Articles | Volume 22, issue 6
https://doi.org/10.5194/hess-22-3435-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-22-3435-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
27 Jun 2018
Research article |
| 27 Jun 2018
| 27 Jun 2018
Geostatistical assessment of warm-season precipitation observations in Korea based on the composite precipitation and satellite water vapor data
Sojung Park
Department of Climate and Energy Systems Engineering, Ewha Womans University, Seoul, Republic of Korea
Severe Storm Research Center, Ewha Womans University, Seoul, Republic of Korea
Center for Climate/Environment Change Prediction Research, Ewha Womans University, Seoul, Republic of Korea
Department of Climate and Energy Systems Engineering, Ewha Womans University, Seoul, Republic of Korea
Department of Environmental Science and Engineering, Ewha Womans University, Seoul, Republic of Korea
Severe Storm Research Center, Ewha Womans University, Seoul, Republic of Korea
Center for Climate/Environment Change Prediction Research, Ewha Womans University, Seoul, Republic of Korea
Jeung Whan Lee
Korea Meteorological Administration, Seoul, Republic of Korea
Yunho Park
Korea Meteorological Administration, Seoul, Republic of Korea
Related authors
Sojung Park and Seon K. Park
Geosci. Model Dev., 14, 6241–6255, https://doi.org/10.5194/gmd-14-6241-2021, https://doi.org/10.5194/gmd-14-6241-2021, 2021
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One of the biggest uncertainties in numerical weather predictions (NWPs) comes from treating subgrid-scale physical processes. Physical processes, such as cumulus, microphysics, and planetary boundary layer processes, are parameterized in NWP models by empirical and theoretical backgrounds. We developed an interface between a micro-genetic algorithm and the WRF model for a combinatorial optimization of physics for heavy rainfall events in Korea. The system improved precipitation forecasts.
Sojung Park and Seon Ki Park
Geosci. Model Dev., 9, 1073–1085, https://doi.org/10.5194/gmd-9-1073-2016, https://doi.org/10.5194/gmd-9-1073-2016, 2016
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Snow albedo varies with snow grain size, snow cover thickness, etc. It also depends on the spatial characteristics of land cover and on the canopy density and structure. The Noah-MP model shows a bias error of albedo in winter due to no proper reflection of the vegetation effect. We developed new parameters, called leaf index and stem index, which reflect the vegetation effect on winter albedo. The Noah-MP's performance in albedo has prominently improved with about 69 % decrease in the RMSE.
Sungmin O, Ji Won Yoon, and Seon Ki Park
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-142, https://doi.org/10.5194/amt-2024-142, 2024
Preprint under review for AMT
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Air pollutants such as PM10 or PM2.5 can cause adverse public health and environment effects, therefore their regular monitoring is crucial to keep the pollutant concentrations under control. Our study demonstrates the potential of high-resolution aerosol optical depth (AOD) data from the Geostationary Environment Monitoring Spectrometer (GEMS) satellite to estimate ground-level PM concentrations using a machine learning model.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-114, https://doi.org/10.5194/gmd-2024-114, 2024
Preprint under review for GMD
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This study evaluates the WRF-Chem model's prediction of a mega Asian Dust Storms (ADSs) over South Korea on March 28–29, 2021. We assessed five dust emission and four land surface schemes for predicting ADSs. Using surface observations and remote sensing data, we examined variables, such as temperature, humidity, wind speed, PM10, and aerosol optical depth. The UoC04 dust emission and CLM4 land surface scheme combination reduced RMSE for PM10 by up to 29.6 %, showing the best performance.
Sujeong Lim, Seon Ki Park, and Claudio Cassardo
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-28, https://doi.org/10.5194/gmd-2023-28, 2023
Revised manuscript not accepted
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The ensembles in the numerical weather prediction system are under-dispersed near the land surface; therefore, an inflation method is required to increase it. In this study, we perturbed soil temperature and soil moisture to represent the near-surface uncertainty. Perturbations were obtained by the optimization algorithm taking into account diurnal variations in soil states. Consequently, it indirectly inflated the temperature and water vapor mixing ratio in the planetary boundary layer.
Sujeong Lim, Hyeon-Ju Gim, Ebony Lee, Seungyeon Lee, Won Young Lee, Yong Hee Lee, Claudio Cassardo, and Seon Ki Park
Geosci. Model Dev., 15, 8541–8559, https://doi.org/10.5194/gmd-15-8541-2022, https://doi.org/10.5194/gmd-15-8541-2022, 2022
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The land surface model (LSM) contains various uncertain parameters, which are obtained by the empirical relations reflecting the specific local region and can be a source of uncertainty. To seek the optimal parameter values in the snow-related processes of the Noah LSM over South Korea, we have implemented an optimization algorithm, a micro-genetic algorithm using the observations. As a result, the optimized snow parameters improve snowfall prediction.
Won Young Lee, Hyeon-Ju Gim, and Seon Ki Park
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-319, https://doi.org/10.5194/tc-2021-319, 2021
Manuscript not accepted for further review
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Snow cover or snow albedo plays a vital role in the atmosphere and land surface interaction. Especially, direct observation of snow is difficult and scarce. That's why a reliable Land Surface Model (LSM), including snow physical processes, is significant. In this study, we tried to give meaningful insights for improving the LSM in the future by identifying the main variables or parameters used and examining the different formulas for snow-related processes of the eight LSMs.
Sojung Park and Seon K. Park
Geosci. Model Dev., 14, 6241–6255, https://doi.org/10.5194/gmd-14-6241-2021, https://doi.org/10.5194/gmd-14-6241-2021, 2021
Short summary
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One of the biggest uncertainties in numerical weather predictions (NWPs) comes from treating subgrid-scale physical processes. Physical processes, such as cumulus, microphysics, and planetary boundary layer processes, are parameterized in NWP models by empirical and theoretical backgrounds. We developed an interface between a micro-genetic algorithm and the WRF model for a combinatorial optimization of physics for heavy rainfall events in Korea. The system improved precipitation forecasts.
Da-Eun Kim and Seon Ki Park
The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-15, https://doi.org/10.5194/tc-2019-15, 2019
Preprint withdrawn
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An accurate prediction of the Eurasian snow is essentially important in predicting the climate and weather phenomena in Asia. Regional climate models are mostly coupled with several land surface models (LSMs) in which the land surface process parameters are calculated under their own physical principles and parameterization schemes. We show that prediction of the Eurasian snow cover is sensitive to the choice of LSMs coupled to regional climate models, and hence the future climate projections.
Claudio Cassardo, Seon Ki Park, Marco Galli, and Sungmin O
Hydrol. Earth Syst. Sci., 22, 3331–3350, https://doi.org/10.5194/hess-22-3331-2018, https://doi.org/10.5194/hess-22-3331-2018, 2018
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Temperature and precipitation can have abnormal states due to climate change and exert a significant impact on the regional hydrologic cycle. We assess the hydrologic component changes in the Alps and northern Italy, on the basis of regional future climate (FC) conditions, using the UTOPIA land surface model. The annual mean number of dry (wet) days increase remarkably (slightly) in FCs, thus increasing the risk of severe droughts and slightly increasing the risk of floods coincidently.
