W. Currier, A. Wood, N. Mizukami, Bart Nijssen, J. Hamman, E. Gutmann
Vegetation parameters for the Variable Infiltration Capacity (VIC) hydrologic model were recently updated using observations from the MODerate Resolution Imaging Spectroradiometer (MODIS). Previous work showed that these MODIS-based parameters improved VIC evapotranspiration simulations when compared to eddy covariance observations. Due to the importance of evapotranspiration within the Colorado River Basin, this study provided a basin-by-basin calibration of VIC soil parameters with updated MODIS-based vegetation parameters to improve streamflow simulations. Interestingly, while both configurations had similar historic streamflow performance, end-of-century hydrologic projections, driven by 29 downscaled global climate models under the RCP8.5 emissions scenario differed between the two configurations. The calibrated MODIS-based configuration had an ensemble mean that simulated little change in end-of-century annual streamflow volume (+0.4%) at Lees Ferry, AZ relative to the historical period (1960-2005). In contrast, the previous VIC configuration, which is used to inform decisions about future water resources in the Colorado River Basin projected an 11.7% decrease in annual streamflow. Both VIC configurations simulated similar amounts of evapotranspiration in the historical period. However, the MODIS-based VIC configuration did not show as much of an increase in evapotranspiration by the end of the century, primarily within the Upper Basin’s forested areas. Differences in evapotranspiration projections were the result of the MODIS-based vegetation parameters having lower leaf area index values and less forested area compared to previous vegetation estimates used in recent Colorado River Basin hydrologic projections. These results highlight the need to accurately characterize vegetation and better constrain climate sensitivities in hydrologic models.
{"title":"Vegetation representation influences projected streamflow changes in the Colorado River Basin","authors":"W. Currier, A. Wood, N. Mizukami, Bart Nijssen, J. Hamman, E. Gutmann","doi":"10.1175/jhm-d-22-0143.1","DOIUrl":"https://doi.org/10.1175/jhm-d-22-0143.1","url":null,"abstract":"\u0000Vegetation parameters for the Variable Infiltration Capacity (VIC) hydrologic model were recently updated using observations from the MODerate Resolution Imaging Spectroradiometer (MODIS). Previous work showed that these MODIS-based parameters improved VIC evapotranspiration simulations when compared to eddy covariance observations. Due to the importance of evapotranspiration within the Colorado River Basin, this study provided a basin-by-basin calibration of VIC soil parameters with updated MODIS-based vegetation parameters to improve streamflow simulations. Interestingly, while both configurations had similar historic streamflow performance, end-of-century hydrologic projections, driven by 29 downscaled global climate models under the RCP8.5 emissions scenario differed between the two configurations. The calibrated MODIS-based configuration had an ensemble mean that simulated little change in end-of-century annual streamflow volume (+0.4%) at Lees Ferry, AZ relative to the historical period (1960-2005). In contrast, the previous VIC configuration, which is used to inform decisions about future water resources in the Colorado River Basin projected an 11.7% decrease in annual streamflow. Both VIC configurations simulated similar amounts of evapotranspiration in the historical period. However, the MODIS-based VIC configuration did not show as much of an increase in evapotranspiration by the end of the century, primarily within the Upper Basin’s forested areas. Differences in evapotranspiration projections were the result of the MODIS-based vegetation parameters having lower leaf area index values and less forested area compared to previous vegetation estimates used in recent Colorado River Basin hydrologic projections. These results highlight the need to accurately characterize vegetation and better constrain climate sensitivities in hydrologic models.","PeriodicalId":15962,"journal":{"name":"Journal of Hydrometeorology","volume":"1989 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82301474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We present a comparative analysis of atmospheric rivers (ARs) and Great Plains low-level jets (GPLLJs) in the central U.S. during April–September 1901–2010 using ECMWF’s CERA-20C. The analysis is motivated by a perceived need to highlight overlap and synergistic opportunities between traditionally disconnected AR and GPLLJ research. First, using the Guan–Walliser integrated vapor transport (IVT)-based AR classification and Bonner–Whiteman-based GPLLJ classification, we identify days with either an AR and/or GPLLJ spanning 15% of the central U.S. These days are grouped into five event samples: 1) all GPLLJ, 2) AR GPLLJ, 3) non-AR GPLLJ, 4) AR non-GPLLJ, and 5) all AR. Then, we quantify differences in the frequency, seasonality, synoptic environment, and extreme weather impacts corresponding to each event sample. Over the 20th century, April–September AR frequency remained constant whereas GPLLJ frequency significantly decreased. Of GPLLJ days, 36% are associated with a coincident AR. Relative to ARs that are equally probable from April–September, GPLLJs exhibit distinct seasonality, with peak occurrence in July. A 500 hPa geopotential height comparison shows a persistent ridge over the central U.S for non-AR GPLLJ days, whereas on AR GPLLJ days, a trough and ridge pattern is present over western to eastern CONUS. AR GPLLJ days have 34% greater 850 hPa windspeeds, 53% greater IVT, and 72% greater 24-hour precipitation accumulation than non-AR GPLLJ days. In terms of 95th percentile 850 hPa windspeed, IVT, and 24-hour precipitation, that of AR GPLLJs is 25%, 45%, and 23% greater than non-AR GPLLJs, respectively.
