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Abstract
The Madden–Julian oscillation (MJO) is a unique type of organized tropical convection varying primarily on subseasonal time scales and is recognized as an important source of subseasonal predictability for midlatitude weather phenomena. This study provides observational evidence of MJO impacts on precipitation extreme intensity, frequency, and duration over the western United States. The results suggest a robust increase in precipitation extremes, especially in frequency, relative to climatological conditions over most of the western United States when the MJO is in its western Pacific phases during the extended boreal winter (October–March). Opposite changes are observed when the MJO is located over the Indian Ocean and Maritime Continent. The above MJO influence is characterized by strong seasonality, with the increase in extreme frequency mainly found in late autumn/early winter (OND) over California and a weaker or opposite response found in late winter (JFM). Also, MJO impacts have stronger regional consistency and persist for a longer time in OND compared to JFM. The seasonality of MJO impacts largely originates from the different amplitudes and patterns of both the MJO and basic states that are weaker and located/retreated more northwestward in OND than in JFM. This leads to different responses in MJO teleconnections including moisture transport and AR activity that contribute to the different precipitation extreme changes. The strong seasonality of the relationship between the MJO and western U.S. extreme precipitation shown in this study has implications to the source of subseasonal-to-seasonal predictions, which has a potential value to stakeholders including water resource managers.
Abstract
The Madden–Julian oscillation (MJO) is a unique type of organized tropical convection varying primarily on subseasonal time scales and is recognized as an important source of subseasonal predictability for midlatitude weather phenomena. This study provides observational evidence of MJO impacts on precipitation extreme intensity, frequency, and duration over the western United States. The results suggest a robust increase in precipitation extremes, especially in frequency, relative to climatological conditions over most of the western United States when the MJO is in its western Pacific phases during the extended boreal winter (October–March). Opposite changes are observed when the MJO is located over the Indian Ocean and Maritime Continent. The above MJO influence is characterized by strong seasonality, with the increase in extreme frequency mainly found in late autumn/early winter (OND) over California and a weaker or opposite response found in late winter (JFM). Also, MJO impacts have stronger regional consistency and persist for a longer time in OND compared to JFM. The seasonality of MJO impacts largely originates from the different amplitudes and patterns of both the MJO and basic states that are weaker and located/retreated more northwestward in OND than in JFM. This leads to different responses in MJO teleconnections including moisture transport and AR activity that contribute to the different precipitation extreme changes. The strong seasonality of the relationship between the MJO and western U.S. extreme precipitation shown in this study has implications to the source of subseasonal-to-seasonal predictions, which has a potential value to stakeholders including water resource managers.
Abstract
Parameterization schemes such as soil thermal conductivity (STC) have an important impact on precipitation simulation. The precipitation in the rainy season (April–September) is the main factor affecting aridification in northern China. However, it is unclear how STC affects precipitation simulation during the rainy season. In this study, comparative experiments were conducted using the regional climate model RegCM4.6 coupled with the third-generation land surface model NCAR CLM4.5 to assess the effect of the Johansen and Lu–Ren STC schemes on precipitation. The results show that the STC had a significant effect on the simulation of rainy season precipitation and its variation in northern China. The precipitation variation characteristics simulated by the Lu–Ren scheme were closer than that of the Johansen scheme to the observation. The difference in land surface temperatures (LSTs) simulated by the two STC schemes could be a major cause of the sensitivity in the simulated precipitation. When the local LST increases by 1 K, precipitation decreases by 5–30 mm in most areas of northern China. The numerical experiments revealed that the rise of LST increases the longwave radiation, reduces the surface net radiation, and causes the redistribution of sensible and latent heat flux, forming local water vapor and thermal conditions that are not conducive to precipitation. Moreover, the difference of LST significantly changes the 500-hPa large-scale circulation field, the 700-hPa vapor transportation, and its divergence. The combined action of local heat, water vapor, and large-scale circulation factors reduces the precipitation in the rainy season. On the other side, the variation of the East Asia summer monsoon (EASM) affects the soil water content. In addition, a new STC scheme was added to NCAR CLM4.5, promoting the development of this land surface model.