Sojung Park and Seon Ki Park
Geosci. Model Dev., 9, 1073–1085, https://doi.org/10.5194/gmd-9-1073-2016, https://doi.org/10.5194/gmd-9-1073-2016, 2016
Short summary
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Snow albedo varies with snow grain size, snow cover thickness, etc. It also depends on the spatial characteristics of land cover and on the canopy density and structure. The Noah-MP model shows a bias error of albedo in winter due to no proper reflection of the vegetation effect. We developed new parameters, called leaf index and stem index, which reflect the vegetation effect on winter albedo. The Noah-MP's performance in albedo has prominently improved with about 69 % decrease in the RMSE.
J. Kim and S. K. Park
Hydrol. Earth Syst. Sci., 20, 651–658, https://doi.org/10.5194/hess-20-651-2016, https://doi.org/10.5194/hess-20-651-2016, 2016
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This study examined the uncertainty in climatological precipitation in East Asia, calculated from five gridded analysis data sets based on in situ rain gauge observations from 1980 to 2007. It is found that the regions of large uncertainties are typically lightly populated and are characterized by severe terrain and/or very high elevations. Thus, care must be taken in using long-term trends calculated from gridded precipitation analysis data for climate studies over such regions in East Asia.
S. Lim, S. K. Park, and M. Zupanski
Atmos. Chem. Phys., 15, 10019–10031, https://doi.org/10.5194/acp-15-10019-2015, https://doi.org/10.5194/acp-15-10019-2015, 2015
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In this study, the impact of O3 observations on the tropical cyclone (TC) structure is examined using the WRF-Chem with an ensemble-based data assimilation (DA) system. For a TC case that occurred over East Asia, the ensemble forecast is reasonable and the O3 assimilation affects both chemical and atmospheric variables near the TC area. All measures indicate a positive impact of DA on the analysis – the cost function and root mean square error have decreased by 16.9% and 8.87%, respectively.
S. K. Park, S. Lim, and M. Zupanski
Geosci. Model Dev., 8, 1315–1320, https://doi.org/10.5194/gmd-8-1315-2015, https://doi.org/10.5194/gmd-8-1315-2015, 2015
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The structure of an ensemble-based coupled atmosphere-chemistry forecast error covariance is examined using the WRF-Chem, a coupled atmosphere-chemistry model. It is found that the coupled error covariance has important cross-variable components that allow a physically meaningful adjustment of all control variables. Additional benefit of the coupled error covariance is that a cross-component impact is allowed; e.g., atmospheric observations can exert impact on chemistry analysis, and vice versa.
S. Hong, X. Yu, S. K. Park, Y.-S. Choi, and B. Myoung
Geosci. Model Dev., 7, 2517–2529, https://doi.org/10.5194/gmd-7-2517-2014, https://doi.org/10.5194/gmd-7-2517-2014, 2014
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Mathematical applications
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Past, present and future rainfall erosivity in central Europe based on convection-permitting climate simulations
The most extreme rainfall erosivity event ever recorded in China up to 2022: the 7.20 storm in Henan Province
The role of atmospheric rivers in the distribution of heavy precipitation events over North America
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Projected changes in droughts and extreme droughts in Great Britain strongly influenced by the choice of drought index
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Rainfall pattern analysis in 24 East Asian megacities using a complex network
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Analysis of flash droughts in China using machine learning
Performance-based comparison of regionalization methods to improve the at-site estimates of daily precipitation
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The 2018 northern European hydrological drought and its drivers in a historical perspective
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Emerging climate signals in the Lena River catchment: a non-parametric statistical approach
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Investigating water budget dynamics in 18 river basins across the Tibetan Plateau through multiple datasets
Does the GPM mission improve the systematic error component in satellite rainfall estimates over TRMM? An evaluation at a pan-India scale
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Yuka Muto and Shunji Kotsuki
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It is crucial to improve global precipitation estimates for understanding water-related disasters and water resources. This study proposes a new methodology to interpolate global precipitation fields from ground rain gauge observations using ensemble data assimilation and the precipitation of a numerical weather prediction model. Our estimates agree with independent rain gauge observations better than the existing precipitation estimates, especially in mountainous or rain-gauge-sparse regions.
Yan Li, Bo Huang, and Henning W. Rust
Hydrol. Earth Syst. Sci., 28, 321–339, https://doi.org/10.5194/hess-28-321-2024, https://doi.org/10.5194/hess-28-321-2024, 2024
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The inconsistent changes in temperature and precipitation induced by forest cover change are very likely to affect drought condition. We use a set of statistical models to explore the relationship between forest cover change and drought change in different timescales and climate zones. We find that the influence of forest cover on droughts varies under different precipitation and temperature quantiles. Forest cover also could modulate the impacts of precipitation and temperature on drought.
Magdalena Uber, Michael Haller, Christoph Brendel, Gudrun Hillebrand, and Thomas Hoffmann
Hydrol. Earth Syst. Sci., 28, 87–102, https://doi.org/10.5194/hess-28-87-2024, https://doi.org/10.5194/hess-28-87-2024, 2024
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We calculated past, present and future rainfall erosivity in central Europe from high-resolution precipitation data (3 km and 1 h) generated by the COSMO-CLM convection-permitting climate model. Future rainfall erosivity can be up to 84 % higher than it was in the past. Such increases are much higher than estimated previously from regional climate model output. Convection-permitting simulations have an enormous and, to date, unexploited potential for the calculation of future rainfall erosivity.
Yuanyuan Xiao, Shuiqing Yin, Bofu Yu, Conghui Fan, Wenting Wang, and Yun Xie
Hydrol. Earth Syst. Sci., 27, 4563–4577, https://doi.org/10.5194/hess-27-4563-2023, https://doi.org/10.5194/hess-27-4563-2023, 2023
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An exceptionally heavy rainfall event occurred on 20 July 2021 in central China (the 7.20 storm). The storm presents a rare opportunity to examine the extreme rainfall erosivity. The storm, with an average recurrence interval of at least 10 000 years, was the largest in terms of its rainfall erosivity on record over the past 70 years in China. The study suggests that extreme erosive events can occur anywhere in eastern China and are not necessarily concentrated in low latitudes.
Sara M. Vallejo-Bernal, Frederik Wolf, Niklas Boers, Dominik Traxl, Norbert Marwan, and Jürgen Kurths
Hydrol. Earth Syst. Sci., 27, 2645–2660, https://doi.org/10.5194/hess-27-2645-2023, https://doi.org/10.5194/hess-27-2645-2023, 2023
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Jiqing Li, Jing Huang, Lei Zheng, and Wei Zheng
Hydrol. Earth Syst. Sci., 27, 2325–2339, https://doi.org/10.5194/hess-27-2325-2023, https://doi.org/10.5194/hess-27-2325-2023, 2023
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Under the joint action of climate–human activities the use of runoff data whose mathematical properties have changed has become the key to watershed management. To determine whether the data have been changed, the number and the location of changes, we proposed a change-point detection framework. The problem of determining the parameters of wavelet transform has been solved by comparing the accuracy of identifying change points. This study helps traditional models adapt to environmental changes.