{"title":"A Comparative Analysis of the Impact of Low-Level Jets and Atmospheric Rivers in the Central U.S.","authors":"Nabin Gyawali, C. Ferguson, L. Bosart","doi":"10.1175/jhm-d-22-0086.1","DOIUrl":"https://doi.org/10.1175/jhm-d-22-0086.1","url":null,"abstract":"\u0000We present a comparative analysis of atmospheric rivers (ARs) and Great Plains low-level jets (GPLLJs) in the central U.S. during April–September 1901–2010 using ECMWF’s CERA-20C. The analysis is motivated by a perceived need to highlight overlap and synergistic opportunities between traditionally disconnected AR and GPLLJ research. First, using the Guan–Walliser integrated vapor transport (IVT)-based AR classification and Bonner–Whiteman-based GPLLJ classification, we identify days with either an AR and/or GPLLJ spanning 15% of the central U.S. These days are grouped into five event samples: 1) all GPLLJ, 2) AR GPLLJ, 3) non-AR GPLLJ, 4) AR non-GPLLJ, and 5) all AR. Then, we quantify differences in the frequency, seasonality, synoptic environment, and extreme weather impacts corresponding to each event sample. Over the 20th century, April–September AR frequency remained constant whereas GPLLJ frequency significantly decreased. Of GPLLJ days, 36% are associated with a coincident AR. Relative to ARs that are equally probable from April–September, GPLLJs exhibit distinct seasonality, with peak occurrence in July. A 500 hPa geopotential height comparison shows a persistent ridge over the central U.S for non-AR GPLLJ days, whereas on AR GPLLJ days, a trough and ridge pattern is present over western to eastern CONUS. AR GPLLJ days have 34% greater 850 hPa windspeeds, 53% greater IVT, and 72% greater 24-hour precipitation accumulation than non-AR GPLLJ days. In terms of 95th percentile 850 hPa windspeed, IVT, and 24-hour precipitation, that of AR GPLLJs is 25%, 45%, and 23% greater than non-AR GPLLJs, respectively.","PeriodicalId":15962,"journal":{"name":"Journal of Hydrometeorology","volume":"7 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87452595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Hurkmans, B. van den Hurk, M. Schmeits, F. Wetterhall, I. Pechlivanidis
For efficient management of the Dutch surface water reservoir Lake IJssel, (sub)seasonal forecasts of the water volumes going in and out of the reservoir are potentially of great interest. Here, streamflow forecasts were analyzed for the river Rhine at Lobith, which is partly routed through the river IJssel, the main influx into the reservoir. We analyzed seasonal forecast data sets derived from EFAS, E-HYPE and HTESSEL, which differ in their underlying hydrological formulation, but are all forced by meteorological forecasts from ECMWF SEAS5. We post-processed the streamflowforecasts using quantile mapping (QM) and analyzed several forecast quality metrics. Forecast performance was assessed based on the available reforecast period, as well as on individual summer seasons. QM increased forecast skill for nearly all metrics evaluated. Averaged over the reforecast period, forecasts were skillful for up to four months in spring, and early summer. Later in summer the skillful period deteriorated to 1-2 months. When investigating specific years with either low or high flow conditions, forecast skill increased with the extremity of the event. Although raw forecasts for both E-HYPE and EFAS were more skillful than HTESSEL, bias correction based on QM can significantly reduce the difference. In operational mode, the three forecast systems show comparable skill. In general, dry conditions can be forecasted with high success rates up to three months ahead, which is very promising for successful use of Rhine streamflow forecasts in downstream reservoir management.
