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Abstract
Compared to precipitation extremes calculated from a high-resolution daily observational dataset in China during 1960–2005, simulations in 31 climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) have been quantitatively assessed using skill-score metrics. Four extreme precipitation indices, including the total precipitation (PRCPTOT), maximum consecutive dry days (CDD), precipitation intensity (SDII), and fraction of total rainfall from heavy events (R95T) are analyzed. Results show that CMIP5 models still have wet biases in western and northern China. Especially in western China, the models’ median relative error is about 120% for PRCPTOT; the 25th and 75th percentile errors are of 70% and 220%, respectively. However, there are dry biases in southeastern China, where the underestimation of PRCPTOT reach 200 mm. The performance of CMIP5 models is quite different between western and eastern China. The simulations are more reliable in the east than in the west in terms of spatial pattern and interannual variability. In the east, precipitation indices are more consistent with observations, and the spread among models is smaller. The multimodel ensemble constructed from a selection of the most skillful models shows improved behavior compared to the all-model ensemble. The wet bias in western and northern China and dry bias over southeastern China are all decreased. The median of errors for PRCPTOT has a decrease of 69% and 17% in the west and east, respectively. The good reproduction of the southwesterlies along the east coast of the Arabian Peninsula is revealed to be the main factor explaining the improvement of precipitation patterns and extreme events.
Abstract
Compared to precipitation extremes calculated from a high-resolution daily observational dataset in China during 1960–2005, simulations in 31 climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) have been quantitatively assessed using skill-score metrics. Four extreme precipitation indices, including the total precipitation (PRCPTOT), maximum consecutive dry days (CDD), precipitation intensity (SDII), and fraction of total rainfall from heavy events (R95T) are analyzed. Results show that CMIP5 models still have wet biases in western and northern China. Especially in western China, the models’ median relative error is about 120% for PRCPTOT; the 25th and 75th percentile errors are of 70% and 220%, respectively. However, there are dry biases in southeastern China, where the underestimation of PRCPTOT reach 200 mm. The performance of CMIP5 models is quite different between western and eastern China. The simulations are more reliable in the east than in the west in terms of spatial pattern and interannual variability. In the east, precipitation indices are more consistent with observations, and the spread among models is smaller. The multimodel ensemble constructed from a selection of the most skillful models shows improved behavior compared to the all-model ensemble. The wet bias in western and northern China and dry bias over southeastern China are all decreased. The median of errors for PRCPTOT has a decrease of 69% and 17% in the west and east, respectively. The good reproduction of the southwesterlies along the east coast of the Arabian Peninsula is revealed to be the main factor explaining the improvement of precipitation patterns and extreme events.
Abstract
Superimposed on a warming trend, Arctic winter surface air temperature (SAT) exhibits substantial interannual variability, the underlying mechanisms of which are unclear, especially with regard to the role of sea ice variations and atmospheric processes. Here, atmospheric reanalysis data and idealized atmospheric model simulations are used to reveal the mechanisms by which sea ice variations and atmospheric anomalous conditions affect interannual variations in wintertime Arctic SAT. Results show that near-surface interannual warming in the Arctic is accompanied by comparable warming throughout large parts of the Arctic troposphere and large-scale anomalous atmospheric circulation patterns. Within the Arctic, changes in large-scale atmospheric circulations due to internal atmospheric variability explain a substantial fraction of interannual variation in SAT and tropospheric temperatures, which lead to an increase in moisture and downward longwave radiation, with the rest likely coming from sea ice–related and other surface processes. Arctic winter sea ice loss allows the ocean to release more heat and moisture, which enhances Arctic warming; however, this effect on SAT is confined to the ice-retreat area and has a limited influence on large-scale atmospheric circulations.
