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Abstract
The atmospheric and oceanic causes of North American droughts are examined using observations and ensemble climate simulations. The models indicate that oceanic forcing of annual mean precipitation variability accounts for up to 40% of total variance in northeastern Mexico, the southern Great Plains, and the Gulf Coast states but less than 10% in central and eastern Canada. Observations and models indicate robust tropical Pacific and tropical North Atlantic forcing of annual mean precipitation and soil moisture with the most heavily influenced areas being in southwestern North America and the southern Great Plains. In these regions, individual wet and dry years, droughts, and decadal variations are well reproduced in atmosphere models forced by observed SSTs. Oceanic forcing was important in causing multiyear droughts in the 1950s and at the turn of the twenty-first century, although a similar ocean configuration in the 1970s was not associated with drought owing to an overwhelming influence of internal atmospheric variability. Up to half of the soil moisture deficits during severe droughts in the southeast United States in 2000, Texas in 2011, and the central Great Plains in 2012 were related to SST forcing, although SST forcing was an insignificant factor for northern Great Plains drought in 1988. During the early twenty-first century, natural decadal swings in tropical Pacific and North Atlantic SSTs have contributed to a dry regime for the United States. Long-term changes caused by increasing trace gas concentrations are now contributing to a modest signal of soil moisture depletion, mainly over the U.S. Southwest, thereby prolonging the duration and severity of naturally occurring droughts.
Abstract
The atmospheric and oceanic causes of North American droughts are examined using observations and ensemble climate simulations. The models indicate that oceanic forcing of annual mean precipitation variability accounts for up to 40% of total variance in northeastern Mexico, the southern Great Plains, and the Gulf Coast states but less than 10% in central and eastern Canada. Observations and models indicate robust tropical Pacific and tropical North Atlantic forcing of annual mean precipitation and soil moisture with the most heavily influenced areas being in southwestern North America and the southern Great Plains. In these regions, individual wet and dry years, droughts, and decadal variations are well reproduced in atmosphere models forced by observed SSTs. Oceanic forcing was important in causing multiyear droughts in the 1950s and at the turn of the twenty-first century, although a similar ocean configuration in the 1970s was not associated with drought owing to an overwhelming influence of internal atmospheric variability. Up to half of the soil moisture deficits during severe droughts in the southeast United States in 2000, Texas in 2011, and the central Great Plains in 2012 were related to SST forcing, although SST forcing was an insignificant factor for northern Great Plains drought in 1988. During the early twenty-first century, natural decadal swings in tropical Pacific and North Atlantic SSTs have contributed to a dry regime for the United States. Long-term changes caused by increasing trace gas concentrations are now contributing to a modest signal of soil moisture depletion, mainly over the U.S. Southwest, thereby prolonging the duration and severity of naturally occurring droughts.
Abstract
A form of the potential vorticity (PV) budget is proposed that facilitates analysis on the role of global heat sources and sinks in the general circulation. A local diabatic source of PV occurs due to vertical variations of heating. Additionally, since the irrotational mass circulation in isentropic coordinates is uniquely linked to diabatic heating, the associated horizontal advection of PV may be viewed as a diabatic source. The sum of these processes constitutes an effective “baroclinic wave source” due to diabatic processes, and is analogous to the effective barotropic Rossby wave source due to divergence as discussed by Sardeshmukh and Hoskins.
Diagnostic results are presented for the upper-tropospheric PV balance at 350 K during northern winter. When the PV budget is diagnosed in its conventional form, the midlatitude flow appears insulated from the influence of tropical heating in the sense that diabatic sources and sinks are mainly due to vertical variations of extratropical heat sources and sinks. In the NH, these sources/sinks are balanced by the mean horizontal advection of PV by the total flow, which acts to transport PV from reservoirs of large values over eastern Asia and Canada to small values over the central North Pacific and western North Atlantic oceans.
Analysis of the effective baroclinic wave source reveals that the midlatitude PV balance depends strongly on the distribution of tropical heating, a result that agrees more favorably with empirical and numerical studies on tropical–extratropical interactions. Sinks due to horizontal PV advection by the irrotational flow occur throughout the eastern hemisphere along 30° latitude, and exceed the local sources associated with in situ diabatic cooling. The implied poleward transport of low PV air from the tropics occurs in the outflow branch of the regional Hadley circulation, revealing the large influence of the Australasian monsoon.
