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- Author or Editor: Henry F. Diaz x
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Abstract
Diagnosing the sensitivity of the tropical belt provides one framework for understanding how global precipitation patterns may change in a warming world. This paper seeks to understand boreal winter rates of subtropical dry zone expansion since 1979, and explores physical mechanisms. Various reanalysis estimates based on the latitude where zonal mean precipitation P exceeds evaporation E and the zero crossing latitude for the zonal mean meridional streamfunction (
The intercomparison of models and reanalyses supports the prevailing view of a tropical widening, but the forced component of tropical widening has likely been only about 0.1°–0.2° latitude decade−1, considerably less than has generally been assumed based on inferences drawn from observations and reanalyses. Climate model diagnosis indicates that the principal mechanism for forced tropical widening since 1979 has been atmospheric sensitivity to warming oceans. The magnitude of this widening and its potential detectability has been greater in the Southern Hemisphere than in the Northern Hemisphere during boreal winter, in part owing to Antarctic stratospheric ozone depletion.
Abstract
Diagnosing the sensitivity of the tropical belt provides one framework for understanding how global precipitation patterns may change in a warming world. This paper seeks to understand boreal winter rates of subtropical dry zone expansion since 1979, and explores physical mechanisms. Various reanalysis estimates based on the latitude where zonal mean precipitation P exceeds evaporation E and the zero crossing latitude for the zonal mean meridional streamfunction (
The intercomparison of models and reanalyses supports the prevailing view of a tropical widening, but the forced component of tropical widening has likely been only about 0.1°–0.2° latitude decade−1, considerably less than has generally been assumed based on inferences drawn from observations and reanalyses. Climate model diagnosis indicates that the principal mechanism for forced tropical widening since 1979 has been atmospheric sensitivity to warming oceans. The magnitude of this widening and its potential detectability has been greater in the Southern Hemisphere than in the Northern Hemisphere during boreal winter, in part owing to Antarctic stratospheric ozone depletion.
Abstract
The tropical belt is expected to expand in response to global warming, although most of the observed tropical widening since 1980, especially in the Northern Hemisphere, is believed to have mainly originated from natural variability. The view is of a small global warming signal relative to natural variability. Here we focus on the question whether and, if so when, the anthropogenic signal of tropical widening will become detectable. Analysis of two large ensemble climate simulations reveals that the forced signal of tropical width is strongly constrained by the forced signal of global mean temperature. Under a representative concentration pathway 8.5 (RCP8.5) emissions scenario, the aggregate of the two models indicates a regression of about 0.5° lat °C−1 during 1980–2080. The models also reveal that interannual variability in tropical width, a measure of noise used herein, is insensitive to global warming. Reanalysis data are therefore used to constrain the interannual variability, whose magnitude is estimated to be 1.1° latitude. Defining the time of emergence (ToE) for tropical width change as the first year (post-1980) when the forced signal exceeds the magnitude of interannual variability, the multimodel simulations of CMIP5 are used to estimate ToE and its confidence interval. The aforementioned strong constraint between the signal of tropical width change and global mean temperature change motivates using CMIP5-simulated global mean temperature changes to infer ToE. Our best estimate for the probable year for ToE, under an RCP8.5 emissions scenario, is 2058 with 10th–90th percentile confidence of 2047–68. Various sources of uncertainty in estimating the ToE are discussed.
Abstract
The tropical belt is expected to expand in response to global warming, although most of the observed tropical widening since 1980, especially in the Northern Hemisphere, is believed to have mainly originated from natural variability. The view is of a small global warming signal relative to natural variability. Here we focus on the question whether and, if so when, the anthropogenic signal of tropical widening will become detectable. Analysis of two large ensemble climate simulations reveals that the forced signal of tropical width is strongly constrained by the forced signal of global mean temperature. Under a representative concentration pathway 8.5 (RCP8.5) emissions scenario, the aggregate of the two models indicates a regression of about 0.5° lat °C−1 during 1980–2080. The models also reveal that interannual variability in tropical width, a measure of noise used herein, is insensitive to global warming. Reanalysis data are therefore used to constrain the interannual variability, whose magnitude is estimated to be 1.1° latitude. Defining the time of emergence (ToE) for tropical width change as the first year (post-1980) when the forced signal exceeds the magnitude of interannual variability, the multimodel simulations of CMIP5 are used to estimate ToE and its confidence interval. The aforementioned strong constraint between the signal of tropical width change and global mean temperature change motivates using CMIP5-simulated global mean temperature changes to infer ToE. Our best estimate for the probable year for ToE, under an RCP8.5 emissions scenario, is 2058 with 10th–90th percentile confidence of 2047–68. Various sources of uncertainty in estimating the ToE are discussed.