Nele Reyniers, Timothy J. Osborn, Nans Addor, and Geoff Darch
Hydrol. Earth Syst. Sci., 27, 1151–1171, https://doi.org/10.5194/hess-27-1151-2023, https://doi.org/10.5194/hess-27-1151-2023, 2023
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In an analysis of future drought projections for Great Britain based on the Standardised Precipitation Index and the Standardised Precipitation Evapotranspiration Index, we show that the choice of drought indicator has a decisive influence on the resulting projected changes in drought characteristics, although both result in increased drying. This highlights the need to understand the interplay between increasing atmospheric evaporative demand and drought impacts under a changing climate.
Dipanjan Dey, Aitor Aldama Campino, and Kristofer Döös
Hydrol. Earth Syst. Sci., 27, 481–493, https://doi.org/10.5194/hess-27-481-2023, https://doi.org/10.5194/hess-27-481-2023, 2023
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One of the most striking and robust features of climate change is the acceleration of the atmospheric water cycle branch. Earlier studies were able to provide a quantification of the global atmospheric water cycle, but they missed addressing the atmospheric water transport connectivity within and between ocean basins and land. These shortcomings were overcome in the present study and presented a complete synthesised and quantitative view of the atmospheric water cycle.
Abbas El Hachem, Jochen Seidel, Florian Imbery, Thomas Junghänel, and András Bárdossy
Hydrol. Earth Syst. Sci., 26, 6137–6146, https://doi.org/10.5194/hess-26-6137-2022, https://doi.org/10.5194/hess-26-6137-2022, 2022
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Through this work, a methodology to identify outliers in intense precipitation data was presented. The results show the presence of several suspicious observations that strongly differ from their surroundings. Many identified outliers did not have unusually high values but disagreed with their neighboring values at the corresponding time steps. Weather radar and discharge data were used to distinguish between single events and false observations.
Qihua Ran, Jin Wang, Xiuxiu Chen, Lin Liu, Jiyu Li, and Sheng Ye
Hydrol. Earth Syst. Sci., 26, 4919–4931, https://doi.org/10.5194/hess-26-4919-2022, https://doi.org/10.5194/hess-26-4919-2022, 2022
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This study aims to further evaluate the relative importance of antecedent soil moisture and rainfall on flood generation and the controlling factors. The relative importance of antecedent soil moisture and daily rainfall present a significant correlation with drainage area; the larger the watershed, and the more essential the antecedent soil saturation rate is in flood generation, the less important daily rainfall will be.
Kyunghun Kim, Jaewon Jung, Hung Soo Kim, Masahiko Haraguchi, and Soojun Kim
Hydrol. Earth Syst. Sci., 26, 4823–4836, https://doi.org/10.5194/hess-26-4823-2022, https://doi.org/10.5194/hess-26-4823-2022, 2022
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This study applied a new methodology (complex network), instead of using classic methods, to establish the relationships between rainfall events in large East Asian cities. The relationships show that western China and Southeast Asia have a lot of influence on each other. Moreover, it is confirmed that the relationships arise from the effect of the East Asian monsoon. In future, complex network may be able to be applied to analyze the concurrent relationships between extreme rainfall events.
Haijiang Wu, Xiaoling Su, Vijay P. Singh, Te Zhang, Jixia Qi, and Shengzhi Huang
Hydrol. Earth Syst. Sci., 26, 3847–3861, https://doi.org/10.5194/hess-26-3847-2022, https://doi.org/10.5194/hess-26-3847-2022, 2022
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Agricultural drought forecasting lies at the core of overall drought risk management and is critical for food security and drought early warning. Using three-dimensional scenarios, we attempted to compare the agricultural drought forecast performance of a canonical vine copula (3C-vine) model and meta-Gaussian (MG) model over China. The findings show that the 3C-vine model exhibits more skill than the MG model when using 1– to 3-month lead times for forecasting agricultural drought.
Linqi Zhang, Yi Liu, Liliang Ren, Adriaan J. Teuling, Ye Zhu, Linyong Wei, Linyan Zhang, Shanhu Jiang, Xiaoli Yang, Xiuqin Fang, and Hang Yin
Hydrol. Earth Syst. Sci., 26, 3241–3261, https://doi.org/10.5194/hess-26-3241-2022, https://doi.org/10.5194/hess-26-3241-2022, 2022
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In this study, three machine learning methods displayed a good detection capacity of flash droughts. The RF model was recommended to estimate the depletion rate of soil moisture and simulate flash drought by considering the multiple meteorological variable anomalies in the adjacent time to drought onset. The anomalies of precipitation and potential evapotranspiration exhibited a stronger synergistic but asymmetrical effect on flash droughts compared to slowly developing droughts.
Abubakar Haruna, Juliette Blanchet, and Anne-Catherine Favre
Hydrol. Earth Syst. Sci., 26, 2797–2811, https://doi.org/10.5194/hess-26-2797-2022, https://doi.org/10.5194/hess-26-2797-2022, 2022
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Reliable prediction of floods depends on the quality of the input data such as precipitation. However, estimation of precipitation from the local measurements is known to be difficult, especially for extremes. Regionalization improves the estimates by increasing the quantity of data available for estimation. Here, we compare three regionalization methods based on their robustness and reliability. We apply the comparison to a dense network of daily stations within and outside Switzerland.
András Bárdossy, Jochen Seidel, and Abbas El Hachem
Hydrol. Earth Syst. Sci., 25, 583–601, https://doi.org/10.5194/hess-25-583-2021, https://doi.org/10.5194/hess-25-583-2021, 2021
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In this study, the applicability of data from private weather stations (PWS) for precipitation interpolation was investigated. Due to unknown errors and biases in these observations, a two-step filter was developed that uses indicator correlations and event-based spatial precipitation patterns. The procedure was tested and cross validated for the state of Baden-Württemberg (Germany). The biggest improvement is achieved for the shortest time aggregations.
Sigrid J. Bakke, Monica Ionita, and Lena M. Tallaksen
Hydrol. Earth Syst. Sci., 24, 5621–5653, https://doi.org/10.5194/hess-24-5621-2020, https://doi.org/10.5194/hess-24-5621-2020, 2020
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This study provides an in-depth analysis of the 2018 northern European drought. Large parts of the region experienced 60-year record-breaking temperatures, linked to high-pressure systems and warm surrounding seas. Meteorological drought developed from May and, depending on local conditions, led to extreme low flows and groundwater drought in the following months. The 2018 event was unique in that it affected most of Fennoscandia as compared to previous droughts.
