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Abstract
The hydrological cycle in the Mediterranean region, as well as its change over the coming decades, is investigated using the Interim European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-Interim) and phase 5 of the Coupled Model Intercomparison Project (CMIP5) historical simulations and projections of the coming decades. The Mediterranean land regions have positive precipitation minus evaporation, P − E, in winter and negative P − E in summer. According to ERA-Interim, positive P − E over land in winter is sustained by transient eddy moisture convergence and opposed by mean flow moisture divergence. Dry mean flow advection is important for opposing the transient eddy moisture flux convergence in the winter half year and the mass divergent mean flow is a prime cause of negative P − E in the summer half year. These features are well reproduced in the CMIP5 ensemble. The models predict reduced P − E over the Mediterranean region in the future year-round. For both land and sea, a common cause of drying is increased mean flow moisture divergence. Changes in transient eddy moisture fluxes largely act diffusively and cause drying over the sea and moistening over many land areas to the north in winter and drying over western land areas and moistening over the eastern sea in summer. Increased mean flow moisture divergence is caused by both the increase in atmospheric humidity in a region of mean flow divergence and strengthening of the mass divergence. Increased mass divergence is related to increased high pressure over the central Mediterranean in winter and over the Atlantic and northern Europe in summer, which favors subsidence and low-level divergence over the Mediterranean region.
Abstract
The hydrological cycle in the Mediterranean region, as well as its change over the coming decades, is investigated using the Interim European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-Interim) and phase 5 of the Coupled Model Intercomparison Project (CMIP5) historical simulations and projections of the coming decades. The Mediterranean land regions have positive precipitation minus evaporation, P − E, in winter and negative P − E in summer. According to ERA-Interim, positive P − E over land in winter is sustained by transient eddy moisture convergence and opposed by mean flow moisture divergence. Dry mean flow advection is important for opposing the transient eddy moisture flux convergence in the winter half year and the mass divergent mean flow is a prime cause of negative P − E in the summer half year. These features are well reproduced in the CMIP5 ensemble. The models predict reduced P − E over the Mediterranean region in the future year-round. For both land and sea, a common cause of drying is increased mean flow moisture divergence. Changes in transient eddy moisture fluxes largely act diffusively and cause drying over the sea and moistening over many land areas to the north in winter and drying over western land areas and moistening over the eastern sea in summer. Increased mean flow moisture divergence is caused by both the increase in atmospheric humidity in a region of mean flow divergence and strengthening of the mass divergence. Increased mass divergence is related to increased high pressure over the central Mediterranean in winter and over the Atlantic and northern Europe in summer, which favors subsidence and low-level divergence over the Mediterranean region.
Abstract
The causes of the California drought during November–April winters of 2011/12–2013/14 are analyzed using observations and ensemble simulations with seven atmosphere models forced by observed SSTs. Historically, dry California winters are most commonly associated with a ridge off the west coast but no obvious SST forcing. Wet winters are most commonly associated with a trough off the west coast and an El Niño event. These attributes of dry and wet winters are captured by many of the seven models. According to the models, SST forcing can explain up to a third of California winter precipitation variance. SST forcing was key to sustaining a high pressure ridge over the west coast and suppressing precipitation during the three winters. In 2011/12 this was a response to a La Niña event, whereas in 2012/13 and 2013/14 it appears related to a warm west–cool east tropical Pacific SST pattern. All models contain a mode of variability linking such tropical Pacific SST anomalies to a wave train with a ridge off the North American west coast. This mode explains less variance than ENSO and Pacific decadal variability, and its importance in 2012/13 and 2013/14 was unusual. The models from phase 5 of CMIP (CMIP5) project rising greenhouse gases to cause changes in California all-winter precipitation that are very small compared to recent drought anomalies. However, a long-term warming trend likely contributed to surface moisture deficits during the drought. As such, the precipitation deficit during the drought was dominated by natural variability, a conclusion framed by discussion of differences between observed and modeled tropical SST trends.