Abstract
One of the major concerns with detecting global climate change is the quality of the data. Climate data are extremely sensitive to errant values and outliers. Prior to analysis of these time series, it is important to remove outliers in a methodical manner.
This study provides statistically derived bounds for the uncertainty associated with surface temperature and precipitation measurements and yields a baseline dataset for validation of climate models as well as for a variety of other climatological uses. A two-step procedure using objective analysis was used to identify outliers. The first step was a temporal check that determines if a particular monthly value is consistent with other monthly values for the same station. The second step utilizes six different spatial interpolation techniques to estimate each monthly time series. Each of the methods is ranked according to its respective correlation coefficients with the actual time series, and the technique with the highest correlation coefficient is chosen as the best estimator. For both temperature and precipitation, a multiple regression scheme was found to be the best estimator for the majority of records. Results from the two steps are merged, and a combined set of quality control flags are generated.
Abstract
One of the major concerns with detecting global climate change is the quality of the data. Climate data are extremely sensitive to errant values and outliers. Prior to analysis of these time series, it is important to remove outliers in a methodical manner.
This study provides statistically derived bounds for the uncertainty associated with surface temperature and precipitation measurements and yields a baseline dataset for validation of climate models as well as for a variety of other climatological uses. A two-step procedure using objective analysis was used to identify outliers. The first step was a temporal check that determines if a particular monthly value is consistent with other monthly values for the same station. The second step utilizes six different spatial interpolation techniques to estimate each monthly time series. Each of the methods is ranked according to its respective correlation coefficients with the actual time series, and the technique with the highest correlation coefficient is chosen as the best estimator. For both temperature and precipitation, a multiple regression scheme was found to be the best estimator for the majority of records. Results from the two steps are merged, and a combined set of quality control flags are generated.
Socioeconomic vulnerabilities and impacts associated with weather and climate hazards in the United States are assessed. Trends in deaths and economic losses resulting from tornadoes, tropical storms and hurricanes, and floods (including flash floods) are presented in detail. To the extent possible, death statistics are normalized by the population at risk, and loss data are adjusted for inflation. The results suggest a significant decline in deaths attributed to tornadoes and hurricanes at the same time that property damages have increased. In contrast, both deaths and losses due to floods have increased substantially in the past few decades.
A qualitative assessment is made of the effects of socioeconomic trends (e.g., the aging population) on the nation's sensitivity to atmospheric hazards and on the need for better information about these hazards. While the tally shows mixed impacts on vulnerability (i.e., some trends may reduce vulnerability while others increase it), the impact on information needs is nearly uniformly greater. More emphasis should be given to the following activities as ways to decrease the overall social burden of atmospheric hazards: 1) improve the use of weather and climate information by emergency managers, 2) develop better impact-assessment methods, and 3) explore new ways to reduce future property losses.
Socioeconomic vulnerabilities and impacts associated with weather and climate hazards in the United States are assessed. Trends in deaths and economic losses resulting from tornadoes, tropical storms and hurricanes, and floods (including flash floods) are presented in detail. To the extent possible, death statistics are normalized by the population at risk, and loss data are adjusted for inflation. The results suggest a significant decline in deaths attributed to tornadoes and hurricanes at the same time that property damages have increased. In contrast, both deaths and losses due to floods have increased substantially in the past few decades.
A qualitative assessment is made of the effects of socioeconomic trends (e.g., the aging population) on the nation's sensitivity to atmospheric hazards and on the need for better information about these hazards. While the tally shows mixed impacts on vulnerability (i.e., some trends may reduce vulnerability while others increase it), the impact on information needs is nearly uniformly greater. More emphasis should be given to the following activities as ways to decrease the overall social burden of atmospheric hazards: 1) improve the use of weather and climate information by emergency managers, 2) develop better impact-assessment methods, and 3) explore new ways to reduce future property losses.