Abstract
A form of the potential vorticity (PV) budget is proposed that facilitates analysis on the role of global heat sources and sinks in the general circulation. A local diabatic source of PV occurs due to vertical variations of heating. Additionally, since the irrotational mass circulation in isentropic coordinates is uniquely linked to diabatic heating, the associated horizontal advection of PV may be viewed as a diabatic source. The sum of these processes constitutes an effective “baroclinic wave source” due to diabatic processes, and is analogous to the effective barotropic Rossby wave source due to divergence as discussed by Sardeshmukh and Hoskins.
Diagnostic results are presented for the upper-tropospheric PV balance at 350 K during northern winter. When the PV budget is diagnosed in its conventional form, the midlatitude flow appears insulated from the influence of tropical heating in the sense that diabatic sources and sinks are mainly due to vertical variations of extratropical heat sources and sinks. In the NH, these sources/sinks are balanced by the mean horizontal advection of PV by the total flow, which acts to transport PV from reservoirs of large values over eastern Asia and Canada to small values over the central North Pacific and western North Atlantic oceans.
Analysis of the effective baroclinic wave source reveals that the midlatitude PV balance depends strongly on the distribution of tropical heating, a result that agrees more favorably with empirical and numerical studies on tropical–extratropical interactions. Sinks due to horizontal PV advection by the irrotational flow occur throughout the eastern hemisphere along 30° latitude, and exceed the local sources associated with in situ diabatic cooling. The implied poleward transport of low PV air from the tropics occurs in the outflow branch of the regional Hadley circulation, revealing the large influence of the Australasian monsoon.
Abstract
The potential for seasonal mean predictability over the Pacific and North American regions is evaluated as a function of the amplitude of equatorial Pacific sea surface temperature forcing, the phase of that forcing, and the phase of the annual cycle. The potential predictability is measured as the ratio of the seasonal mean SST-forced signal and the internally generated seasonal mean noise. The authors’ assessments are derived from the output of ensemble atmospheric general circulation model experiments forced with observed monthly SSTs for 1950–94. Using a perfect prognostic approach, results are presented on the predictability of upper-tropospheric circulation, North American land temperature, and precipitation.
Seasonal predictability is shown to depend on the amplitude of the SST-forced signal, whereas the background noise is largely independent of SSTs. To zero order, that signal grows linearly with the amplitude of anomalous SSTs. An important departure from this is with respect to the phase of tropical Pacific SST anomalies, and the simulated atmospheric signals were stronger for ENSO’s extreme warm phases compared to ENSO’s extreme cold phases. This asymmetry can be traced throughout the teleconnection chain that links the ENSO forcing region with North American climate.
With regard to the annual cycle’s role, the North American climate is shown to be most predictable during the late winter and early spring season of warm events. This stems from the fact that the SST-forced signal during warm events at that time of year is only slightly weaker than in midwinter, whereas the background noise is substantially reduced. Predictability during spring is significantly greater than that occurring in fall, due to a much weaker fall signal. Observational analyses are presented that corroborate these key model results, in particular enhanced skill during ENSO’s warm phase and a springtime predictability peak.
Finally, a comparison is made between the classic ratio of variance measure of predictability that commingles all warm, cold, and non-ENSO years to yield a single estimate, against such a ratio calculated for individual events. North American seasonal predictability for specific events can greatly exceed this single gross measure, and it is shown that the latter is a poor yardstick of the prospects for skillful predictions during extreme ENSO states.
Abstract
The potential for seasonal mean predictability over the Pacific and North American regions is evaluated as a function of the amplitude of equatorial Pacific sea surface temperature forcing, the phase of that forcing, and the phase of the annual cycle. The potential predictability is measured as the ratio of the seasonal mean SST-forced signal and the internally generated seasonal mean noise. The authors’ assessments are derived from the output of ensemble atmospheric general circulation model experiments forced with observed monthly SSTs for 1950–94. Using a perfect prognostic approach, results are presented on the predictability of upper-tropospheric circulation, North American land temperature, and precipitation.
