Abstract
Previous studies show that some soil moisture products have a good agreement with in situ measurements on the Tibetan Plateau (TP). However, the soil moisture response to precipitation variability in different products is yet to be assessed. In this study, we focus on the soil moisture response to precipitation variability across weekly to decadal time scales in satellite observations and reanalyses. The response of soil moisture to precipitation variability differs between products, with large uncertainties observed for variations in weekly accumulated precipitation. Using June 2009 as an example, weekly mean anomalous soil moisture varies by up to 25% between products. Across decadal time scales, soil moisture trends vary spatially and across different products. In light of the soil moisture response to precipitation at different time scales, we conclude that remote sensing products developed as part of the European Space Agency’s (ESA) Water Cycle Multimission Observation Strategy and Soil Moisture Climate Change Initiative (CCI) projects are the most reliable, followed by the Global Land Evaporation Amsterdam Model (GLEAM) dataset. Even products that strongly agree with in situ observations on daily time scales, such as the Global Land Data Assimilation System (GLDAS), show inconsistent soil moisture responses to decadal precipitation trends. European Centre for Medium-Range Weather Forecasts (ECWMF) reanalysis products have a relatively poor agreement with in situ observations compared to satellite observations and land-only reanalysis datasets. Unsurprisingly, products which show a consistent soil moisture response to precipitation variability are those mostly aligned to observations or describe the physical relationship between soil moisture and precipitation well.
Significance Statement
We focus on soil moisture responses to precipitation across weekly to decadal time scales by using multiple satellite observations and reanalysis products. Several soil moisture products illustrate good consistency with in situ measurements in different biomes on the Tibetan Plateau, while the response to precipitation variability differs between products, with large uncertainties observed for variations in weekly accumulated precipitation. The response of soil moisture to decadal trends in boreal summer precipitation varies spatially and temporally across products. Based on the assessments of the soil moisture response to precipitation variability across different time scales, we conclude that remote sensing products developed as part of the European Space Agency’s Water Cycle Multimission Observation Strategy and Soil Moisture Climate Change Initiative (CCI) projects are the most reliable, followed by the Global Land Evaporation Amsterdam Model (GLEAM) dataset. Reanalysis products from ECWMF show inconsistent soil moisture responses to precipitation. The results highlight the importance of using multiple soil moisture products to understand the surface response to precipitation variability and to inform developments in soil moisture modeling and satellite retrievals.
Abstract
Previous studies show that some soil moisture products have a good agreement with in situ measurements on the Tibetan Plateau (TP). However, the soil moisture response to precipitation variability in different products is yet to be assessed. In this study, we focus on the soil moisture response to precipitation variability across weekly to decadal time scales in satellite observations and reanalyses. The response of soil moisture to precipitation variability differs between products, with large uncertainties observed for variations in weekly accumulated precipitation. Using June 2009 as an example, weekly mean anomalous soil moisture varies by up to 25% between products. Across decadal time scales, soil moisture trends vary spatially and across different products. In light of the soil moisture response to precipitation at different time scales, we conclude that remote sensing products developed as part of the European Space Agency’s (ESA) Water Cycle Multimission Observation Strategy and Soil Moisture Climate Change Initiative (CCI) projects are the most reliable, followed by the Global Land Evaporation Amsterdam Model (GLEAM) dataset. Even products that strongly agree with in situ observations on daily time scales, such as the Global Land Data Assimilation System (GLDAS), show inconsistent soil moisture responses to decadal precipitation trends. European Centre for Medium-Range Weather Forecasts (ECWMF) reanalysis products have a relatively poor agreement with in situ observations compared to satellite observations and land-only reanalysis datasets. Unsurprisingly, products which show a consistent soil moisture response to precipitation variability are those mostly aligned to observations or describe the physical relationship between soil moisture and precipitation well.
Significance Statement
We focus on soil moisture responses to precipitation across weekly to decadal time scales by using multiple satellite observations and reanalysis products. Several soil moisture products illustrate good consistency with in situ measurements in different biomes on the Tibetan Plateau, while the response to precipitation variability differs between products, with large uncertainties observed for variations in weekly accumulated precipitation. The response of soil moisture to decadal trends in boreal summer precipitation varies spatially and temporally across products. Based on the assessments of the soil moisture response to precipitation variability across different time scales, we conclude that remote sensing products developed as part of the European Space Agency’s Water Cycle Multimission Observation Strategy and Soil Moisture Climate Change Initiative (CCI) projects are the most reliable, followed by the Global Land Evaporation Amsterdam Model (GLEAM) dataset. Reanalysis products from ECWMF show inconsistent soil moisture responses to precipitation. The results highlight the importance of using multiple soil moisture products to understand the surface response to precipitation variability and to inform developments in soil moisture modeling and satellite retrievals.