Abstract
Observed United States trends in the annual maximum 1-day precipitation (RX1day) over the last century consist of 15%–25% increases over the eastern United States (East) and 10% decreases over the far western United States (West). This heterogeneous trend pattern departs from comparatively uniform observed increases in precipitable water over the contiguous United States. Here we use an event attribution framework involving parallel sets of global atmospheric model experiments with and without climate change drivers to explain this spatially diverse pattern of extreme daily precipitation trends. We find that RX1day events in our model ensembles respond to observed historical climate change forcing differently across the United States with 5%–10% intensity increases over the East but no appreciable change over the West. This spatially diverse forced signal is broadly similar among three models used, and is positively correlated with the observed trend pattern. Our analysis of model and observations indicates the lack of appreciable RX1day signals over the West is likely due to dynamical effects of climate change forcing—via a wintertime atmospheric circulation anomaly that suppresses vertical motion over the West—largely cancelling thermodynamic effects of increased water vapor availability. The large magnitude of eastern U.S. RX1day increases is unlikely a symptom of a regional heightened sensitivity to climate change forcing. Instead, our ensemble simulations reveal considerable variability in RX1day trend magnitudes arising from internal atmospheric processes alone, and we argue that the remarkable observed increases over the East has most likely resulted from a superposition of strong internal variability with a moderate climate change signal. Implications for future changes in U.S. extreme daily precipitation are discussed.
Abstract
Observed United States trends in the annual maximum 1-day precipitation (RX1day) over the last century consist of 15%–25% increases over the eastern United States (East) and 10% decreases over the far western United States (West). This heterogeneous trend pattern departs from comparatively uniform observed increases in precipitable water over the contiguous United States. Here we use an event attribution framework involving parallel sets of global atmospheric model experiments with and without climate change drivers to explain this spatially diverse pattern of extreme daily precipitation trends. We find that RX1day events in our model ensembles respond to observed historical climate change forcing differently across the United States with 5%–10% intensity increases over the East but no appreciable change over the West. This spatially diverse forced signal is broadly similar among three models used, and is positively correlated with the observed trend pattern. Our analysis of model and observations indicates the lack of appreciable RX1day signals over the West is likely due to dynamical effects of climate change forcing—via a wintertime atmospheric circulation anomaly that suppresses vertical motion over the West—largely cancelling thermodynamic effects of increased water vapor availability. The large magnitude of eastern U.S. RX1day increases is unlikely a symptom of a regional heightened sensitivity to climate change forcing. Instead, our ensemble simulations reveal considerable variability in RX1day trend magnitudes arising from internal atmospheric processes alone, and we argue that the remarkable observed increases over the East has most likely resulted from a superposition of strong internal variability with a moderate climate change signal. Implications for future changes in U.S. extreme daily precipitation are discussed.
Abstract
Year-to-year extreme alterations in California (CA) precipitation, denoted here as flips, present significant challenges to resource managers, emergency management officials, and the state’s economy and ecosystems generally. We evaluate regional (north, central, and south) and statewide flip behavior since 1571 CE utilizing instrumental data and paleoclimate reconstructions. Flips, defined as dry-to-wet and wet-to-dry consecutive alterations between the tailward 30th percentiles of the precipitation distribution, have occurred throughout this period without indication of systematic change through the recent time of modern anthropogenic forcing. Statewide “grand flips” are notably absent between 1892 and 1957; bootstrap Monte Carlo analysis indicates that this feature is consistent with random behavior. Composites for northeastern Pacific Ocean winter sea level pressure and jet-stream winds associated with flip events indicate anomalous high or low pressure during the core precipitation delivery season for dry or wet flip years, respectively, and jet-stream conditions that are also like those associated with individual dry or wet years. Equatorial Pacific sea surface temperatures play a partial role in both dry-to-wet and wet-to-dry events in central and southern CA in the longer-period reconstruction data, with response restricted primarily to southern CA in the smaller sample-size instrumental data. Knowledge of a prior year extreme, potentially representing initiation of a flip, provides no enhancement of prediction quality for the second year beyond that achievable from skillful seasonal prediction of equatorial Pacific sea surface temperatures. Overall, results indicate that the first-order nature of flip behavior from the later 1500s reflects the quasi–white noise nature of precipitation variability in CA, influenced secondarily by equatorial Pacific sea surface conditions, particularly in southern CA.
