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Abstract
Three versions of the single-column European Centre for Medium-Range Weather Forecasts–Hamburg (ECHAM4) climate model are compared that differ either in the technique of the numerical coupling between land surface and atmosphere or the physical parameterization of the land surface processes. The standard ECHAM4 model utilizes a semi-implicit coupling technique between land surface and atmosphere in a way in which energy at the land surface–atmosphere interface is not conserved. This is a major deficiency. Two new model versions were developed: ECHAM4/IMPL and ECHAM4/SECHIBA. They incorporate an implicit coupling technique that conserves energy. ECHAM4 and ECHAM4/IMPL are identical with respect to all physical parameterizations they apply; the only difference is the coupling. In ECHAM4/SECHIBA, the ECHAM land surface scheme was replaced by SECHIBA (Schématisation des Echanges Hydriques à l’Interface entre la Biosphère et l’Atmosphère). The intercomparison of one-dimensional versions of these three models shows that the energy residual term in ECHAM4 is not negligibly small, but it is rather of the order of the physical fluxes. Biases of more than 1300 W m−2 are found due to the coupling technique. These are avoided in ECHAM4/IMPL, which results in a more pronounced diurnal cycle of surface temperature and generally higher temperature maxima during a warming phase. In an offline intercomparison of the three model versions, using an observational atmospheric forcing dataset, an important impact of the coupling technique on the simulated surface energy cycle is found as well. The turbulent heat fluxes in ECHAM4 tend to be underestimated; their rise in the morning and decrease in the afternoon are delayed. Because of the improved coupling, the turbulent heat fluxes of the implicit models are in better agreement with the observations, especially regarding the phases of their diurnal cycles. Differences between ECHAM4/IMPL and ECHAM4/SECHIBA are mainly found for the simulated surface temperature, which gets closer to the observed radiative temperature for the latter model. Furthermore, the diurnal amplitude of the ground heat flux is increased in ECHAM4/SECHIBA in agreement with the observations.
Abstract
Three versions of the single-column European Centre for Medium-Range Weather Forecasts–Hamburg (ECHAM4) climate model are compared that differ either in the technique of the numerical coupling between land surface and atmosphere or the physical parameterization of the land surface processes. The standard ECHAM4 model utilizes a semi-implicit coupling technique between land surface and atmosphere in a way in which energy at the land surface–atmosphere interface is not conserved. This is a major deficiency. Two new model versions were developed: ECHAM4/IMPL and ECHAM4/SECHIBA. They incorporate an implicit coupling technique that conserves energy. ECHAM4 and ECHAM4/IMPL are identical with respect to all physical parameterizations they apply; the only difference is the coupling. In ECHAM4/SECHIBA, the ECHAM land surface scheme was replaced by SECHIBA (Schématisation des Echanges Hydriques à l’Interface entre la Biosphère et l’Atmosphère). The intercomparison of one-dimensional versions of these three models shows that the energy residual term in ECHAM4 is not negligibly small, but it is rather of the order of the physical fluxes. Biases of more than 1300 W m−2 are found due to the coupling technique. These are avoided in ECHAM4/IMPL, which results in a more pronounced diurnal cycle of surface temperature and generally higher temperature maxima during a warming phase. In an offline intercomparison of the three model versions, using an observational atmospheric forcing dataset, an important impact of the coupling technique on the simulated surface energy cycle is found as well. The turbulent heat fluxes in ECHAM4 tend to be underestimated; their rise in the morning and decrease in the afternoon are delayed. Because of the improved coupling, the turbulent heat fluxes of the implicit models are in better agreement with the observations, especially regarding the phases of their diurnal cycles. Differences between ECHAM4/IMPL and ECHAM4/SECHIBA are mainly found for the simulated surface temperature, which gets closer to the observed radiative temperature for the latter model. Furthermore, the diurnal amplitude of the ground heat flux is increased in ECHAM4/SECHIBA in agreement with the observations.