Abstract
The Tibetan Plateau is a sensitive area of global climate change, where few conventional observations exist. Satellite AMSU-A microwave temperature sounding observations of brightness temperature (TB) are located in the absorption band of oxygen, which is well mixed in the atmosphere, and have microwave frequencies varying from 50.3 to 57.6 GHz. Therefore, AMSU-A TB observations at different sounding channels reflect atmospheric temperatures at different altitudes. In this study, AMSU-A TB observations during 1998–2020 from five polar-orbiting environmental meteorological satellites (POESs) are employed to investigate the interdecadal warming/cooling trends over the Tibetan Plateau. A limb correction is first applied to all AMSU-A channels before using TB observations at all fields of view for examining geographic distributions and differences of global warming/cooling trends. It is found that interdecadal trends of upper-tropospheric warming and stratospheric cooling are stronger over the Qinghai Tibetan Plateau than its eastern plain areas. An interdecadal variation of the annual cycle over the Tibetan Plateau is an important factor for the enhanced tropospheric warming trend. We also applied a different approach of significance testing that is based on counting signs of local trends (sign test) and confirmed that the detected significant local trends were not a result of chance. In addition, high-frequency noise in TB observations with periods smaller than annual and semiannual oscillations do not affect the climate trends of TB very much, but significantly reduced the uncertainty of the TB trends over the Tibetan Plateau.
Abstract
The Tibetan Plateau is a sensitive area of global climate change, where few conventional observations exist. Satellite AMSU-A microwave temperature sounding observations of brightness temperature (TB) are located in the absorption band of oxygen, which is well mixed in the atmosphere, and have microwave frequencies varying from 50.3 to 57.6 GHz. Therefore, AMSU-A TB observations at different sounding channels reflect atmospheric temperatures at different altitudes. In this study, AMSU-A TB observations during 1998–2020 from five polar-orbiting environmental meteorological satellites (POESs) are employed to investigate the interdecadal warming/cooling trends over the Tibetan Plateau. A limb correction is first applied to all AMSU-A channels before using TB observations at all fields of view for examining geographic distributions and differences of global warming/cooling trends. It is found that interdecadal trends of upper-tropospheric warming and stratospheric cooling are stronger over the Qinghai Tibetan Plateau than its eastern plain areas. An interdecadal variation of the annual cycle over the Tibetan Plateau is an important factor for the enhanced tropospheric warming trend. We also applied a different approach of significance testing that is based on counting signs of local trends (sign test) and confirmed that the detected significant local trends were not a result of chance. In addition, high-frequency noise in TB observations with periods smaller than annual and semiannual oscillations do not affect the climate trends of TB very much, but significantly reduced the uncertainty of the TB trends over the Tibetan Plateau.
Abstract
In the postprocessing of ensemble forecasts of weather variables, it is standard practice to first calibrate the forecasts in a univariate setting, before reconstructing multivariate ensembles that have a correct covariability in space, time, and across variables, via so-called “reordering” methods. Within this framework though, postprocessors cannot fully extract the skill of the raw forecast that may exist at larger scales. A multi-temporal-scale modulation mechanism for precipitation is here presented, which aims at improving the forecasts over different accumulation periods, and which can be coupled with any univariate calibration and multivariate reordering techniques. The idea, originally known under the term “canonical events,” has been implemented for more than a decade in the Meteorological Ensemble Forecast Processor (MEFP), a component of the U.S. National Weather Service’s (NWS) Hydrologic Ensemble Forecast Service (HEFS), although users were left with material in the gray literature. This paper proposes a formal description of the mechanism and studies its intrinsic connection with the multivariate reordering process. The verification of modulated and unmodulated forecasts, when coupled with two popular methods for reordering, the Schaake shuffle and ensemble copula coupling (ECC), is performed on 11 Californian basins, on both precipitation and streamflow. Results demonstrate the clear benefit of the multi-temporal-scale modulation, in particular on multiday total streamflow. However, the relative gain depends on the method used for reordering, with more benefits expected when this latter method is not able to reconstruct an adequate temporal structure on the calibrated precipitation forecasts.