{"title":"Seasonal streamflow forecasting for fresh water reservoir management in the Netherlands: an assessment of multiple prediction systems","authors":"R. Hurkmans, B. van den Hurk, M. Schmeits, F. Wetterhall, I. Pechlivanidis","doi":"10.1175/jhm-d-22-0107.1","DOIUrl":"https://doi.org/10.1175/jhm-d-22-0107.1","url":null,"abstract":"\u0000For efficient management of the Dutch surface water reservoir Lake IJssel, (sub)seasonal forecasts of the water volumes going in and out of the reservoir are potentially of great interest. Here, streamflow forecasts were analyzed for the river Rhine at Lobith, which is partly routed through the river IJssel, the main influx into the reservoir. We analyzed seasonal forecast data sets derived from EFAS, E-HYPE and HTESSEL, which differ in their underlying hydrological formulation, but are all forced by meteorological forecasts from ECMWF SEAS5. We post-processed the streamflowforecasts using quantile mapping (QM) and analyzed several forecast quality metrics. Forecast performance was assessed based on the available reforecast period, as well as on individual summer seasons. QM increased forecast skill for nearly all metrics evaluated. Averaged over the reforecast period, forecasts were skillful for up to four months in spring, and early summer. Later in summer the skillful period deteriorated to 1-2 months. When investigating specific years with either low or high flow conditions, forecast skill increased with the extremity of the event. Although raw forecasts for both E-HYPE and EFAS were more skillful than HTESSEL, bias correction based on QM can significantly reduce the difference. In operational mode, the three forecast systems show comparable skill. In general, dry conditions can be forecasted with high success rates up to three months ahead, which is very promising for successful use of Rhine streamflow forecasts in downstream reservoir management.","PeriodicalId":15962,"journal":{"name":"Journal of Hydrometeorology","volume":"1 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83474246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yongliang Jiao, Ren Li, Tonghua Wu, Lin Zhao, Xiaodong Wu, Junjie Ma, Jimin Yao, G. Hu, Yao Xiao, Shuhua Yang, Wenhao Liu, Y. Qiao, Jianzong Shi, E. Du, Xiaofan Zhu, Shenning Wang
Climate changes significantly impact the hydrological cycle. Precipitation is one of the most important atmospheric inputs to the terrestrial hydrologic system, and its variability considerably influences environmental and socioeconomic development. Atmospheric warming intensifies the hydrological cycle, increasing both atmospheric water vapor concentration and global precipitation. The relationship between heavy precipitation and temperature has been extensively investigated in literature. However, the relationship in different percentile ranges has not been thoroughly analyzed. Moreover, a percentile-based regression provides a simple but effective framework for investigation into other factors (precipitation type) affecting this relationship. Herein, a comprehensive investigation is presented on the temperature dependence of daily precipitation in various percentile ranges over the Qinghai–Tibet Plateau. The results show that 1) most stations exhibit a peaklike scaling structure, while the northeast part and south margin of the plateau exhibit monotonic positive and negative scaling structures, respectively. The scaling structure is associated with the precipitation type, and 2) the positive and negative scaling rates exhibit similar spatial patterns, with stronger (weaker) sensitivity in the south (north) part of the plateau. The overall increase rate of daily precipitation with temperature is scaled by Clausius–Clapeyron relationship. 3) The higher percentile of daily precipitation shows a larger positive scaling rate than the lower percentile. 4) The peak-point temperature is closely related to the local temperature, and the regional peak-point temperature is roughly around 10°C. This study aims to better understand the relationship between precipitation and surface air temperature in various percentile ranges over the Qinghai–Tibet Plateau. This is important because percentile-based regression not only accurately describes the response of precipitation to warming temperature but also provides a simple but effective framework for investigating other factors (precipitation type) that may be affecting this relationship. Furthermore, the sensitivity and peak-point temperature are evaluated and compared among different regions and percentile ranges; this study also attempts to outline their influencing factors. To our knowledge, this study is the first integration of percentile-based analysis of the dependence of daily precipitation on surface air temperature.