Abstract
Year-to-year extreme alterations in California (CA) precipitation, denoted here as flips, present significant challenges to resource managers, emergency management officials, and the state’s economy and ecosystems generally. We evaluate regional (north, central, and south) and statewide flip behavior since 1571 CE utilizing instrumental data and paleoclimate reconstructions. Flips, defined as dry-to-wet and wet-to-dry consecutive alterations between the tailward 30th percentiles of the precipitation distribution, have occurred throughout this period without indication of systematic change through the recent time of modern anthropogenic forcing. Statewide “grand flips” are notably absent between 1892 and 1957; bootstrap Monte Carlo analysis indicates that this feature is consistent with random behavior. Composites for northeastern Pacific Ocean winter sea level pressure and jet-stream winds associated with flip events indicate anomalous high or low pressure during the core precipitation delivery season for dry or wet flip years, respectively, and jet-stream conditions that are also like those associated with individual dry or wet years. Equatorial Pacific sea surface temperatures play a partial role in both dry-to-wet and wet-to-dry events in central and southern CA in the longer-period reconstruction data, with response restricted primarily to southern CA in the smaller sample-size instrumental data. Knowledge of a prior year extreme, potentially representing initiation of a flip, provides no enhancement of prediction quality for the second year beyond that achievable from skillful seasonal prediction of equatorial Pacific sea surface temperatures. Overall, results indicate that the first-order nature of flip behavior from the later 1500s reflects the quasi–white noise nature of precipitation variability in CA, influenced secondarily by equatorial Pacific sea surface conditions, particularly in southern CA.
Abstract
The recent dryness in California was unprecedented in the instrumental record. This article employs spatially explicit precipitation reconstructions for California in combination with instrumental data to provide perspective on this event since 1571. The period 2012–15 stands out as particularly extreme in the southern Central Valley and south coast regions. which likely experienced unprecedented precipitation deficits over this time, apart from considerations of increasing temperatures and drought metrics that combine temperature and moisture information. Some areas lost more than two years’ average moisture delivery during these four years, and full recovery to long-term average moisture delivery could typically take up to several decades in the hardest-hit areas. These results highlight the value of the additional centuries of information provided by the paleo record, which indicates the shorter instrumental record may underestimate the statewide recovery time by over 30%. The extreme El Niño that occurred in 2015/16 ameliorated recovery in much of the northern half of the state, and since 1571 very-strong-to-extreme El Niños during the first year after a 2012–15-type event reduce statewide recovery times by approximately half. The southern part of California did not experience the high precipitation anticipated, and the multicentury analysis suggests the north-wet–south-dry pattern for such an El Niño was a low-likelihood anomaly. Recent wetness in California motivated evaluation of recovery times when the first two years are relatively wet, suggesting the state is benefiting from a one-in-five (or lower) likelihood situation: the likelihood of full recovery within two years is ~1% in the instrumental data and even lower in the reconstruction data.
Abstract
The recent dryness in California was unprecedented in the instrumental record. This article employs spatially explicit precipitation reconstructions for California in combination with instrumental data to provide perspective on this event since 1571. The period 2012–15 stands out as particularly extreme in the southern Central Valley and south coast regions. which likely experienced unprecedented precipitation deficits over this time, apart from considerations of increasing temperatures and drought metrics that combine temperature and moisture information. Some areas lost more than two years’ average moisture delivery during these four years, and full recovery to long-term average moisture delivery could typically take up to several decades in the hardest-hit areas. These results highlight the value of the additional centuries of information provided by the paleo record, which indicates the shorter instrumental record may underestimate the statewide recovery time by over 30%. The extreme El Niño that occurred in 2015/16 ameliorated recovery in much of the northern half of the state, and since 1571 very-strong-to-extreme El Niños during the first year after a 2012–15-type event reduce statewide recovery times by approximately half. The southern part of California did not experience the high precipitation anticipated, and the multicentury analysis suggests the north-wet–south-dry pattern for such an El Niño was a low-likelihood anomaly. Recent wetness in California motivated evaluation of recovery times when the first two years are relatively wet, suggesting the state is benefiting from a one-in-five (or lower) likelihood situation: the likelihood of full recovery within two years is ~1% in the instrumental data and even lower in the reconstruction data.