Abstract
In the postprocessing of ensemble forecasts of weather variables, it is standard practice to first calibrate the forecasts in a univariate setting, before reconstructing multivariate ensembles that have a correct covariability in space, time, and across variables, via so-called “reordering” methods. Within this framework though, postprocessors cannot fully extract the skill of the raw forecast that may exist at larger scales. A multi-temporal-scale modulation mechanism for precipitation is here presented, which aims at improving the forecasts over different accumulation periods, and which can be coupled with any univariate calibration and multivariate reordering techniques. The idea, originally known under the term “canonical events,” has been implemented for more than a decade in the Meteorological Ensemble Forecast Processor (MEFP), a component of the U.S. National Weather Service’s (NWS) Hydrologic Ensemble Forecast Service (HEFS), although users were left with material in the gray literature. This paper proposes a formal description of the mechanism and studies its intrinsic connection with the multivariate reordering process. The verification of modulated and unmodulated forecasts, when coupled with two popular methods for reordering, the Schaake shuffle and ensemble copula coupling (ECC), is performed on 11 Californian basins, on both precipitation and streamflow. Results demonstrate the clear benefit of the multi-temporal-scale modulation, in particular on multiday total streamflow. However, the relative gain depends on the method used for reordering, with more benefits expected when this latter method is not able to reconstruct an adequate temporal structure on the calibrated precipitation forecasts.
Abstract
The processes underlying heavy rainfall in the higher elevations of the Himalayas are still not well known despite their importance. Here, we examine the detailed process causing a heavy rainfall event, observed by our rain gauge network in the Rolwaling valley, eastern Nepal Himalayas, using ERA5 and a regional cloud-resolving numerical simulation. Heavy precipitation (112 mm day−1) was observed on 8 July 2019 at Dongang (2790 m above sea level). Most of the precipitation (81 mm) occurred during 1900–2300 local time (LT). The synoptic-scale environment is characterized by a monsoon low pressure system (LPS) over northeastern India. The LPS lifted moisture upward from the lower troposphere and then horizontally transported it into the eastern Nepal Himalayas within the middle troposphere, increasing the content of the water vapor around Dongang. A mesoscale convective system passed over Dongang around the time of the intense precipitation. The numerical simulation showed that surface heat fluxes prevailed under the middle tropospheric (∼500 hPa) southeasterly flow associated with the LPS around a mountain ridge on the upwind side of Dongang until 1900 LT, enhancing convective instability. Topographic lifting led to the release of the enhanced instability, which triggered the development of a mesoscale precipitation system. The southeasterly flow pushed the precipitation system northward, which then passed over Dongang during 2000–2200 LT, resulting in heavy precipitation. Thus, we conclude that the heavy precipitation came from the multiscale processes such as three-dimensional moisture transport driven by the LPS and the diurnal variation in heat fluxes from the land surface.
Significance Statement
Precipitation in the Himalayas is closely related to the hydrological cycle, floods, and landslide disasters in South Asia. Thus, elucidating the features of precipitation in the Himalayas is important. This study explored multiscale processes leading to a heavy precipitation event that was observed on 8 July 2019 at Dongang in the Rolwaling valley of the eastern Nepal Himalayas. We identified new processes producing heavy precipitation in the Himalayas: the three-dimensional synoptic-scale moisture transport driven by a monsoon low pressure system and the effect of the diurnal variation in heat fluxes from the land surface on the development and movement of a mesoscale precipitation system causing heavy precipitation. These findings broaden our understanding of heavy precipitation in the Himalayas.