Abstract
Parameterization schemes such as soil thermal conductivity (STC) have an important impact on precipitation simulation. The precipitation in the rainy season (April–September) is the main factor affecting aridification in northern China. However, it is unclear how STC affects precipitation simulation during the rainy season. In this study, comparative experiments were conducted using the regional climate model RegCM4.6 coupled with the third-generation land surface model NCAR CLM4.5 to assess the effect of the Johansen and Lu–Ren STC schemes on precipitation. The results show that the STC had a significant effect on the simulation of rainy season precipitation and its variation in northern China. The precipitation variation characteristics simulated by the Lu–Ren scheme were closer than that of the Johansen scheme to the observation. The difference in land surface temperatures (LSTs) simulated by the two STC schemes could be a major cause of the sensitivity in the simulated precipitation. When the local LST increases by 1 K, precipitation decreases by 5–30 mm in most areas of northern China. The numerical experiments revealed that the rise of LST increases the longwave radiation, reduces the surface net radiation, and causes the redistribution of sensible and latent heat flux, forming local water vapor and thermal conditions that are not conducive to precipitation. Moreover, the difference of LST significantly changes the 500-hPa large-scale circulation field, the 700-hPa vapor transportation, and its divergence. The combined action of local heat, water vapor, and large-scale circulation factors reduces the precipitation in the rainy season. On the other side, the variation of the East Asia summer monsoon (EASM) affects the soil water content. In addition, a new STC scheme was added to NCAR CLM4.5, promoting the development of this land surface model.
Abstract
The Las Vegas metropolitan area in Nevada has experienced extensive urban growth since 1950 coincident with regional and local climate change. This study explores the nonstationary flood history of the Las Vegas Wash (LVW) watershed by deconstructing it into its constituent physical drivers. Observations and reanalysis products are used to examine the hydroclimatology, hydrometeorology, and hydrology of flash flooding in the watershed. Annual peak flows have increased nonlinearly over the past seven decades, with an abrupt changepoint detected in the mid-1990s, which is attributed to the implementation of flood conveyance systems rather than changes in land use. The LVW watershed exhibits two pronounced flood seasons, associated with distinct synoptic atmospheric circulations: winter floods linked to inland-penetrating atmospheric rivers and summer floods linked to the North American monsoon. El Niño–Southern Oscillation also plays a role in modulating extreme rainfall and the resultant floods because annual maximum daily rainfall totals positively correlate with El Niño, with Spearman’s correlation coefficient of 0.36 (p value < 0.05). Winter maximum daily rainfall totals have increased since 1950, whereas summer daily rainfall maxima have decreased. The trends in hydrometeorological drivers interact with urbanization to shift flood seasonality toward more frequent winter floods in the LVW watershed. A process-based understanding of the flood hydrology of the watershed also provides insights into flood frequency analysis and flood forecasting.
Abstract
The Las Vegas metropolitan area in Nevada has experienced extensive urban growth since 1950 coincident with regional and local climate change. This study explores the nonstationary flood history of the Las Vegas Wash (LVW) watershed by deconstructing it into its constituent physical drivers. Observations and reanalysis products are used to examine the hydroclimatology, hydrometeorology, and hydrology of flash flooding in the watershed. Annual peak flows have increased nonlinearly over the past seven decades, with an abrupt changepoint detected in the mid-1990s, which is attributed to the implementation of flood conveyance systems rather than changes in land use. The LVW watershed exhibits two pronounced flood seasons, associated with distinct synoptic atmospheric circulations: winter floods linked to inland-penetrating atmospheric rivers and summer floods linked to the North American monsoon. El Niño–Southern Oscillation also plays a role in modulating extreme rainfall and the resultant floods because annual maximum daily rainfall totals positively correlate with El Niño, with Spearman’s correlation coefficient of 0.36 (p value < 0.05). Winter maximum daily rainfall totals have increased since 1950, whereas summer daily rainfall maxima have decreased. The trends in hydrometeorological drivers interact with urbanization to shift flood seasonality toward more frequent winter floods in the LVW watershed. A process-based understanding of the flood hydrology of the watershed also provides insights into flood frequency analysis and flood forecasting.
