Abstract
There is no simple explanation for the spatial structure of near-surface relative humidity over land. We present a diagnostic theory for zonally- and temporally-averaged near-surface relative humidity (RH) over land based on energy budgets of an atmospheric column in radiative-convective equilibrium. The theory analytically relates RH to the surface evaporative fraction (EF), has no calibrated parameters, and is quantitatively accurate when compared with RH from a reanalysis, and with cloud-permitting simulations over an idealized land surface. The theory is used to answer two basic questions. First, why is RH never especially low (for example, 1%)? The theory shows that established lower bounds on EF over land and ocean are equivalent to lower bounds on RH that preclude particularly low values, at least for conditions typical of the modern Earth. Second, why is the latitudinal profile of RH over land shaped like the letter ‘W’, when both specific humidity and saturation specific humidity essentially decline monotonically from the equator to the poles? The theory predicts that the latitudinal profile of RH should look more like that of water stored in the soil (which also exhibits a W-shaped profile) than in the air (which does not).
Abstract
There is no simple explanation for the spatial structure of near-surface relative humidity over land. We present a diagnostic theory for zonally- and temporally-averaged near-surface relative humidity (RH) over land based on energy budgets of an atmospheric column in radiative-convective equilibrium. The theory analytically relates RH to the surface evaporative fraction (EF), has no calibrated parameters, and is quantitatively accurate when compared with RH from a reanalysis, and with cloud-permitting simulations over an idealized land surface. The theory is used to answer two basic questions. First, why is RH never especially low (for example, 1%)? The theory shows that established lower bounds on EF over land and ocean are equivalent to lower bounds on RH that preclude particularly low values, at least for conditions typical of the modern Earth. Second, why is the latitudinal profile of RH over land shaped like the letter ‘W’, when both specific humidity and saturation specific humidity essentially decline monotonically from the equator to the poles? The theory predicts that the latitudinal profile of RH should look more like that of water stored in the soil (which also exhibits a W-shaped profile) than in the air (which does not).
Abstract
Surface waves grow through a mechanism in which atmospheric pressure is offset in phase from the wavy surface. A pattern of low atmospheric pressure over upward wave orbital motions (leeward side) and high pressure over downward wave orbital motions (windward side) travels with the water wave, leading to a pumping of kinetic energy from the atmospheric boundary layer into the waves. This pressure pattern persists above the air/water interface, modifying the turbulent kinetic energy in the atmospheric wave-affected boundary layer. Here, we present field measurements of wave-coherent atmospheric pressure and velocity to elucidate the transfer of energy from the atmospheric turbulence budget into waves through wave-coherent atmospheric pressure work. Measurements show that the phase between wave-coherent pressure and velocity is shifted slightly above 90° when wind speed exceeds the wave phase speed, allowing for a downwards energy flux via pressure work. Although previous studies have reported wave-coherent pressure, to the authors’ knowledge, these are the first reported field measurements of wave-coherent pressure work. Measured pressure work cospectra are consistent with an existing model for atmospheric pressure work. The implications for these measurements and their importance to the turbulent kinetic energy budget are discussed.
Abstract
Surface waves grow through a mechanism in which atmospheric pressure is offset in phase from the wavy surface. A pattern of low atmospheric pressure over upward wave orbital motions (leeward side) and high pressure over downward wave orbital motions (windward side) travels with the water wave, leading to a pumping of kinetic energy from the atmospheric boundary layer into the waves. This pressure pattern persists above the air/water interface, modifying the turbulent kinetic energy in the atmospheric wave-affected boundary layer. Here, we present field measurements of wave-coherent atmospheric pressure and velocity to elucidate the transfer of energy from the atmospheric turbulence budget into waves through wave-coherent atmospheric pressure work. Measurements show that the phase between wave-coherent pressure and velocity is shifted slightly above 90° when wind speed exceeds the wave phase speed, allowing for a downwards energy flux via pressure work. Although previous studies have reported wave-coherent pressure, to the authors’ knowledge, these are the first reported field measurements of wave-coherent pressure work. Measured pressure work cospectra are consistent with an existing model for atmospheric pressure work. The implications for these measurements and their importance to the turbulent kinetic energy budget are discussed.