Abstract
The causes of the California drought during November–April winters of 2011/12–2013/14 are analyzed using observations and ensemble simulations with seven atmosphere models forced by observed SSTs. Historically, dry California winters are most commonly associated with a ridge off the west coast but no obvious SST forcing. Wet winters are most commonly associated with a trough off the west coast and an El Niño event. These attributes of dry and wet winters are captured by many of the seven models. According to the models, SST forcing can explain up to a third of California winter precipitation variance. SST forcing was key to sustaining a high pressure ridge over the west coast and suppressing precipitation during the three winters. In 2011/12 this was a response to a La Niña event, whereas in 2012/13 and 2013/14 it appears related to a warm west–cool east tropical Pacific SST pattern. All models contain a mode of variability linking such tropical Pacific SST anomalies to a wave train with a ridge off the North American west coast. This mode explains less variance than ENSO and Pacific decadal variability, and its importance in 2012/13 and 2013/14 was unusual. The models from phase 5 of CMIP (CMIP5) project rising greenhouse gases to cause changes in California all-winter precipitation that are very small compared to recent drought anomalies. However, a long-term warming trend likely contributed to surface moisture deficits during the drought. As such, the precipitation deficit during the drought was dominated by natural variability, a conclusion framed by discussion of differences between observed and modeled tropical SST trends.
Abstract
The authors investigate a sea surface temperature anomaly (SSTA)-only vector autoregressive (VAR) model for prediction of El Niño–Southern Oscillation (ENSO). VAR generalizes the linear inverse method (LIM) framework to incorporate an extended state vector including many months of recent prior SSTA in addition to the present state. An SSTA-only VAR model implicitly captures subsurface forcing observable in the LIM residual as red noise. Optimal skill is achieved using a state vector of order 14–17 months in an exhaustive 120-yr cross-validated hindcast assessment. It is found that VAR outperforms LIM, increasing forecast skill by 3 months, in a 30-yr retrospective forecast experiment.
Abstract
The authors investigate a sea surface temperature anomaly (SSTA)-only vector autoregressive (VAR) model for prediction of El Niño–Southern Oscillation (ENSO). VAR generalizes the linear inverse method (LIM) framework to incorporate an extended state vector including many months of recent prior SSTA in addition to the present state. An SSTA-only VAR model implicitly captures subsurface forcing observable in the LIM residual as red noise. Optimal skill is achieved using a state vector of order 14–17 months in an exhaustive 120-yr cross-validated hindcast assessment. It is found that VAR outperforms LIM, increasing forecast skill by 3 months, in a 30-yr retrospective forecast experiment.
Abstract
Unlike the commonly used relative humidity, vapor pressure deficit (VPD) is an absolute measure of the difference between the water vapor content of the air and its saturation value and an accurate metric of the ability of the atmosphere to extract moisture from the land surface. VPD has been shown to be closely related to variability in burned forest areas in the western United States. Here, the climatology, variability, and trends in VPD across the United States are presented. VPD reaches its climatological maximum in summer in the interior southwest United States because of both high temperatures and low vapor pressure under the influence of the northerly, subsiding eastern flank of the Pacific subtropical anticyclone. Maxima of variance of VPD are identified in the Southwest and southern plains in spring and summer and are to a large extent driven by temperature variance, but vapor pressure variance is also important in the Southwest. La Niña–induced circulation anomalies cause subsiding, northerly flow that drives down actual vapor pressure and increases saturation vapor pressure from fall through spring. High spring and summer VPDs can also be caused by reduced precipitation in preceding months, as measured by Bowen ratio anomalies. Case studies of 2002 (the Rodeo–Chediski and Hayman fires, which occurred in Arizona and Colorado, respectively) and 2007 (the Murphy Complex fire, which occurred in Idaho and Nevada) show very high VPDs caused by antecedent surface drying and subsidence warming and drying of the atmosphere. VPD has increased in the southwest United States since 1961, driven by warming and a drop in actual vapor pressure, but has decreased in the northern plains and Midwest, driven by an increase in actual vapor pressure.
Abstract
Unlike the commonly used relative humidity, vapor pressure deficit (VPD) is an absolute measure of the difference between the water vapor content of the air and its saturation value and an accurate metric of the ability of the atmosphere to extract moisture from the land surface. VPD has been shown to be closely related to variability in burned forest areas in the western United States. Here, the climatology, variability, and trends in VPD across the United States are presented. VPD reaches its climatological maximum in summer in the interior southwest United States because of both high temperatures and low vapor pressure under the influence of the northerly, subsiding eastern flank of the Pacific subtropical anticyclone. Maxima of variance of VPD are identified in the Southwest and southern plains in spring and summer and are to a large extent driven by temperature variance, but vapor pressure variance is also important in the Southwest. La Niña–induced circulation anomalies cause subsiding, northerly flow that drives down actual vapor pressure and increases saturation vapor pressure from fall through spring. High spring and summer VPDs can also be caused by reduced precipitation in preceding months, as measured by Bowen ratio anomalies. Case studies of 2002 (the Rodeo–Chediski and Hayman fires, which occurred in Arizona and Colorado, respectively) and 2007 (the Murphy Complex fire, which occurred in Idaho and Nevada) show very high VPDs caused by antecedent surface drying and subsidence warming and drying of the atmosphere. VPD has increased in the southwest United States since 1961, driven by warming and a drop in actual vapor pressure, but has decreased in the northern plains and Midwest, driven by an increase in actual vapor pressure.