Abstract
An ideal spatial interpolation approach is indispensable for obtaining high-quality gridded climatic data in mountainous regions with scarce observations, particularly for the Hengduan Mountains Region (HMR) with dense longitudinal ranges and gorges. However, there is much controversy about the applicability of thin plate smooth spline (TPSS), cokriging, and inverse distance weighting (IDW) in mountainous regions. Here, we use the daily observations of temperature and precipitation at 125 stations in HMR and its surroundings from 1961 to 2018 and adopt three interpolation methods to map the annual average temperature and precipitation at a resolution of 500 m in HMR. Then, we assess the applicability of three interpolation methods in HMR from the perspectives of interpolation accuracy and effects. The evaluation implies a satisfactory interpolation accuracy of TPSS with the highest correlation and lowest error, whether for temperature (R2 = 0.92, RMSE = 1.2°C) or precipitation (R2 = 0.54, RMSE = 165.9 mm). In addition, the TPSS could better display the temperature (precipitation) gradient along elevation and depict dry valleys’ high-temperature and low-precipitation characteristics. Moreover, the satisfactory interpolation performance of TPSS mainly benefits from the screening of optimal TPSS model that varied primarily with the regional topography feature and meteorological observation density. The uncertainty of gridded climate datasets has become an urgent problem to solve in the complex terrain. This research illustrates the satisfactory applicability of TPSS for climatic spatial interpolation in HMR, providing theoretical support for high-precision interpolation in complex terrain, hopefully improving the regional weather forecasts and disaster warnings.
Abstract
An ideal spatial interpolation approach is indispensable for obtaining high-quality gridded climatic data in mountainous regions with scarce observations, particularly for the Hengduan Mountains Region (HMR) with dense longitudinal ranges and gorges. However, there is much controversy about the applicability of thin plate smooth spline (TPSS), cokriging, and inverse distance weighting (IDW) in mountainous regions. Here, we use the daily observations of temperature and precipitation at 125 stations in HMR and its surroundings from 1961 to 2018 and adopt three interpolation methods to map the annual average temperature and precipitation at a resolution of 500 m in HMR. Then, we assess the applicability of three interpolation methods in HMR from the perspectives of interpolation accuracy and effects. The evaluation implies a satisfactory interpolation accuracy of TPSS with the highest correlation and lowest error, whether for temperature (R2 = 0.92, RMSE = 1.2°C) or precipitation (R2 = 0.54, RMSE = 165.9 mm). In addition, the TPSS could better display the temperature (precipitation) gradient along elevation and depict dry valleys’ high-temperature and low-precipitation characteristics. Moreover, the satisfactory interpolation performance of TPSS mainly benefits from the screening of optimal TPSS model that varied primarily with the regional topography feature and meteorological observation density. The uncertainty of gridded climate datasets has become an urgent problem to solve in the complex terrain. This research illustrates the satisfactory applicability of TPSS for climatic spatial interpolation in HMR, providing theoretical support for high-precision interpolation in complex terrain, hopefully improving the regional weather forecasts and disaster warnings.
Abstract
Portions of the northeastern United States (NE) have experienced drought every year since 2016. The U.S. Drought Monitor (USDM) has played an important role in drought characterization and management by providing weekly drought maps across the entire United States, including the NE. Unfortunately, the USDM lacks consistency between input variables leading to difficulties in defining boundaries between drought categories. This paper evaluates the National Water Model’s (NWM) ability to model streamflow and soil moisture, two important hydrological products that are frequently incorporated in drought indices. Using a 26-yr NWM retrospective simulation, comparisons were conducted between NWM output and observations of streamflow and soil moisture, as well as between drought categories derived from the NWM and observations and the USDM. Results indicate that NWM provides moderate predictions of streamflow at NE stations when comparing to historical observations, that NWM streamflow estimators are generally upwardly biased, and performance is worse at lower streamflow magnitudes. The NWM’s ability to predict soil moisture is worse than streamflow, with again a positive bias at most sites and strong variations in anomaly correlation across sites. When predicting drought categories, NWM streamflow is as strong a predictor of USDM drought categories as observed streamflow. Extending the NWM streamflow series using a maintenance of variance technique and only past records provides slight improvements over drought categories derived from the entire 26-yr retrospective simulation. Output from the NWM appears to have some skill in characterizing drought in the NE and provides a spatial resolution to improve the designation of drought boundaries.
