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- Author or Editor: Yang Hong x
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Abstract
Considerable progress has been made in understanding the internal eddy–mean flow feedback in the subseasonal variability of the North Atlantic Oscillation (NAO) during winter. Using daily atmospheric and oceanic reanalysis data, this study highlights the role of extratropical air–sea interaction in the NAO variability during autumn when the daily sea surface temperature (SST) variability is more active and eddy–mean flow interactions are still relevant. Our analysis shows that a horseshoe-like SST tripolar pattern in the North Atlantic Ocean, marked by a cold anomaly in the Gulf Stream and two warm anomalies to the south of the Gulf Stream and off the western coast of northern Europe, can induce a quasi-barotropic NAO-like atmospheric response through eddy-mediated processes. An initial southwest–northeast tripolar geopotential anomaly in the North Atlantic forces this horseshoe-like SST anomaly tripole. Then the SST anomalies, through surface heat flux exchange, alter the spatial patterns of the lower-tropospheric temperature and thus baroclinicity anomalies, which are manifested as the midlatitude baroclinicity shifted poleward and reduced baroclinicity poleward of 70°N. In response to such changes of the lower-level baroclinicity, anomalous synoptic eddy generation, eddy kinetic energy, and eddy momentum forcing in the midlatitudes all shift poleward. Meanwhile, the 10–30-day low-frequency anticyclonic wave activities in the high latitudes decrease significantly. We illustrate that both the latitudinal displacement of midlatitude synoptic eddy activities and intensity variation of high-latitude low-frequency wave activities contribute to inducing the NAO-like anomalies.
Abstract
Considerable progress has been made in understanding the internal eddy–mean flow feedback in the subseasonal variability of the North Atlantic Oscillation (NAO) during winter. Using daily atmospheric and oceanic reanalysis data, this study highlights the role of extratropical air–sea interaction in the NAO variability during autumn when the daily sea surface temperature (SST) variability is more active and eddy–mean flow interactions are still relevant. Our analysis shows that a horseshoe-like SST tripolar pattern in the North Atlantic Ocean, marked by a cold anomaly in the Gulf Stream and two warm anomalies to the south of the Gulf Stream and off the western coast of northern Europe, can induce a quasi-barotropic NAO-like atmospheric response through eddy-mediated processes. An initial southwest–northeast tripolar geopotential anomaly in the North Atlantic forces this horseshoe-like SST anomaly tripole. Then the SST anomalies, through surface heat flux exchange, alter the spatial patterns of the lower-tropospheric temperature and thus baroclinicity anomalies, which are manifested as the midlatitude baroclinicity shifted poleward and reduced baroclinicity poleward of 70°N. In response to such changes of the lower-level baroclinicity, anomalous synoptic eddy generation, eddy kinetic energy, and eddy momentum forcing in the midlatitudes all shift poleward. Meanwhile, the 10–30-day low-frequency anticyclonic wave activities in the high latitudes decrease significantly. We illustrate that both the latitudinal displacement of midlatitude synoptic eddy activities and intensity variation of high-latitude low-frequency wave activities contribute to inducing the NAO-like anomalies.
Abstract
Fire emissions from the Maritime Continent (MC) over the western tropical Pacific are strongly influenced by El Niño–Southern Oscillation (ENSO), posing various climate effects to the Earth system. In this study, we show that the historical biomass burning emissions of black carbon (BCbb) aerosol in the dry season from the MC are strengthened in El Niño years due to the dry conditions. The eastern Pacific type of El Niño exerts a stronger modulation in BCbb emissions over the MC region than the central Pacific type of El Niño. Based on simulations using the fully coupled Community Earth System Model (CESM), the impacts of increased BCbb emissions on ENSO variability and frequency are also investigated in this study. With BCbb emissions from the MC scaled up by a factor of 10, which enables the identification of climate response from the internal variability, the increased BCbb heats the local atmosphere and changes land–sea thermal contrast, which suppresses the westward transport of the eastern Pacific surface water. It leads to an increase in sea surface temperature in the eastern tropical Pacific, which further enhances ENSO variability and increases the frequency of extreme El Niño and La Niña events. This study highlights the potential role of BCbb emissions on extreme ENSO frequency, and this role may be increasingly important in the warming future with higher wildfire risks.