{"title":"Percentile-Based Relationship between Daily Precipitation and Surface Air Temperature over the Qinghai–Tibet Plateau","authors":"Yongliang Jiao, Ren Li, Tonghua Wu, Lin Zhao, Xiaodong Wu, Junjie Ma, Jimin Yao, G. Hu, Yao Xiao, Shuhua Yang, Wenhao Liu, Y. Qiao, Jianzong Shi, E. Du, Xiaofan Zhu, Shenning Wang","doi":"10.1175/jhm-d-22-0152.1","DOIUrl":"https://doi.org/10.1175/jhm-d-22-0152.1","url":null,"abstract":"\u0000Climate changes significantly impact the hydrological cycle. Precipitation is one of the most important atmospheric inputs to the terrestrial hydrologic system, and its variability considerably influences environmental and socioeconomic development. Atmospheric warming intensifies the hydrological cycle, increasing both atmospheric water vapor concentration and global precipitation. The relationship between heavy precipitation and temperature has been extensively investigated in literature. However, the relationship in different percentile ranges has not been thoroughly analyzed. Moreover, a percentile-based regression provides a simple but effective framework for investigation into other factors (precipitation type) affecting this relationship. Herein, a comprehensive investigation is presented on the temperature dependence of daily precipitation in various percentile ranges over the Qinghai–Tibet Plateau. The results show that 1) most stations exhibit a peaklike scaling structure, while the northeast part and south margin of the plateau exhibit monotonic positive and negative scaling structures, respectively. The scaling structure is associated with the precipitation type, and 2) the positive and negative scaling rates exhibit similar spatial patterns, with stronger (weaker) sensitivity in the south (north) part of the plateau. The overall increase rate of daily precipitation with temperature is scaled by Clausius–Clapeyron relationship. 3) The higher percentile of daily precipitation shows a larger positive scaling rate than the lower percentile. 4) The peak-point temperature is closely related to the local temperature, and the regional peak-point temperature is roughly around 10°C.\u0000\u0000\u0000This study aims to better understand the relationship between precipitation and surface air temperature in various percentile ranges over the Qinghai–Tibet Plateau. This is important because percentile-based regression not only accurately describes the response of precipitation to warming temperature but also provides a simple but effective framework for investigating other factors (precipitation type) that may be affecting this relationship. Furthermore, the sensitivity and peak-point temperature are evaluated and compared among different regions and percentile ranges; this study also attempts to outline their influencing factors. To our knowledge, this study is the first integration of percentile-based analysis of the dependence of daily precipitation on surface air temperature.\u0000","PeriodicalId":15962,"journal":{"name":"Journal of Hydrometeorology","volume":"7 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82637244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohamed Saadi, C. Furusho‐Percot, Alexandre Belleflamme, S. Trömel, S. Kollet, R. Reinoso-Rondinel
Quantitative precipitation nowcasts (QPN) can improve the accuracy of flood forecasts especially for lead times up to 12 hours, but their evaluation depends on a variety of factors, namely the choice of the hydrological model and the benchmark. We tested three precipitation nowcasting techniques based on radar observations for the disastrous mid-July 2021 event in seven German catchments (140-1670 km2). Two deterministic (advection-based and S-PROG) and one probabilistic (STEPS) QPN with maximum lead time of 3 h were used as input to two hydrological models: a physically-based, 3D-distributed model (ParFlowCLM) and a conceptual, lumped model (GR4H). We quantified the hydrological added value of QPN compared to hydrological persistence and zero-precipitation nowcasts as benchmarks. For the 14 July 2021 event, we obtained the following key results: (1) According to the quality of the forecasted hydrographs, exploiting QPN improved the lead times by up to 4 h (8 h) compared to adopting zero-precipitation nowcasts (hydrological persistence) as a benchmark. Using a skill-based approach, obtained improvements were up to 7-12 h depending on the benchmark. (2) The three QPN techniques obtained similar performances regardless of the applied hydrological model. (3) Using zero-precipitation nowcasts instead of hydrological persistence as benchmark reduced the added value of QPN. These results highlight the need for combining a skill-based approach with an analysis of the quality of forecasted hydrographs to rigorously estimate the added value of QPN.