Abstract
Superimposed on a warming trend, Arctic winter surface air temperature (SAT) exhibits substantial interannual variability, the underlying mechanisms of which are unclear, especially with regard to the role of sea ice variations and atmospheric processes. Here, atmospheric reanalysis data and idealized atmospheric model simulations are used to reveal the mechanisms by which sea ice variations and atmospheric anomalous conditions affect interannual variations in wintertime Arctic SAT. Results show that near-surface interannual warming in the Arctic is accompanied by comparable warming throughout large parts of the Arctic troposphere and large-scale anomalous atmospheric circulation patterns. Within the Arctic, changes in large-scale atmospheric circulations due to internal atmospheric variability explain a substantial fraction of interannual variation in SAT and tropospheric temperatures, which lead to an increase in moisture and downward longwave radiation, with the rest likely coming from sea ice–related and other surface processes. Arctic winter sea ice loss allows the ocean to release more heat and moisture, which enhances Arctic warming; however, this effect on SAT is confined to the ice-retreat area and has a limited influence on large-scale atmospheric circulations.
Abstract
The present article is the second part of a study on the extreme precipitation indices over China in CMIP5 models that perform a probabilistic projection of future precipitation indices with reference to the period 1986–2005. This is realized with a rank-based weighting method. The ranking of the 25 models is done according to their performance in simulating rainfall indices in present-day climate. Such weights are used to form a weighted ensemble for future climate projection. Results show that, compared to the unweighted raw ensemble, the projection with the weighted scheme is more credible, as the signal-to-noise ratio (SNR) of indices is larger from the weighted ensemble. From the beginning of the mid-twenty-first century, changes of wet indices with probability >0.5 increase significantly, especially over western China and the Yellow–Huai River basin, where the changes of all wet indices are in excess of 10%, the increase of total precipitation (PRCPTOT) can reach up to 20% over western China at the end of twenty-first century, and the SNR of PRCPTOT and precipitation intensity (SDII) is the highest at those two regions. This indicates that the precipitation in those regions has a high reliability to become more extreme. The maximum consecutive dry days (CDD) decreases throughout the north of 30°N, which shows that drought conditions in northern China would be reduced, and they are more likely to increase in southern China. However, the SNR for projection of CDD is less than 1.0 almost everywhere. Such a situation seems related to a strengthening of the East Asian summer monsoon and the associated northward shift of the monsoon front.
Abstract
The present article is the second part of a study on the extreme precipitation indices over China in CMIP5 models that perform a probabilistic projection of future precipitation indices with reference to the period 1986–2005. This is realized with a rank-based weighting method. The ranking of the 25 models is done according to their performance in simulating rainfall indices in present-day climate. Such weights are used to form a weighted ensemble for future climate projection. Results show that, compared to the unweighted raw ensemble, the projection with the weighted scheme is more credible, as the signal-to-noise ratio (SNR) of indices is larger from the weighted ensemble. From the beginning of the mid-twenty-first century, changes of wet indices with probability >0.5 increase significantly, especially over western China and the Yellow–Huai River basin, where the changes of all wet indices are in excess of 10%, the increase of total precipitation (PRCPTOT) can reach up to 20% over western China at the end of twenty-first century, and the SNR of PRCPTOT and precipitation intensity (SDII) is the highest at those two regions. This indicates that the precipitation in those regions has a high reliability to become more extreme. The maximum consecutive dry days (CDD) decreases throughout the north of 30°N, which shows that drought conditions in northern China would be reduced, and they are more likely to increase in southern China. However, the SNR for projection of CDD is less than 1.0 almost everywhere. Such a situation seems related to a strengthening of the East Asian summer monsoon and the associated northward shift of the monsoon front.
Abstract
The Pacific–North American (PNA) pattern and the North Atlantic Oscillation (NAO) are known to contain a tropical sea surface temperature (SST)-forced component. This study examines the sensitivity of the wintertime NAO and PNA to patterns of tropical SST anomalies using a linear statistical–dynamic method. The NAO index is sensitive to SST anomalies over the tropical Indian Ocean, the central Pacific Ocean, and the Caribbean Sea, and the PNA index is sensitive to SST anomalies over the tropical Pacific and Indian Oceans. The NAO and PNA patterns can be reproduced well by combining the linear operator with the consistent SST anomaly over the Indian Ocean and the Niño-4 regions, respectively, suggesting that these are the most efficient ocean basins that force the teleconnection patterns. During the period of 1950–2000, the NAO time series reconstructed by using SST anomalies over the Indian Ocean + Niño-4 region + Caribbean Sea or the Indian Ocean + Niño-4 region is significantly correlated with the observation. Using a cross-spectral analysis, the NAO index is coherent with the SST forcing over the Indian Ocean at a significant 3-yr period and a less significant 10-yr period, with the Indian Ocean SST leading by about a quarter phase. Unsurprisingly, the PNA index is most coherent with the Niño-4 SST at 4–5-yr periods. When compared with the observation, the NAO variability from the linear reconstruction is better reproduced than that of the coupled model, which is better than the Atmospheric Model Intercomparison Project (AMIP) run, while the PNA variability from the AMIP simulations is better than that of the reconstruction, which is better than the coupled model run.