Abstract
Fire emissions from the Maritime Continent (MC) over the western tropical Pacific are strongly influenced by El Niño–Southern Oscillation (ENSO), posing various climate effects to the Earth system. In this study, we show that the historical biomass burning emissions of black carbon (BCbb) aerosol in the dry season from the MC are strengthened in El Niño years due to the dry conditions. The eastern Pacific type of El Niño exerts a stronger modulation in BCbb emissions over the MC region than the central Pacific type of El Niño. Based on simulations using the fully coupled Community Earth System Model (CESM), the impacts of increased BCbb emissions on ENSO variability and frequency are also investigated in this study. With BCbb emissions from the MC scaled up by a factor of 10, which enables the identification of climate response from the internal variability, the increased BCbb heats the local atmosphere and changes land–sea thermal contrast, which suppresses the westward transport of the eastern Pacific surface water. It leads to an increase in sea surface temperature in the eastern tropical Pacific, which further enhances ENSO variability and increases the frequency of extreme El Niño and La Niña events. This study highlights the potential role of BCbb emissions on extreme ENSO frequency, and this role may be increasingly important in the warming future with higher wildfire risks.
Abstract
Satellite-based precipitation estimates with high spatial and temporal resolution and large areal coverage provide a potential alternative source of forcing data for hydrological models in regions where conventional in situ precipitation measurements are not readily available. The La Plata basin in South America provides a good example of a case where the use of satellite-derived precipitation could be beneficial. This study evaluates basinwide precipitation estimates from 9 yr (1998–2006) of Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA; 3B42 V.6) through comparison with available gauged data and the Variable Infiltration Capacity (VIC) semidistributed hydrology model applied to the La Plata basin. In general, the TMPA estimates agreed well with the gridded gauge data at monthly time scales, most likely because of the monthly adjustment to gauges performed in TMPA. The agreement between TMPA and gauge precipitation estimates was reduced at daily time scales, particularly for high rain rates. The TMPA-driven hydrologic model simulations were able to capture the daily flooding events and to represent low flows, although peak flows tended to be biased upward. There was a good agreement between TMPA-driven simulated flows in terms of their reproduction of seasonal and interannual streamflow variability. This analysis shows that TMPA has potential for hydrologic forecasting in data-sparse regions.
Abstract
Satellite-based precipitation estimates with high spatial and temporal resolution and large areal coverage provide a potential alternative source of forcing data for hydrological models in regions where conventional in situ precipitation measurements are not readily available. The La Plata basin in South America provides a good example of a case where the use of satellite-derived precipitation could be beneficial. This study evaluates basinwide precipitation estimates from 9 yr (1998–2006) of Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA; 3B42 V.6) through comparison with available gauged data and the Variable Infiltration Capacity (VIC) semidistributed hydrology model applied to the La Plata basin. In general, the TMPA estimates agreed well with the gridded gauge data at monthly time scales, most likely because of the monthly adjustment to gauges performed in TMPA. The agreement between TMPA and gauge precipitation estimates was reduced at daily time scales, particularly for high rain rates. The TMPA-driven hydrologic model simulations were able to capture the daily flooding events and to represent low flows, although peak flows tended to be biased upward. There was a good agreement between TMPA-driven simulated flows in terms of their reproduction of seasonal and interannual streamflow variability. This analysis shows that TMPA has potential for hydrologic forecasting in data-sparse regions.
