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Abstract
The influence of heating over Africa on the South American precipitation climatology, and the influence of South America on Africa, is examined through the application of GCM simulations with idealized boundary conditions and perpetual solstice (January and July) conditions.
The presence of Africa is associated with a pronounced (up to 4 mm day−1) decrease in precipitation in Brazil's Nordeste region during austral summer. Low-level moisture divergence and dry-air advection associated with the downbranch of a Walker circulation induced by heating over southern Africa is amplified over the Nordeste due to the response of the land surface. The response is much smaller during austral winter due to differences in the heat source over Africa and a reduced sensitivity in the surface heat balance over tropical South America. Forcing from South America in January shifts the position of the South Indian convergence zone (SICZ) to the southwest over southern Africa in association with the formation of the South Atlantic convergence zone (SACZ). In July, a Rossby wave train generated over South America induces a response in the surface temperature of Africa that leads to stronger precipitation in central and western Africa.
This study suggests a zonal mode of variability for South American and African circulation and precipitation fields. The resulting perturbations depend as much on land surface–atmosphere interactions as on the direct forcing from the adjacent continent, and the mechanisms are highly nonlinear.
Abstract
The influence of heating over Africa on the South American precipitation climatology, and the influence of South America on Africa, is examined through the application of GCM simulations with idealized boundary conditions and perpetual solstice (January and July) conditions.
The presence of Africa is associated with a pronounced (up to 4 mm day−1) decrease in precipitation in Brazil's Nordeste region during austral summer. Low-level moisture divergence and dry-air advection associated with the downbranch of a Walker circulation induced by heating over southern Africa is amplified over the Nordeste due to the response of the land surface. The response is much smaller during austral winter due to differences in the heat source over Africa and a reduced sensitivity in the surface heat balance over tropical South America. Forcing from South America in January shifts the position of the South Indian convergence zone (SICZ) to the southwest over southern Africa in association with the formation of the South Atlantic convergence zone (SACZ). In July, a Rossby wave train generated over South America induces a response in the surface temperature of Africa that leads to stronger precipitation in central and western Africa.
This study suggests a zonal mode of variability for South American and African circulation and precipitation fields. The resulting perturbations depend as much on land surface–atmosphere interactions as on the direct forcing from the adjacent continent, and the mechanisms are highly nonlinear.
Abstract
Four Tropical Rainfall Measuring Mission (TRMM) datasets of latent heating were diagnosed for signals in the Madden–Julian oscillation (MJO). In all four datasets, vertical structures of latent heating are dominated by two components—one deep with its peak above the melting level and one shallow with its peak below. Profiles of the two components are nearly ubiquitous in longitude, allowing a separation of the vertical and zonal/temporal variations when the latitudinal dependence is not considered. All four datasets exhibit robust MJO spectral signals in the deep component as eastward propagating spectral peaks centered at a period of 50 days and zonal wavenumber 1, well distinguished from lower- and higher-frequency power and much stronger than the corresponding westward power. The shallow component shows similar but slightly less robust MJO spectral peaks. MJO signals were further extracted from a combination of bandpass (30–90 day) filtered deep and shallow components. Largest amplitudes of both deep and shallow components of the MJO are confined to the Indian and western Pacific Oceans. There is a local minimum in the deep components over the Maritime Continent. The shallow components of the MJO differ substantially among the four TRMM datasets in their detailed zonal distributions in the Eastern Hemisphere. In composites of the heating evolution through the life cycle of the MJO, the shallow components lead the deep ones in some datasets and at certain longitudes. In many respects, the four TRMM datasets agree well in their deep components, but not in their shallow components and in the phase relations between the deep and shallow components. These results indicate that caution must be exercised in applications of these latent heating data.
Abstract
Four Tropical Rainfall Measuring Mission (TRMM) datasets of latent heating were diagnosed for signals in the Madden–Julian oscillation (MJO). In all four datasets, vertical structures of latent heating are dominated by two components—one deep with its peak above the melting level and one shallow with its peak below. Profiles of the two components are nearly ubiquitous in longitude, allowing a separation of the vertical and zonal/temporal variations when the latitudinal dependence is not considered. All four datasets exhibit robust MJO spectral signals in the deep component as eastward propagating spectral peaks centered at a period of 50 days and zonal wavenumber 1, well distinguished from lower- and higher-frequency power and much stronger than the corresponding westward power. The shallow component shows similar but slightly less robust MJO spectral peaks. MJO signals were further extracted from a combination of bandpass (30–90 day) filtered deep and shallow components. Largest amplitudes of both deep and shallow components of the MJO are confined to the Indian and western Pacific Oceans. There is a local minimum in the deep components over the Maritime Continent. The shallow components of the MJO differ substantially among the four TRMM datasets in their detailed zonal distributions in the Eastern Hemisphere. In composites of the heating evolution through the life cycle of the MJO, the shallow components lead the deep ones in some datasets and at certain longitudes. In many respects, the four TRMM datasets agree well in their deep components, but not in their shallow components and in the phase relations between the deep and shallow components. These results indicate that caution must be exercised in applications of these latent heating data.