Abstract
The processes underlying heavy rainfall in the higher elevations of the Himalayas are still not well known despite their importance. Here, we examine the detailed process causing a heavy rainfall event, observed by our rain gauge network in the Rolwaling valley, eastern Nepal Himalayas, using ERA5 and a regional cloud-resolving numerical simulation. Heavy precipitation (112 mm day−1) was observed on 8 July 2019 at Dongang (2790 m above sea level). Most of the precipitation (81 mm) occurred during 1900–2300 local time (LT). The synoptic-scale environment is characterized by a monsoon low pressure system (LPS) over northeastern India. The LPS lifted moisture upward from the lower troposphere and then horizontally transported it into the eastern Nepal Himalayas within the middle troposphere, increasing the content of the water vapor around Dongang. A mesoscale convective system passed over Dongang around the time of the intense precipitation. The numerical simulation showed that surface heat fluxes prevailed under the middle tropospheric (∼500 hPa) southeasterly flow associated with the LPS around a mountain ridge on the upwind side of Dongang until 1900 LT, enhancing convective instability. Topographic lifting led to the release of the enhanced instability, which triggered the development of a mesoscale precipitation system. The southeasterly flow pushed the precipitation system northward, which then passed over Dongang during 2000–2200 LT, resulting in heavy precipitation. Thus, we conclude that the heavy precipitation came from the multiscale processes such as three-dimensional moisture transport driven by the LPS and the diurnal variation in heat fluxes from the land surface.
Significance Statement
Precipitation in the Himalayas is closely related to the hydrological cycle, floods, and landslide disasters in South Asia. Thus, elucidating the features of precipitation in the Himalayas is important. This study explored multiscale processes leading to a heavy precipitation event that was observed on 8 July 2019 at Dongang in the Rolwaling valley of the eastern Nepal Himalayas. We identified new processes producing heavy precipitation in the Himalayas: the three-dimensional synoptic-scale moisture transport driven by a monsoon low pressure system and the effect of the diurnal variation in heat fluxes from the land surface on the development and movement of a mesoscale precipitation system causing heavy precipitation. These findings broaden our understanding of heavy precipitation in the Himalayas.
Abstract
Accurate simulations of convectively coupled equatorial waves (CCEWs) are key to properly forecasting rainfall and weather patterns within (and outside) the tropics. Many studies have shown that global numerical weather prediction (NWP) models usually do not accurately simulate CCEWs; however, it is unclear if this problem can be alleviated with a better representation of deep convection in the models. To this end, this study investigates the representation of multiple types of CCEWs in the Model for Prediction Across Scales-Atmosphere (MPAS-A). The simulated structure of CCEWs is analyzed from three MPAS-A aquaplanet experiments with horizontal cell spacing of 30, 15, and 3 km, respectively. Using a wave-phase composite technique, the simulated structure is compared against observed CCEWs as represented by satellite and reanalysis data. All aquaplanet experiments capture the overall structure of gravity wave–type equatorial waves (e.g., Kelvin waves and inertio-gravity waves). Those waves are more realistic in the 3-km experiment, particularly in terms of the vertical structure of temperature, water vapor, and wind anomalies associated with the waves. The main reason for this improvement is a more realistic diabatic heating profile; the experiment with resolved convection produces stronger heating (or weaker cooling) below the melting level during the convectively active phase of Kelvin and inertio-gravity waves. Intriguingly, the rainfall and lower-tropospheric structure associated with easterly waves show pronounced discrepancies between the aquaplanet experiments and reanalysis. Resolved deep convection primarily affects the intensity and propagation speeds of these waves.
Abstract
Accurate simulations of convectively coupled equatorial waves (CCEWs) are key to properly forecasting rainfall and weather patterns within (and outside) the tropics. Many studies have shown that global numerical weather prediction (NWP) models usually do not accurately simulate CCEWs; however, it is unclear if this problem can be alleviated with a better representation of deep convection in the models. To this end, this study investigates the representation of multiple types of CCEWs in the Model for Prediction Across Scales-Atmosphere (MPAS-A). The simulated structure of CCEWs is analyzed from three MPAS-A aquaplanet experiments with horizontal cell spacing of 30, 15, and 3 km, respectively. Using a wave-phase composite technique, the simulated structure is compared against observed CCEWs as represented by satellite and reanalysis data. All aquaplanet experiments capture the overall structure of gravity wave–type equatorial waves (e.g., Kelvin waves and inertio-gravity waves). Those waves are more realistic in the 3-km experiment, particularly in terms of the vertical structure of temperature, water vapor, and wind anomalies associated with the waves. The main reason for this improvement is a more realistic diabatic heating profile; the experiment with resolved convection produces stronger heating (or weaker cooling) below the melting level during the convectively active phase of Kelvin and inertio-gravity waves. Intriguingly, the rainfall and lower-tropospheric structure associated with easterly waves show pronounced discrepancies between the aquaplanet experiments and reanalysis. Resolved deep convection primarily affects the intensity and propagation speeds of these waves.