Abstract
Understanding spatiotemporal rainfall patterns in mountainous areas is of great importance for prevention of natural disasters such as flash floods and landslides. There is little knowledge about rainfall variability over historically underobserved complex terrains, however, and especially about the variations of hourly rainfall. In this study, the spatiotemporal variations of hourly rainfall in the Three Gorges region (TGR) of China are investigated with gauge and newly available radar data. The spatial pattern of hourly rainfall has been examined by a number of statistics, and they all show that the rainfall variations are time-scale and location dependent. In general, the northern TGR receives more-intense and longer-duration rainfall than do other parts of the TGR, and short-duration storms could occur in most of the TGR. For temporal variations, the summer diurnal cycle shifts from a morning peak in the west to a late-afternoon peak in the east while a mixed pattern of two peaks exists in the middle. In statistical terms, empirical model–based estimation indicates that the correlation scale of hourly rainfall is about 40 km. Further investigation shows that the correlation distance varies with season, from 30 km in the warm season to 60 km in the cold season. In addition, summer rainstorms extracted from radar rainfall data are characterized by short duration (6–8 h) and highly localized patterns (5–17 and 13–36 km in the minor and major directions, respectively). Overall, this research provides quantitative information about the rainfall regime in the TGR and shows that the combination of gauge and radar data is useful for characterizing the spatiotemporal pattern of storm rainfall over complex terrain.
Abstract
Understanding spatiotemporal rainfall patterns in mountainous areas is of great importance for prevention of natural disasters such as flash floods and landslides. There is little knowledge about rainfall variability over historically underobserved complex terrains, however, and especially about the variations of hourly rainfall. In this study, the spatiotemporal variations of hourly rainfall in the Three Gorges region (TGR) of China are investigated with gauge and newly available radar data. The spatial pattern of hourly rainfall has been examined by a number of statistics, and they all show that the rainfall variations are time-scale and location dependent. In general, the northern TGR receives more-intense and longer-duration rainfall than do other parts of the TGR, and short-duration storms could occur in most of the TGR. For temporal variations, the summer diurnal cycle shifts from a morning peak in the west to a late-afternoon peak in the east while a mixed pattern of two peaks exists in the middle. In statistical terms, empirical model–based estimation indicates that the correlation scale of hourly rainfall is about 40 km. Further investigation shows that the correlation distance varies with season, from 30 km in the warm season to 60 km in the cold season. In addition, summer rainstorms extracted from radar rainfall data are characterized by short duration (6–8 h) and highly localized patterns (5–17 and 13–36 km in the minor and major directions, respectively). Overall, this research provides quantitative information about the rainfall regime in the TGR and shows that the combination of gauge and radar data is useful for characterizing the spatiotemporal pattern of storm rainfall over complex terrain.
Abstract
Despite the severe impacts on Eurasian extreme weather, the mechanisms and causes of the “warm Arctic–cold Eurasia” (WACE) pattern and its opposite phase “cold Arctic–warm Eurasia” (CAWE) remain a subject of active debate. With a focus on subseasonal time scale, this study investigates the roles of atmospheric variability and Arctic sea ice in the variation of asymmetric WACE and CAWE patterns in the cold season. WACE (CAWE) patterns are predominantly driven by the temperature advection by anticyclonic (cyclonic) wave activity anomaly over Ural region. Low-frequency processes from both eddy vorticity and heat fluxes are important for the formation of the Ural wave activity anomaly. The subseasonal Arctic sea ice anomaly plays an additional role in maintaining the persistence of WACE and CAWE anomalies through surface heat flux exchange and alteration of Ural wave activity anomaly. Both comprehensive and idealized numerical experiments suggest that sea ice anomalies or thermal forcing act to maintain the WACE pattern by increasing the persistence of Ural anticyclonic anomaly through reducing background flow. The net effect of subseasonal thermal forcing on the WACE and CAWE anomalies is dependent on the mean state on longer time scale. We argue that the dominance of WACE over CAWE is mainly attributed to stronger roles of internal low-frequency atmospheric variability in driving the Ural anticyclonic anomaly and sea ice anomaly or thermal forcing in extending the persistence of the Ural anticyclonic anomaly through modulation on the background flow.
Significance Statement
The purpose of this study is to better understand the subseasonal variability of the “warm Arctic–cold Eurasia” (WACE) and “cold Arctic–warm Eurasia” (CAWE) patterns, which have severe impacts on Eurasian extreme weather. We highlight a dominance of WACE over CAWE, and attribute it to stronger roles of atmospheric variability in driving the WACE pattern and Arctic sea ice in maintaining the WACE anomalies. These findings have important implications for improving the subseasonal prediction of regional extremes.