Seasonal predictability is shown to depend on the amplitude of the SST-forced signal, whereas the background noise is largely independent of SSTs. To zero order, that signal grows linearly with the amplitude of anomalous SSTs. An important departure from this is with respect to the phase of tropical Pacific SST anomalies, and the simulated atmospheric signals were stronger for ENSO’s extreme warm phases compared to ENSO’s extreme cold phases. This asymmetry can be traced throughout the teleconnection chain that links the ENSO forcing region with North American climate.
With regard to the annual cycle’s role, the North American climate is shown to be most predictable during the late winter and early spring season of warm events. This stems from the fact that the SST-forced signal during warm events at that time of year is only slightly weaker than in midwinter, whereas the background noise is substantially reduced. Predictability during spring is significantly greater than that occurring in fall, due to a much weaker fall signal. Observational analyses are presented that corroborate these key model results, in particular enhanced skill during ENSO’s warm phase and a springtime predictability peak.
Finally, a comparison is made between the classic ratio of variance measure of predictability that commingles all warm, cold, and non-ENSO years to yield a single estimate, against such a ratio calculated for individual events. North American seasonal predictability for specific events can greatly exceed this single gross measure, and it is shown that the latter is a poor yardstick of the prospects for skillful predictions during extreme ENSO states.
Abstract
The variability in extratropical atmospheric anomalies from one El Niño winter to another is examined. This study offers an interpretation for such observed inter–El Niño variations and discusses implications for seasonal atmospheric predictability.
The seven strongest El Niño events of the 1950–94 period are selected in order to form a composite 500-mb circulation anomaly over the Pacific–North American region. Individual events are shown to deviate significantly from such a composite. Using a large ensemble of atmospheric general circulation model simulations forced with the observed sea surface temperatures of 1950–94, the authors argue that the observed inter–El Niño atmospheric variations are primarily due to internal atmospheric variability. The observed inter–El Niño variability in spatial patterns of the extratropical circulation anomalies appears not to be a deterministic feature of the SSTs and may thus be inherently unpredictable.
Atmospheric general circulation model results further suggest that the spatial pattern of the extratropical response to El Niño consists largely of a single deterministic structure. Some variability in the spatial pattern of the simulated extratropical signal exists, but this is appreciably smaller than the internal atmospheric variability. On the other hand, the amplitude of the signal in the extratropics is shown to be a sensitive function of the particular El Niño, and the model response increases almost linearly with the strength of the SST warming. The practical implications for dynamic seasonal climate prediction in the extratropics are discussed, including an assessment of accuracy requirements for the SST predictions themselves.
Abstract
The variability in extratropical atmospheric anomalies from one El Niño winter to another is examined. This study offers an interpretation for such observed inter–El Niño variations and discusses implications for seasonal atmospheric predictability.
The seven strongest El Niño events of the 1950–94 period are selected in order to form a composite 500-mb circulation anomaly over the Pacific–North American region. Individual events are shown to deviate significantly from such a composite. Using a large ensemble of atmospheric general circulation model simulations forced with the observed sea surface temperatures of 1950–94, the authors argue that the observed inter–El Niño atmospheric variations are primarily due to internal atmospheric variability. The observed inter–El Niño variability in spatial patterns of the extratropical circulation anomalies appears not to be a deterministic feature of the SSTs and may thus be inherently unpredictable.
Atmospheric general circulation model results further suggest that the spatial pattern of the extratropical response to El Niño consists largely of a single deterministic structure. Some variability in the spatial pattern of the simulated extratropical signal exists, but this is appreciably smaller than the internal atmospheric variability. On the other hand, the amplitude of the signal in the extratropics is shown to be a sensitive function of the particular El Niño, and the model response increases almost linearly with the strength of the SST warming. The practical implications for dynamic seasonal climate prediction in the extratropics are discussed, including an assessment of accuracy requirements for the SST predictions themselves.