Abstract
The Pacific–North American (PNA) pattern and the North Atlantic Oscillation (NAO) are known to contain a tropical sea surface temperature (SST)-forced component. This study examines the sensitivity of the wintertime NAO and PNA to patterns of tropical SST anomalies using a linear statistical–dynamic method. The NAO index is sensitive to SST anomalies over the tropical Indian Ocean, the central Pacific Ocean, and the Caribbean Sea, and the PNA index is sensitive to SST anomalies over the tropical Pacific and Indian Oceans. The NAO and PNA patterns can be reproduced well by combining the linear operator with the consistent SST anomaly over the Indian Ocean and the Niño-4 regions, respectively, suggesting that these are the most efficient ocean basins that force the teleconnection patterns. During the period of 1950–2000, the NAO time series reconstructed by using SST anomalies over the Indian Ocean + Niño-4 region + Caribbean Sea or the Indian Ocean + Niño-4 region is significantly correlated with the observation. Using a cross-spectral analysis, the NAO index is coherent with the SST forcing over the Indian Ocean at a significant 3-yr period and a less significant 10-yr period, with the Indian Ocean SST leading by about a quarter phase. Unsurprisingly, the PNA index is most coherent with the Niño-4 SST at 4–5-yr periods. When compared with the observation, the NAO variability from the linear reconstruction is better reproduced than that of the coupled model, which is better than the Atmospheric Model Intercomparison Project (AMIP) run, while the PNA variability from the AMIP simulations is better than that of the reconstruction, which is better than the coupled model run.
Atmospheric Cold Front–Induced Exchange Flows through a Microtidal Multi-Inlet Bay: Analysis Using Multiple Horizontal ADCPs and FVCOM SimulationsAbstract
Atmospheric cold fronts provide recurring forcing for circulations and long-term transport in estuaries with microtides. Multiple horizontal ADCPs were used to obtain time series data from three inlets in Barataria Bay. The data cover a period of 51 atmospheric cold fronts between 2013 and 2015. The weather and subtidal ocean response are highly correlated in the “weather band” (3–7 days). The cold front–associated winds produce alternating flows into, out of, and then back into the bay, forming an asymmetric “M” for low-pass filtered flows. Results show that cold front–induced flows are the most important component in this region, and the flows can be predicted based on wind vector time series. Numerical simulations using a validated Finite-Volume Coastal Ocean Model (FVCOM) demonstrate that the wind-driven oscillations within the bay are consistent with the quasi-steady state with little influence of the Coriolis effect for cold front–related wind-driven flows. The four major inlets (from the southwest to the northeast) consistently carry 10%, 57%, 21%, and 12% of the tidal exchange of the bay, respectively. The subtidal exchange rates through them however fluctuate greatly with averages of 18% ± 13%, 35% ± 18%, 31% ± 16%, and 16% ± 9%, respectively. Several modes of exchange flows through the multiple inlets are found, consisting of the all-in and all-out mode (45% occurrence) under strong winds perpendicular to the coastline; the shallow-downwind, deep-upwind mode (41%), particularly during wind-relaxation periods; and the upwind-in and downwind-out mode (13%) under northerly or southerly winds. These modes are discussed with the low-pass filtered model results and verified by a forcing–response joint EOF analysis.