Abstract
This study used air temperatures from a suite of regional climate models participating in the North American Climate Change Assessment Program (NARCCAP) together with two atmospheric reanalysis datasets to investigate changes in freezing days (defined as days with daily average temperature below freezing) likely to occur between 30-yr baseline (1971–2000) and midcentury (2041–70) periods across most of North America. Changes in NARCCAP ensemble mean winter temperature show a strong gradient with latitude, with warming of over 4°C near Hudson Bay. The decline in freezing days ranges from less than 10 days across north-central Canada to nearly 90 days in the warmest areas of the continent that currently undergo seasonally freezing conditions. The area experiencing freezing days contracts by 0.9–1.0 × 106 km2 (5.7%–6.4% of the total area). Areas with mean annual temperature between 2° and 6°C and a relatively low rate of change in climatological daily temperatures (<0.2°C day−) near the time of spring thaw will encounter the greatest decreases in freezing days. Advances in the timing of spring thaw will exceed the delay in fall freeze across much of the United States, with the reverse pattern likely over most of Canada.
Abstract
This study used air temperatures from a suite of regional climate models participating in the North American Climate Change Assessment Program (NARCCAP) together with two atmospheric reanalysis datasets to investigate changes in freezing days (defined as days with daily average temperature below freezing) likely to occur between 30-yr baseline (1971–2000) and midcentury (2041–70) periods across most of North America. Changes in NARCCAP ensemble mean winter temperature show a strong gradient with latitude, with warming of over 4°C near Hudson Bay. The decline in freezing days ranges from less than 10 days across north-central Canada to nearly 90 days in the warmest areas of the continent that currently undergo seasonally freezing conditions. The area experiencing freezing days contracts by 0.9–1.0 × 106 km2 (5.7%–6.4% of the total area). Areas with mean annual temperature between 2° and 6°C and a relatively low rate of change in climatological daily temperatures (<0.2°C day−) near the time of spring thaw will encounter the greatest decreases in freezing days. Advances in the timing of spring thaw will exceed the delay in fall freeze across much of the United States, with the reverse pattern likely over most of Canada.
Abstract
Few if any high-resolution (annually resolved) paleoclimate records are available for the Hawaiian Islands prior to ~1850 CE, after which some instrumental records start to become available. This paper shows how atmospheric teleconnection patterns between North America and the northeastern North Pacific (NNP) allow for reconstruction of Hawaiian Islands rainfall using remote proxy information from North America. Based on a newly available precipitation dataset for the state of Hawaii and observed and reconstructed December–February (DJF) sea level pressures (SLPs) in the North Pacific Ocean, the authors make use of a strong relationship between winter SLP variability in the northeast Pacific and corresponding DJF Hawaii rainfall variations to reconstruct and evaluate that season’s rainfall over the period 1500–2012 CE. A general drying trend, though with substantial decadal and longer-term variability, is evident, particularly during the last ~160 years. Hawaiian Islands rainfall exhibits strong modulation by El Niño–Southern Oscillation (ENSO), as well as in relation to Pacific decadal oscillation (PDO)-like variability. For significant periods of time, the reconstructed large-scale changes in the North Pacific SLP field described here and by construction the long-term decline in Hawaiian winter rainfall are broadly consistent with long-term changes in tropical Pacific sea surface temperature (SST) based on ENSO reconstructions documented in several other studies, particularly over the last two centuries. Also noted are some rather large multidecadal fluctuations in rainfall (and hence in NNP SLP) in the eighteenth century of undetermined provenance.
Abstract
Few if any high-resolution (annually resolved) paleoclimate records are available for the Hawaiian Islands prior to ~1850 CE, after which some instrumental records start to become available. This paper shows how atmospheric teleconnection patterns between North America and the northeastern North Pacific (NNP) allow for reconstruction of Hawaiian Islands rainfall using remote proxy information from North America. Based on a newly available precipitation dataset for the state of Hawaii and observed and reconstructed December–February (DJF) sea level pressures (SLPs) in the North Pacific Ocean, the authors make use of a strong relationship between winter SLP variability in the northeast Pacific and corresponding DJF Hawaii rainfall variations to reconstruct and evaluate that season’s rainfall over the period 1500–2012 CE. A general drying trend, though with substantial decadal and longer-term variability, is evident, particularly during the last ~160 years. Hawaiian Islands rainfall exhibits strong modulation by El Niño–Southern Oscillation (ENSO), as well as in relation to Pacific decadal oscillation (PDO)-like variability. For significant periods of time, the reconstructed large-scale changes in the North Pacific SLP field described here and by construction the long-term decline in Hawaiian winter rainfall are broadly consistent with long-term changes in tropical Pacific sea surface temperature (SST) based on ENSO reconstructions documented in several other studies, particularly over the last two centuries. Also noted are some rather large multidecadal fluctuations in rainfall (and hence in NNP SLP) in the eighteenth century of undetermined provenance.