Abstract
Elevated spring and summer rainfall in the U.S. Midwest is often associated with a strong Great Plains low-level jet (GPLLJ), which transports moist air northward to the region from the Gulf of Mexico. While the intensity of hourly precipitation extremes depends on local moisture availability and vertical velocity, sustained moisture convergence on longer time scales depends on horizontal moisture advection from remote sources. Therefore, the magnitude of moisture convergence in the Midwest depends in part on the humidity in these moisture source regions. Past work has identified the time-mean spatial distribution of moisture sources for the Midwest and studied how this pattern changes in years with anomalous rainfall. Here, using reanalysis products and an Eulerian moisture tracking model, we seek to increase physical understanding of this moisture source variability by linking it to the GPLLJ, which has been studied extensively. We find that on interannual time scales, an anomalously strong GPLLJ is associated with a shift in the distribution of moisture sources from land to ocean, with most of the anomalous moisture transported to—and converged in—the Midwest originating from the Atlantic Ocean. This effect is more pronounced on synoptic time scales, when almost all anomalous moisture transported to the region originates over the ocean. We also show that the observed positive trend in oceanic moisture contribution to the Midwest from 1979 to 2020 is consistent with a strengthening of the GPLLJ over the same period. We conclude by outlining how projected changes in a region’s upstream moisture sources may be useful for understanding changes in local precipitation variability.
Significance Statement
In this work, we study how the origin of moisture that forms precipitation in the U.S. Midwest covaries with large-scale atmospheric circulation. Our results show that an intensification of the mean winds tends to increase the proportion of total rainfall that originates from the ocean. This analysis may help to constrain future projections of rainfall extremes in the central United States, as projected changes in humidity over the ocean are typically more robust and better understood than those over land.
Abstract
Elevated spring and summer rainfall in the U.S. Midwest is often associated with a strong Great Plains low-level jet (GPLLJ), which transports moist air northward to the region from the Gulf of Mexico. While the intensity of hourly precipitation extremes depends on local moisture availability and vertical velocity, sustained moisture convergence on longer time scales depends on horizontal moisture advection from remote sources. Therefore, the magnitude of moisture convergence in the Midwest depends in part on the humidity in these moisture source regions. Past work has identified the time-mean spatial distribution of moisture sources for the Midwest and studied how this pattern changes in years with anomalous rainfall. Here, using reanalysis products and an Eulerian moisture tracking model, we seek to increase physical understanding of this moisture source variability by linking it to the GPLLJ, which has been studied extensively. We find that on interannual time scales, an anomalously strong GPLLJ is associated with a shift in the distribution of moisture sources from land to ocean, with most of the anomalous moisture transported to—and converged in—the Midwest originating from the Atlantic Ocean. This effect is more pronounced on synoptic time scales, when almost all anomalous moisture transported to the region originates over the ocean. We also show that the observed positive trend in oceanic moisture contribution to the Midwest from 1979 to 2020 is consistent with a strengthening of the GPLLJ over the same period. We conclude by outlining how projected changes in a region’s upstream moisture sources may be useful for understanding changes in local precipitation variability.
Significance Statement
In this work, we study how the origin of moisture that forms precipitation in the U.S. Midwest covaries with large-scale atmospheric circulation. Our results show that an intensification of the mean winds tends to increase the proportion of total rainfall that originates from the ocean. This analysis may help to constrain future projections of rainfall extremes in the central United States, as projected changes in humidity over the ocean are typically more robust and better understood than those over land.
Abstract
The contributions of local and remote forcings to the interannual sea level anomalies (SLAs) along the U.S. East Coast (USEC) during the satellite altimetry era from 1993 to 2019 are quantified with analytical models assisted by statistical methods. The local forcings from alongshore wind stress, sea level pressure via inverted barometer (IB) effect, and river discharges together explain 47%, 60.4%, and 66.8% of coastal sea level variance in the South Atlantic Bight (SAB), Mid-Atlantic Bight (MAB), and Gulf of Maine (GOM), respectively, with river discharges having the minimum contribution. Over a longer period of 1960–2019, the contribution of local forcings reduces significantly, with the IB effect having the minimum contribution. The remote forcings associated with open-ocean signals from the east and from the northern boundary at the Scotian coast together with the Gulf Stream (GS) variability explain 45.7%, 28.5%, and 37.7% of coastal sea level variance in the SAB, MAB, and GOM, respectively, playing a role comparable to that of local forcings in the SAB. The open-ocean sea level signals from 35° to 38°N strongly influence coastal SLAs in the SAB. The coastal SLAs in the SAB are also affected by the upstream GS strength (28°–36°N) and basin-scale wind stress curl anomaly, which is linked to the meridional shift in the downstream GS (74°–68°W). Remote forcings from the subpolar North Atlantic and wind stress curl from the Grand Banks to the Scotian coast influence coastal SLAs in the GOM and MAB via the northern boundary of the USEC at the Scotian coast.