{"title":"Comparison of three radar-based precipitation nowcasts for the extreme July 2021 flooding event in Germany","authors":"Mohamed Saadi, C. Furusho‐Percot, Alexandre Belleflamme, S. Trömel, S. Kollet, R. Reinoso-Rondinel","doi":"10.1175/jhm-d-22-0121.1","DOIUrl":"https://doi.org/10.1175/jhm-d-22-0121.1","url":null,"abstract":"\u0000Quantitative precipitation nowcasts (QPN) can improve the accuracy of flood forecasts especially for lead times up to 12 hours, but their evaluation depends on a variety of factors, namely the choice of the hydrological model and the benchmark. We tested three precipitation nowcasting techniques based on radar observations for the disastrous mid-July 2021 event in seven German catchments (140-1670 km2). Two deterministic (advection-based and S-PROG) and one probabilistic (STEPS) QPN with maximum lead time of 3 h were used as input to two hydrological models: a physically-based, 3D-distributed model (ParFlowCLM) and a conceptual, lumped model (GR4H). We quantified the hydrological added value of QPN compared to hydrological persistence and zero-precipitation nowcasts as benchmarks. For the 14 July 2021 event, we obtained the following key results: (1) According to the quality of the forecasted hydrographs, exploiting QPN improved the lead times by up to 4 h (8 h) compared to adopting zero-precipitation nowcasts (hydrological persistence) as a benchmark. Using a skill-based approach, obtained improvements were up to 7-12 h depending on the benchmark. (2) The three QPN techniques obtained similar performances regardless of the applied hydrological model. (3) Using zero-precipitation nowcasts instead of hydrological persistence as benchmark reduced the added value of QPN. These results highlight the need for combining a skill-based approach with an analysis of the quality of forecasted hydrographs to rigorously estimate the added value of QPN.","PeriodicalId":15962,"journal":{"name":"Journal of Hydrometeorology","volume":"7 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83598568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Drought monitoring is critical for managing agriculture and water resources and for triggering state emergency response plans and hazard mitigation activities. Fixed thresholds serve as guidelines for the United States Drought Monitor (USDM). However, fixed drought thresholds (i.e., using the same threshold in all seasons and climate regions) may not properly reflect local conditions and impacts. Therefore, this study develops impacts-based drought thresholds that are appropriate for drought monitoring in Ohio. We examined four drought indices that are currently used by the State of Ohio: Standardized Precipitation Index (SPI), Standardized Precipitation-Evapotranspiration Index (SPEI), Palmer’s Z-Index and Palmer Hydrological Drought Index (PHDI). Streamflow and corn yield are used as indicators of hydrological and agricultural drought impacts, respectively. Our results show that fixed thresholds tend to indicate milder drought conditions in Ohio, while the proposed impacts-based drought thresholds are more sensitive to exceptional drought (D4) conditions. The area percentage of D4 based on impacts-based drought thresholds is more strongly correlated with corn yield and streamflow. This study provides a methodology for developing local impacts-based drought thresholds that can be applied to other regions where long-term drought impact records exist to provide regionally representative depictions of conditions and improve drought monitoring.