Abstract
Despite the severe impacts on Eurasian extreme weather, the mechanisms and causes of the “warm Arctic–cold Eurasia” (WACE) pattern and its opposite phase “cold Arctic–warm Eurasia” (CAWE) remain a subject of active debate. With a focus on subseasonal time scale, this study investigates the roles of atmospheric variability and Arctic sea ice in the variation of asymmetric WACE and CAWE patterns in the cold season. WACE (CAWE) patterns are predominantly driven by the temperature advection by anticyclonic (cyclonic) wave activity anomaly over Ural region. Low-frequency processes from both eddy vorticity and heat fluxes are important for the formation of the Ural wave activity anomaly. The subseasonal Arctic sea ice anomaly plays an additional role in maintaining the persistence of WACE and CAWE anomalies through surface heat flux exchange and alteration of Ural wave activity anomaly. Both comprehensive and idealized numerical experiments suggest that sea ice anomalies or thermal forcing act to maintain the WACE pattern by increasing the persistence of Ural anticyclonic anomaly through reducing background flow. The net effect of subseasonal thermal forcing on the WACE and CAWE anomalies is dependent on the mean state on longer time scale. We argue that the dominance of WACE over CAWE is mainly attributed to stronger roles of internal low-frequency atmospheric variability in driving the Ural anticyclonic anomaly and sea ice anomaly or thermal forcing in extending the persistence of the Ural anticyclonic anomaly through modulation on the background flow.
Significance Statement
The purpose of this study is to better understand the subseasonal variability of the “warm Arctic–cold Eurasia” (WACE) and “cold Arctic–warm Eurasia” (CAWE) patterns, which have severe impacts on Eurasian extreme weather. We highlight a dominance of WACE over CAWE, and attribute it to stronger roles of atmospheric variability in driving the WACE pattern and Arctic sea ice in maintaining the WACE anomalies. These findings have important implications for improving the subseasonal prediction of regional extremes.
Abstract
The present study aims to evaluate three global satellite precipitation products [TMPA 3B42, version 7 (3B42 V7); TMPA 3B42 real time (3B42 RT); and Climate Prediction Center morphing technique (CMORPH)] during 2003–12 for multiscale hydrologic applications—including annual water budgeting, monthly and daily streamflow simulation, and extreme flood modeling—via a distributed hydrological model in the Yangtze River basin. The comparison shows that the 3B42 V7 data generally have a better performance in annual water budgeting and monthly streamflow simulation, but this superiority is not guaranteed for daily simulation, especially for flood monitoring. It is also found that, for annual water budgeting, the positive (negative) bias of the 3B42 RT (CMORPH) estimate is mainly propagated into the simulated runoff, and simulated evapotranspiration tends to be more sensitive to negative bias. Regarding streamflow simulation, both near-real-time products show a region-dependent bias: 3B42 RT tends to overestimate streamflow in the upper Yangtze River, and, in contrast, CMORPH shows serious underestimation in those downstream subbasins while it is able to effectively monitor streamflow into the Three Gorges Reservoir. Using 394 selected flood events, the results indicate that 3B42 RT and CMORPH have competitive performances for near-real-time flood monitoring in the upper Yangtze, but for those downstream subbasins, 3B42 RT seems to perform better than CMORPH. Furthermore, the inability of all satellite products to capture some key features of the July 2012 extreme floods reveals the deficiencies associated with them, which will limit their hydrologic utility in local flood monitoring.