Abstract
The components of the land surface energy balance respond to periodic incoming radiation forcing with different amplitude and phase characteristics. Evaporative fraction (EF), the ratio of latent heat to available energy at the land surface, supposedly isolates surface control (soil moisture and vegetation) from radiation and turbulent factors. EF is thus supposed to be a diagnostic of the surface energy balance that is constant or self-preserved during daytime. If this holds, EF can be an effective way to estimate surface characteristics from temperature and energy flux measurements. Evidence for EF diurnal self-preservation is based on limited-duration field measurements. The daytime EF self-preservation using both long-term measurements and a model of the soil–vegetation–atmosphere continuum is reexamined here. It is demonstrated that EF is rarely constant and that its temporal power spectrum is wide; thus emphasizing the role of all diurnal frequencies associated with reduced predictability in its daylight response. Oppositely, surface turbulent heat fluxes are characterized by a strong response to the principal daily frequencies (daily and semi-daily) of the solar radiative forcing. It is shown that the phase lag and bias between the turbulent flux components of the surface energy balance are key to the shape of the daytime EF. Therefore, an understanding of the physical factors that affect the phase lag and bias in the response of the components of the surface energy balance to periodic radiative forcing is needed. A linearized model of the soil–vegetation–atmosphere continuum is used that can be solved in terms of harmonics to explore the physical factors that determine the phase characteristics. The dependency of these phase and offsets on environmental parameters—friction velocity, water availability, solar radiation intensity, relative humidity, and boundary layer entrainment—is then analyzed using the model that solves the dynamics of subsurface and atmospheric boundary layer temperatures and heat fluxes in a continuum. Additionally, the asymptotical diurnal lower limit of EF is derived as a function of these surface parameters and shown to be an important indicator of the self-preservation value when the conditions (also identified) for such behavior are present.
Abstract
The components of the land surface energy balance respond to periodic incoming radiation forcing with different amplitude and phase characteristics. Evaporative fraction (EF), the ratio of latent heat to available energy at the land surface, supposedly isolates surface control (soil moisture and vegetation) from radiation and turbulent factors. EF is thus supposed to be a diagnostic of the surface energy balance that is constant or self-preserved during daytime. If this holds, EF can be an effective way to estimate surface characteristics from temperature and energy flux measurements. Evidence for EF diurnal self-preservation is based on limited-duration field measurements. The daytime EF self-preservation using both long-term measurements and a model of the soil–vegetation–atmosphere continuum is reexamined here. It is demonstrated that EF is rarely constant and that its temporal power spectrum is wide; thus emphasizing the role of all diurnal frequencies associated with reduced predictability in its daylight response. Oppositely, surface turbulent heat fluxes are characterized by a strong response to the principal daily frequencies (daily and semi-daily) of the solar radiative forcing. It is shown that the phase lag and bias between the turbulent flux components of the surface energy balance are key to the shape of the daytime EF. Therefore, an understanding of the physical factors that affect the phase lag and bias in the response of the components of the surface energy balance to periodic radiative forcing is needed. A linearized model of the soil–vegetation–atmosphere continuum is used that can be solved in terms of harmonics to explore the physical factors that determine the phase characteristics. The dependency of these phase and offsets on environmental parameters—friction velocity, water availability, solar radiation intensity, relative humidity, and boundary layer entrainment—is then analyzed using the model that solves the dynamics of subsurface and atmospheric boundary layer temperatures and heat fluxes in a continuum. Additionally, the asymptotical diurnal lower limit of EF is derived as a function of these surface parameters and shown to be an important indicator of the self-preservation value when the conditions (also identified) for such behavior are present.
Abstract
A land surface model (LSM) has been included in the ECMWF Hamburg version 4 (ECHAM4) atmospheric general circulation model (AGCM). The LSM is an early version of the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) and it replaces the simple land surface scheme previously included in ECHAM4. The purpose of this paper is to document how a more exhaustive consideration of the land surface–vegetation processes affects the simulated boreal summer surface climate.
To investigate the impacts on the simulated climate, different sets of Atmospheric Model Intercomparison Project (AMIP)-type simulations have been performed with ECHAM4 alone and with the AGCM coupled with ORCHIDEE. Furthermore, to assess the effects of the increase in horizontal resolution the coupling of ECHAM4 with the LSM has been implemented at different horizontal resolutions.
The analysis reveals that the LSM has large effects on the simulated boreal summer surface climate of the atmospheric model. Considerable impacts are found in the surface energy balance due to changes in the surface latent heat fluxes over tropical and midlatitude areas covered with vegetation. Rainfall and atmospheric circulation are substantially affected by these changes. In particular, increased precipitation is found over evergreen and summergreen vegetated areas.
Because of the socioeconomical relevance, particular attention has been devoted to the Indian summer monsoon (ISM) region. The results of this study indicate that precipitation over the Indian subcontinent is better simulated with the coupled ECHAM4–ORCHIDEE model compared to the atmospheric model alone.
Abstract
A land surface model (LSM) has been included in the ECMWF Hamburg version 4 (ECHAM4) atmospheric general circulation model (AGCM). The LSM is an early version of the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) and it replaces the simple land surface scheme previously included in ECHAM4. The purpose of this paper is to document how a more exhaustive consideration of the land surface–vegetation processes affects the simulated boreal summer surface climate.