{"title":"Developing Impacts-Based Drought Thresholds for Ohio","authors":"Ning Zhang, Zhiying Li, S. Quiring","doi":"10.1175/jhm-d-22-0054.1","DOIUrl":"https://doi.org/10.1175/jhm-d-22-0054.1","url":null,"abstract":"\u0000Drought monitoring is critical for managing agriculture and water resources and for triggering state emergency response plans and hazard mitigation activities. Fixed thresholds serve as guidelines for the United States Drought Monitor (USDM). However, fixed drought thresholds (i.e., using the same threshold in all seasons and climate regions) may not properly reflect local conditions and impacts. Therefore, this study develops impacts-based drought thresholds that are appropriate for drought monitoring in Ohio. We examined four drought indices that are currently used by the State of Ohio: Standardized Precipitation Index (SPI), Standardized Precipitation-Evapotranspiration Index (SPEI), Palmer’s Z-Index and Palmer Hydrological Drought Index (PHDI). Streamflow and corn yield are used as indicators of hydrological and agricultural drought impacts, respectively. Our results show that fixed thresholds tend to indicate milder drought conditions in Ohio, while the proposed impacts-based drought thresholds are more sensitive to exceptional drought (D4) conditions. The area percentage of D4 based on impacts-based drought thresholds is more strongly correlated with corn yield and streamflow. This study provides a methodology for developing local impacts-based drought thresholds that can be applied to other regions where long-term drought impact records exist to provide regionally representative depictions of conditions and improve drought monitoring.","PeriodicalId":15962,"journal":{"name":"Journal of Hydrometeorology","volume":"29 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89448182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hong Wang, F. Sun, Fa Liu, Tingting Wang, Yao Feng, Wenbin Liu
The most basic features of climatological normals and variability are useful for describing observed or likely future climate fluctuations. Pan evaporation (Epan) is an important indicator of climate change; however, current research on Epan has focused on its change in mean rather than its variability. The variability of monthly Epan from 1961 to 2020 at 969 stations in China was analyzed using a theoretical framework that can distinguish changes in Epan variance between space and time. The Epan variance was decomposed into spatial and temporal components, and the temporal component was further decomposed into inter-annual and intra-annual components. The results show that the variance in Epan was mainly controlled by the temporal component. The time variance was mainly controlled by intra-annual variance, decreasing continuously in the first 30 years, and slightly increasing after the 1990s. This is mainly due to the fact that the decrease of wind speed and the increase of water vapor pressure deficit with the temperature increase offset each other and inhibit the variability of Epan. The variance decreased more in the northern region, whereas it exhibited a small decrease or slight increase in the southern region. The reduction in seasonality was dominated by spring, followed by summer. The differences in Epan variability in space and season were mainly caused by the differing rates of change in evaporation driving forces, such as a greater reduction in wind speed in the northern region and spring.
{"title":"The variability of pan evaporation over China during 1961-2020","authors":"Hong Wang, F. Sun, Fa Liu, Tingting Wang, Yao Feng, Wenbin Liu","doi":"10.1175/jhm-d-22-0232.1","DOIUrl":"https://doi.org/10.1175/jhm-d-22-0232.1","url":null,"abstract":"\u0000The most basic features of climatological normals and variability are useful for describing observed or likely future climate fluctuations. Pan evaporation (Epan) is an important indicator of climate change; however, current research on Epan has focused on its change in mean rather than its variability. The variability of monthly Epan from 1961 to 2020 at 969 stations in China was analyzed using a theoretical framework that can distinguish changes in Epan variance between space and time. The Epan variance was decomposed into spatial and temporal components, and the temporal component was further decomposed into inter-annual and intra-annual components. The results show that the variance in Epan was mainly controlled by the temporal component. The time variance was mainly controlled by intra-annual variance, decreasing continuously in the first 30 years, and slightly increasing after the 1990s. This is mainly due to the fact that the decrease of wind speed and the increase of water vapor pressure deficit with the temperature increase offset each other and inhibit the variability of Epan. The variance decreased more in the northern region, whereas it exhibited a small decrease or slight increase in the southern region. The reduction in seasonality was dominated by spring, followed by summer. The differences in Epan variability in space and season were mainly caused by the differing rates of change in evaporation driving forces, such as a greater reduction in wind speed in the northern region and spring.","PeriodicalId":15962,"journal":{"name":"Journal of Hydrometeorology","volume":"27 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87474030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anthropogenic land-use change, irrigation, is considered to strongly modulate the hydroclimate at the regional scale by directly triggering evaporative cooling as the preliminary local effect. However, subsequent interactions with the background climate are highly nonlinear, which introduces diverse and unexpected consequences. The North China Plain (NCP) is one of the regions where irrigation has expanded most rapidly since the 20th century. The scarce rainfall in this region makes it necessary for irrigation to supplement the level of soil water for agricultural production. In this study, we quantify the effect of irrigation on the regional climate in China. Two regional climate models, WRF and RegCM, are used to mimic the large-scale practice of irrigation on the NCP. The results of our experiments show consistent cooling and moistening effects centered over the NCP across all experiments. Although the moisture budget and wind field pattern demonstrate that the vertical downdraft and low-level divergence could inhibit rainfall, the humidification dominates the climatic response in the dry April-May-June and increases the amount of precipitation significantly and consistently in the NCP region and the surrounding area in northern China. The enhanced CAPE increase sharply on some ‘calm days’ when the vertical moisture advection is small, especially during afternoon, triggering frequent light rains convectively by destabilizing the atmosphere. The consistent response to irrigation in two different models that employ structurally different land surface schemes could enhance the robustness of the physical mechanism behind the precipitation increase in the heavily irrigated region of NCP.
