Journal of Hydrometeorology最新文献

{"title":"Nonstationarity in Extreme Precipitation Return Values Along the United States Gulf and Southeastern Coasts","authors":"Savannah K. Jorgensen, J. Nielsen‐Gammon","doi":"10.1175/jhm-d-22-0157.1","DOIUrl":"https://doi.org/10.1175/jhm-d-22-0157.1","url":null,"abstract":"\u0000This study estimates extreme rainfall trends across the Gulf and Southeastern Coasts of the US while applying methods for extending the temporal record and aggregating across spatial trend variations. Nonstationary generalized extreme value (GEV) models are applied to historical annual daily maximum precipitation data (1890-2019) while using CMIP5 global mean model surface temperature (GMST) as the covariate. County composites and multi-county regions are used for local data record extension and pooling. Unlike most previous studies, return periods as long as 100 years are analyzed.\u0000The local trend estimates themselves are found to be too noisy to be reliable as estimates of climate-driven trends. However, application of a Gaussian process model to the spatial distribution of observed trends yields overall trend detection at the 95% significance level. The overall historical increase due to nonstationarity across the study region, with associated 95% confidence intervals, is 19% (5%, 33%) for the 2-yr return period and 14% (4%, 24%) for the 100-yr return period. A trend is also detectable in the Gulf Coast subregion, but not in the smaller Southeast subregion. Recent weather events and nonstationarity have caused the official return value estimates for parts of North and South Carolina to be much lower than the return values estimated here.","PeriodicalId":503314,"journal":{"name":"Journal of Hydrometeorology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140251824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the challenges of simulating streamflow in glacierized catchments of the Himalayas using satellite and reanalysis forcing data","authors":"Anju Vijayan Nair, Sungwook Wi, R. Kayastha, Colin J. Gleason, I. Dollan, Viviana Maggioni, E. Nikolopoulos","doi":"10.1175/jhm-d-23-0048.1","DOIUrl":"https://doi.org/10.1175/jhm-d-23-0048.1","url":null,"abstract":"\u0000Hydrologic assessment of climate change impacts on complex terrains and data-sparse regions like High Mountain Asia is a major challenge. Combining hydrological models with satellite and reanalysis data for evaluating changes in hydrological variables is often the only available approach. However, uncertainties associated with forcing dataset, coupled with model parameter uncertainties, can have significant impacts on hydrologic simulations. This work aims to understand and quantify how the uncertainty in precipitation and its interaction with the model uncertainty affect streamflow estimation in glacierized catchments. Simulations for four precipitation datasets (IMERG, CHIRPS, ERA5 Land, and APHRODITE) and two glaciohydrological models (GDM and HYMOD_DS) are evaluated for the Marsyangdi and Budhigandaki river basins in Nepal. Temperature sensitivity of streamflow simulations is also investigated. Relative to APHRODITE, which compared well with ground stations, ERA5 Land overestimate the catchment average precipitation for both basins by more than 70%; IMERG and CHIRPS overestimates by ∼20%. Precipitation uncertainty propagation to streamflow exhibits strong dependencies to model structure and streamflow components (snowmelt, icemelt, rainfallrunoff), but overall uncertainty dampens through precipitation-to-streamflow transformation. Temperature exerts a significant additional source of uncertainty in hydrologic simulations of such environments. GDM was found to be more sensitive to temperature variations, with >50% increase in total flow for 20% increase in actual temperature, emphasizing that models that rely on lapse rates for the spatial distribution of temperature have much higher sensitivity. Results from this study provide critical insight into the challenges of utilizing satellite and reanalysis products for simulating streamflow in glacierized catchments.","PeriodicalId":503314,"journal":{"name":"Journal of Hydrometeorology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140259835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Statistical Characteristics and Synoptic Patterns of Convection Initiation over the Middle Reaches of the Yangtze River Basin as Observed Using the Fengyun-4A Satellite","authors":"Shanshan Li, Xiaofang Wang, Jianhua Sun, Zheng Ma, Yuanchun Zhang, Yuan Gao, Yang Hu, Wengang Zhang","doi":"10.1175/jhm-d-23-0157.1","DOIUrl":"https://doi.org/10.1175/jhm-d-23-0157.1","url":null,"abstract":"\u0000Convection initiations (CIs) observed using the advanced geosynchronous radiation imager on the Chinese Fengyun-4A satellite were identified over the middle reaches of the Yangtze River basin during warm season (May–September) of 2018–21. A hybrid objective tracking algorithm combining the conventional area overlapping with the Kalman filter method was applied. Subsequently, spatial and temporal variations in the identified CIs and their synoptic circulation patterns were analyzed. The frequency of CIs was highest in August and lowest in May. Nearly 81% of CIs occurred during noon–afternoon (1100–1859 LST), with the highest frequency in the southern mountains of the study