To investigate the impacts on the simulated climate, different sets of Atmospheric Model Intercomparison Project (AMIP)-type simulations have been performed with ECHAM4 alone and with the AGCM coupled with ORCHIDEE. Furthermore, to assess the effects of the increase in horizontal resolution the coupling of ECHAM4 with the LSM has been implemented at different horizontal resolutions.
The analysis reveals that the LSM has large effects on the simulated boreal summer surface climate of the atmospheric model. Considerable impacts are found in the surface energy balance due to changes in the surface latent heat fluxes over tropical and midlatitude areas covered with vegetation. Rainfall and atmospheric circulation are substantially affected by these changes. In particular, increased precipitation is found over evergreen and summergreen vegetated areas.
Because of the socioeconomical relevance, particular attention has been devoted to the Indian summer monsoon (ISM) region. The results of this study indicate that precipitation over the Indian subcontinent is better simulated with the coupled ECHAM4–ORCHIDEE model compared to the atmospheric model alone.
African Monsoon Multidisciplinary Analysis (AMMA) is an international project to improve our knowledge and understanding of the West African monsoon (WAM) and its variability with an emphasis on daily-to-interannual time scales. AMMA is motivated by an interest in fundamental scientific issues and by the societal need for improved prediction of the WAM and its impacts on West African nations. Recognizing the societal need to develop strategies that reduce the socioeconomic impacts of the variability of the WAM, AMMA will facilitate the multidisciplinary research required to provide improved predictions of the WAM and its impacts. This will be achieved and coordinated through the following five international working groups: i) West African monsoon and global climate, ii) water cycle, iii) surface-atmosphere feedbacks, iv) prediction of climate impacts, and v) high-impact weather prediction and predictability.
AMMA promotes the international coordination of ongoing activities, basic research, and a multiyear field campaign over West Africa and the tropical Atlantic. AMMA is developing close partnerships between those involved in basic research of the WAM, operational forecasting, and decision making, and is establishing blended training and education activities for Africans.
African Monsoon Multidisciplinary Analysis (AMMA) is an international project to improve our knowledge and understanding of the West African monsoon (WAM) and its variability with an emphasis on daily-to-interannual time scales. AMMA is motivated by an interest in fundamental scientific issues and by the societal need for improved prediction of the WAM and its impacts on West African nations. Recognizing the societal need to develop strategies that reduce the socioeconomic impacts of the variability of the WAM, AMMA will facilitate the multidisciplinary research required to provide improved predictions of the WAM and its impacts. This will be achieved and coordinated through the following five international working groups: i) West African monsoon and global climate, ii) water cycle, iii) surface-atmosphere feedbacks, iv) prediction of climate impacts, and v) high-impact weather prediction and predictability.
AMMA promotes the international coordination of ongoing activities, basic research, and a multiyear field campaign over West Africa and the tropical Atlantic. AMMA is developing close partnerships between those involved in basic research of the WAM, operational forecasting, and decision making, and is establishing blended training and education activities for Africans.
No abstract available.
No abstract available.
Abstract
As an essential source of freshwater river flow comprises ~80% of the water consumed in China. Per capita water resources in China are only a quarter of the global average, and its economy is demanding in water resources; this creates an urgent need to quantify the factors that contribute to changes in river flow. Here, we used an offline process-based land surface model (ORCHIDEE) at high spatial resolution (0.1° × 0.1°) to simulate the contributions of climate change, rising atmospheric CO2 concentration, and land-use change to the change in natural river flow for 10 Chinese basins from 1979 to 2015. We found that climate change, especially an increase in precipitation, was responsible for more than 90% of the changes in natural river flow, while the direct effect of rising CO2 concentration and land-use change contributes at most 6.3%. Nevertheless, rising CO2 concentration and land-use change cannot be neglected in most basins as these two factors significantly change transpiration. From 2003 to 2015, the increase in water consumption offset more than 30% of the increase in natural river flow in northern China, especially in the Yellow River basin (~140%), but it had little effect on observed river flow in southern China. Although the uncertainties of rainfall data and the statistical water consumption data could propagate the uncertainties in simulated river flow, this study could be helpful for water planning and management in China under the context of global warming.