Abstract
The present study aims to evaluate three global satellite precipitation products [TMPA 3B42, version 7 (3B42 V7); TMPA 3B42 real time (3B42 RT); and Climate Prediction Center morphing technique (CMORPH)] during 2003–12 for multiscale hydrologic applications—including annual water budgeting, monthly and daily streamflow simulation, and extreme flood modeling—via a distributed hydrological model in the Yangtze River basin. The comparison shows that the 3B42 V7 data generally have a better performance in annual water budgeting and monthly streamflow simulation, but this superiority is not guaranteed for daily simulation, especially for flood monitoring. It is also found that, for annual water budgeting, the positive (negative) bias of the 3B42 RT (CMORPH) estimate is mainly propagated into the simulated runoff, and simulated evapotranspiration tends to be more sensitive to negative bias. Regarding streamflow simulation, both near-real-time products show a region-dependent bias: 3B42 RT tends to overestimate streamflow in the upper Yangtze River, and, in contrast, CMORPH shows serious underestimation in those downstream subbasins while it is able to effectively monitor streamflow into the Three Gorges Reservoir. Using 394 selected flood events, the results indicate that 3B42 RT and CMORPH have competitive performances for near-real-time flood monitoring in the upper Yangtze, but for those downstream subbasins, 3B42 RT seems to perform better than CMORPH. Furthermore, the inability of all satellite products to capture some key features of the July 2012 extreme floods reveals the deficiencies associated with them, which will limit their hydrologic utility in local flood monitoring.
Abstract
Compound hazards are more destructive than the individual ones. Using observational and reanalysis datasets during 1960–2019, this study shows a remarkable concurrent relationship between extreme heatwaves (HWs) over southeastern coast of China (SECC) and tropical cyclone (TC) activities over western North Pacific (WNP). Overall, 70% of HWs co-occurred with TC activities (TC–HWs) in the past 60 years. Although the total frequency of TCs over WNP exhibited a decreasing trend, the occurrences of TC–HWs over SECC have been increasing, primarily due to the increasing HWs in the warming climate. In addition, TC–HWs are stronger and longer lasting than HWs that occur alone (AHWs). And in the long-term perspective, both AHWs and TC–HWs exhibit increasing trends, especially since the mid-1980s. The enhancement on HWs caused by TC activities is sustained until TCs make their landfalls and then collapse. Based on composite analysis, TC activities enhance HWs by modulating atmospheric circulations and triggering anomalous descending motion over southern China mainland which intensifies the western Pacific subtropical high (WPSH) and favors increased temperatures therein. Given the severe adverse impacts of TC–HWs on coastal populations, more research is needed to assess the future projections of TC–HWs, as HWs are expected to be more frequent and stronger as the climate warms, whereas TCs over WNP may occur less often.
Abstract
Compound hazards are more destructive than the individual ones. Using observational and reanalysis datasets during 1960–2019, this study shows a remarkable concurrent relationship between extreme heatwaves (HWs) over southeastern coast of China (SECC) and tropical cyclone (TC) activities over western North Pacific (WNP). Overall, 70% of HWs co-occurred with TC activities (TC–HWs) in the past 60 years. Although the total frequency of TCs over WNP exhibited a decreasing trend, the occurrences of TC–HWs over SECC have been increasing, primarily due to the increasing HWs in the warming climate. In addition, TC–HWs are stronger and longer lasting than HWs that occur alone (AHWs). And in the long-term perspective, both AHWs and TC–HWs exhibit increasing trends, especially since the mid-1980s. The enhancement on HWs caused by TC activities is sustained until TCs make their landfalls and then collapse. Based on composite analysis, TC activities enhance HWs by modulating atmospheric circulations and triggering anomalous descending motion over southern China mainland which intensifies the western Pacific subtropical high (WPSH) and favors increased temperatures therein. Given the severe adverse impacts of TC–HWs on coastal populations, more research is needed to assess the future projections of TC–HWs, as HWs are expected to be more frequent and stronger as the climate warms, whereas TCs over WNP may occur less often.