Climate simulations and hindcast experiments of increasingly large ensemble size are being performed to determine the predictive capability of atmospheric general circulation models (AGCMs) on seasonal or longer timescales. These have exhibited large sensitivity to anomalous boundary forcing associated with global sea surface temperatures (SSTs). Large-scale patterns of climate anomalies are at times generated in the extratropics when the AGCM is forced by the SSTs associated with El Niño events. It remains to be determined whether on average such results imply useful predictive skill for seasonal means in the extratropics. Indeed, given the prospects for small, if not negligible, skill in the extratropics as revealed in variance tests of boundary-forced potential predictability, one is forced to question and examine the limits of AGCM methods.
These issues are addressed within the context of a large ensemble of climate simulations using an AGCM forced with observed SSTs for the 1982–93 period. From the analysis of the model data it is argued that the impact of interannual changes in SSTs is to create a shift in the extratropical-mean state, although this shift is small and resides within the envelope of atmospheric states attained with climatological SSTs. This effect does not have any appreciable impact on the total variance of seasonal-mean atmospheric states and confirms the conclusions drawn from earlier studies.
A reliable detection of the boundary-forced shift in the mean state, however, is shown to be feasible when a sufficiently large ensemble of model runs is considered. The shift in the mean state has a certain probability of being in phase with the observed seasonal anomalies. Indeed, the benefit of generating the ensemble prediction lies in the fact that it is the ensemble-mean response that nature has the greatest probability of selecting. Nonetheless, to the extent that the observed anomalies are at least partly the result of natural variability, AGCM-based seasonal predictions will be inherently probabilistic. Implications for AGCM simulations of the extratropical response to the boundary forcing, and for seasonal-mean predictions in general, are discussed.
Climate simulations and hindcast experiments of increasingly large ensemble size are being performed to determine the predictive capability of atmospheric general circulation models (AGCMs) on seasonal or longer timescales. These have exhibited large sensitivity to anomalous boundary forcing associated with global sea surface temperatures (SSTs). Large-scale patterns of climate anomalies are at times generated in the extratropics when the AGCM is forced by the SSTs associated with El Niño events. It remains to be determined whether on average such results imply useful predictive skill for seasonal means in the extratropics. Indeed, given the prospects for small, if not negligible, skill in the extratropics as revealed in variance tests of boundary-forced potential predictability, one is forced to question and examine the limits of AGCM methods.
These issues are addressed within the context of a large ensemble of climate simulations using an AGCM forced with observed SSTs for the 1982–93 period. From the analysis of the model data it is argued that the impact of interannual changes in SSTs is to create a shift in the extratropical-mean state, although this shift is small and resides within the envelope of atmospheric states attained with climatological SSTs. This effect does not have any appreciable impact on the total variance of seasonal-mean atmospheric states and confirms the conclusions drawn from earlier studies.
A reliable detection of the boundary-forced shift in the mean state, however, is shown to be feasible when a sufficiently large ensemble of model runs is considered. The shift in the mean state has a certain probability of being in phase with the observed seasonal anomalies. Indeed, the benefit of generating the ensemble prediction lies in the fact that it is the ensemble-mean response that nature has the greatest probability of selecting. Nonetheless, to the extent that the observed anomalies are at least partly the result of natural variability, AGCM-based seasonal predictions will be inherently probabilistic. Implications for AGCM simulations of the extratropical response to the boundary forcing, and for seasonal-mean predictions in general, are discussed.
Abstract
The origin of extreme climate states during the exceptional 1982–83 El Niño event has continued to be a source of controversy and debate. On the one hand, empirical analyses of extratropical climate patterns during past El Niño events suggests the observed anomalies during 1982–83 were consistent with tropical forcing. On the other hand, the large amplitude of those anomalies have not been replicated in atmospheric general circulation model (AGCM) simulations for that period performed as part of the Atmospheric Model Intercomparison Project (AMIP).
It has recently become apparent, however, that the sea surface boundary conditions used to drive the multitude of AMIP simulations were deficient, in that at least 30% of available tropical Pacific SST observations were discarded in the analysis cycle due to excessive trimming constraints. It is shown from a reanalysis of the sea surface temperatures that the observed east equatorial Pacific waters were 1.5°C warmer than original estimates.