Bo Dan, Xiaogu Zheng, Guocan Wu, and Tao Li
Hydrol. Earth Syst. Sci., 24, 5187–5201, https://doi.org/10.5194/hess-24-5187-2020, https://doi.org/10.5194/hess-24-5187-2020, 2020
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Data assimilation is a procedure to generate an optimal combination of the state variable in geoscience, based on the model outputs and observations. The ensemble Kalman filter (EnKF) scheme is a widely used assimilation method in soil moisture estimation. This study proposed several modifications of EnKF for improving this assimilation. The study shows that the quality of the assimilation result is improved, while the degree of water budget imbalance is reduced.
Eric Pohl, Christophe Grenier, Mathieu Vrac, and Masa Kageyama
Hydrol. Earth Syst. Sci., 24, 2817–2839, https://doi.org/10.5194/hess-24-2817-2020, https://doi.org/10.5194/hess-24-2817-2020, 2020
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Existing approaches to quantify the emergence of climate change require several user choices that make these approaches less objective. We present an approach that uses a minimum number of choices and showcase its application in the extremely sensitive, permafrost-dominated region of eastern Siberia. Designed as a Python toolbox, it allows for incorporating climate model, reanalysis, and in situ data to make use of numerous existing data sources and reduce uncertainties in obtained estimates.
Eva Mekis, Ronald E. Stewart, Julie M. Theriault, Bohdan Kochtubajda, Barrie R. Bonsal, and Zhuo Liu
Hydrol. Earth Syst. Sci., 24, 1741–1761, https://doi.org/10.5194/hess-24-1741-2020, https://doi.org/10.5194/hess-24-1741-2020, 2020
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This article provides a Canada-wide analysis of near-0°C temperature conditions (±2°C) using hourly surface temperature and precipitation type observations from 92 locations for the 1981–2011 period. Higher annual occurrences were found in Atlantic Canada, although high values also occur in other regions. Trends of most indicators show little or no change despite a systematic warming over Canada. A higher than expected tendency for near-0°C conditions was also found at some stations.
Jianjun Zhang, Guangyao Gao, Bojie Fu, Cong Wang, Hoshin V. Gupta, Xiaoping Zhang, and Rui Li
Hydrol. Earth Syst. Sci., 24, 809–826, https://doi.org/10.5194/hess-24-809-2020, https://doi.org/10.5194/hess-24-809-2020, 2020
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We proposed an approach that integrates universal multifractals and a segmentation algorithm to precisely identify extreme precipitation (EP) and assess spatiotemporal EP variation over the Loess Plateau, using daily data. Our results explain how EP contributes to the widely distributed severe natural hazards. These findings are of great significance for ecological management in the Loess Plateau. Our approach is also helpful for spatiotemporal EP assessment at the regional scale.
Tongtiegang Zhao, Wei Zhang, Yongyong Zhang, Zhiyong Liu, and Xiaohong Chen
Hydrol. Earth Syst. Sci., 24, 1–16, https://doi.org/10.5194/hess-24-1-2020, https://doi.org/10.5194/hess-24-1-2020, 2020
Guoxiao Wei, Xiaoying Zhang, Ming Ye, Ning Yue, and Fei Kan
Hydrol. Earth Syst. Sci., 23, 2877–2895, https://doi.org/10.5194/hess-23-2877-2019, https://doi.org/10.5194/hess-23-2877-2019, 2019
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Accurately evaluating evapotranspiration (ET) is a critical challenge in improving hydrological process modeling. Here we evaluated four ET models (PM, SW, PT–FC, and AA) under the Bayesian framework. Our results reveal that the SW model has the best performance. This is in part because the SW model captures the main physical mechanism in ET; the other part is that the key parameters, such as the extinction factor, could be well constrained with observation data.
Chongli Di, Tiejun Wang, Xiaohua Yang, and Siliang Li
Hydrol. Earth Syst. Sci., 22, 5069–5079, https://doi.org/10.5194/hess-22-5069-2018, https://doi.org/10.5194/hess-22-5069-2018, 2018
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The original Grassberger–Procaccia algorithm for complex analysis was modified by incorporating the normal-based K-means clustering technique and the RANSAC algorithm. The calculation accuracy of the proposed method was shown to outperform traditional algorithms. The proposed algorithm was used to diagnose climate system complexity in the Hai He basin. The spatial patterns of the complexity of precipitation and air temperature reflected the influence of the dominant climate system.
César Cisneros Vaca, Christiaan van der Tol, and Chandra Prasad Ghimire
Hydrol. Earth Syst. Sci., 22, 3701–3719, https://doi.org/10.5194/hess-22-3701-2018, https://doi.org/10.5194/hess-22-3701-2018, 2018
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The influence of long-term changes in canopy structure on rainfall interception loss was studied in a 55-year old forest. Interception loss was similar at the same site (38 %), when the forest was 29 years old. In the past, the forest was denser and had a higher storage capacity, but the evaporation rates were lower. We emphasize the importance of quantifying downward sensible heat flux and heat release from canopy biomass in tall forest in order to improve the quantification of evaporation.
Wenbin Liu, Fubao Sun, Yanzhong Li, Guoqing Zhang, Yan-Fang Sang, Wee Ho Lim, Jiahong Liu, Hong Wang, and Peng Bai
Hydrol. Earth Syst. Sci., 22, 351–371, https://doi.org/10.5194/hess-22-351-2018, https://doi.org/10.5194/hess-22-351-2018, 2018
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The dynamics of basin-scale water budgets over the Tibetan Plateau (TP) are not well understood nowadays due to the lack of hydro-climatic observations. In this study, we investigate seasonal cycles and trends of water budget components (e.g. precipitation P, evapotranspiration ET and runoff Q) in 18 TP river basins during the period 1982–2011 through the use of multi-source datasets (e.g. in situ observations, satellite retrievals, reanalysis outputs and land surface model simulations).
Harsh Beria, Trushnamayee Nanda, Deepak Singh Bisht, and Chandranath Chatterjee
Hydrol. Earth Syst. Sci., 21, 6117–6134, https://doi.org/10.5194/hess-21-6117-2017, https://doi.org/10.5194/hess-21-6117-2017, 2017
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High-quality satellite precipitation forcings have provided a viable alternative to hydrologic modeling in data-scarce regions. Ageing TRMM sensors have recently been upgraded to GPM, promising enhanced spatio-temporal resolutions. Statistical and hydrologic evaluation of GPM measurements across 86 Indian river basins revealed improved low rainfall estimates with reduced effects of climatology and topography.
James C. Bennett, Quan J. Wang, David E. Robertson, Andrew Schepen, Ming Li, and Kelvin Michael
Hydrol. Earth Syst. Sci., 21, 6007–6030, https://doi.org/10.5194/hess-21-6007-2017, https://doi.org/10.5194/hess-21-6007-2017, 2017
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We assess a new streamflow forecasting system in Australia. The system is designed to meet the need of water agencies for 12-month forecasts. The forecasts perform well in a wide range of rivers. Forecasts for shorter periods (up to 6 months) are generally informative. Forecasts sometimes did not perform well in a few very dry rivers. We test several techniques for improving streamflow forecasts in drylands, with mixed success.