Abstract
The contributions of local and remote forcings to the interannual sea level anomalies (SLAs) along the U.S. East Coast (USEC) during the satellite altimetry era from 1993 to 2019 are quantified with analytical models assisted by statistical methods. The local forcings from alongshore wind stress, sea level pressure via inverted barometer (IB) effect, and river discharges together explain 47%, 60.4%, and 66.8% of coastal sea level variance in the South Atlantic Bight (SAB), Mid-Atlantic Bight (MAB), and Gulf of Maine (GOM), respectively, with river discharges having the minimum contribution. Over a longer period of 1960–2019, the contribution of local forcings reduces significantly, with the IB effect having the minimum contribution. The remote forcings associated with open-ocean signals from the east and from the northern boundary at the Scotian coast together with the Gulf Stream (GS) variability explain 45.7%, 28.5%, and 37.7% of coastal sea level variance in the SAB, MAB, and GOM, respectively, playing a role comparable to that of local forcings in the SAB. The open-ocean sea level signals from 35° to 38°N strongly influence coastal SLAs in the SAB. The coastal SLAs in the SAB are also affected by the upstream GS strength (28°–36°N) and basin-scale wind stress curl anomaly, which is linked to the meridional shift in the downstream GS (74°–68°W). Remote forcings from the subpolar North Atlantic and wind stress curl from the Grand Banks to the Scotian coast influence coastal SLAs in the GOM and MAB via the northern boundary of the USEC at the Scotian coast.
Abstract
Intraseasonal and diurnal variations are two basic periodic oscillations in global/regional climate and weather. To investigate their joint impacts over East Asia, this paper categorizes the boreal summer intraseasonal oscillations (ISOs) in 1998–2019 into two groups with different diurnal cycles. It is shown that the active ISOs with large diurnal cycles feature a northwestward-moving anomalous anticyclone with strong southerlies at the western flank. These ISOs have in-phase patterns of geopotential height anomaly between low and midlatitudes over East Asia, associated with the simultaneous expansions of the western Pacific subtropical high (WPSH) and South Asian high (SAH). They couple with the anomalous ABL heating by daytime solar radiation over East Asia, which acts to enhance monsoon southerlies at midnight. The nocturnally strengthened southerlies facilitate dynamic lifting, moisture transport, and convective instability for producing midnight to morning rainfall at their northern terminus, thereby yielding a remarkable northward propagation of the monsoon rain belt. In contrast, the other ISOs with small diurnal cycles are related to a westward-moving anomalous anticyclone, while the WPSH and SAH have relatively small expansions and the westerly trough is active at middle latitudes. They lead to the dipole patterns of geopotential height anomaly and weak ABL heating over East Asia. The daily-mean southerlies and moisture conditions as well as their nocturnal enhancements are relatively weak, and thus, the northward shift of the monsoon rain belt is less pronounced. These results highlight that the large-scale conditions of ISOs can be distinguished by their different couplings with regional-scale diurnal forcings, which help the understanding and prediction of multiscale rainfall activities.