{"title":"An increase in precipitation driven by irrigation over the North China Plain based on RegCM and WRF simulations","authors":"Yuwen Fan, E. Im, C. Lan, M. Lo","doi":"10.1175/jhm-d-22-0131.1","DOIUrl":"https://doi.org/10.1175/jhm-d-22-0131.1","url":null,"abstract":"Anthropogenic land-use change, irrigation, is considered to strongly modulate the hydroclimate at the regional scale by directly triggering evaporative cooling as the preliminary local effect. However, subsequent interactions with the background climate are highly nonlinear, which introduces diverse and unexpected consequences. The North China Plain (NCP) is one of the regions where irrigation has expanded most rapidly since the 20th century. The scarce rainfall in this region makes it necessary for irrigation to supplement the level of soil water for agricultural production. In this study, we quantify the effect of irrigation on the regional climate in China. Two regional climate models, WRF and RegCM, are used to mimic the large-scale practice of irrigation on the NCP. The results of our experiments show consistent cooling and moistening effects centered over the NCP across all experiments. Although the moisture budget and wind field pattern demonstrate that the vertical downdraft and low-level divergence could inhibit rainfall, the humidification dominates the climatic response in the dry April-May-June and increases the amount of precipitation significantly and consistently in the NCP region and the surrounding area in northern China. The enhanced CAPE increase sharply on some ‘calm days’ when the vertical moisture advection is small, especially during afternoon, triggering frequent light rains convectively by destabilizing the atmosphere. The consistent response to irrigation in two different models that employ structurally different land surface schemes could enhance the robustness of the physical mechanism behind the precipitation increase in the heavily irrigated region of NCP.","PeriodicalId":15962,"journal":{"name":"Journal of Hydrometeorology","volume":"1 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80826502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Longwave radiation (LR) is one of the energy balance components responsible for warming and cooling water during hot summers. Both downward incoming LR, emitted by the atmosphere, and outgoing LR emitted by land surface are not widely measured. The influence of clouds on the LR heat budget makes it even harder to establish reliable formulations for all-sky conditions. This paper uses air temperature and cloud cover from the ERA5 reanalysis database to compare 20 models for the downward longwave irradiance (DLI) at the Earth’s surface and compare them with ERA5’s DLI product. Our work uses long-time continuous DLI measured data at three stations over Canada, and ERA5 reanalysis, a reliable source for data-scarce regions, such as central British Columbia (Canada). The results show the feasibility of the local calibration of different formulations using ERA5 reanalysis data for all-sky conditions with RMSE metrics ranging from 37.1 to , which is comparable with ERA5 reanalysis data and can easily be applied at broader scales by implementing it into hydrological models. Moreover, it is shown that ERA5 gridded data for DLI shows the best results with . This higher performance suggests using ERA5 data directly as input data for hydrological and ecological models.