Abstract
Since China implemented the Air Pollution Prevention and Control Action Plan in 2013, the aerosol emissions in East Asia have been greatly reduced, while emissions in South Asia have continued to increase. This has led to a dipole pattern of aerosol emissions between South Asia and East Asia. Here, the East Asian summer monsoon (EASM) responses to the dipole changes in aerosol emissions during 2013–17 are investigated using the atmosphere model of Community Earth System Model version 2 (CESM2). We show that decreases in East Asian emissions alone lead to a positive aerosol effective radiative forcing (ERF) of 1.59 (±0.97) W m−2 over central-eastern China (25°–40°N, 105°–122.5°E), along with a 0.09 (±0.07)°C warming in summer during 2013–17. The warming intensified the land–sea thermal contrast and increased the rainfall by 0.32 (±0.16) mm day−1. When considering both the emission reductions in East Asia and increases in South Asia, the ERF is increased to 3.39 (±0.89) W m−2, along with an enhanced warming of 0.20 (±0.08)°C over central-eastern China, while the rainfall insignificant decreased by 0.07 (±0.16) mm day−1. It is due to the westward shift of the strengthened western Pacific subtropical high, linked to the increase in black carbon in South Asia. Based on multiple EASM indices, the reductions in aerosol emissions from East Asia alone increased the EASM strength by almost 5%. Considering the effect of the westward shift of WPSH, the dipole changes in emissions together increased the EASM by 5%–15% during 2013–17, revealing an important role of South Asian aerosols in changing the East Asian climate.
Abstract
Since China implemented the Air Pollution Prevention and Control Action Plan in 2013, the aerosol emissions in East Asia have been greatly reduced, while emissions in South Asia have continued to increase. This has led to a dipole pattern of aerosol emissions between South Asia and East Asia. Here, the East Asian summer monsoon (EASM) responses to the dipole changes in aerosol emissions during 2013–17 are investigated using the atmosphere model of Community Earth System Model version 2 (CESM2). We show that decreases in East Asian emissions alone lead to a positive aerosol effective radiative forcing (ERF) of 1.59 (±0.97) W m−2 over central-eastern China (25°–40°N, 105°–122.5°E), along with a 0.09 (±0.07)°C warming in summer during 2013–17. The warming intensified the land–sea thermal contrast and increased the rainfall by 0.32 (±0.16) mm day−1. When considering both the emission reductions in East Asia and increases in South Asia, the ERF is increased to 3.39 (±0.89) W m−2, along with an enhanced warming of 0.20 (±0.08)°C over central-eastern China, while the rainfall insignificant decreased by 0.07 (±0.16) mm day−1. It is due to the westward shift of the strengthened western Pacific subtropical high, linked to the increase in black carbon in South Asia. Based on multiple EASM indices, the reductions in aerosol emissions from East Asia alone increased the EASM strength by almost 5%. Considering the effect of the westward shift of WPSH, the dipole changes in emissions together increased the EASM by 5%–15% during 2013–17, revealing an important role of South Asian aerosols in changing the East Asian climate.
Abstract
During the mei-yu season of the summer of 2003, the Yangtze and Huai River basin (YHRB) encountered anomalously heavy rainfall, and the northern YHRB (nYHRB) suffered a severe flood because of five continuous extreme rainfall events. A spectral analysis of daily rainfall data over YHRB reveals two dominant frequency modes: one peak on day 14 and the other on day 4 (i.e., the quasi-biweekly and synoptic-scale mode, respectively). Results indicate that the two scales of disturbances contributed southwesterly and northeasterly anomalies, respectively, to the mei-yu frontal convergence over the southern YHRB (sYHRB) at the peak wet phase. An analysis of bandpass-filtered circulations shows that the lower and upper regions of the troposphere were fully coupled at the quasi-biweekly scale, and a lower-level cyclonic anomaly over sYHRB was phase locked with an anticyclonic anomaly over the Philippines. At the synoptic scale, the strong northeasterly components of an anticyclonic anomaly with a deep cold and dry layer helped generate the heavy rainfall over sYHRB. Results also indicate the passages of five synoptic-scale disturbances during the nYHRB rainfall. Like the sYHRB rainfall, these disturbances originated from the periodical generations of cyclonic and anticyclonic anomalies at the downstream of the Tibetan Plateau. The nYHRB rainfalls were generated as these disturbances moved northeastward under the influence of monsoonal flows and higher-latitude eastward-propagating Rossby wave trains. It is concluded that the sYHRB heavy rainfall resulted from the superposition of quasi-biweekly and synoptic-scale disturbances, whereas the intermittent passages of five synoptic-scale disturbances led to the flooding rainfall over nYHRB.