Abstract
Recent record-breaking wildfire seasons in California prompt an investigation into the climate patterns that typically precede anomalous summer burned forest area. Using burned-area data from the U.S. Forest Service’s Monitoring Trends in Burn Severity (MTBS) product and climate data from the fifth major global reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ERA5) over 1984–2018, relationships between the interannual variability of antecedent climate anomalies and July California burned area are spatially and temporally characterized. Lag correlations show that antecedent high vapor pressure deficit (VPD), high temperatures, frequent extreme high temperature days, low precipitation, high subsidence, high geopotential height, low soil moisture, and low snowpack and snowmelt anomalies all correlate significantly with July California burned area as far back as the January before the fire season. Seasonal regression maps indicate that a global midlatitude atmospheric wave train in late winter is associated with anomalous July California burned area. July 2018, a year with especially high burned area, was to some extent consistent with the general patterns revealed by the regressions: low winter precipitation and high spring VPD preceded the extreme burned area. However, geopotential height anomaly patterns were distinct from those in the regressions. Extreme July heat likely contributed to the extent of the fires ignited that month, even though extreme July temperatures do not historically significantly correlate with July burned area. While the 2018 antecedent climate conditions were typical of a high-burned-area year, they were not extreme, demonstrating the likely limits of statistical prediction of extreme fire seasons and the need for individual case studies of extreme years.
Significance Statement
The purpose of this study is to identify the local and global climate patterns in the preceding seasons that influence how the burned summer forest area in California varies year-to-year. We find that a dry atmosphere, high temperatures, dry soils, less snowpack, low precipitation, subsiding air, and high pressure centered west of California all correlate significantly with large summer burned area as far back as the preceding January. These climate anomalies occur as part of a hemispheric scale pattern with weak connections to the tropical Pacific Ocean. We also describe the climate anomalies preceding the extreme and record-breaking burned-area year of 2018, and how these compared with the more general patterns found. These results give important insight into how well and how early it might be possible to predict the severity of an upcoming summer wildfire season in California.
Abstract
Recent record-breaking wildfire seasons in California prompt an investigation into the climate patterns that typically precede anomalous summer burned forest area. Using burned-area data from the U.S. Forest Service’s Monitoring Trends in Burn Severity (MTBS) product and climate data from the fifth major global reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ERA5) over 1984–2018, relationships between the interannual variability of antecedent climate anomalies and July California burned area are spatially and temporally characterized. Lag correlations show that antecedent high vapor pressure deficit (VPD), high temperatures, frequent extreme high temperature days, low precipitation, high subsidence, high geopotential height, low soil moisture, and low snowpack and snowmelt anomalies all correlate significantly with July California burned area as far back as the January before the fire season. Seasonal regression maps indicate that a global midlatitude atmospheric wave train in late winter is associated with anomalous July California burned area. July 2018, a year with especially high burned area, was to some extent consistent with the general patterns revealed by the regressions: low winter precipitation and high spring VPD preceded the extreme burned area. However, geopotential height anomaly patterns were distinct from those in the regressions. Extreme July heat likely contributed to the extent of the fires ignited that month, even though extreme July temperatures do not historically significantly correlate with July burned area. While the 2018 antecedent climate conditions were typical of a high-burned-area year, they were not extreme, demonstrating the likely limits of statistical prediction of extreme fire seasons and the need for individual case studies of extreme years.
Significance Statement
The purpose of this study is to identify the local and global climate patterns in the preceding seasons that influence how the burned summer forest area in California varies year-to-year. We find that a dry atmosphere, high temperatures, dry soils, less snowpack, low precipitation, subsiding air, and high pressure centered west of California all correlate significantly with large summer burned area as far back as the preceding January. These climate anomalies occur as part of a hemispheric scale pattern with weak connections to the tropical Pacific Ocean. We also describe the climate anomalies preceding the extreme and record-breaking burned-area year of 2018, and how these compared with the more general patterns found. These results give important insight into how well and how early it might be possible to predict the severity of an upcoming summer wildfire season in California.