region, whereas the CIs with relatively low frequency moved to the plains from afternoon to morning (1700–1059 LST). The diurnal variation of CIs throughout the study region exhibited a unimodal structure, with a peak appearing at noon (1200–1259 LST). CIs during noon–afternoon in July and August had faster cloud-top cooling rates. The synoptic circulations without tropical cyclones during noon–afternoon hours were classified into four patterns by hierarchical clustering; two dominant patterns (i.e., SW-Flows and S-Flows) had broader areas of higher most unstable convective available potential energy (MUCAPE), whereas the 0–3-km shear (SHR3) was the weakest in the S-Flows pattern. It was clear that the high-frequency areas of CIs were most likely to occur in stronger MUCAPE and weaker SHR3 environments, and CIs were more controlled by thermally unstable environments. We further illustrated that CIs tend to concentrate in unstable and moisture flux convergence areas affected by mountains.","PeriodicalId":503314,"journal":{"name":"Journal of Hydrometeorology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140274425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiscale Features and Triggering Mechanisms of the Warm-Sector Heavy Rainfall Accompanied by Warm Shear Along the Yangtze–Huaihe Coastal Regions","authors":"Yiping Yu, Ling Zhang, Liuxian Song, Wei Li, Lu Zhou, Ouyang Lin","doi":"10.1175/jhm-d-23-0143.1","DOIUrl":"https://doi.org/10.1175/jhm-d-23-0143.1","url":null,"abstract":"\u0000Using high-resolution hourly precipitation data and ERA5 reanalysis data, this study employs the K-means method to categorize 32 cases of warm-sector heavy rainfall events accompanied by a warm-type shear line (WSWR) along the Yangtze–Huaihe coastal region (YHCR) from April to September during 2010–17. Considering the synoptic system features of WSWR by K means, the result reveals 15 southwest type (SW-type) and 17 south-biased type (S-type) WSWR events. Composite analysis illuminates the distinct dynamic and thermodynamic features of each type. For the SW-type WSWR, the maximum value of water vapor is concentrated around 850 hPa in the lower troposphere. The YHCR is located at the intersection of the exit area of the 850-hPa synoptic low-level jet (LLJ) and the entrance area of the 600-hPa jet. The suction effects, combined with the location of YHCR on the left side of the boundary layer jet (BLJ), facilitate the triggering of local convection. Conversely, the S-type WSWR shows peak water vapor in the boundary layer. Before the onset of WSWR events, a warm, humid tongue indicated by pseudoequivalent potential temperature θse is present in the boundary layer, signified by substantial unstable energy. The BLJ aids mesoscale ascent on its terminus, enhancing convergence along the coastline. The BLJ also channels unstable energy and water vapor to the YHCR, causing significant rainfall. Typical case studies of both types show similar environmental backgrounds. The scale analysis shows mesoscales of dynamic field are crucial in shaping both types of WSWR, while the large-scale and meso-α-scale dynamic field facilitate the transportation of moist and warm airflow.","PeriodicalId":503314,"journal":{"name":"Journal of Hydrometeorology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140277903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Effect of Convective/Advective Precipitation Partitions on the Precipitation Isotopes in the Monsoon Regions of China: A Case Study of Changsha","authors":"Zhuoyong Xiao, Xinping Zhang, Xiong Xiao, Xin Chang, Xinguang He","doi":"10.1175/jhm-d-23-0084.1","DOIUrl":"https://doi.org/10.1175/jhm-d-23-0084.1","url":null,"abstract":"\u0000Convective/advective precipitation partitions refer to the divisions of precipitation that are either convective or advective in nature, relative to the total precipitation amount. These distinct partitions can have a significant influence on stable isotope composition of precipitation. This study analyzed and compared the effect of precipitation partitions on δ18O in precipitation (δ18Op) by using daily precipitation stable isotope data from Changsha station and monthly precipitation stable isotope data from the Global Network of Isotopes in Precipitation (GNIP), under different time scales, time intervals (i.e., annual, warm season, and cold season), and precipitation intensities. The results showed that the correlation between convective precipitation fraction (CPF) and total precipitation amount was influenced by the intensity of convection in different time intervals. On both the daily and monthly scales, the CPF decreased as the precipitation amount increased in the warm season, while increased with increasing precipitation amount in the cold season. Regardless of the season, daily δ18Op at Changsha station consistently increased with an increase in daily CPF. On a daily scale, the effect of convective activity on δ18Op was stronger than that of the “precipitation amount effect” in the cold season, as compared to the situation in the warm season. As a result, the regression line slope between δ18Op and CPF increased with increasing precipitation intensity in the warm season, meaning that as the CPF increased, the δ18Op increased at a faster rate under higher precipitation intensity. Similarly, the slope increased with increasing