Abstract
Atmospheric cold fronts provide recurring forcing for circulations and long-term transport in estuaries with microtides. Multiple horizontal ADCPs were used to obtain time series data from three inlets in Barataria Bay. The data cover a period of 51 atmospheric cold fronts between 2013 and 2015. The weather and subtidal ocean response are highly correlated in the “weather band” (3–7 days). The cold front–associated winds produce alternating flows into, out of, and then back into the bay, forming an asymmetric “M” for low-pass filtered flows. Results show that cold front–induced flows are the most important component in this region, and the flows can be predicted based on wind vector time series. Numerical simulations using a validated Finite-Volume Coastal Ocean Model (FVCOM) demonstrate that the wind-driven oscillations within the bay are consistent with the quasi-steady state with little influence of the Coriolis effect for cold front–related wind-driven flows. The four major inlets (from the southwest to the northeast) consistently carry 10%, 57%, 21%, and 12% of the tidal exchange of the bay, respectively. The subtidal exchange rates through them however fluctuate greatly with averages of 18% ± 13%, 35% ± 18%, 31% ± 16%, and 16% ± 9%, respectively. Several modes of exchange flows through the multiple inlets are found, consisting of the all-in and all-out mode (45% occurrence) under strong winds perpendicular to the coastline; the shallow-downwind, deep-upwind mode (41%), particularly during wind-relaxation periods; and the upwind-in and downwind-out mode (13%) under northerly or southerly winds. These modes are discussed with the low-pass filtered model results and verified by a forcing–response joint EOF analysis.
Abstract
This study compares the impacts of Arctic sea ice decline on the Atlantic meridional overturning circulation (AMOC) in two configurations of the Community Earth System Model with different horizontal resolution. In a suite of model experiments, we impose radiative imbalance at the ice surface, replicating a loss of sea ice cover comparable to that observed during 1979–2014, and we find dramatic differences in the AMOC response between the two models. In the lower-resolution configuration, the AMOC weakens by about one-third over the first 100 years, approaching a new quasi-equilibrium. By contrast, in the higher-resolution configuration, the AMOC weakens by ~10% during the first 20–30 years followed by a full recovery driven by invigorated deep water formation in the Labrador Sea and adjacent regions. We investigate these differences using a diagnostic AMOC stability indicator, which reflects the AMOC freshwater transport in and out of the basin and hence the strength of the basin-scale salt-advection feedback. This indicator suggests that the AMOC in the lower-resolution model is less stable and more sensitive to surface perturbations, as confirmed by hosing experiments mimicking Arctic freshening due to sea ice decline. Differences between the models’ mean states, including the Atlantic Ocean mean surface freshwater fluxes, control the differences in AMOC stability. Our results demonstrate that the AMOC stability indicator is indeed useful for evaluating AMOC sensitivity to perturbations. We emphasize that, despite the differences in the long-term adjustment, both models simulate a multidecadal AMOC weakening caused by Arctic sea ice decline, relevant to climate change.
Abstract
This study compares the impacts of Arctic sea ice decline on the Atlantic meridional overturning circulation (AMOC) in two configurations of the Community Earth System Model with different horizontal resolution. In a suite of model experiments, we impose radiative imbalance at the ice surface, replicating a loss of sea ice cover comparable to that observed during 1979–2014, and we find dramatic differences in the AMOC response between the two models. In the lower-resolution configuration, the AMOC weakens by about one-third over the first 100 years, approaching a new quasi-equilibrium. By contrast, in the higher-resolution configuration, the AMOC weakens by ~10% during the first 20–30 years followed by a full recovery driven by invigorated deep water formation in the Labrador Sea and adjacent regions. We investigate these differences using a diagnostic AMOC stability indicator, which reflects the AMOC freshwater transport in and out of the basin and hence the strength of the basin-scale salt-advection feedback. This indicator suggests that the AMOC in the lower-resolution model is less stable and more sensitive to surface perturbations, as confirmed by hosing experiments mimicking Arctic freshening due to sea ice decline. Differences between the models’ mean states, including the Atlantic Ocean mean surface freshwater fluxes, control the differences in AMOC stability. Our results demonstrate that the AMOC stability indicator is indeed useful for evaluating AMOC sensitivity to perturbations. We emphasize that, despite the differences in the long-term adjustment, both models simulate a multidecadal AMOC weakening caused by Arctic sea ice decline, relevant to climate change.