Abstract
As an essential source of freshwater river flow comprises ~80% of the water consumed in China. Per capita water resources in China are only a quarter of the global average, and its economy is demanding in water resources; this creates an urgent need to quantify the factors that contribute to changes in river flow. Here, we used an offline process-based land surface model (ORCHIDEE) at high spatial resolution (0.1° × 0.1°) to simulate the contributions of climate change, rising atmospheric CO2 concentration, and land-use change to the change in natural river flow for 10 Chinese basins from 1979 to 2015. We found that climate change, especially an increase in precipitation, was responsible for more than 90% of the changes in natural river flow, while the direct effect of rising CO2 concentration and land-use change contributes at most 6.3%. Nevertheless, rising CO2 concentration and land-use change cannot be neglected in most basins as these two factors significantly change transpiration. From 2003 to 2015, the increase in water consumption offset more than 30% of the increase in natural river flow in northern China, especially in the Yellow River basin (~140%), but it had little effect on observed river flow in southern China. Although the uncertainties of rainfall data and the statistical water consumption data could propagate the uncertainties in simulated river flow, this study could be helpful for water planning and management in China under the context of global warming.
This article describes the upper-air program, which has been conducted as part of the African Monsoon Multidisciplinary Analysis (AMMA). Since 2004, AMMA scientists have been working in partnership with operational agencies in Africa to reactivate silent radiosonde stations, to renovate unreliable stations, and to install new stations in regions of particular climatic importance. A comprehensive upper-air network is now active over West Africa and has contributed to high-quality atmospheric monitoring over three monsoon seasons. During the period June to September 2006 high-frequency soundings were performed, in conjunction with intensive aircraft and ground-based activities: some 7,000 soundings were made, representing the greatest density of upper air measurements ever collected over the region. An important goal of AMMA is to evaluate the impact of these data on weather and climate prediction for West Africa, and for the hurricane genesis regions of the tropical Atlantic. Many operational difficulties were encountered in the program, involving technical problems in the harsh environment of sub-Saharan Africa and issues of funding, coordination, and communication among the many nations and agencies involved. In facing up to these difficulties, AMMA achieved a steady improvement in the number of soundings received by numerical weather prediction centers, with a success rate of over 88% by August 2007. From the experience of AMMA, we are therefore able to make firm recommendations for the maintenance and operation of a useful upper-air network in WMO Region I in the future.
This article describes the upper-air program, which has been conducted as part of the African Monsoon Multidisciplinary Analysis (AMMA). Since 2004, AMMA scientists have been working in partnership with operational agencies in Africa to reactivate silent radiosonde stations, to renovate unreliable stations, and to install new stations in regions of particular climatic importance. A comprehensive upper-air network is now active over West Africa and has contributed to high-quality atmospheric monitoring over three monsoon seasons. During the period June to September 2006 high-frequency soundings were performed, in conjunction with intensive aircraft and ground-based activities: some 7,000 soundings were made, representing the greatest density of upper air measurements ever collected over the region. An important goal of AMMA is to evaluate the impact of these data on weather and climate prediction for West Africa, and for the hurricane genesis regions of the tropical Atlantic. Many operational difficulties were encountered in the program, involving technical problems in the harsh environment of sub-Saharan Africa and issues of funding, coordination, and communication among the many nations and agencies involved. In facing up to these difficulties, AMMA achieved a steady improvement in the number of soundings received by numerical weather prediction centers, with a success rate of over 88% by August 2007. From the experience of AMMA, we are therefore able to make firm recommendations for the maintenance and operation of a useful upper-air network in WMO Region I in the future.
The rainfall over West Africa has been characterized by extreme variability in the last half-century, with prolonged droughts resulting in humanitarian crises. There is, therefore, an urgent need to better understand and predict the West African monsoon (WAM), because social stability in this region depends to a large degree on water resources. The economies are primarily agrarian, and there are issues related to food security and health. In particular, there is a need to better understand land-atmosphere and hydrological processes over West Africa because of their potential feedbacks with the WAM. This is being addressed through a multiscale modeling approach using an ensemble of land surface models that rely on dedicated satellite-based forcing and land surface parameter products, and data from the African Multidisciplinary Monsoon Analysis (AMMA) observational field campaigns. The AMMA land surface model (LSM) Intercomparison Project (ALMIP) offline, multimodel simulations comprise the equivalent of a multimodel reanalysis product. They currently represent the best estimate of the land surface processes over West Africa from 2004 to 2007. An overview of model intercomparison and evaluation is presented. The far-reaching goal of this effort is to obtain better understanding and prediction of the WAM and the feedbacks with the surface. This can be used to improve water management and agricultural practices over this region.