Abstract
For the Community Atmosphere Model version 6 (CAM6), an adjustment is needed to conserve dry air mass. This adjustment exposes an inconsistency in how CAM6’s energy budget incorporates water—in CAM6 water in the vapor phase has energy, but condensed phases of water do not. When water vapor condenses, only its latent energy is retained in the model, while its remaining internal, potential, and kinetic energy are lost. A global fixer is used in the default CAM6 model to maintain global energy conservation, but locally the energy tendency associated with water changing phase violates the divergence theorem. This error in energy tendency is intrinsically tied to the water vapor tendency, and reaches its highest values in regions of heavy rainfall, where the error can be as high as 40 W m−2 annually averaged. Several possible changes are outlined within this manuscript that would allow CAM6 to satisfy the divergence theorem locally. These fall into one of two categories: 1) modifying the surface flux to balance the local atmospheric energy tendency and 2) modifying the local atmospheric tendency to balance the surface plus top-of-atmosphere energy fluxes. To gauge which aspects of the simulated climate are most sensitive to this error, the simplest possible change—where condensed water still does not carry energy and a local energy fixer is used in place of the global one—is implemented within CAM6. Comparing this experiment with the default configuration of CAM6 reveals precipitation, particularly its variability, to be highly sensitive to the energy budget formulation.
Significance Statement
This study examines and explains spurious regional sources and sinks of energy in a widely used climate model. These energy errors result from not tracking energy associated with water after it transitions from the vapor phase to either liquid or ice. Instead, the model used a global fixer to offset the energy tendency related to the energy sources and sinks associated with condensed water species. We replace this global fixer with a local one to examine the model sensitivity to the regional energy error and find a large sensitivity in the simulated hydrologic cycle. This work suggests that the underlying thermodynamic assumptions in the model should be revisited to build confidence in the model-simulated regional-scale water and energy cycles.
Abstract
For the Community Atmosphere Model version 6 (CAM6), an adjustment is needed to conserve dry air mass. This adjustment exposes an inconsistency in how CAM6’s energy budget incorporates water—in CAM6 water in the vapor phase has energy, but condensed phases of water do not. When water vapor condenses, only its latent energy is retained in the model, while its remaining internal, potential, and kinetic energy are lost. A global fixer is used in the default CAM6 model to maintain global energy conservation, but locally the energy tendency associated with water changing phase violates the divergence theorem. This error in energy tendency is intrinsically tied to the water vapor tendency, and reaches its highest values in regions of heavy rainfall, where the error can be as high as 40 W m−2 annually averaged. Several possible changes are outlined within this manuscript that would allow CAM6 to satisfy the divergence theorem locally. These fall into one of two categories: 1) modifying the surface flux to balance the local atmospheric energy tendency and 2) modifying the local atmospheric tendency to balance the surface plus top-of-atmosphere energy fluxes. To gauge which aspects of the simulated climate are most sensitive to this error, the simplest possible change—where condensed water still does not carry energy and a local energy fixer is used in place of the global one—is implemented within CAM6. Comparing this experiment with the default configuration of CAM6 reveals precipitation, particularly its variability, to be highly sensitive to the energy budget formulation.
Significance Statement
This study examines and explains spurious regional sources and sinks of energy in a widely used climate model. These energy errors result from not tracking energy associated with water after it transitions from the vapor phase to either liquid or ice. Instead, the model used a global fixer to offset the energy tendency related to the energy sources and sinks associated with condensed water species. We replace this global fixer with a local one to examine the model sensitivity to the regional energy error and find a large sensitivity in the simulated hydrologic cycle. This work suggests that the underlying thermodynamic assumptions in the model should be revisited to build confidence in the model-simulated regional-scale water and energy cycles.
Abstract
Yanai and coauthors utilized the meteorological data collected from a sounding network to present a pioneering work in 1973 on thermodynamic budgets, which are referred to as the apparent heat source (Q 1) and apparent moisture sink (Q 2). Latent heating (LH) is one of the most dominant terms in Q 1. Yanai’s paper motivated the development of satellite-based LH algorithms and provided a theoretical background for imposing large-scale advective forcing into cloud-resolving models (CRMs). These CRM-simulated LH and Q 1 data have been used to generate the look-up tables in Tropical Rainfall Measuring Mission (TRMM) LH algorithms. A set of algorithms developed for retrieving LH profiles from TRMM-based rainfall profiles is described and evaluated, including details concerning their intrinsic space–time resolutions. Included in the paper are results from a variety of validation analyses that define the uncertainty of the LH profile estimates. Also, examples of how TRMM-retrieved LH profiles have been used to understand the life cycle of the MJO and improve the predictions of global weather and climate models as well as comparisons with large-scale analyses are provided. Areas for further improvement of the TRMM products are discussed.
Abstract
Yanai and coauthors utilized the meteorological data collected from a sounding network to present a pioneering work in 1973 on thermodynamic budgets, which are referred to as the apparent heat source (Q 1) and apparent moisture sink (Q 2). Latent heating (LH) is one of the most dominant terms in Q 1. Yanai’s paper motivated the development of satellite-based LH algorithms and provided a theoretical background for imposing large-scale advective forcing into cloud-resolving models (CRMs). These CRM-simulated LH and Q 1 data have been used to generate the look-up tables in Tropical Rainfall Measuring Mission (TRMM) LH algorithms. A set of algorithms developed for retrieving LH profiles from TRMM-based rainfall profiles is described and evaluated, including details concerning their intrinsic space–time resolutions. Included in the paper are results from a variety of validation analyses that define the uncertainty of the LH profile estimates. Also, examples of how TRMM-retrieved LH profiles have been used to understand the life cycle of the MJO and improve the predictions of global weather and climate models as well as comparisons with large-scale analyses are provided. Areas for further improvement of the TRMM products are discussed.