Abstract
The diurnal cycle of precipitation is highly regional and is typically a product of multiple competing, highly localized effects. The diurnal cycle in regions such as the Amazon and the Maritime Continent are of particular interest, due to the complex coastal and terrain effects. The high spatial and temporal resolution provided by the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG) dataset are used in this study to examine the fine-scale features of the diurnal cycle in these regions. Using an 18-yr (2000–18) record of IMERG precipitation observations, diurnal and semidiurnal phase and amplitude are calculated using a fast Fourier transform (FFT) method on half-hourly averaged precipitation at 0.1° × 0.1°. Clear patterns of precipitation phase propagation with distance from shore are shown over both regions, with the diurnal phase and amplitude exhibiting a strong dependence on the distance from the coastline. Semidiurnal cycles are generally weaker than the diurnal cycle except in some isolated locations. Similar analysis is also conducted on the ERA5 reanalysis data in order to evaluate the model’s representation of the precipitation diurnal cycle. The model captures the broadscale patterns of diurnal variability but does not capture all the fine-scale patterns nor the exact timing that is observed by IMERG. Comparisons are also made to a long-record Ku radar dataset created by combining Tropical Rainfall Measuring Mission (TRMM) and GPM observations, thus providing an additional point of comparison for the timing of the ERA5 precipitation peak, since the timing precipitation can be different, even in between observational datasets.
Abstract
The diurnal cycle of precipitation is highly regional and is typically a product of multiple competing, highly localized effects. The diurnal cycle in regions such as the Amazon and the Maritime Continent are of particular interest, due to the complex coastal and terrain effects. The high spatial and temporal resolution provided by the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG) dataset are used in this study to examine the fine-scale features of the diurnal cycle in these regions. Using an 18-yr (2000–18) record of IMERG precipitation observations, diurnal and semidiurnal phase and amplitude are calculated using a fast Fourier transform (FFT) method on half-hourly averaged precipitation at 0.1° × 0.1°. Clear patterns of precipitation phase propagation with distance from shore are shown over both regions, with the diurnal phase and amplitude exhibiting a strong dependence on the distance from the coastline. Semidiurnal cycles are generally weaker than the diurnal cycle except in some isolated locations. Similar analysis is also conducted on the ERA5 reanalysis data in order to evaluate the model’s representation of the precipitation diurnal cycle. The model captures the broadscale patterns of diurnal variability but does not capture all the fine-scale patterns nor the exact timing that is observed by IMERG. Comparisons are also made to a long-record Ku radar dataset created by combining Tropical Rainfall Measuring Mission (TRMM) and GPM observations, thus providing an additional point of comparison for the timing of the ERA5 precipitation peak, since the timing precipitation can be different, even in between observational datasets.
Abstract
This study aims to comprehend the propagation of meteorological drought [expressed by the standardized precipitation evapotranspiration index (SPEI)] into hydrological drought [expressed by the standardized runoff index (SRI)] using the combined application of principal component analysis (PCA) and wavelet analysis for a period of 39 years (1980–2018) in the Indus basin, Pakistan. PCA was used to calculate principal components of precipitation, temperature, and streamflow, which were used to systematically propagate drought from one catchment to another, resulting in a catchment-scale drought assessment. The systematic propagation of drought was useful in capturing the effects of local climate variability in the 27 catchments of the Indus basin. Wavelet analyses are used to calculate the variability of SPEI/SRI and propagation (analyzed with the wavelet coherence) from SPEI to SRI. The propagation time from SPEI to SRI was cross correlated. SPEI/SRI time series showed extreme/severe droughts in 16 out of the 39 years, where relatively weak apparent wet and drought events are observed at short periods (1 month) and apparent at longer periods (6 and 12 months). Propagation from SPEI to SRI is catchment specific, with most catchments showing transition in early years (1997–2003). Propagation rate is higher in the upper Indus basin (UIB) and lower Indus basin (LIB) than in the middle Indus basin (MIB), suggesting that climate plays an important role in drought development and propagation. Results also showed a shorter and longer propagation time in the UIB and LIB, respectively. This study has helped us understand the behavior of droughts at catchment scale and will therefore help in the development of drought mitigation plans in Pakistan and similar regions around the world.