In order to address the extent to which simulations of the extratropical climate of 1982–83 are sensitive to different SST analyses of that period, a parallel suite of AGCM simulations using two SST prescriptions is performed. One set is based on the blended satellite–in situ data used also in the AMIP runs, whereas the other is based on the optimum interpolation (OI) reanalysis. A nine-member ensemble of such simulations is performed, and this is compared with observations. The model response using the original blended SSTs is shown to severely underestimate the tropical rainfall anomalies, and this contributes to the simulation of a weak extratropical response as reported earlier in the AMIP experiments. A larger, more realistic response during 1982–83 is shown to occur in an identical set of runs based on the OI SST boundary conditions, and most aspects of the observed pattern and strength of the Pacific–North American climate anomalies during that winter are reproduced in the model’s ensemble mean response.
Further analysis of the models’ intersample variability are performed to ascertain the extent to which the observed anomalies may have been influenced by atmospheric initial conditions. It is shown from the OI runs that the observed tropical Pacific rainfall anomalies and the Southern Oscillation index were phenomena causally determined by the El Niño. Even over the Pacific–North American region, the spatial pattern of the anomalies in individual runs was highly reproducible, and several members of the OI runs achieved climate anomalies exceeding in amplitude those observed. The findings strongly indicate the important role of El Niño in determining the climate state over the Pacific–North American region during 1982–83, and various competing hypotheses are critiqued in light of these new model results.
Abstract
The origin of extreme climate states during the exceptional 1982–83 El Niño event has continued to be a source of controversy and debate. On the one hand, empirical analyses of extratropical climate patterns during past El Niño events suggests the observed anomalies during 1982–83 were consistent with tropical forcing. On the other hand, the large amplitude of those anomalies have not been replicated in atmospheric general circulation model (AGCM) simulations for that period performed as part of the Atmospheric Model Intercomparison Project (AMIP).
It has recently become apparent, however, that the sea surface boundary conditions used to drive the multitude of AMIP simulations were deficient, in that at least 30% of available tropical Pacific SST observations were discarded in the analysis cycle due to excessive trimming constraints. It is shown from a reanalysis of the sea surface temperatures that the observed east equatorial Pacific waters were 1.5°C warmer than original estimates.
In order to address the extent to which simulations of the extratropical climate of 1982–83 are sensitive to different SST analyses of that period, a parallel suite of AGCM simulations using two SST prescriptions is performed. One set is based on the blended satellite–in situ data used also in the AMIP runs, whereas the other is based on the optimum interpolation (OI) reanalysis. A nine-member ensemble of such simulations is performed, and this is compared with observations. The model response using the original blended SSTs is shown to severely underestimate the tropical rainfall anomalies, and this contributes to the simulation of a weak extratropical response as reported earlier in the AMIP experiments. A larger, more realistic response during 1982–83 is shown to occur in an identical set of runs based on the OI SST boundary conditions, and most aspects of the observed pattern and strength of the Pacific–North American climate anomalies during that winter are reproduced in the model’s ensemble mean response.
Further analysis of the models’ intersample variability are performed to ascertain the extent to which the observed anomalies may have been influenced by atmospheric initial conditions. It is shown from the OI runs that the observed tropical Pacific rainfall anomalies and the Southern Oscillation index were phenomena causally determined by the El Niño. Even over the Pacific–North American region, the spatial pattern of the anomalies in individual runs was highly reproducible, and several members of the OI runs achieved climate anomalies exceeding in amplitude those observed. The findings strongly indicate the important role of El Niño in determining the climate state over the Pacific–North American region during 1982–83, and various competing hypotheses are critiqued in light of these new model results.
Abstract
Four observed El Niño-Southern Oscillation (ENSO) events are studied to determine the mechanisms responsible for the anomalous extratropical atmospheric circulation during northern winter. A parallel analysis of a GCM's response to El Niño is performed in order to assess if similar mechanisms are operative in the model atmosphere. The observed stationary wave anomalies over the Pacific/North American (PNA) region are found to he similar during the four winters despite appreciable differences in sea surface temperatures. The anomalous transient vorticity fluxes are remarkably robust over the North Pacific during each event, with an eastward extension of the climatological storm track leading to strong cyclonic forcing near 40°N, 150°W. This forcing is in phase with the seasonal mean Aleutian trough anomaly suggesting the importance of eddy-mean flow interactions. By comparison, the intersample variability of the GCM response over the PNA region is found to exceed the observed inter-El Niño variability. This stems primarily from a large variability in the model's anomalous transients over the North Pacific.