{"title":"Assessing the surface downward longwave irradiance models using ERA5 input data in Canada","authors":"","doi":"10.1175/jhm-d-22-0184.1","DOIUrl":"https://doi.org/10.1175/jhm-d-22-0184.1","url":null,"abstract":"\u0000Longwave radiation (LR) is one of the energy balance components responsible for warming and cooling water during hot summers. Both downward incoming LR, emitted by the atmosphere, and outgoing LR emitted by land surface are not widely measured. The influence of clouds on the LR heat budget makes it even harder to establish reliable formulations for all-sky conditions. This paper uses air temperature and cloud cover from the ERA5 reanalysis database to compare 20 models for the downward longwave irradiance (DLI) at the Earth’s surface and compare them with ERA5’s DLI product. Our work uses long-time continuous DLI measured data at three stations over Canada, and ERA5 reanalysis, a reliable source for data-scarce regions, such as central British Columbia (Canada). The results show the feasibility of the local calibration of different formulations using ERA5 reanalysis data for all-sky conditions with RMSE metrics ranging from 37.1 to \u0000, which is comparable with ERA5 reanalysis data and can easily be applied at broader scales by implementing it into hydrological models. Moreover, it is shown that ERA5 gridded data for DLI shows the best results with . This higher performance suggests using ERA5 data directly as input data for hydrological and ecological models.","PeriodicalId":15962,"journal":{"name":"Journal of Hydrometeorology","volume":"192 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83069160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Chug, F. Dominguez, C. Taylor, C. Klein, S. Nesbitt
Soil moisture-precipitation (SM-PPT) feedbacks at the mesoscale represent a major challenge for numerical weather prediction, especially for subtropical regions that exhibit large variability in surface SM. How does surface heterogeneity, specifically mesoscale gradients in SM and land surface temperature (LST), affect convective initiation (CI) over South America? Using satellite data, we track nascent, daytime convective clouds and quantify the underlying antecedent (morning) surface heterogeneity. We find that convection initiates preferentially on the dry side of strong SM/LST boundaries with spatial scales of tens of kilometers. The strongest alongwind gradients in LST anomalies at 30 km length scale underlying the CI location occur during weak background low-level wind (<2.5m/s), high convective available potential energy (>1500J/kg) and low convective inhibition (<250J/kg) over sparse vegetation. At 100 km scale, strong gradients occur at the CI location during convectively unfavorable conditions and strong background flow. The location of PPT is strongly sensitive to the strength of the background flow. The wind profile during weak background flow inhibits propagation of convection away from the dry regions leading to negative SM-PPT feedback whereas strong background flow is related to longer lifecycle and rainfall hundreds of kilometers away from the CI location. Thus, the sign of the SM-PPT feedback is dependent on the background flow. This work presents the first observational evidence that CI over subtropical South America is associated with dry soil patches on the order of tens of kilometers. Convection-permitting numerical weather prediction models need to be examined for accurately capturing the effect of SM heterogeneity in initiating convection over such semi-arid regions.
{"title":"Dry-to-Wet Soil Gradients Enhance Convection and Rainfall over Subtropical South America","authors":"D. Chug, F. Dominguez, C. Taylor, C. Klein, S. Nesbitt","doi":"10.1175/jhm-d-23-0031.1","DOIUrl":"https://doi.org/10.1175/jhm-d-23-0031.1","url":null,"abstract":"Soil moisture-precipitation (SM-PPT) feedbacks at the mesoscale represent a major challenge for numerical weather prediction, especially for subtropical regions that exhibit large variability in surface SM. How does surface heterogeneity, specifically mesoscale gradients in SM and land surface temperature (LST), affect convective initiation (CI) over South America? Using satellite data, we track nascent, daytime convective clouds and quantify the underlying antecedent (morning) surface heterogeneity. We find that convection initiates preferentially on the dry side of strong SM/LST boundaries with spatial scales of tens of kilometers. The strongest alongwind gradients in LST anomalies at 30 km length scale underlying the CI location occur during weak background low-level wind (<2.5m/s), high convective available potential energy (>1500J/kg) and low convective inhibition (<250J/kg) over sparse vegetation. At 100 km scale, strong gradients occur at the CI location during convectively unfavorable conditions and strong background flow. The location of PPT is strongly sensitive to the strength of the background flow. The wind profile during weak background flow inhibits propagation of convection away from the dry regions leading to negative SM-PPT feedback whereas strong background flow is related to longer lifecycle and rainfall hundreds of kilometers away from the CI location. Thus, the sign of the SM-PPT feedback is dependent on the background flow. This work presents the first observational evidence that CI over subtropical South America is associated with dry soil patches on the order of tens of kilometers. Convection-permitting numerical weather prediction models need to be examined for accurately capturing the effect of SM heterogeneity in initiating convection over such semi-arid regions.","PeriodicalId":15962,"journal":{"name":"Journal of Hydrometeorology","volume":"54 11 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83406858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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