Abstract
John Wesley Powell, in the nineteenth century, introduced the notion that the 100th meridian divides the North American continent into arid western regions and humid eastern regions. This concept remains firmly fixed in the national imagination. It is reexamined in terms of climate, hydrology, vegetation, land use, settlement, and the agricultural economy. It is shown there is a stark east–west gradient in aridity roughly at the 100th meridian that is well expressed in hydroclimate, soil moisture, and “potential vegetation.” The gradient arises from atmospheric circulations and moisture transports. In winter, the arid regions west of the 100th meridian are shielded from Pacific storm-related precipitation and are too far west to benefit from Atlantic storms. In summer, the southerly flow on the western flank of the North Atlantic subtropical high has a westerly component over the western plains, bringing air from the interior southwest, but it also brings air from the Gulf of Mexico over the eastern plains, generating a west–east moisture transport and precipitation gradient. The aridity gradient is realized in soil moisture and a west-to-east transition from shortgrass to tallgrass prairie. The gradient is sharp in terms of greater fractional coverage of developed land east of the 100th meridian than to the west. Farms are fewer but larger west of the meridian, reflective of lower land productivity. Wheat and corn cultivation preferentially occur west and east of the 100th meridian, respectively. The 100th meridian is a very real arid–humid divide in the physical climate and landscape, and this has exerted a powerful influence on human settlement and agricultural development.
Abstract
John Wesley Powell, in the nineteenth century, introduced the notion that the 100th meridian divides the North American continent into arid western regions and humid eastern regions. This concept remains firmly fixed in the national imagination. It is reexamined in terms of climate, hydrology, vegetation, land use, settlement, and the agricultural economy. It is shown there is a stark east–west gradient in aridity roughly at the 100th meridian that is well expressed in hydroclimate, soil moisture, and “potential vegetation.” The gradient arises from atmospheric circulations and moisture transports. In winter, the arid regions west of the 100th meridian are shielded from Pacific storm-related precipitation and are too far west to benefit from Atlantic storms. In summer, the southerly flow on the western flank of the North Atlantic subtropical high has a westerly component over the western plains, bringing air from the interior southwest, but it also brings air from the Gulf of Mexico over the eastern plains, generating a west–east moisture transport and precipitation gradient. The aridity gradient is realized in soil moisture and a west-to-east transition from shortgrass to tallgrass prairie. The gradient is sharp in terms of greater fractional coverage of developed land east of the 100th meridian than to the west. Farms are fewer but larger west of the meridian, reflective of lower land productivity. Wheat and corn cultivation preferentially occur west and east of the 100th meridian, respectively. The 100th meridian is a very real arid–humid divide in the physical climate and landscape, and this has exerted a powerful influence on human settlement and agricultural development.
Abstract
The 100th meridian bisects the Great Plains of the United States and effectively divides the continent into more arid western and less arid eastern halves and is well expressed in terms of vegetation, land hydrology, crops, and the farm economy. Here, it is considered how this arid–humid divide will change in intensity and location during the current century under rising greenhouse gases. It is first shown that state-of-the-art climate models from phase 5 of the Coupled Model Intercomparison Project generally underestimate the degree of aridity of the United States and simulate an arid–humid divide that is too diffuse. These biases are traced to excessive precipitation and evapotranspiration and inadequate blocking of eastward moisture flux by the Pacific coastal ranges and Rockies. Bias-corrected future projections are developed that modify observationally based measures of aridity by the model-projected fractional changes in aridity. Aridity increases across the United States, and the aridity gradient weakens. The main contributor to the changes is rising potential evapotranspiration, while changes in precipitation working alone increase aridity across the southern and decrease across the northern United States. The “effective 100th meridian” moves to the east as the century progresses. In the current farm economy, farm size and percent of county under rangelands increase and percent of cropland under corn decreases as aridity increases. Statistical relations between these quantities and the bias-corrected aridity projections suggest that, all else being equal (which it will not be), adjustment to changing environmental conditions would cause farm size and rangeland area to increase across the plains and percent of cropland under corn to decrease in the northern plains as the century advances.