Abstract
Portions of the northeastern United States (NE) have experienced drought every year since 2016. The U.S. Drought Monitor (USDM) has played an important role in drought characterization and management by providing weekly drought maps across the entire United States, including the NE. Unfortunately, the USDM lacks consistency between input variables leading to difficulties in defining boundaries between drought categories. This paper evaluates the National Water Model’s (NWM) ability to model streamflow and soil moisture, two important hydrological products that are frequently incorporated in drought indices. Using a 26-yr NWM retrospective simulation, comparisons were conducted between NWM output and observations of streamflow and soil moisture, as well as between drought categories derived from the NWM and observations and the USDM. Results indicate that NWM provides moderate predictions of streamflow at NE stations when comparing to historical observations, that NWM streamflow estimators are generally upwardly biased, and performance is worse at lower streamflow magnitudes. The NWM’s ability to predict soil moisture is worse than streamflow, with again a positive bias at most sites and strong variations in anomaly correlation across sites. When predicting drought categories, NWM streamflow is as strong a predictor of USDM drought categories as observed streamflow. Extending the NWM streamflow series using a maintenance of variance technique and only past records provides slight improvements over drought categories derived from the entire 26-yr retrospective simulation. Output from the NWM appears to have some skill in characterizing drought in the NE and provides a spatial resolution to improve the designation of drought boundaries.
Abstract
Using abundant rainfall gauge measurements and Global Precipitation Mission (GPM) data, spatial patterns of rainfall diurnal cycles and their seasonality over high mountain Asia (HMA) were examined. Spatial distributions of rainfall diurnal cycles over the HMA have a prominent seasonality regulated by circulations at different spatiotemporal scales, within which large regional contrasts are embedded. Rainfall diurnal variability is relatively weak in the premonsoon season, with larger amplitude over the western HMA, the southeastern HMA, as well as southern periphery regions, characterized by a dominant late afternoon to morning rainfall preference. The pattern of rainfall spatial distributions is closely related to the midlatitude westerlies. Both the mean rainfall and amplitudes of diurnal cycles become more pronounced with the advance of monsoon season but weaken during postmonsoon. The widespread late afternoon to night pattern over HMA migrating with seasonal atmospheric circulation is consistent with the lifetime of convective systems, which become active from the afternoon due to radiative heating and decay during the night. Stationary terrain-dependent night-to-morning rainfall patterns are visible in those east–west-orientated valleys over HMA and the Qaidam basin throughout the seasons. This salient geographical dependence is associated with local circulation produced by the strong differential thermal conditions over mountains and valleys, which can lift the warm moist air at the mouth of the valley and trigger nocturnal convection.
Significance Statement
The main purpose of this study is to explore how spatial patterns of rainfall diurnal cycles over high mountain Asia vary with the seasons. Our results show that the widespread late afternoon to night rainfall over high mountain Asia migrating with seasonal atmospheric circulation is consistent with the lifetime of convective systems. Stationary terrain-dependent night-to-morning rainfall patterns are visible in those east–west-orientated valleys over high mountain Asia and the Qaidam basin throughout the seasons. These results highlight the importance of large-scale atmospheric circulation and local circulation on precipitation, which is critical for water resources over high mountain Asia.
Abstract
Using abundant rainfall gauge measurements and Global Precipitation Mission (GPM) data, spatial patterns of rainfall diurnal cycles and their seasonality over high mountain Asia (HMA) were examined. Spatial distributions of rainfall diurnal cycles over the HMA have a prominent seasonality regulated by circulations at different spatiotemporal scales, within which large regional contrasts are embedded. Rainfall diurnal variability is relatively weak in the premonsoon season, with larger amplitude over the western HMA, the southeastern HMA, as well as southern periphery regions, characterized by a dominant late afternoon to morning rainfall preference. The pattern of rainfall spatial distributions is closely related to the midlatitude westerlies. Both the mean rainfall and amplitudes of diurnal cycles become more pronounced with the advance of monsoon season but weaken during postmonsoon. The widespread late afternoon to night pattern over HMA migrating with seasonal atmospheric circulation is consistent with the lifetime of convective systems, which become active from the afternoon due to radiative heating and decay during the night. Stationary terrain-dependent night-to-morning rainfall patterns are visible in those east–west-orientated valleys over HMA and the Qaidam basin throughout the seasons. This salient geographical dependence is associated with local circulation produced by the strong differential thermal conditions over mountains and valleys, which can lift the warm moist air at the mouth of the valley and trigger nocturnal convection.
Significance Statement
The main purpose of this study is to explore how spatial patterns of rainfall diurnal cycles over high mountain Asia vary with the seasons. Our results show that the widespread late afternoon to night rainfall over high mountain Asia migrating with seasonal atmospheric circulation is consistent with the lifetime of convective systems. Stationary terrain-dependent night-to-morning rainfall patterns are visible in those east–west-orientated valleys over high mountain Asia and the Qaidam basin throughout the seasons. These results highlight the importance of large-scale atmospheric circulation and local circulation on precipitation, which is critical for water resources over high mountain Asia.