Further analysis using a linear stationary wave model reveals that the extratropical vorticity transients are the primary mechanism maintaining the stationary wave anomalies over the PNA region during all four observed ENSO winters. In the case of the GCM, the organization of transient eddies is ill defined over the North Pacific, a behavior that appears more indicative of model error than the unpredictable component of seasonal mean storm track anomalies. A physical model is proposed to explain the robustness of the tropical controlling influence of the extratropical transients in nature. A simple equatorial Pacific heat source directly forces a tropical anticyclone whose phase relative to the climatological tropical anticyclone leads to an eastward extension of the subtropical jet stream. This mechanism appears to be equally effective for a beat source located either in the central or eastern Pacific basin.
Abstract
Four observed El Niño-Southern Oscillation (ENSO) events are studied to determine the mechanisms responsible for the anomalous extratropical atmospheric circulation during northern winter. A parallel analysis of a GCM's response to El Niño is performed in order to assess if similar mechanisms are operative in the model atmosphere. The observed stationary wave anomalies over the Pacific/North American (PNA) region are found to he similar during the four winters despite appreciable differences in sea surface temperatures. The anomalous transient vorticity fluxes are remarkably robust over the North Pacific during each event, with an eastward extension of the climatological storm track leading to strong cyclonic forcing near 40°N, 150°W. This forcing is in phase with the seasonal mean Aleutian trough anomaly suggesting the importance of eddy-mean flow interactions. By comparison, the intersample variability of the GCM response over the PNA region is found to exceed the observed inter-El Niño variability. This stems primarily from a large variability in the model's anomalous transients over the North Pacific.
Further analysis using a linear stationary wave model reveals that the extratropical vorticity transients are the primary mechanism maintaining the stationary wave anomalies over the PNA region during all four observed ENSO winters. In the case of the GCM, the organization of transient eddies is ill defined over the North Pacific, a behavior that appears more indicative of model error than the unpredictable component of seasonal mean storm track anomalies. A physical model is proposed to explain the robustness of the tropical controlling influence of the extratropical transients in nature. A simple equatorial Pacific heat source directly forces a tropical anticyclone whose phase relative to the climatological tropical anticyclone leads to an eastward extension of the subtropical jet stream. This mechanism appears to be equally effective for a beat source located either in the central or eastern Pacific basin.
Abstract
Remarkable among the atmospheric phenomena associated with El Niño–Southern Oscillation (ENSO) is the lag in the zonal mean tropical thermal anomalies relative to equatorial east Pacific sea surface temperatures (SSTs). For the period 1950–99, the maximum correlation between observed zonal mean tropical 200-mb heights and a Niño-3.4 (5°N–5°S, 120°–170°W) SST index occurs when the atmosphere lags by 1–3 months, consistent with numerous previous studies. Results from atmospheric general circulation model (GCM) simulations forced by the monthly SST variations of the last half-century confirm and establish the robustness of this observed lag.
An additional feature of the delay in atmospheric response that involves an apparent memory or lingering of the tropical thermal anomalies several seasons beyond the Niño-3.4 SST index peak is documented in this study. It is characterized by a strong asymmetry in the strength of the zonal mean tropical 200-mb height response relative to that peak, being threefold stronger in the summer following the peak compared to the preceding summer. This occurs despite weaker Niño-3.4 SST forcing in the following summer compared to the preceding summer.