precipitation intensity in the cold season. This suggests that precipitation intensity and convection intensity can affect the relationship between δ18Op and CPF. Our findings shed light on how different precipitation partitions affect stable isotope composition of precipitation, thus enhancing our understanding of the variability of precipitation stable isotopes in the monsoon regions of China.","PeriodicalId":503314,"journal":{"name":"Journal of Hydrometeorology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140420268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal variations of tropical and non-tropical cyclone-induced rainfall over southeast China and the teleconnections to climatic indices","authors":"Yuanyuan Zhou, Liang Gao","doi":"10.1175/jhm-d-23-0095.1","DOIUrl":"https://doi.org/10.1175/jhm-d-23-0095.1","url":null,"abstract":"\u0000The spatiotemporal variations of annual tropical cyclone- and non-tropical cyclone-induced rainfall (TCR and NTCR) during 1960 – 2017 in Southeast China are investigated in this study. The teleconnections to sea surface temperature, Arctic Oscillation, Southern Oscillation, and Indian Ocean Dipole are examined. A significant decrease in annual TCR in the Pearl River Basin was detected, while an increase in annual TCR in rainstorms was observed in the northeast of the Pearl River Basin and south of the Yangtze River Basin. Northward migration of a TCR belt was identified, which was also indicated by the pronounced anomalies of annual TCR. There was in general an increasing trend of non-tropical cyclone-induced moderate rain, heavy rain, and rainstorms in Southeast China. Compared with the non-tropical cyclone-induced heavy rain, the abnormal non-tropical cyclone-induced rainstorms are more northerly. Both monthly TCR and NTCR were remarkably affected by the Arctic Oscillation, Southern Oscillation, and Indian Ocean Dipole. TCR was more easily affected by Arctic Oscillation compared to NTCR.","PeriodicalId":503314,"journal":{"name":"Journal of Hydrometeorology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140437786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Contributions of initial conditions and meteorological forecast to subseasonal-to-seasonal hydrological forecast skill in Western Tropical South America.","authors":"G. C. Recalde-Coronel, Benjamin Zaitchik, William Pan, Yifan Zhou, Hamada Badr","doi":"10.1175/jhm-d-23-0064.1","DOIUrl":"https://doi.org/10.1175/jhm-d-23-0064.1","url":null,"abstract":"\u0000Hydrological predictions at sub-seasonal to seasonal (S2S) timescales can support improved decision-making in climate-dependent sectors like agriculture and hydropower. Here, we present an S2S hydrological forecasting system (S2S-HFS) for western tropical South America (WTSA). The system uses the global NASA Goddard Earth Observing System S2S meteorological forecast system (GEOS-S2S) in combination with the Generalized Analog Regression Downscaling algorithm and the NASA Land Information System (LIS). In this implementation study, we evaluate system performance for three-month hydrological forecasts for the austral autumn season (March–April–May) using ensemble hindcasts for 2002-2017. Results indicate that the S2S-HFS generally offers skill in predictions of monthly precipitation up to one month lead, evapotranspiration up to 2 months lead, and soil moisture content up to three months lead. Ecoregions with better hindcast performance are located either in the coastal lowlands or in the Amazon lowland forest. We perform dedicated analysis to understand how two important teleconnections affecting the region are represented in the S2S-HFS: the El Niño Southern Oscillation (ENSO) and the Antarctic Oscillation (AAO). We find that forecast skill for all variables at one month lead is enhanced during the positive phase of ENSO and the negative phase of AAO. Overall, this study indicates that there is meaningful skill in the S2S-HFS for many ecoregions in WTSA, particularly for long memory variables such as soil moisture. The skill of the precipitation forecast, however, decays rapidly after forecast initialization, a phenomenon that is consistent with S2S meteorological forecasts over much of the world.","PeriodicalId":503314,"journal":{"name":"Journal of Hydrometeorology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140436049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hydrological verification of two rainfall short-term forecasting methods with floods anticipation perspective","authors":"M. Poletti, M. Lagasio, Antonio Parodi, Massimo Milelli, Vincenzo Mazzarella, Stefano Federico, Lorenzo Campo, Marco Falzacappa, F. Silvestro","doi":"10.1175/jhm-d-23-0125.1","DOIUrl":"https://doi.org/10.1175/jhm-d-23-0125.1","url":null,"abstract":"\u0000Flood forecast remains a significant challenge, particularly when dealing with basins characterized by small drainage areas (i.e. 103 km2 or lower with response time in the range 0.5-10 h) especially because of the rainfall prediction uncertainties (Buzzi et al., 2014) . This study aims to investigate the performances of streamflow predictions using two short-term rainfall forecast methods.