Abstract
In recent years the semiarid region of northern China, which has total annual precipitation between 200 and 500 mm, has shown signs of severe desertification. Intensive theoretical and observational studies are currently underway to examine the climate changes and other contributing factors. In this study, we used the 1951–86 monthly precipitation measurements in this region to study their fluctuations and relationship with the El Niño/Southern Oscillation. Three main features are identified: 1) a 2–3 year quasi-periodic fluctuation, 2) a tendency for rainfall deficiency for the whole region during ENSO years, and 3) a significant correlation between the precipitation fluctuation in the southern part of this region and Southern Oscillation index, with the former lagging the latter by 2–5 months. These features are also evident from analysis of the proxy data during the last hundred years. Discussions on the possible link between the precipitation fluctuation, the summer monsoon, the western Pacific subtropical high, and ENSO are also presented.
Abstract
In recent years the semiarid region of northern China, which has total annual precipitation between 200 and 500 mm, has shown signs of severe desertification. Intensive theoretical and observational studies are currently underway to examine the climate changes and other contributing factors. In this study, we used the 1951–86 monthly precipitation measurements in this region to study their fluctuations and relationship with the El Niño/Southern Oscillation. Three main features are identified: 1) a 2–3 year quasi-periodic fluctuation, 2) a tendency for rainfall deficiency for the whole region during ENSO years, and 3) a significant correlation between the precipitation fluctuation in the southern part of this region and Southern Oscillation index, with the former lagging the latter by 2–5 months. These features are also evident from analysis of the proxy data during the last hundred years. Discussions on the possible link between the precipitation fluctuation, the summer monsoon, the western Pacific subtropical high, and ENSO are also presented.
Abstract
A computationally efficient method is developed to analyze the vortex wind fields of radar-observed mesocyclones. The method has the following features. (i) The analysis is performed in a nested domain over the mesocyclone area on a selected tilt of radar low-elevation scan. (ii) The background error correlation function is formulated with a desired vortex-flow dependence in the cylindrical coordinates cocentered with the mesocyclone. (iii) The square root of the background error covariance matrix is derived analytically to precondition the cost function and thus enhance the computational efficiency. Using this method, the vortex wind analysis can be performed efficiently either in a stand-alone fashion or as an additional step of targeted finescale analysis in the existing radar wind analysis system developed for nowcast applications. The effectiveness and performance of the method are demonstrated by examples of analyzed wind fields for the tornadic mesocyclones observed by operational Doppler radars in Oklahoma on 24 May 2011 and 20 May 2013.
Abstract
A computationally efficient method is developed to analyze the vortex wind fields of radar-observed mesocyclones. The method has the following features. (i) The analysis is performed in a nested domain over the mesocyclone area on a selected tilt of radar low-elevation scan. (ii) The background error correlation function is formulated with a desired vortex-flow dependence in the cylindrical coordinates cocentered with the mesocyclone. (iii) The square root of the background error covariance matrix is derived analytically to precondition the cost function and thus enhance the computational efficiency. Using this method, the vortex wind analysis can be performed efficiently either in a stand-alone fashion or as an additional step of targeted finescale analysis in the existing radar wind analysis system developed for nowcast applications. The effectiveness and performance of the method are demonstrated by examples of analyzed wind fields for the tornadic mesocyclones observed by operational Doppler radars in Oklahoma on 24 May 2011 and 20 May 2013.
A Three-Step Method for Estimating Vortex Center Locations in Four-Dimensional Space from Radar-Observed Tornadic MesocyclonesAbstract
The recently developed two-dimensional variational methods for analyzing vortex winds from radar-observed mesocyclones can be extended to analyze three-dimensional vortex winds, but the first task for this extension is to estimate the vortex center location and its continuous variations in four-dimensional space so that the horizontal location of the vortex center can be expressed as a continuous function of height and time. To accomplish this task, a three-step method is developed in this paper. The method is applied to the Moore, Oklahoma, tornadic mesocyclone observed by the operational KTLX radar (Oklahoma City, Oklahoma) and the NSSL phased-array radar on 20 May 2013. The estimated vortex center trajectory at the ground level is verified with the tornado damage survey data. The estimated vortex center trajectories above the ground (up to 4-km height) reveal that the vortex core was initially tilted northeastward along the direction of the environmental flow and its vertical shear but became nearly vertical about 16 min later and 4 min before the vortex started to cause EF5 damages.