The 1–3-month lag in maximum correlation is reconciled by the fact that the rainfall evolution in the tropical Pacific associated with the ENSO SST anomalies itself lags one season, with the latter acting as the immediate forcing for the 200-mb heights. This aspect of the lagged behavior in the tropical atmospheric response occurs independent of any changes in SSTs outside of the tropical east Pacific core region of SST variability related to ENSO. The lingering of the tropical atmospheric thermal signal cannot, however, be reconciled with the ENSO-related SST variability in the tropical eastern Pacific. This part of the tropical atmospheric response is instead intimately tied to the tropical ocean's lagged response to the equatorial east Pacific SST variability, including a warming of the tropical Indian and Atlantic SSTs that peak several seasons after the Niño-3.4 warming peak.
Abstract
Remarkable among the atmospheric phenomena associated with El Niño–Southern Oscillation (ENSO) is the lag in the zonal mean tropical thermal anomalies relative to equatorial east Pacific sea surface temperatures (SSTs). For the period 1950–99, the maximum correlation between observed zonal mean tropical 200-mb heights and a Niño-3.4 (5°N–5°S, 120°–170°W) SST index occurs when the atmosphere lags by 1–3 months, consistent with numerous previous studies. Results from atmospheric general circulation model (GCM) simulations forced by the monthly SST variations of the last half-century confirm and establish the robustness of this observed lag.
An additional feature of the delay in atmospheric response that involves an apparent memory or lingering of the tropical thermal anomalies several seasons beyond the Niño-3.4 SST index peak is documented in this study. It is characterized by a strong asymmetry in the strength of the zonal mean tropical 200-mb height response relative to that peak, being threefold stronger in the summer following the peak compared to the preceding summer. This occurs despite weaker Niño-3.4 SST forcing in the following summer compared to the preceding summer.
The 1–3-month lag in maximum correlation is reconciled by the fact that the rainfall evolution in the tropical Pacific associated with the ENSO SST anomalies itself lags one season, with the latter acting as the immediate forcing for the 200-mb heights. This aspect of the lagged behavior in the tropical atmospheric response occurs independent of any changes in SSTs outside of the tropical east Pacific core region of SST variability related to ENSO. The lingering of the tropical atmospheric thermal signal cannot, however, be reconciled with the ENSO-related SST variability in the tropical eastern Pacific. This part of the tropical atmospheric response is instead intimately tied to the tropical ocean's lagged response to the equatorial east Pacific SST variability, including a warming of the tropical Indian and Atlantic SSTs that peak several seasons after the Niño-3.4 warming peak.
A thought experiment on atmospheric interannual variability associated with El Nino is formulated and is used to investigate the seasonal predictability as it relates to the practice of generating ensemble GCM predictions. The purpose of the study is to gain insight on two important issues within seasonal climate forecasting: (i) the dependence of seasonal forecast skill on a GCM's ensemble size, and the benefits to be expected from using increasingly larger ensembles, and (ii) the merits of dynamical GCM techniques relative to empirical statistical ones for making seasonal forecasts, and the scenarios under which the former may be the superior tool.
It is first emphasized that seasonal predictability is an intrinsic property of the observed system, and is inherently limited owing to the nonzero spread of seasonally averaged atmospheric states subjected to identical SST boundary forcing. Further, such boundary forced predictability can be diagnosed from the change in the statistical distribution of the atmospheric states with respect to different SSTs. The GCM prediction problem is thus cast as one of determining this statistical distribution, and its variation with respect to SST forcing.
For a perfect GCM, the skill of the seasonal prediction based on the ensemble mean is shown to be always greater than that based on a single realization, consistent with the results of other studies. However, prediction skill for larger ensembles cannot exceed the observed system's inherent predictability. It is argued that the very necessity for larger ensembles is a testimony for the low predictability of the system.
The advantage of perfect GCM-based seasonal predictions versus ones based on empirical methods is argued to depend on the nonlinearity of the observed atmosphere to SST forcings. If such nonlinearity is high, GCM methods will in principle yield superior seasonal forecast skill. On the other hand, in the absence of nonlinearity, empirical methods trained on the instrumental record may be equally skillful.
A thought experiment on atmospheric interannual variability associated with El Nino is formulated and is used to investigate the seasonal predictability as it relates to the practice of generating ensemble GCM predictions. The purpose of the study is to gain insight on two important issues within seasonal climate forecasting: (i) the dependence of seasonal forecast skill on a GCM's ensemble size, and the benefits to be expected from using increasingly larger ensembles, and (ii) the merits of dynamical GCM techniques relative to empirical statistical ones for making seasonal forecasts, and the scenarios under which the former may be the superior tool.