Konrad Bogner, Katharina Liechti, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 21, 5493–5502, https://doi.org/10.5194/hess-21-5493-2017, https://doi.org/10.5194/hess-21-5493-2017, 2017
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The enhanced availability of many different weather prediction systems nowadays makes it very difficult for flood and water resource managers to choose the most reliable and accurate forecast. In order to circumvent this problem of choice, different approaches for combining this information have been applied at the Sihl River (CH) and the results have been verified. The outcome of this study highlights the importance of forecast combination in order to improve the quality of forecast systems.
Matthew B. Switanek, Peter A. Troch, Christopher L. Castro, Armin Leuprecht, Hsin-I Chang, Rajarshi Mukherjee, and Eleonora M. C. Demaria
Hydrol. Earth Syst. Sci., 21, 2649–2666, https://doi.org/10.5194/hess-21-2649-2017, https://doi.org/10.5194/hess-21-2649-2017, 2017
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The commonly used bias correction method called quantile mapping assumes a constant function of error correction values between modeled and observed distributions. Our article finds that this function cannot be assumed to be constant. We propose a new bias correction method, called scaled distribution mapping, that does not rely on this assumption. Furthermore, the proposed method more explicitly accounts for the frequency of rain days and the likelihood of individual events.
Tesfay G. Gebremicael, Yasir A. Mohamed, Pieter v. Zaag, and Eyasu Y. Hagos
Hydrol. Earth Syst. Sci., 21, 2127–2142, https://doi.org/10.5194/hess-21-2127-2017, https://doi.org/10.5194/hess-21-2127-2017, 2017
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This study was conducted to understand the spatio-temporal variations of streamflow in the Tekezē basin. Results showed rainfall over the basin did not significantly change. However, streamflow experienced high variabilities at seasonal and annual scales. Further studies are needed to verify hydrological changes by identifying the physical mechanisms behind those changes. Findings are useful as prerequisite for studying the effects of catchment management dynamics on the hydrological processes.
Louise Crochemore, Maria-Helena Ramos, Florian Pappenberger, and Charles Perrin
Hydrol. Earth Syst. Sci., 21, 1573–1591, https://doi.org/10.5194/hess-21-1573-2017, https://doi.org/10.5194/hess-21-1573-2017, 2017
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The use of general circulation model outputs for streamflow forecasting has developed in the last decade. In parallel, traditional streamflow forecasting is commonly based on historical data. This study investigates the impact of conditioning historical data based on circulation model precipitation forecasts on seasonal streamflow forecast quality. Results highlighted a trade-off between the sharpness and reliability of forecasts.
Louise Crochemore, Maria-Helena Ramos, and Florian Pappenberger
Hydrol. Earth Syst. Sci., 20, 3601–3618, https://doi.org/10.5194/hess-20-3601-2016, https://doi.org/10.5194/hess-20-3601-2016, 2016
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This study investigates the way bias correcting precipitation forecasts can improve the skill of streamflow forecasts at extended lead times. Eight variants of bias correction approaches based on the linear scaling and the distribution mapping methods are applied to the precipitation forecasts prior to generating the streamflow forecasts. One of the main results of the study is that distribution mapping of daily values is successful in improving forecast reliability.
P. Froidevaux, J. Schwanbeck, R. Weingartner, C. Chevalier, and O. Martius
Hydrol. Earth Syst. Sci., 19, 3903–3924, https://doi.org/10.5194/hess-19-3903-2015, https://doi.org/10.5194/hess-19-3903-2015, 2015
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We investigate precipitation characteristics prior to 4000 annual floods in Switzerland since 1961. The floods were preceded by heavy precipitation, but in most catchments extreme precipitation occurred only during the last 3 days prior to the flood events. Precipitation sums for earlier time periods (like e.g. 4-14 days prior to floods) were mostly average and do not correlate with the return period of the floods.
G. H. Fang, J. Yang, Y. N. Chen, and C. Zammit
Hydrol. Earth Syst. Sci., 19, 2547–2559, https://doi.org/10.5194/hess-19-2547-2015, https://doi.org/10.5194/hess-19-2547-2015, 2015
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This study compares the effects of five precipitation and three temperature correction methods on precipitation, temperature, and streamflow through loosely coupling RCM (RegCM) and a distributed hydrological model (SWAT) in terms of frequency-based indices and time-series-based indices. The methodology and results can be used for other regions and other RCM and hydrologic models, and for impact studies of climate change on water resources at a regional scale.
M. S. Siam and E. A. B. Eltahir
Hydrol. Earth Syst. Sci., 19, 1181–1192, https://doi.org/10.5194/hess-19-1181-2015, https://doi.org/10.5194/hess-19-1181-2015, 2015
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This paper explains the different natural modes of interannual variability in the flow of the Nile River and also presents a new index based on the sea surface temperature (SST) over the southern Indian Ocean to forecast the flow of the Nile River. It also presents a new hybrid forecasting algorithm that can be used to predict the Nile flow based on indices of the SST in the eastern Pacific and southern Indian oceans.
D. Halwatura, A. M. Lechner, and S. Arnold
Hydrol. Earth Syst. Sci., 19, 1069–1091, https://doi.org/10.5194/hess-19-1069-2015, https://doi.org/10.5194/hess-19-1069-2015, 2015
G. Panthou, T. Vischel, T. Lebel, G. Quantin, and G. Molinié
Hydrol. Earth Syst. Sci., 18, 5093–5107, https://doi.org/10.5194/hess-18-5093-2014, https://doi.org/10.5194/hess-18-5093-2014, 2014
D. Masson and C. Frei
Hydrol. Earth Syst. Sci., 18, 4543–4563, https://doi.org/10.5194/hess-18-4543-2014, https://doi.org/10.5194/hess-18-4543-2014, 2014
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The question of how to utilize information from the physiography/topography in the spatial interpolation of rainfall is a long-standing discussion in the literature. In this study we test ideas that go beyond the approach in popular interpolation schemes today. The key message of our study is that these ideas can at best marginally improve interpolation accuracy, even in a region where a clear benefit would intuitively be expected.