Abstract
This study aims to comprehend the propagation of meteorological drought [expressed by the standardized precipitation evapotranspiration index (SPEI)] into hydrological drought [expressed by the standardized runoff index (SRI)] using the combined application of principal component analysis (PCA) and wavelet analysis for a period of 39 years (1980–2018) in the Indus basin, Pakistan. PCA was used to calculate principal components of precipitation, temperature, and streamflow, which were used to systematically propagate drought from one catchment to another, resulting in a catchment-scale drought assessment. The systematic propagation of drought was useful in capturing the effects of local climate variability in the 27 catchments of the Indus basin. Wavelet analyses are used to calculate the variability of SPEI/SRI and propagation (analyzed with the wavelet coherence) from SPEI to SRI. The propagation time from SPEI to SRI was cross correlated. SPEI/SRI time series showed extreme/severe droughts in 16 out of the 39 years, where relatively weak apparent wet and drought events are observed at short periods (1 month) and apparent at longer periods (6 and 12 months). Propagation from SPEI to SRI is catchment specific, with most catchments showing transition in early years (1997–2003). Propagation rate is higher in the upper Indus basin (UIB) and lower Indus basin (LIB) than in the middle Indus basin (MIB), suggesting that climate plays an important role in drought development and propagation. Results also showed a shorter and longer propagation time in the UIB and LIB, respectively. This study has helped us understand the behavior of droughts at catchment scale and will therefore help in the development of drought mitigation plans in Pakistan and similar regions around the world.
Abstract
Much of Siberia experienced exceptional warmth during the spring of 2020, which followed an unusually warm winter over the same region. Here, we investigate the drivers of the spring warmth from the perspective of atmospheric dynamics and remote influences, focusing on monthly timescale features of the event. We find that the warm anomalies were associated with separate quasi-stationary Rossby wave trains emanating from the North Atlantic in April and May. The wave trains are shown to be extreme manifestations of the dominant modes of spring subseasonal meridional wind variability over the Northern Hemisphere. Using a large ensemble of simulations from NASA’s GEOS atmospheric model, in which the model is constrained to remain close to observations over selected regions, we further elucidate the remote drivers of the unusual spring temperatures in Siberia. In both April and May, the wave trains were likely forced from an upstream region including eastern North America and the western North Atlantic. Analysis with a stationary wave model shows that transient vorticity flux forcing over and downwind of the North Atlantic, which is strongly related to storm activity caused by internal variability, is key to generating the wave trains, suggesting limited subseasonal predictability of the Rossby waves and hence the exceptional Siberian warmth. Our observational and model analysis also suggests that anomalous tropical atmospheric heating contributed to the unusual warmth in Siberia through a teleconnection involving upper-troposphere dynamics and the mean meridional circulation. This tropical-extratropical teleconnection offers a possible physical mechanism by which anthropogenic climate change influenced the extreme Siberian warmth.
Abstract
Much of Siberia experienced exceptional warmth during the spring of 2020, which followed an unusually warm winter over the same region. Here, we investigate the drivers of the spring warmth from the perspective of atmospheric dynamics and remote influences, focusing on monthly timescale features of the event. We find that the warm anomalies were associated with separate quasi-stationary Rossby wave trains emanating from the North Atlantic in April and May. The wave trains are shown to be extreme manifestations of the dominant modes of spring subseasonal meridional wind variability over the Northern Hemisphere. Using a large ensemble of simulations from NASA’s GEOS atmospheric model, in which the model is constrained to remain close to observations over selected regions, we further elucidate the remote drivers of the unusual spring temperatures in Siberia. In both April and May, the wave trains were likely forced from an upstream region including eastern North America and the western North Atlantic. Analysis with a stationary wave model shows that transient vorticity flux forcing over and downwind of the North Atlantic, which is strongly related to storm activity caused by internal variability, is key to generating the wave trains, suggesting limited subseasonal predictability of the Rossby waves and hence the exceptional Siberian warmth. Our observational and model analysis also suggests that anomalous tropical atmospheric heating contributed to the unusual warmth in Siberia through a teleconnection involving upper-troposphere dynamics and the mean meridional circulation. This tropical-extratropical teleconnection offers a possible physical mechanism by which anthropogenic climate change influenced the extreme Siberian warmth.