Abstract
During the mei-yu season of the summer of 2003, the Yangtze and Huai River basin (YHRB) encountered anomalously heavy rainfall, and the northern YHRB (nYHRB) suffered a severe flood because of five continuous extreme rainfall events. A spectral analysis of daily rainfall data over YHRB reveals two dominant frequency modes: one peak on day 14 and the other on day 4 (i.e., the quasi-biweekly and synoptic-scale mode, respectively). Results indicate that the two scales of disturbances contributed southwesterly and northeasterly anomalies, respectively, to the mei-yu frontal convergence over the southern YHRB (sYHRB) at the peak wet phase. An analysis of bandpass-filtered circulations shows that the lower and upper regions of the troposphere were fully coupled at the quasi-biweekly scale, and a lower-level cyclonic anomaly over sYHRB was phase locked with an anticyclonic anomaly over the Philippines. At the synoptic scale, the strong northeasterly components of an anticyclonic anomaly with a deep cold and dry layer helped generate the heavy rainfall over sYHRB. Results also indicate the passages of five synoptic-scale disturbances during the nYHRB rainfall. Like the sYHRB rainfall, these disturbances originated from the periodical generations of cyclonic and anticyclonic anomalies at the downstream of the Tibetan Plateau. The nYHRB rainfalls were generated as these disturbances moved northeastward under the influence of monsoonal flows and higher-latitude eastward-propagating Rossby wave trains. It is concluded that the sYHRB heavy rainfall resulted from the superposition of quasi-biweekly and synoptic-scale disturbances, whereas the intermittent passages of five synoptic-scale disturbances led to the flooding rainfall over nYHRB.
Abstract
A satellite-based rainfall estimation algorithm, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) Cloud Classification System (CCS), is described. This algorithm extracts local and regional cloud features from infrared (10.7 μm) geostationary satellite imagery in estimating finescale (0.04° × 0.04° every 30 min) rainfall distribution. This algorithm processes satellite cloud images into pixel rain rates by 1) separating cloud images into distinctive cloud patches; 2) extracting cloud features, including coldness, geometry, and texture; 3) clustering cloud patches into well-organized subgroups; and 4) calibrating cloud-top temperature and rainfall (T b –R) relationships for the classified cloud groups using gauge-corrected radar hourly rainfall data. Several cloud-patch categories with unique cloud-patch features and T b –R curves were identified and explained. Radar and gauge rainfall measurements were both used to evaluate the PERSIANN CCS rainfall estimates at a range of temporal (hourly and daily) and spatial (0.04°, 0.12°, and 0.25°) scales. Hourly evaluation shows that the correlation coefficient (CC) is 0.45 (0.59) at a 0.04° (0.25°) grid scale. The averaged CC of daily rainfall is 0.57 (0.63) for the winter (summer) season.
Abstract
A satellite-based rainfall estimation algorithm, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) Cloud Classification System (CCS), is described. This algorithm extracts local and regional cloud features from infrared (10.7 μm) geostationary satellite imagery in estimating finescale (0.04° × 0.04° every 30 min) rainfall distribution. This algorithm processes satellite cloud images into pixel rain rates by 1) separating cloud images into distinctive cloud patches; 2) extracting cloud features, including coldness, geometry, and texture; 3) clustering cloud patches into well-organized subgroups; and 4) calibrating cloud-top temperature and rainfall (T b –R) relationships for the classified cloud groups using gauge-corrected radar hourly rainfall data. Several cloud-patch categories with unique cloud-patch features and T b –R curves were identified and explained. Radar and gauge rainfall measurements were both used to evaluate the PERSIANN CCS rainfall estimates at a range of temporal (hourly and daily) and spatial (0.04°, 0.12°, and 0.25°) scales. Hourly evaluation shows that the correlation coefficient (CC) is 0.45 (0.59) at a 0.04° (0.25°) grid scale. The averaged CC of daily rainfall is 0.57 (0.63) for the winter (summer) season.