A. Casanueva, C. Rodríguez-Puebla, M. D. Frías, and N. González-Reviriego
Hydrol. Earth Syst. Sci., 18, 709–725, https://doi.org/10.5194/hess-18-709-2014, https://doi.org/10.5194/hess-18-709-2014, 2014
D. H. Yan, D. Wu, R. Huang, L. N. Wang, and G. Y. Yang
Hydrol. Earth Syst. Sci., 17, 2859–2871, https://doi.org/10.5194/hess-17-2859-2013, https://doi.org/10.5194/hess-17-2859-2013, 2013
F. Yusof, I. L. Kane, and Z. Yusop
Hydrol. Earth Syst. Sci., 17, 1311–1318, https://doi.org/10.5194/hess-17-1311-2013, https://doi.org/10.5194/hess-17-1311-2013, 2013
J. H. Lee, J. Timmermans, Z. Su, and M. Mancini
Hydrol. Earth Syst. Sci., 16, 4291–4302, https://doi.org/10.5194/hess-16-4291-2012, https://doi.org/10.5194/hess-16-4291-2012, 2012
L. Gudmundsson, J. B. Bremnes, J. E. Haugen, and T. Engen-Skaugen
Hydrol. Earth Syst. Sci., 16, 3383–3390, https://doi.org/10.5194/hess-16-3383-2012, https://doi.org/10.5194/hess-16-3383-2012, 2012
T. Bosshard, S. Kotlarski, T. Ewen, and C. Schär
Hydrol. Earth Syst. Sci., 15, 2777–2788, https://doi.org/10.5194/hess-15-2777-2011, https://doi.org/10.5194/hess-15-2777-2011, 2011
S. Nie, J. Zhu, and Y. Luo
Hydrol. Earth Syst. Sci., 15, 2437–2457, https://doi.org/10.5194/hess-15-2437-2011, https://doi.org/10.5194/hess-15-2437-2011, 2011
G. Ibarra-Berastegi, J. Saénz, A. Ezcurra, A. Elías, J. Diaz Argandoña, and I. Errasti
Hydrol. Earth Syst. Sci., 15, 1895–1907, https://doi.org/10.5194/hess-15-1895-2011, https://doi.org/10.5194/hess-15-1895-2011, 2011
R. Schiemann, R. Erdin, M. Willi, C. Frei, M. Berenguer, and D. Sempere-Torres
Hydrol. Earth Syst. Sci., 15, 1515–1536, https://doi.org/10.5194/hess-15-1515-2011, https://doi.org/10.5194/hess-15-1515-2011, 2011
A. Lü, S. Jia, W. Zhu, H. Yan, S. Duan, and Z. Yao
Hydrol. Earth Syst. Sci., 15, 1273–1281, https://doi.org/10.5194/hess-15-1273-2011, https://doi.org/10.5194/hess-15-1273-2011, 2011
G. Wang, A. J. Dolman, and A. Alessandri
Hydrol. Earth Syst. Sci., 15, 57–64, https://doi.org/10.5194/hess-15-57-2011, https://doi.org/10.5194/hess-15-57-2011, 2011
F. Garavaglia, J. Gailhard, E. Paquet, M. Lang, R. Garçon, and P. Bernardara
Hydrol. Earth Syst. Sci., 14, 951–964, https://doi.org/10.5194/hess-14-951-2010, https://doi.org/10.5194/hess-14-951-2010, 2010
Cited articles
Anselin, L.: Local Indicators of Spatial Association – LISA, Geogr. Anal.,
27, 93–115, https://doi.org/10.1111/j.1538-4632.1995.tb00338.x, 1995.
Bacchi, B. and Kottegoda, N. T.: Identification and calibration of spatial
correlation patterns of rainfall, J. Hydrol., 165, 311–348, 1995.
Barros, A. P. and Kuligowski, R. J.: Orographic effects during a severe
wintertime rainstorm in the Appalachian mountain, Mon. Weather Rev., 126, 2648–2672, 1997.
Barton, Y., Giannakaki, P., Von Waldow, H., Chevalier, C., Pfahl, S., and
Martius, O.: Clustering of regional-scale extreme precipitation events in
southern Switzerland, Mon. Weather Rev., 144, 347–369, 2016.
Bessho, K., Date, K., Hayashi, M., Ikeda, A., Imai, T., Inoue, H., Kumagai, Y.,
Miyakawa, T., Murata, H., Ohno, T., Okuyama, A., Oyama, R., Sasaki, Y., Shimazu,
Y., Shimoji, K., Sumida, Y., Suzuki, M., Taniguchi, H., Tsuchiyama, H., Uesawa,
D., Yokota, H., and Yoshida, R.: An introduction to Himawari-8/9 – Japan's
new-generation geostationary meteorological satellites, J. Meteorol. Soc. Jpn.
Ser. II, 94, 151–183, https://doi.org/10.2151/jmsj.2016-009, 2016.
Bretherton, C. S., Peters, M. E., and Back, L. E.: Relationships between water
vapor path and precipitation over the tropical oceans, J. Climate, 17,
1517–1528, https://doi.org/10.1175/1520-0442(2004)017<1517:RBWVPA>2.0.CO;2, 2004.
Carruthers, D. J. and Choularton, T. W.: A model of the feeder-seeder mechanism
of orographic rain including stratification and wind-drift effects, Q. J. Roy.
Meteorol. Soc., 109, 575–588, 1983.
Cassardo, C., Park, S. K., Thakuri, B. M., Priolo, D., and Zhang, Y.: Soil
surface energy and water budgets during a monsoon season in Korea, J. Hydrometeorol.,
10, 1379–1396, 2009.
Chang, H. and Kwon, W.-T.: Spatial variations of summer precipitation trends
in South Korea, 1973–2005, Environ. Res. Lett., 2, 045012, https://doi.org/10.1088/1748-9326/2/4/045012, 2007.
Choi, S.-W., Lee, S.-J., Kim, J. Lee, B.-L., Kim, K.-R., and Choi, B.-C.:
Agrometeorological observation environment and periodic report of Korea
Meteorological Administration: Current status and suggestions, Korean J. Agr.
Forest Meteorol., 17, 144–155, https://doi.org/10.5532/KJAFM.2015.17.2.144, 2015.
Chosh, A., Lohar, D., and Das, J.: Initiation of Nor'wester in relation to
mid-upper and low-level water vapor patterns on METEOSAT-5 images, Atmos. Res.,
87, 116–135, 2008.
Ciach, G. J. and Krajewski, W. F.: Analysis and modeling of spatial correlation
structure in small-scale rainfall in Central Oklahoma, Adv. Water Resour.,
29, 1450–1463, 2006.
De Haan, S., Barlag, S., Baltink, H. K., Debie, F., and Van der Marel, H.:
Synergetic use of GPS water vapor and Meteosat images for synoptic weather
forecasting, J. Appl. Meteorol., 43, 514–518, 2004.
Eltahir, E. A. B. and Bras, R. L.: Precipitation recycling, Rev. Geophys.,
34, 367–378, https://doi.org/10.1029/96RG01927, 1996.
Emmanuel, I., Andrieu, H., Leblois, E., and Flahaut, B.: Temporal and spatial
variability of rainfall at the urban hydrological scale, J. Hydrol., 430, 162–172, 2012.
Feng, Y. and Kitzmiller, D. H.: A short-range quantitative precipitation
forecast algorithm using back-propagation neural network approach, Adv. Atmos.
Sci., 23, 405–414, 2006.
Fritsch, J. M., Houze Jr., R. A., Adler, R., Bluestein, H., Bosart, L., Brown,
J., Carr, F., Davis, C., Johnson, R. H., Junker, N., Kuo, Y.-H., Rutledge, S.,
Smith, J., Toth, Z., Wilson, J. W., Zipser, E., and Zrnic, D.: Quantitative
precipitation forecasting: Report of the eighth prospectus development team,
U.S. Weather Research Program, B. Am. Meteorol. Soc., 79, 285–299, 1998.
Fu, W. J., Jiang, P. K., Zhou, G. M., and Zhao, K. L.: Using Moran's I and
GIS to study the spatial pattern of forest litter carbon density in a subtropical
region of southeastern China, Biogeosciences, 11, 2401–2409, https://doi.org/10.5194/bg-11-2401-2014, 2014.
