larger than the ensemble means, exceeding 40% in some cases. These projected changes are related to the changes in regional circulations associated with the winter and summer monsoons, which are projected to weaken. The drier (wetter) condition is associated with the enhanced subsidence (rising motion).

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Section: Introductionmentioning

confidence: 99%

Projected future changes in mean precipitation over Thailand based on multi‐model regional climate simulations of CORDEX Southeast Asia

Tangang

Juneng

Salimun

et al. 2019

Intl Journal of Climatology

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“…() and Torsri et al . () where the KZ filter was used and tested for separating the three timescales. The same periods were used as limits for the FFT filter.…”

Section: Methodsmentioning

confidence: 99%

“…The periods less than the above mentioned limits (33 days and 1.7 years) have been completely removed from time series using KZ in settings KZ(15,5) and KZ(365,3), respectively. The KZ parameters and limits of periods for separating individual components were taken from studies by Eskridge et al (1997) and Torsri et al (2013) where the KZ filter was used and tested for separating the three timescales. The same periods were used as limits for the FFT filter.…”

Section: Methodsmentioning

confidence: 99%

“…The evaluation of how climate models represent variances on individual timescales together with the usually assessed total variances could provide more useful information. This evaluation reflects the ability of the model and its physics parameterizations to reproduce the variability due to processes associated with individual timescales (Torsri et al, 2013). Such evaluation may provide a mean for evaluation of the underlying physical processes in the models.…”

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confidence: 99%

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Temperature and precipitation variability in regional climate models and driving global climate models: Total variance and its temporal‐scale components

Crhová

Holtanová

2018

Intl Journal of Climatology

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This paper presents an evaluation of the variability and its temporal‐scale components of daily air temperature and precipitation simulated by two regional climate models (RCMs) and two driving global climate models (GCMs) from the EURO‐CORDEX and CMIP5 projects. The analysis was performed for eight geographical areas of central Europe for the period 1971–2000. After a brief evaluation of total variance, we focus on the ability of the simulations to represent short‐term, seasonal and long‐term variability components. This analysis was carried out for original time series as well as for series with the annual cycle removed. A fast Fourier transformation and a Kolmogorov–Zurbenko filter were used to separate the three temporal components. The two methods of time series decomposition generally agree, which confirms the robustness of the results. Although the observed total variability of daily air temperature and precipitation is not well represented in many cases and considerable differences among simulations exist, the separation of total variance into the three components is well represented. Regarding the air temperature, the results for the time series with the annual cycle removed are generally somewhat worse than for original series. The simulations tend to underestimate the short‐term component of temperature variability, while the results for the other two components are inconclusive. Moreover, it was found that temperature variability caused by the annual cycle is overestimated by the simulation of HadGEM2 GCM and CCLM4‐8‐17 RCM driven by HadGEM2, which explains the relatively poor results of these simulations regarding air temperature total variance and short‐term as well as seasonal components in the original temperature series. The RCMs provide better results than GCMs for temperature total variance but our results are rather inconclusive in the case of precipitation total variance and distribution of the variance of both studied variables into the three temporal components.

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“…The uncertainties associated with global reanalysis data or simulated output from the atmosphere-ocean global circulation models (GCMs), hydrological processes models and land surface models (HPMs and LSMs) to predict terrestrial water and energy balance [1,2], have been usually evaluated by means of multiple statistical indicators, such as the efficiency, skewness, and the mean quadratic error [3,4]. The most appropriate calibration models are based on error minimization under the hypothesis that the only source of error in measurements is Gaussian type.…”

Section: Introductionmentioning

confidence: 99%

Estimating Potential Evapotranspiration by Missing Temperature Data Reconstruction

Ventura-Ramos

Trinidad

Júnez-Ferreira

et al. 2015

Journal of Applied Mathematics

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This work studies the statistical characteristics of potential evapotranspiration calculations and their relevance within the water balance used to determine water availability in hydrological basins. The purpose of this study was as follows: first, to apply a missing data reconstruction scheme in weather stations of the Rio Queretaro basin; second, to reduce the generated uncertainty of temperature data: mean, minimum, and maximum values in the evapotranspiration calculation which has a paramount importance in the manner of obtaining the water balance at any hydrological basin. The reconstruction of missing data was carried out in three steps: (1) application of a 4-parameter sinusoidal type regression to temperature data, (2) linear regression to residuals to obtain a regional behavior, and (3) estimation of missing temperature values for a certain year and during a certain season within the basin under study; estimated and observed temperature values were compared. Finally, using the obtained temperature values, the methods of Hamon, Papadakis, Blaney and Criddle, Thornthwaite, and Hargreaves were employed to calculate potential evapotranspiration that was compared to the real observed values in weather stations. With the results obtained from the application of this procedure, the surface water balance was corrected for the case study.

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Regional mean and variability characteristics of temperature and precipitation over Thailand in 1961–2000 by a regional climate model and their evaluation

Cited by 19 publications

References 33 publications

Projected future changes in mean precipitation over Thailand based on multi‐model regional climate simulations of CORDEX Southeast Asia

Projected future changes in mean precipitation over Thailand based on multi‐model regional climate simulations of CORDEX Southeast Asia

Temperature and precipitation variability in regional climate models and driving global climate models: Total variance and its temporal‐scale components

Estimating Potential Evapotranspiration by Missing Temperature Data Reconstruction

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