\u0000These methods utilize a combination of nowcasting extrapolation algorithm and numerical weather predictions by employing three-dimensional variational assimilation system and nudging assimilation techniques, meteorological radar and lightning data are frequently updated, allowing new forecasts with high temporal frequency (i.e. 1-3 hours). A distributed hydrological model is used to convert rainfall forecasts in streamflow prediction. The potential of assimilating radar and lightning data or radar data alone, is also discussed.\u0000A hindcast experiment on two rainy periods in the north-west region of Italy was designed. The selected skill scores were analyzed to assess their degradation with increasing lead time, and the results were further aggregated based on basin dimensions to investigate the catchment integration effect. The findings indicate that both rainfall forecast methods yield good performance, with neither definitively outperforming the other. Furthermore, the results demonstrate that, on average, assimilating both radar and lightning data enhances the performance.","PeriodicalId":503314,"journal":{"name":"Journal of Hydrometeorology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140443832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Local and Object-based Perspectives on Atmospheric Rivers Making Landfall on the Western North American Coastline","authors":"Wen-Shu Lin, Joel R. Norris, M. DeFlorio, F. M. Ralph","doi":"10.1175/jhm-d-22-0155.1","DOIUrl":"https://doi.org/10.1175/jhm-d-22-0155.1","url":null,"abstract":"\u0000We apply the Ralph et al. (2019) scaling method to a reanalysis dataset to examine the climatology and variability of landfalling atmospheric rivers (ARs) along the western North American coastline during 1980–2019. The local perspective ranks AR intensity on a scale from 1 (weak) to 5 (strong) at each grid point along the coastline. The object-based perspective analyzes the characteristics of spatially independent and temporally coherent AR objects making landfall. The local perspective shows that the annual AR frequency of weak and strong ARs along the coast are highest in Oregon and Washington and lowest in southern California. Strong ARs occur less frequently than weak ARs and have a more pronounced seasonal cycle. If those ARs with integrated water vapor transport (IVT) weaker than 250 kg m−1 s−1 are included, there is an enhanced seasonal cycle of AR frequency in southern California and a seasonal cycle of AR intensity but not AR frequency in Alaska. The object-based analysis additionally indicates that strong ARs at lower latitudes are associated with stronger wind than weak ARs but similar moisture, whereas strong ARs at higher latitudes are associated with greater moisture than weak ARs but similar wind. For strong ARs, IVT at the core is largest for ARs in Oregon and Washington and smaller poleward and equatorward. Both IVT in the AR core and cumulative IVT along the coastline usually decrease after the first day of landfall for weak ARs but increase from the first to second day for strong ARs.","PeriodicalId":503314,"journal":{"name":"Journal of Hydrometeorology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140444628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Regional precipitation regimes and evaluation of national precipitation datasets against satellite-based precipitation estimates, Republic of Georgia","authors":"Nika Tsitelashvili, Trent Biggs, Ye Mu, V. Trapaidze","doi":"10.1175/jhm-d-23-0116.1","DOIUrl":"https://doi.org/10.1175/jhm-d-23-0116.1","url":null,"abstract":"\u0000Analyzing water resources in areas with few hydrometeorological stations, such as those in post-Soviet countries, is difficult due to station closures after 1989. In Caucasus, evaluations often rely on outdated data from nearby rivers. We evaluated one national-level precipitation dataset, the Water Balance of Georgia (WBG) with two satellite-based precipitation products from 1981 to 2021, including the Climate Hazards Group Infrared Precipitation with station data (CHIRPS), and CHIRPS blended with a dense rain gauge network (geoCHIRPS). We modelled mean annual precipitation from geoCHIRPS as a function of coastal distance and elevation. CHIRPS underestimated precipitation in the cold and wet seasons (R2 = 0.74, r = 0.86), and overestimated dry season precipitation, while geoCHIRPS performed well in all seasons (R2 = 0.86, r = 0.92). Distance from the coast was a more important predictor of precipitation than elevation in Western Georgia, while precipitation correlated positively with elevation in the East. At four hydroelectric plants, the underperformance as a percentage of capacity (∼37%) corresponds with the percentage difference between difference in precipitation products (∼38%), suggesting that plants designed based on WBG may be systematically over-designed, but further work is needed to determine the reasons for the underperformance of the plants and frequency. We conclude that 1) existing WBG does not accurately reflect elevation-precipitation relationships near the coast and 2) for accurate analysis of spatiotemporal precipitation variability and its impacts on hydropower generation, environmental and sustainable water resource management, it is essential to calibrate satellite-based precipitation estimates with additional rain gauge data.","PeriodicalId":503314,"journal":{"name":"Journal of Hydrometeorology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139837105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}