Evaluation of reanalysis and global meteorological products in Beas river basin of North-Western Himalaya

Bhattacharya, Tanmoyee; Khare, Deepak; Arora, Manohar

doi:10.1186/s40068-020-00186-1

Cited by 21 publications

(10 citation statements)

References 95 publications

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Section: Relationship Between Observation and Reanalysis Datamentioning

confidence: 99%

“…Generally, the reanalysis data are subject to high uncertainty because of the coarse spatial resolution and assimilation of limited observation [49][50][51]. Therefore, before using in further analysis, consistency check between reanalysis and observation data could provide a basic evaluation for the reliability of both datasets [4,50,51]. In the present study, the mean annual cycles of temperature variables (annual mean, maximum and minimum temperatures) were evaluated and correlations between the ERA5 reanalysis data and the observed data at individual stations were analyzed (Figure 3).…”

Section: Relationship Between Observation and Reanalysis Datamentioning

confidence: 99%

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Land Use Land Cover Changes and Their Effects on Surface Air Temperature in Myanmar and Thailand

et al. 2021

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Land use land cover (LULC) change is one of the main drivers contributing to global climate change. It alters surface hydrology and energy balance between the land surface and atmosphere. However, its impacts on surface air temperature have not been well understood in a dynamic region of LULC changes like Southeast Asia (SEA). This study quantitatively examined the contribution of LULC changes to temperature trends in Myanmar and Thailand as the typical parts of SEA during 1990–2019 using the “observation minus reanalysis” (OMR) method. Overall, the average maximum, mean, and minimum temperatures obtained from OMR trends indicate significant warming trends of 0.17 °C/10a, 0.20 °C/10a, and 0.42 °C/10a, respectively. The rates of minimum temperature increase were larger than maximum and mean temperatures. The decreases of forest land and cropland, and the expansions of settlements land fractions were strongly correlated with the observed warming trends. It was found that the effects of forest land converted to settlement land on warming were higher than forest conversion to cropland. A comprehensive discussion on this study could provide scientific information for the future development of more sustainable land use planning to mitigate and adapt to climate change at the local and national levels.

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Section: Relationship Between Observation and Reanalysis Datamentioning

confidence: 99%

Section: Relationship Between Observation and Reanalysis Datamentioning

confidence: 99%

Land Use Land Cover Changes and Their Effects on Surface Air Temperature in Myanmar and Thailand

et al. 2021

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“…It is therefore important to compare datasets from different sources and different providers. A number of such comparisons exist already, but they are typically either focused mostly on observational data (e.g., [2]), include only selected reanalysis and observational datasets (e.g., [18][19][20]), concentrate on specific continental regions such as, for example, the continental U.S. [21], North-Western Himalaya [22], or a river basin in China [23], or focus on selected ocean basins (e.g., the Southern Ocean [24]).…”

Section: Introductionmentioning

confidence: 99%

Comparison of Reanalysis and Observational Precipitation Datasets Including ERA5 and WFDE5

Haßler

Lauer

2021

Atmosphere

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Precipitation is a key component of the hydrological cycle and one of the most important variables in weather and climate studies. Accurate and reliable precipitation data are crucial for determining climate trends and variability. In this study, eleven different precipitation datasets are compared, six reanalysis and five observational datasets, including the reanalysis datasets ERA5 and WFDE5 from the ECMWF family, to quantify the differences between the widely used precipitation datasets and to identify their particular strengths and shortcomings. The comparisons are focused on the common time period 1983 through 2016 and on monthly, seasonal, and inter-annual times scales in regions representing different precipitation regimes, i.e., the Tropics, the Pacific Inter Tropical Convergence Zone (ITCZ), Central Europe, and the South Asian Monsoon region. For the analysis, satellite-gauge precipitation data from the Global Precipitation Climatology Project (GPCP-SG) are used as a reference. The comparison shows that ERA5 and ERA5-Land are a clear improvement over ERA-Interim and show in most cases smaller biases than the other reanalysis datasets (e.g., around 13% high bias in the Tropics compared to 17% for MERRA-2 and 36% for JRA-55). ERA5 agrees well with observations for Central Europe and the South Asian Monsoon region but underestimates very low precipitation rates in the Tropics. In particular, the tropical ocean remains challenging for reanalyses with three out of four products overestimating precipitation rates over the Atlantic and Indian Ocean.

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“…Therefore, due to the sparse distribution of rain gauge networks in the Baro-Akobo basin, a pixel-to-point approach was used to compare gridded RCM data against point rainfall data of the rain gauge observations. Findings in (Bhattacharya and Khare 2020) show that point to pixel approach comparison of observed data with gridded climate data has resulted in good agreement in the Beas River basin of Northwestern Himalaya.…”

Section: Observed Climate Datamentioning

confidence: 95%

Evaluation of the performance of bias-corrected CORDEX regional climate models in reproducing Baro–Akobo basin climate

Mengistu

Woldesenbet

Dile

2021

Theor Appl Climatol

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The applicability of the regional climate model (RCMs) for catchment hydroclimate is obscured due to their systematic bias. As a result, bias correction has become an essential precondition for the study of climate change. This study aimed to evaluate the skill of seven rainfall and five maximum and minimum temperature RCM outputs against observed data in simulating the characteristics of climate at several locations over the Baro-Akobo basin in Ethiopia. The evaluation was performed based on raw and bias-corrected RCMs against observed for a long-term basis. Several statistical metrics were used to compare RCMs against observed using a pixel-to-point approach. In this finding, raw RCMs showed pronounced biases such as lower correlation and higher PBIAS in estimating rainfall and minimum temperature than maximum temperature. However, most RCMs after bias correction showed better performance in reproducing the magnitude and distribution of the mean monthly rainfall and temperature and improve all the statistical metrics. The Mann-Kendall trend test for observed and bias-corrected RCMs indicated a decreasing annual rainfall trend while the maximum and minimum temperature showed an increasing trend in most stations. In most statistical metrics, the ensemble mean resulted in better agreement with observation than individual models in most stations. In general, after bias correction, the ensemble adequately simulates the Baro-Akobo basin climate and can be used for evaluation of future climate projections in the region.

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Evaluation of reanalysis and global meteorological products in Beas river basin of North-Western Himalaya

Cited by 21 publications

References 95 publications

Land Use Land Cover Changes and Their Effects on Surface Air Temperature in Myanmar and Thailand

Land Use Land Cover Changes and Their Effects on Surface Air Temperature in Myanmar and Thailand

Comparison of Reanalysis and Observational Precipitation Datasets Including ERA5 and WFDE5

Evaluation of the performance of bias-corrected CORDEX regional climate models in reproducing Baro–Akobo basin climate

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