It is first emphasized that seasonal predictability is an intrinsic property of the observed system, and is inherently limited owing to the nonzero spread of seasonally averaged atmospheric states subjected to identical SST boundary forcing. Further, such boundary forced predictability can be diagnosed from the change in the statistical distribution of the atmospheric states with respect to different SSTs. The GCM prediction problem is thus cast as one of determining this statistical distribution, and its variation with respect to SST forcing.
For a perfect GCM, the skill of the seasonal prediction based on the ensemble mean is shown to be always greater than that based on a single realization, consistent with the results of other studies. However, prediction skill for larger ensembles cannot exceed the observed system's inherent predictability. It is argued that the very necessity for larger ensembles is a testimony for the low predictability of the system.
The advantage of perfect GCM-based seasonal predictions versus ones based on empirical methods is argued to depend on the nonlinearity of the observed atmosphere to SST forcings. If such nonlinearity is high, GCM methods will in principle yield superior seasonal forecast skill. On the other hand, in the absence of nonlinearity, empirical methods trained on the instrumental record may be equally skillful.
Abstract
The semiarid U.S. Great Plains is prone to severe droughts having major consequences for agricultural production, livestock health, and river navigation. The recent 2012 event was accompanied by record deficits in precipitation and high temperatures during the May–August growing season. Here the physics of Great Plains drought are explored by addressing how meteorological drivers induce soil moisture deficits during the growing season. Land surface model (LSM) simulations driven by daily observed meteorological forcing from 1950 to 2013 compare favorably with satellite-derived terrestrial water anomalies and reproduce key features found in the U.S. Drought Monitor. Results from simulations by two LSMs reveal that precipitation was directly responsible for between 72% and 80% of the soil moisture depletion during 2012, and likewise has accounted for the majority of Great Plains soil moisture variability since 1950. Energy balance considerations indicate that a large fraction of the growing season temperature variability is itself driven by precipitation, pointing toward an even larger net contribution of precipitation to soil moisture variability.
To assess robustness across a larger sample of drought events, daily meteorological output from 1050 years of climate simulations, representative of conditions in 1979–2013, are used to drive two LSMs. Growing season droughts, and low soil moisture conditions especially, are confirmed to result principally from rainfall deficits. Antecedent meteorological and soil moisture conditions are shown to affect growing season soil moisture, but their effects are secondary to forcing by contemporaneous rainfall deficits. This understanding of the physics of growing season droughts is used to comment on plausible Great Plains soil moisture changes in a warmer world.
Abstract
The semiarid U.S. Great Plains is prone to severe droughts having major consequences for agricultural production, livestock health, and river navigation. The recent 2012 event was accompanied by record deficits in precipitation and high temperatures during the May–August growing season. Here the physics of Great Plains drought are explored by addressing how meteorological drivers induce soil moisture deficits during the growing season. Land surface model (LSM) simulations driven by daily observed meteorological forcing from 1950 to 2013 compare favorably with satellite-derived terrestrial water anomalies and reproduce key features found in the U.S. Drought Monitor. Results from simulations by two LSMs reveal that precipitation was directly responsible for between 72% and 80% of the soil moisture depletion during 2012, and likewise has accounted for the majority of Great Plains soil moisture variability since 1950. Energy balance considerations indicate that a large fraction of the growing season temperature variability is itself driven by precipitation, pointing toward an even larger net contribution of precipitation to soil moisture variability.
To assess robustness across a larger sample of drought events, daily meteorological output from 1050 years of climate simulations, representative of conditions in 1979–2013, are used to drive two LSMs. Growing season droughts, and low soil moisture conditions especially, are confirmed to result principally from rainfall deficits. Antecedent meteorological and soil moisture conditions are shown to affect growing season soil moisture, but their effects are secondary to forcing by contemporaneous rainfall deficits. This understanding of the physics of growing season droughts is used to comment on plausible Great Plains soil moisture changes in a warmer world.