Abstract
The 100th meridian bisects the Great Plains of the United States and effectively divides the continent into more arid western and less arid eastern halves and is well expressed in terms of vegetation, land hydrology, crops, and the farm economy. Here, it is considered how this arid–humid divide will change in intensity and location during the current century under rising greenhouse gases. It is first shown that state-of-the-art climate models from phase 5 of the Coupled Model Intercomparison Project generally underestimate the degree of aridity of the United States and simulate an arid–humid divide that is too diffuse. These biases are traced to excessive precipitation and evapotranspiration and inadequate blocking of eastward moisture flux by the Pacific coastal ranges and Rockies. Bias-corrected future projections are developed that modify observationally based measures of aridity by the model-projected fractional changes in aridity. Aridity increases across the United States, and the aridity gradient weakens. The main contributor to the changes is rising potential evapotranspiration, while changes in precipitation working alone increase aridity across the southern and decrease across the northern United States. The “effective 100th meridian” moves to the east as the century progresses. In the current farm economy, farm size and percent of county under rangelands increase and percent of cropland under corn decreases as aridity increases. Statistical relations between these quantities and the bias-corrected aridity projections suggest that, all else being equal (which it will not be), adjustment to changing environmental conditions would cause farm size and rangeland area to increase across the plains and percent of cropland under corn to decrease in the northern plains as the century advances.
Abstract
The Prairie Pothole Region (PPR) of the northern Great Plains is a vital ecosystem responsible each year for producing 50%–80% of new recruits to the North American duck population. Climate variability and change can impact the hydrology and ecology of the region with implications for waterfowl populations. The historical relationship between PPR wetlands, duck populations, and seasonal hydroclimate are explored. Model experiments from phase 5 of the Coupled Model Intercomparison Project are used to determine whether a recent wetting trend is due to natural variability or changing climate and how PPR hydroclimate will change into the future. Year-to-year variations in May duck populations, pond numbers, and the Palmer drought severity index are well correlated over past decades. Pond and duck numbers tend to increase in spring following La Niña events, but the correlation is not strong. Model simulations suggest that the strengthening of the precipitation gradient across the PPR over the past century is predominantly due to natural variability and therefore could reverse. Model projections of future climate indicate precipitation will increase across the PPR in all seasons except summer, but this gain for surface moisture is largely offset by increased evapotranspiration because of higher temperatures and increased atmospheric evaporative demand. In summer, the combined effects of warming and precipitation changes indicate seasonal surface drying in the future. The presented hydroclimate analyses produce potential inputs to ecological and hydrological simulations of PPR wetlands to inform risk analysis of how this North American waterfowl habitat will evolve in the future, providing guidance to land managers facing conservation decisions.
Abstract
The Prairie Pothole Region (PPR) of the northern Great Plains is a vital ecosystem responsible each year for producing 50%–80% of new recruits to the North American duck population. Climate variability and change can impact the hydrology and ecology of the region with implications for waterfowl populations. The historical relationship between PPR wetlands, duck populations, and seasonal hydroclimate are explored. Model experiments from phase 5 of the Coupled Model Intercomparison Project are used to determine whether a recent wetting trend is due to natural variability or changing climate and how PPR hydroclimate will change into the future. Year-to-year variations in May duck populations, pond numbers, and the Palmer drought severity index are well correlated over past decades. Pond and duck numbers tend to increase in spring following La Niña events, but the correlation is not strong. Model simulations suggest that the strengthening of the precipitation gradient across the PPR over the past century is predominantly due to natural variability and therefore could reverse. Model projections of future climate indicate precipitation will increase across the PPR in all seasons except summer, but this gain for surface moisture is largely offset by increased evapotranspiration because of higher temperatures and increased atmospheric evaporative demand. In summer, the combined effects of warming and precipitation changes indicate seasonal surface drying in the future. The presented hydroclimate analyses produce potential inputs to ecological and hydrological simulations of PPR wetlands to inform risk analysis of how this North American waterfowl habitat will evolve in the future, providing guidance to land managers facing conservation decisions.
Abstract
A suite of empirical model experiments under the empirical model reduction framework are conducted to advance the understanding of ENSO diversity, nonlinearity, seasonality, and the memory effect in the simulation and prediction of tropical Pacific sea surface temperature (SST) anomalies. The model training and evaluation are carried out using 4000-yr preindustrial control simulation data from the coupled model GFDL CM2.1. The results show that multivariate models with tropical Pacific subsurface information and multilevel models with SST history information both improve the prediction skill dramatically. These two types of models represent the ENSO memory effect based on either the recharge oscillator or the time-delayed oscillator viewpoint. Multilevel SST models are a bit more efficient, requiring fewer model coefficients. Nonlinearity is found necessary to reproduce the ENSO diversity feature for extreme events. The nonlinear models reconstruct the skewed probability density function of SST anomalies and improve the prediction of the skewed amplitude, though the role of nonlinearity may be slightly overestimated given the strong nonlinear ENSO in GFDL CM2.1. The models with periodic terms reproduce the SST seasonal phase locking but do not improve the prediction appreciably. The models with multiple ingredients capture several ENSO characteristics simultaneously and exhibit overall better prediction skill for more diverse target patterns. In particular, they alleviate the spring/autumn prediction barrier and reduce the tendency for predicted values to lag the target month value.