Abstract
Intraseasonal and diurnal variations are two basic periodic oscillations in global/regional climate and weather. To investigate their joint impacts over East Asia, this paper categorizes the boreal summer intraseasonal oscillations (ISOs) in 1998–2019 into two groups with different diurnal cycles. It is shown that the active ISOs with large diurnal cycles feature a northwestward-moving anomalous anticyclone with strong southerlies at the western flank. These ISOs have in-phase patterns of geopotential height anomaly between low and midlatitudes over East Asia, associated with the simultaneous expansions of the western Pacific subtropical high (WPSH) and South Asian high (SAH). They couple with the anomalous ABL heating by daytime solar radiation over East Asia, which acts to enhance monsoon southerlies at midnight. The nocturnally strengthened southerlies facilitate dynamic lifting, moisture transport, and convective instability for producing midnight to morning rainfall at their northern terminus, thereby yielding a remarkable northward propagation of the monsoon rain belt. In contrast, the other ISOs with small diurnal cycles are related to a westward-moving anomalous anticyclone, while the WPSH and SAH have relatively small expansions and the westerly trough is active at middle latitudes. They lead to the dipole patterns of geopotential height anomaly and weak ABL heating over East Asia. The daily-mean southerlies and moisture conditions as well as their nocturnal enhancements are relatively weak, and thus, the northward shift of the monsoon rain belt is less pronounced. These results highlight that the large-scale conditions of ISOs can be distinguished by their different couplings with regional-scale diurnal forcings, which help the understanding and prediction of multiscale rainfall activities.
Abstract
For over 75 years, the National Oceanic and Atmospheric Administration’s Air Resources Laboratory (NOAA ARL) has been at the forefront of federal meteorological and climate research. As the Special Projects Section (SPS) of the U.S. Weather Bureau (USWB), the laboratory pioneered the development of atmospheric trajectory modeling, initially used in studies related to nuclear weapons following World War II. Model development was guided by observations following weapons tests, assisted by later experiments using a wide variety of atmospheric tracers. Today’s familiar Gaussian plume dispersion model, previously in nascent form, was developed and promoted with ARL research, as was the much later and widely used HYSPLIT model. Much of ARL’s early research was focused on the challenges presented by the complex terrain surrounding nuclear installations, often addressed with high-spatial-resolution meteorological measurements, atmospheric tracers, and site-specific models. ARL has since extended boundary layer research to increasingly complex landscapes, such as forests, agricultural lands, and urban areas, and has expanded its research scope to air quality, weather, and climate applications based on the knowledge and experience developed throughout its long history. Examples of these research endeavors include the establishment of the U.S. Climate Reference Network, fundamental contributions to the development of the National Air Quality Forecast Capability, and foundational participation in the National Atmospheric Deposition Program. ARL looks forward to continuing to refine scientific understanding from field experiments, including coupling ground-based experimentation with modeling, and sustained observations, in order to facilitate the transfer of knowledge into practical applications of societal relevance.
Abstract
For over 75 years, the National Oceanic and Atmospheric Administration’s Air Resources Laboratory (NOAA ARL) has been at the forefront of federal meteorological and climate research. As the Special Projects Section (SPS) of the U.S. Weather Bureau (USWB), the laboratory pioneered the development of atmospheric trajectory modeling, initially used in studies related to nuclear weapons following World War II. Model development was guided by observations following weapons tests, assisted by later experiments using a wide variety of atmospheric tracers. Today’s familiar Gaussian plume dispersion model, previously in nascent form, was developed and promoted with ARL research, as was the much later and widely used HYSPLIT model. Much of ARL’s early research was focused on the challenges presented by the complex terrain surrounding nuclear installations, often addressed with high-spatial-resolution meteorological measurements, atmospheric tracers, and site-specific models. ARL has since extended boundary layer research to increasingly complex landscapes, such as forests, agricultural lands, and urban areas, and has expanded its research scope to air quality, weather, and climate applications based on the knowledge and experience developed throughout its long history. Examples of these research endeavors include the establishment of the U.S. Climate Reference Network, fundamental contributions to the development of the National Air Quality Forecast Capability, and foundational participation in the National Atmospheric Deposition Program. ARL looks forward to continuing to refine scientific understanding from field experiments, including coupling ground-based experimentation with modeling, and sustained observations, in order to facilitate the transfer of knowledge into practical applications of societal relevance.