Abstract
The recently developed two-dimensional variational methods for analyzing vortex winds from radar-observed mesocyclones can be extended to analyze three-dimensional vortex winds, but the first task for this extension is to estimate the vortex center location and its continuous variations in four-dimensional space so that the horizontal location of the vortex center can be expressed as a continuous function of height and time. To accomplish this task, a three-step method is developed in this paper. The method is applied to the Moore, Oklahoma, tornadic mesocyclone observed by the operational KTLX radar (Oklahoma City, Oklahoma) and the NSSL phased-array radar on 20 May 2013. The estimated vortex center trajectory at the ground level is verified with the tornado damage survey data. The estimated vortex center trajectories above the ground (up to 4-km height) reveal that the vortex core was initially tilted northeastward along the direction of the environmental flow and its vertical shear but became nearly vertical about 16 min later and 4 min before the vortex started to cause EF5 damages.
Abstract
This study investigates modulation of El Niño–Southern Oscillation (ENSO) on the Madden–Julian oscillation (MJO) propagation during boreal winter. Results show that the spatiotemporal evolution of MJO manifests as a fast equatorially symmetric propagation from the Indian Ocean to the equatorial western Pacific (EWP) during El Niño, whereas the MJO during La Niña is very slow and tends to frequently “detour” via the southern Maritime Continent (MC). The westward group velocity of the MJO is also more significant during El Niño. Based on the dynamics-oriented diagnostics, it is found that, during El Niño, the much stronger leading suppressed convection over the EWP excites a significant front Walker cell, which further triggers a larger Kelvin wave easterly wind anomaly and premoistening and heating effects to the east. However, the equatorial Rossby wave to the west tends to decouple with the MJO convection. Both effects can result in fast MJO propagation. The opposite holds during La Niña. A column-integrated moisture budget analysis reveals that the sea surface temperature anomaly driving both the eastward and equatorward gradients of the low-frequency moisture anomaly during El Niño, as opposed to the westward and poleward gradients during La Niña, induces moist advection over the equatorial eastern MC–EWP region due to the intraseasonal wind anomaly and therefore enhances the zonal asymmetry of the moisture tendency, supporting fast propagation. The role of nonlinear advection by synoptic-scale Kelvin waves is also nonnegligible in distinguishing fast and slow MJO modes. This study emphasizes the crucial roles of dynamical wave feedback and moisture–convection feedback in modulating the MJO propagation by ENSO.
Abstract
This study investigates modulation of El Niño–Southern Oscillation (ENSO) on the Madden–Julian oscillation (MJO) propagation during boreal winter. Results show that the spatiotemporal evolution of MJO manifests as a fast equatorially symmetric propagation from the Indian Ocean to the equatorial western Pacific (EWP) during El Niño, whereas the MJO during La Niña is very slow and tends to frequently “detour” via the southern Maritime Continent (MC). The westward group velocity of the MJO is also more significant during El Niño. Based on the dynamics-oriented diagnostics, it is found that, during El Niño, the much stronger leading suppressed convection over the EWP excites a significant front Walker cell, which further triggers a larger Kelvin wave easterly wind anomaly and premoistening and heating effects to the east. However, the equatorial Rossby wave to the west tends to decouple with the MJO convection. Both effects can result in fast MJO propagation. The opposite holds during La Niña. A column-integrated moisture budget analysis reveals that the sea surface temperature anomaly driving both the eastward and equatorward gradients of the low-frequency moisture anomaly during El Niño, as opposed to the westward and poleward gradients during La Niña, induces moist advection over the equatorial eastern MC–EWP region due to the intraseasonal wind anomaly and therefore enhances the zonal asymmetry of the moisture tendency, supporting fast propagation. The role of nonlinear advection by synoptic-scale Kelvin waves is also nonnegligible in distinguishing fast and slow MJO modes. This study emphasizes the crucial roles of dynamical wave feedback and moisture–convection feedback in modulating the MJO propagation by ENSO.