Georgiev, C. G., Santurette, P., and Maynard K.: Weather Analysis and Forecasting:
Applying Satellite Water Vapor Imagery and Potential Vorticity Analysis, 2nd Edn.,
Academic Press, Cambridge, USA, 2016.
Getis, A. and Ord, J. K.: The analysis of spatial association by use of distance
statistics, Geogr. Anal., 24, 189–206, 1992.
Gimeno, L., Stohl, A., Trigo, R. M., Dominguez, F., Yoshimura, K., Yu, L.,
Drumond, A., Durán-Quesada, A. M., and Nieto, R.: Oceanic and terrestrial
sources of continental precipitation, Rev. Geophys., 50, RG4003, https://doi.org/10.1029/2012RG000389, 2012.
Ha, K.-J., Jeon, E.-H., and Oh, H.-M.: Spatial and temporal characteristics
of precipitation using an extensive network of ground gauge in the Korean
Peninsula, Atmos. Res., 86, 330–339, 2007.
Hong, K.-O., Shu, M.-S., and Rha, D.-K.: Temporal and spatial variations of
precipitation in South Korea for recent 30 Years (1976–2005) and geographic
environments, J. Korean Earth Sci. Soc., 27, 433–449, 2006.
Hwang, D.-I., Lee, J. W., Seo, D.-I., Na, H., and Seo, Y.-K.: Prediction system
using extrapolation-based nowcasting techniques for very short-range forecasting
and improvement of 1 hr accumulated precipitation forecasts, in: Proceedings
of the Autumn Meeting of Korean Meteorological Society, 12–14 October 2015,
Jeju, Korea, 260–261, http://203.247.66.28/, 2015.
In, S.-R., Han, S.-O., Im, E.-S., Kim, K.-H., and Shim, J.: Study on temporal
and spatial characteristics of summertime precipitation over Korean
Peninsula, Atmos., 24, 159–171, 2014 (in Korean with English abstract).
Jeong, J.-H., Lee, D.-I., Wang, C.-C., Jang, S.-M., You, C.-H., and Jang, M.:
Environment and morphology of mesoscale convective systems associated with the
Changma front during 9–10 July 2007, Ann. Geophys., 30, 1235–1248,
https://doi.org/10.5194/angeo-30-1235-2012, 2012.
Jeong, J.-H., Lee, D.-I., Wang, C.-C., and Han, I.-S.: Characteristics of
mesoscale-convective-system-produced extreme rainfall over southeastern South
Korea: 7 July 2009, Nat. Hazards Earth Syst. Sci., 16, 927–939, https://doi.org/10.5194/nhess-16-927-2016, 2016.
Jung, W. and Lee, T.-Y.: Formation and evolution of mesoscale convective systems
that brought the heavy rainfall over Seoul on September 21, 2010, Asia-Pacific
J. Atmos. Sci., 49, 635–647, https://doi.org/10.1007/s13143-013-0056-4, 2013.
Kim, B. J., Kripalani, R., Oh, J. H., and Moon, S.-E.: Summer monsoon rainfall
patterns over South Korea and associated circulation features, Theor. Appl.
Climatol. 72, 65–74, https://doi.org/10.1007/s007040200013, 2002.
Kim, E.-H., Kim, M.-K., and Lee, W.-S.: The regional characteristics of daily
precipitation intensity in Korea for recent 30 years, J. Korean Earth Sci. Soc.,
26, 404–416, 2005.
Kim, H. W. and Lee, D. K.: An observational study of mesoscale convective
systems with heavy rainfall over the Korean Peninsula, Weather Forecast., 21,
125–148, https://doi.org/10.1175/WAF912.1, 2006.
Kim, O. Y. and Oh, J. H.: Verification of the Performance of the High Resolution
QPF Model for Heavy Rainfall Event over the Korean Peninsula, Asia-Pacific J.
Atmos. Sci., 46, 119–133, 2010.
Ko, J.-W., Baek, H.-J., and Kwon, W.-T.: The characteristics of precipitation
and regionalization during rainy season in Korea, J. Korean Meteorol. Soc.,
41, 101–114, 2005.
Krennert, T. and Zwatz-Meise, V.: Initiation of convective cells in relation to
water vapour boundaries in satellite images, Atmos. Res., 67–68, 353–366, 2003.
Kursinski, A. L. and Mullen, S. L.: Spatiotemporal variability of hourly
precipitation over the eastern contiguous United States from stage IV
multisensor analyses, J. Hydrometeorol., 9, 3–21, 2008.
Lalor, G. and Zhang, C. S.: Multivariate outlier detection and remediation in
geochemical databases, Sci. Total Environ., 281, 99–109, 2001.
Lee, D.-K., Park, J.-G., and Kim, J.-W.: Heavy Rainfall Events Lasting 18 Days
from July 31 to August 17, 1998, over Korea, J. Meteorol. Soc. Jpn. Ser. II,
86, 313–333, https://doi.org/10.2151/jmsj.86.313, 2008.
Lee, J., Yoon, J., and Jun, H. D.: Evaluation for the correction of radar
rainfall due to the spatial distribution of raingauge network, J. Korea Soc.
Hazard Mitig., 14, 337–345, https://doi.org/10.9798/KOSHAM.2014.14.6.337, 2014.
Lee, J.-Y., Kim, W., and Lee, T.-Y.: Physical and dynamic factors that drove
the heavy rainfall event over the middle Korean Peninsula on 26–27 July 2011,
Asia-Pacific J. Atmos. Sci., 53, 101–120, https://doi.org/10.1007/s13143-017-0009-4, 2017a.
Lee, J.-Y., Kwon, M., Yun, K.-S., Min, S.-K., Park, I.-H., Ham, Y.-G., Jin, E.
K., Kim, J.-H., Seo, K.-H., Kim, W., Yim, S.-Y., and Yoon, J.-H.: The long-term
variability of Changma in the East Asian summer monsoon system: A review and
revisit, Asia-Pacific J. Atmos. Sci., 53, 257–272, https://doi.org/10.1007/s13143-017-0032-5, 2017b.
Lee, T.-Y. and Kim, Y.-H.: Heavy precipitation systems over the Korean Peninsula
and their classification, J. Korean Meteorol. Soc., 43, 367–396, 2007.
Lee, Y. H., Park, S. K., and Chang, D.-E.: Parameter estimation using the
genetic algorithm and its impact on quantitative precipitation forecast, Ann.
Geophys., 24, 3185–3189, https://doi.org/10.5194/angeo-24-3185-2006, 2006.
Mass, C.: Topographically forced convergence in western Washington State, Mon.
Weather Rev., 109, 1335–1347, 1981.
McGrath, D. and Zhang, C.: Spatial distribution of soil organic carbon
concentrations in grassland of Ireland, Appl. Geochem., 18, 1629–1639, 2003.