Abstract
This study investigates the tropical and extratropical circulation anomalies that directly affect the summer rainfall over the Yangtze River basin (YRB). In the lower troposphere, the tropical circulation anomalies that enhance the YRB rainfall manifest as an anticyclonic anomaly over the tropical western North Pacific (WNP) and the extratropical circulation anomalies are characterized by northeasterly anomalies to the north of the YRB. It is found that the heavier the YRB rainfall, the more necessary the cooperation between the tropical WNP anticyclonic anomaly and the mid-latitude northeasterly anomalies, and compared to the tropical WNP anticyclonic anomaly, the mid-latitude northeasterly anomalies can more efficiently induce the YRB rainfall. Further results indicate that the tropical WNP anticyclonic anomaly exhibits notable quasi-biweekly feature and provides a favorable background for the enhanced YRB rainfall. By contrast, the northeasterly anomalies are dominated by synoptic variability. Furthermore, there are significant precursor signals for the lower-tropospheric northeasterly anomalies. These signals manifest as the eastward propagation of two wave trains in the upper troposphere: a mid-latitude one and a high-latitude one, which tend to be independent. The mid-latitude one originates around the Mediterranean Sea and propagates eastward along the Asian westerly jet. The high-latitude one propagates over the high-latitude Eurasian continent, from Europe eastward to Lake Baikal and then southeastward to East Asia.
Abstract
This study investigates the tropical and extratropical circulation anomalies that directly affect the summer rainfall over the Yangtze River basin (YRB). In the lower troposphere, the tropical circulation anomalies that enhance the YRB rainfall manifest as an anticyclonic anomaly over the tropical western North Pacific (WNP) and the extratropical circulation anomalies are characterized by northeasterly anomalies to the north of the YRB. It is found that the heavier the YRB rainfall, the more necessary the cooperation between the tropical WNP anticyclonic anomaly and the mid-latitude northeasterly anomalies, and compared to the tropical WNP anticyclonic anomaly, the mid-latitude northeasterly anomalies can more efficiently induce the YRB rainfall. Further results indicate that the tropical WNP anticyclonic anomaly exhibits notable quasi-biweekly feature and provides a favorable background for the enhanced YRB rainfall. By contrast, the northeasterly anomalies are dominated by synoptic variability. Furthermore, there are significant precursor signals for the lower-tropospheric northeasterly anomalies. These signals manifest as the eastward propagation of two wave trains in the upper troposphere: a mid-latitude one and a high-latitude one, which tend to be independent. The mid-latitude one originates around the Mediterranean Sea and propagates eastward along the Asian westerly jet. The high-latitude one propagates over the high-latitude Eurasian continent, from Europe eastward to Lake Baikal and then southeastward to East Asia.
Abstract
The Maritime Continent (MC), located in the heart of the Indo-Pacific warm pool, plays an important role in the global climate. However, the future MC climate is largely unknown, in particular the ENSO-rainfall teleconnection. ENSO induces a zonal dipole pattern of rainfall variability across the Indo-Pacific Ocean, i.e., positive variability in the Tropical Pacific and negative variability towards the MC. Here new CMIP6 models robustly project that, for both land and sea rainfall, the negative ENSO teleconnection over the MC (drier/wetter during El Niño/La Niña) could intensify significantly under the SSP585 warming scenario. Strengthened teleconnection may cause enhanced droughts and flooding, leading to agricultural impacts and altering rainfall predictability over the region. Models also project that the Indo-Pacific rainfall center and the zero-crossing of dipole-like rainfall variability both shift eastward, which adjustments are more notable during boreal summer than winter. All these projections are robustly supported by the model agreement and scale up with the warming trend.
Abstract
The Maritime Continent (MC), located in the heart of the Indo-Pacific warm pool, plays an important role in the global climate. However, the future MC climate is largely unknown, in particular the ENSO-rainfall teleconnection. ENSO induces a zonal dipole pattern of rainfall variability across the Indo-Pacific Ocean, i.e., positive variability in the Tropical Pacific and negative variability towards the MC. Here new CMIP6 models robustly project that, for both land and sea rainfall, the negative ENSO teleconnection over the MC (drier/wetter during El Niño/La Niña) could intensify significantly under the SSP585 warming scenario. Strengthened teleconnection may cause enhanced droughts and flooding, leading to agricultural impacts and altering rainfall predictability over the region. Models also project that the Indo-Pacific rainfall center and the zero-crossing of dipole-like rainfall variability both shift eastward, which adjustments are more notable during boreal summer than winter. All these projections are robustly supported by the model agreement and scale up with the warming trend.