The rainfall over West Africa has been characterized by extreme variability in the last half-century, with prolonged droughts resulting in humanitarian crises. There is, therefore, an urgent need to better understand and predict the West African monsoon (WAM), because social stability in this region depends to a large degree on water resources. The economies are primarily agrarian, and there are issues related to food security and health. In particular, there is a need to better understand land-atmosphere and hydrological processes over West Africa because of their potential feedbacks with the WAM. This is being addressed through a multiscale modeling approach using an ensemble of land surface models that rely on dedicated satellite-based forcing and land surface parameter products, and data from the African Multidisciplinary Monsoon Analysis (AMMA) observational field campaigns. The AMMA land surface model (LSM) Intercomparison Project (ALMIP) offline, multimodel simulations comprise the equivalent of a multimodel reanalysis product. They currently represent the best estimate of the land surface processes over West Africa from 2004 to 2007. An overview of model intercomparison and evaluation is presented. The far-reaching goal of this effort is to obtain better understanding and prediction of the WAM and the feedbacks with the surface. This can be used to improve water management and agricultural practices over this region.
The African Monsoon Multidisciplinary Analyses-Model Intercomparison Project (AMMA-MIP) was developed within the framework of the AMMA project. It is a relatively light intercomparison and evaluation exercise of both global and regional atmospheric models, focused on the study of the seasonal and intraseasonal variations of the climate and rainfall over the Sahel. Taking advantage of the relative zonal symmetry of the West African climate, one major target of the exercise is the documentation of a meridional cross section made of zonally averaged (10°W–10°E) outputs. This paper presents the motivations and design of the exercise, and it discusses preliminary results and further extensions of the project.
The African Monsoon Multidisciplinary Analyses-Model Intercomparison Project (AMMA-MIP) was developed within the framework of the AMMA project. It is a relatively light intercomparison and evaluation exercise of both global and regional atmospheric models, focused on the study of the seasonal and intraseasonal variations of the climate and rainfall over the Sahel. Taking advantage of the relative zonal symmetry of the West African climate, one major target of the exercise is the documentation of a meridional cross section made of zonally averaged (10°W–10°E) outputs. This paper presents the motivations and design of the exercise, and it discusses preliminary results and further extensions of the project.
Abstract
Six land surface models and five global hydrological models participate in a model intercomparison project [Water Model Intercomparison Project (WaterMIP)], which for the first time compares simulation results of these different classes of models in a consistent way. In this paper, the simulation setup is described and aspects of the multimodel global terrestrial water balance are presented. All models were run at 0.5° spatial resolution for the global land areas for a 15-yr period (1985–99) using a newly developed global meteorological dataset. Simulated global terrestrial evapotranspiration, excluding Greenland and Antarctica, ranges from 415 to 586 mm yr−1 (from 60 000 to 85 000 km3 yr−1), and simulated runoff ranges from 290 to 457 mm yr−1 (from 42 000 to 66 000 km3 yr−1). Both the mean and median runoff fractions for the land surface models are lower than those of the global hydrological models, although the range is wider. Significant simulation differences between land surface and global hydrological models are found to be caused by the snow scheme employed. The physically based energy balance approach used by land surface models generally results in lower snow water equivalent values than the conceptual degree-day approach used by global hydrological models. Some differences in simulated runoff and evapotranspiration are explained by model parameterizations, although the processes included and parameterizations used are not distinct to either land surface models or global hydrological models. The results show that differences between models are a major source of uncertainty. Climate change impact studies thus need to use not only multiple climate models but also some other measure of uncertainty (e.g., multiple impact models).
Abstract
Six land surface models and five global hydrological models participate in a model intercomparison project [Water Model Intercomparison Project (WaterMIP)], which for the first time compares simulation results of these different classes of models in a consistent way. In this paper, the simulation setup is described and aspects of the multimodel global terrestrial water balance are presented. All models were run at 0.5° spatial resolution for the global land areas for a 15-yr period (1985–99) using a newly developed global meteorological dataset. Simulated global terrestrial evapotranspiration, excluding Greenland and Antarctica, ranges from 415 to 586 mm yr−1 (from 60 000 to 85 000 km3 yr−1), and simulated runoff ranges from 290 to 457 mm yr−1 (from 42 000 to 66 000 km3 yr−1). Both the mean and median runoff fractions for the land surface models are lower than those of the global hydrological models, although the range is wider. Significant simulation differences between land surface and global hydrological models are found to be caused by the snow scheme employed. The physically based energy balance approach used by land surface models generally results in lower snow water equivalent values than the conceptual degree-day approach used by global hydrological models. Some differences in simulated runoff and evapotranspiration are explained by model parameterizations, although the processes included and parameterizations used are not distinct to either land surface models or global hydrological models. The results show that differences between models are a major source of uncertainty. Climate change impact studies thus need to use not only multiple climate models but also some other measure of uncertainty (e.g., multiple impact models).