Abstract
Statistical postprocessing is used to translate ensembles of raw numerical weather forecasts into reliable probabilistic forecast distributions. In this study, we examine the use of permutation-invariant neural networks for this task. In contrast to previous approaches, which often operate on ensemble summary statistics and dismiss details of the ensemble distribution, we propose networks that treat forecast ensembles as a set of unordered member forecasts and learn link functions that are by design invariant to permutations of the member ordering. We evaluate the quality of the obtained forecast distributions in terms of calibration and sharpness and compare the models against classical and neural network-based benchmark methods. In case studies addressing the postprocessing of surface temperature and wind gust forecasts, we demonstrate state-of-the-art prediction quality. To deepen the understanding of the learned inference process, we further propose a permutation-based importance analysis for ensemble-valued predictors, which highlights specific aspects of the ensemble forecast that are considered important by the trained postprocessing models. Our results suggest that most of the relevant information is contained in a few ensemble-internal degrees of freedom, which may impact the design of future ensemble forecasting and postprocessing systems.
Abstract
Statistical postprocessing is used to translate ensembles of raw numerical weather forecasts into reliable probabilistic forecast distributions. In this study, we examine the use of permutation-invariant neural networks for this task. In contrast to previous approaches, which often operate on ensemble summary statistics and dismiss details of the ensemble distribution, we propose networks that treat forecast ensembles as a set of unordered member forecasts and learn link functions that are by design invariant to permutations of the member ordering. We evaluate the quality of the obtained forecast distributions in terms of calibration and sharpness and compare the models against classical and neural network-based benchmark methods. In case studies addressing the postprocessing of surface temperature and wind gust forecasts, we demonstrate state-of-the-art prediction quality. To deepen the understanding of the learned inference process, we further propose a permutation-based importance analysis for ensemble-valued predictors, which highlights specific aspects of the ensemble forecast that are considered important by the trained postprocessing models. Our results suggest that most of the relevant information is contained in a few ensemble-internal degrees of freedom, which may impact the design of future ensemble forecasting and postprocessing systems.
Abstract
Over recent decades, the Bering Sea has experienced oceanic and atmospheric climate extremes, including record warm ocean temperature anomalies and marine heatwaves (MHWs), and increasingly variable air–sea heat fluxes. In this work, we assess the relative roles of surface forcing and ocean dynamical processes on mixed layer temperature (MLT) tendency by computing a closed mixed layer heat budget using the NASA/JPL Estimating the Circulation and Climate of the Ocean (ECCO) Ocean State and Sea Ice Estimate. We show that surface forcing drives the majority of the MLT tendency in the spring and fall and remains dominant to a lesser degree in winter and summer. Surface forcing anomalies are the dominant driver of monthly mixed layer temperature tendency anomalies (MLTa), driving an average of 72% of the MLTa over the ECCO record length (1992–2017). The surface turbulent heat flux (latent plus sensible) accounts for most of the surface heat flux anomalies in January–April and September–December, and the net radiative flux (net longwave plus net shortwave) dominates the surface heat flux anomalies in May–August. Our results suggest that atmospheric variability plays a significant role in Bering Sea ocean temperature anomalies through most of the year. Furthermore, they indicate a recent increase in ocean warming surface forcing anomalies, beginning in 2010.
Significance Statement
In recent years, the Bering Sea has experienced extremes in ocean temperature, which have had adverse impacts on ocean ecology and marine fisheries and have contributed to increasingly variable sea ice extent. Our results identify anomalous heating by air–sea heat flux anomalies as the process responsible for most of the observed ocean temperature anomalies over the period 1992–2017. We additionally show that there has been an increase in atmosphere-driven ocean warming since 2010. Our work highlights the importance of investigating how ocean–atmosphere interactions might change under future climate change and how this will impact the Bering Sea.
Abstract
Over recent decades, the Bering Sea has experienced oceanic and atmospheric climate extremes, including record warm ocean temperature anomalies and marine heatwaves (MHWs), and increasingly variable air–sea heat fluxes. In this work, we assess the relative roles of surface forcing and ocean dynamical processes on mixed layer temperature (MLT) tendency by computing a closed mixed layer heat budget using the NASA/JPL Estimating the Circulation and Climate of the Ocean (ECCO) Ocean State and Sea Ice Estimate. We show that surface forcing drives the majority of the MLT tendency in the spring and fall and remains dominant to a lesser degree in winter and summer. Surface forcing anomalies are the dominant driver of monthly mixed layer temperature tendency anomalies (MLTa), driving an average of 72% of the MLTa over the ECCO record length (1992–2017). The surface turbulent heat flux (latent plus sensible) accounts for most of the surface heat flux anomalies in January–April and September–December, and the net radiative flux (net longwave plus net shortwave) dominates the surface heat flux anomalies in May–August. Our results suggest that atmospheric variability plays a significant role in Bering Sea ocean temperature anomalies through most of the year. Furthermore, they indicate a recent increase in ocean warming surface forcing anomalies, beginning in 2010.