Abstract
A suite of empirical model experiments under the empirical model reduction framework are conducted to advance the understanding of ENSO diversity, nonlinearity, seasonality, and the memory effect in the simulation and prediction of tropical Pacific sea surface temperature (SST) anomalies. The model training and evaluation are carried out using 4000-yr preindustrial control simulation data from the coupled model GFDL CM2.1. The results show that multivariate models with tropical Pacific subsurface information and multilevel models with SST history information both improve the prediction skill dramatically. These two types of models represent the ENSO memory effect based on either the recharge oscillator or the time-delayed oscillator viewpoint. Multilevel SST models are a bit more efficient, requiring fewer model coefficients. Nonlinearity is found necessary to reproduce the ENSO diversity feature for extreme events. The nonlinear models reconstruct the skewed probability density function of SST anomalies and improve the prediction of the skewed amplitude, though the role of nonlinearity may be slightly overestimated given the strong nonlinear ENSO in GFDL CM2.1. The models with periodic terms reproduce the SST seasonal phase locking but do not improve the prediction appreciably. The models with multiple ingredients capture several ENSO characteristics simultaneously and exhibit overall better prediction skill for more diverse target patterns. In particular, they alleviate the spring/autumn prediction barrier and reduce the tendency for predicted values to lag the target month value.
Abstract
The mechanisms of model-projected atmospheric moisture budget change across North America are examined in simulations conducted with 22 models from phase 5 of the Coupled Model Intercomparison Project. Modern-day model budgets are validated against the European Centre for Medium-Range Weather Forecasts Interim Re-Analysis. In the winter half year transient eddies converge moisture across the continent while the mean flow wets the west from central California northward and dries the southwest. In the summer half year there is widespread mean flow moisture divergence across the west and convergence over the Great Plains that is offset by transient eddy divergence. In the winter half year the models project drying for the southwest and wetting to the north. Changes in the mean flow moisture convergence are largely responsible across the west but intensified transient eddy moisture convergence wets the northeast. In the summer half year widespread declines in precipitation minus evaporation (P − E) are supported by mean flow moisture divergence across the west and transient eddy divergence in the Great Plains. The changes in mean flow convergence are related to increases in specific humidity but also depend on changes in the mean flow including increased low-level divergence in the U.S. Southwest and a zonally varying wave that wets the North American west and east coasts in winter and dries the U.S. Southwest. Increased transient eddy fluxes occur even as low-level eddy activity weakens and arise from strengthened humidity gradients. A full explanation of North American hydroclimate changes will require explanation of mean and transient circulation changes and the coupling between the moisture and circulation fields.
Abstract
The mechanisms of model-projected atmospheric moisture budget change across North America are examined in simulations conducted with 22 models from phase 5 of the Coupled Model Intercomparison Project. Modern-day model budgets are validated against the European Centre for Medium-Range Weather Forecasts Interim Re-Analysis. In the winter half year transient eddies converge moisture across the continent while the mean flow wets the west from central California northward and dries the southwest. In the summer half year there is widespread mean flow moisture divergence across the west and convergence over the Great Plains that is offset by transient eddy divergence. In the winter half year the models project drying for the southwest and wetting to the north. Changes in the mean flow moisture convergence are largely responsible across the west but intensified transient eddy moisture convergence wets the northeast. In the summer half year widespread declines in precipitation minus evaporation (P − E) are supported by mean flow moisture divergence across the west and transient eddy divergence in the Great Plains. The changes in mean flow convergence are related to increases in specific humidity but also depend on changes in the mean flow including increased low-level divergence in the U.S. Southwest and a zonally varying wave that wets the North American west and east coasts in winter and dries the U.S. Southwest. Increased transient eddy fluxes occur even as low-level eddy activity weakens and arise from strengthened humidity gradients. A full explanation of North American hydroclimate changes will require explanation of mean and transient circulation changes and the coupling between the moisture and circulation fields.