Milford, J. R. and Dugdale, G.: Estimation of rainfall using geostationary
satellite data, in: Applications of Remote Sensing in Agriculture, edited by:
Steven, M. D. and Clark, J. A., Butterworth, London, 97–110, 1990.
Moran, P. A. P.: The interpretation of statistical maps, J. Roy. Stat. Soc. B,
10, 243–251, 1948.
Mukhopadhyay, P., Singh, H. A. K., and Singh, S. S.: Two severe Nor'westers in
April 2003 over Kolkata using Doppler Radar observations and satellite imagery,
Weather, 60, 343–353, 2005.
Nam, J.-E., Lee, Y. H., Ha, J.-C., and Cho, C.-H.: A study on the e-folding
distance of summer precipitation using precipitation reanalysis data, in:
Proc. the Autumn Meeting of Korean Meteorological Society, Korean Meteorol.
Soc., 13–15 October 2014, Jeju, Korea, 657–658, 2014.
Okuyama, A., Andou, A., Date, K., Hosaka, K., Mori, N., Murata, H., Tabata, T.,
Takahashi, M., Yoshino, R. and Bessho, K.: Preliminary validation of Himawari-8/AHI
navigation and calibration. Proc. SPIE, 9607, 96072E, https://doi.org/10.1117/12.2188978, 2015.
Ord, J. K. and Getis, A.: Local spatial autocorrelation statistics:
distributional issues and an application, Geogr. Anal., 27, 286–306, 1995.
Park, S. K.: Nonlinearity and predictability of convective rainfall associated
with water vapor perturbations in a numerically simulated storm, J. Geophys.
Res., 104, 31575–31587, https://doi.org/10.1029/1999JD900446, 1999.
Park, S. K. and Lee, E.: Synoptic features of orographically enhanced heavy
rainfall on the east coast of Korea associated with Typhoon Rusa (2002), Geophys.
Res. Lett., 34, L02803, https://doi.org/10.1029/2006GL028592, 2007.
Rabin, R. M., Corfidi, S. F., Brunner, J. C., and Hane, C. E.: Detecting winds
aloft from water vapor satellite imagery in the vicinity of storms, Weather,
59, 251–257, https://doi.org/10.1256/wea.182.03, 2004.
Ritschel, C., Ulbrich, U., Névir, P., and Rust, H. W.: Precipitation
extremes on multiple timescales – Bartlett–Lewis rectangular pulse model and
intensity-duration-frequency curves, Hydrol. Earth Syst. Sci., 21, 6501–6517,
https://doi.org/10.5194/hess-21-6501-2017, 2017.
Riyu, L., Oh, J. H., Kim, B. J., Baek, H.-J., and Ronghui, H.: Associations
with the interannual variations of onset and withdrawal of the Changma, Adv.
Atmos. Sci., 18, 1066–1080, https://doi.org/10.1007/s00376-001-0023-3, 2001.
Rodriguez-Iturbe, I., Cox, D. R., and Isham, V.: Some models for rainfall based
on stochastic point processes, P. Roy. Soc. Lond. A, 410, 269–288, 1987.
Schiemann, R., Erdin, R., Willi, M., Frei, C., Berenguer, M., and Sempere-Torres,
D.: Geostatistical radar-raingauge combination with nonparametric correlograms:
methodological considerations and application in Switzerland, Hydrol. Earth
Syst. Sci., 15, 1515–1536, https://doi.org/10.5194/hess-15-1515-2011, 2011.
Skøien, J. O., Blöschl, G., and Western, A. W.: Characteristic space
scales and timescales in hydrology, Water Resour. Res., 39, 1304, https://doi.org/10.1029/2002WR001736, 2003.
Smith, B. L. and Yuter, S. E.: Water vapor fluxes and orographic precipitation
over northern California associated with a landfalling atmospheric river, Mon.
Weather Rev., 138, 74–100, https://doi.org/10.1175/2009MWR2939.1, 2010.
Song, H.-J. and Sohn, B.-J.: Two heavy rainfall types over the Korean Peninsula
in the humid East Asian summer environment: A satellite observation study, Mon.
Weather Rev., 143, 363–382, https://doi.org/10.1175/MWR-D-14-00184.1, 2015.
Stohl, A., Forster, C., and Sodemann, H.: Remote sources of water vapor forming
precipitation on the Norwegian west coast at 60∘ N – a tale of hurricanes
and an atmospheric river, J. Geophys. Res., 113, D05102, https://doi.org/10.1029/2007JD009006, 2008.
Sun, J. and Lee, T.-Y.: A Numerical Study of an Intense Quasi-stationary
Convection Band over the Korean Peninsula, J. Meteorol. Soc. Jpn. Ser. II, 80,
1221–1245, https://doi.org/10.2151/jmsj.80.1221, 2002.
Tompkins, A. M.: Organization of tropical convection in low vertical wind shears:
The role of water vapor, J. Atmos. Sci., 58, 529–545, https://doi.org/10.1175/1520-0469(2001)058<0529:OOTCIL>2.0.CO;2, 2001.
Trenberth, K. E.: Atmospheric moisture recycling: Role of advection and local
evaporation, J. Climate, 12, 1368–1381, 1999.
Trenberth, K. E. and Stepaniak, D. P.: Co-variability of components of poleward
atmospheric energy transports on seasonal and interannual timescales, J. Climate,
16, 3690–3704, 2003a.
Trenberth, K. E. and Stepaniak, D. P.: Seamless poleward atmospheric energy
transports and implications for the Hadley circulation, J. Climate, 16, 3705–3721, 2003b.
Velden, C. S.: Satellite observations of Hurricane Elena (1985) using the VAS
6.7 µm “watervapor” channel, B. Am. Meteorol. Soc., 68, 210–215, 1987.
Volkmann, T. H. M., Lyon, S. W., Gupta, H. V., and Troch, P. A.: Multicriteria
design of rain gauge networks for flash flood prediction in semiarid catchments
with complex terrain, Water Resour. Res., 46, W11554, https://doi.org/10.1029/2010WR009145, 2010.
Yu, X., Park, S. K., Lee, Y. H., and Choi, Y. S.: Quantitative precipitation
forecast of a tropical cyclone through optimal parameter estimation in a
convective parameterization, Sci. Online Lett. Atmos., 9, 36–39, 2013.
Zeweldi, D. A. and Gebremichael, M.: Evaluation of CMORPH precipitation
products at fine space-time scales, J. Hydrometeorol., 10, 300–307, 2009.
Zhou, T.-J. and Yu, R.-C.: Atmospheric water vapor transport associated with
typical anomalous summer rainfall patterns in China, J. Geophys. Res., 110,
D08104, https://doi.org/10.1029/2004JD005413, 2005.
Short summary
Understanding the precipitation characteristics is essential to design an optimal observation network. We studied the spatial and temporal characteristics of summertime precipitation systems in Korea via geostatistical analyses on the ground-based precipitation and satellite water vapor data. We found that, under a strict standard, an observation network with higher resolution is required in local areas with frequent heavy rainfalls, depending on directional features of precipitation systems.
Understanding the precipitation characteristics is essential to design an optimal observation...