Significance Statement
In recent years, the Bering Sea has experienced extremes in ocean temperature, which have had adverse impacts on ocean ecology and marine fisheries and have contributed to increasingly variable sea ice extent. Our results identify anomalous heating by air–sea heat flux anomalies as the process responsible for most of the observed ocean temperature anomalies over the period 1992–2017. We additionally show that there has been an increase in atmosphere-driven ocean warming since 2010. Our work highlights the importance of investigating how ocean–atmosphere interactions might change under future climate change and how this will impact the Bering Sea.
Abstract
The Intertropical Convergence Zone (ITCZ), with its twice-annual passage over central Africa, is considered as the main driver of the rainfall seasonality. In this ITCZ paradigm, high rainfall occurs over regions of large low-level convergence. But recently, this paradigm was challenged over central Africa. Here, we show that a shallow meridional overturning circulation– driven by surface conditions– plays a thermodynamical control on the rainfall seasonality over central Africa. Indeed, due to the local evaporative cooling effect, the foot of the ascending branch of Hadley cells occurs where the temperature is the warmest, indicating a thermal low. This distorts the southern Hadley cell by developing its bottom-heavy structure. As result, both shallow and deep Hadley cells coexist over central Africa year–round. The deep mode is associated with the poleward transport of atmospheric energy at upper levels. The shallow mode is characterized by a shallow meridional circulation, with its moisture transport vanishing and converging in the mid-troposphere rather than at lower troposphere. This mid-tropospheric moisture convergence is also the dominant component that shapes the vertically integrated moisture flux convergence, with little contribution of African easterly jets. This convergence zone thus controls the precipitating convection. Its meridional migration highlights the interhemispheric rainfall contrast over central Africa and outlines the unimodal seasonality. On the other hand, forced by the Congo basin cell, the precipitable water regulates the deep convection from the vegetated surface of Congo basin, acting as a continental sea. This nonlinear mechanism separates the rainfall into three distinct regimes: the moisture-convergence-controlled regime, with convective rainfall exclusively occurs in rainy season; the local evaporation-controlled regime with drizzle and the precipitable-water-controlled regime, with exponential rainfall increase occur both in dry season.
Abstract
The Intertropical Convergence Zone (ITCZ), with its twice-annual passage over central Africa, is considered as the main driver of the rainfall seasonality. In this ITCZ paradigm, high rainfall occurs over regions of large low-level convergence. But recently, this paradigm was challenged over central Africa. Here, we show that a shallow meridional overturning circulation– driven by surface conditions– plays a thermodynamical control on the rainfall seasonality over central Africa. Indeed, due to the local evaporative cooling effect, the foot of the ascending branch of Hadley cells occurs where the temperature is the warmest, indicating a thermal low. This distorts the southern Hadley cell by developing its bottom-heavy structure. As result, both shallow and deep Hadley cells coexist over central Africa year–round. The deep mode is associated with the poleward transport of atmospheric energy at upper levels. The shallow mode is characterized by a shallow meridional circulation, with its moisture transport vanishing and converging in the mid-troposphere rather than at lower troposphere. This mid-tropospheric moisture convergence is also the dominant component that shapes the vertically integrated moisture flux convergence, with little contribution of African easterly jets. This convergence zone thus controls the precipitating convection. Its meridional migration highlights the interhemispheric rainfall contrast over central Africa and outlines the unimodal seasonality. On the other hand, forced by the Congo basin cell, the precipitable water regulates the deep convection from the vegetated surface of Congo basin, acting as a continental sea. This nonlinear mechanism separates the rainfall into three distinct regimes: the moisture-convergence-controlled regime, with convective rainfall exclusively occurs in rainy season; the local evaporation-controlled regime with drizzle and the precipitable-water-controlled regime, with exponential rainfall increase occur both in dry season.
