scholarly journals The Rainfall Annual Cycle Bias over East Africa in CMIP5 Coupled Climate Models

2015 ◽  
Vol 28 (24) ◽  
pp. 9789-9802 ◽  
Author(s):  
Wenchang Yang ◽  
Richard Seager ◽  
Mark A. Cane ◽  
Bradfield Lyon
Keyword(s):  
East Africa ◽  
Annual Cycle ◽  
Climate Models ◽  
Western Indian Ocean ◽  
Shortwave Radiation ◽  
Coupled Models ◽  
Near Surface ◽  
Historical Simulation ◽  
Sst Bias ◽  
Short Rains

Abstract East Africa has two rainy seasons: the long rains [March–May (MAM)] and the short rains [October–December (OND)]. Most CMIP3/5 coupled models overestimate the short rains while underestimating the long rains. In this study, the East African rainfall bias is investigated by comparing the coupled historical simulations from CMIP5 to the corresponding SST-forced AMIP simulations. Much of the investigation is focused on the MRI-CGCM3 model, which successfully reproduces the observed rainfall annual cycle in East Africa in the AMIP experiment but its coupled historical simulation has a similar but stronger bias as the coupled multimodel mean. The historical–AMIP monthly climatology rainfall bias in East Africa can be explained by the bias in the convective instability (CI), which is dominated by the near-surface moisture static energy (MSE) and ultimately by the MSE’s moisture component. The near-surface MSE bias is modulated by the sea surface temperature (SST) over the western Indian Ocean. The warm SST bias in OND can be explained by both insufficient ocean dynamical cooling and latent flux, while the insufficient shortwave radiation and excess latent heat flux mainly contribute to the cool SST bias in MAM.

scholarly journals The Annual Cycle of East African Precipitation

2015 ◽  
Vol 28 (6) ◽  
pp. 2385-2404 ◽  
Author(s):  
Wenchang Yang ◽  
Richard Seager ◽  
Mark A. Cane ◽  
Bradfield Lyon
Keyword(s):  
East Africa ◽  
Annual Cycle ◽  
Lower Troposphere ◽  
Moisture Flux ◽  
Convective Stability ◽  
East African ◽  
Coupled Models ◽  
Annual Cycles ◽  
Short Rains ◽  
Static Energy

Abstract East African precipitation is characterized by a dry annual mean climatology compared to other deep tropical land areas and a bimodal annual cycle with the major rainy season during March–May (MAM; often called the “long rains”) and the second during October–December (OND; often called the “short rains”). To explore these distinctive features, ERA-Interim data are used to analyze the associated annual cycles of atmospheric convective stability, circulation, and moisture budget. The atmosphere over East Africa is found to be convectively stable in general year-round but with an annual cycle dominated by the surface moist static energy (MSE), which is in phase with the precipitation annual cycle. Throughout the year, the atmospheric circulation is dominated by a pattern of convergence near the surface, divergence in the lower troposphere, and convergence again at upper levels. Consistently, the convergence of the vertically integrated moisture flux is mostly negative across the year, but becomes weakly positive in the two rainy seasons. It is suggested that the semiarid/arid climate in East Africa and its bimodal precipitation annual cycle can be explained by the ventilation mechanism, in which the atmospheric convective stability over East Africa is controlled by the import of low MSE air from the relatively cool Indian Ocean off the coast. During the rainy seasons, however, the off-coast sea surface temperature (SST) increases (and is warmest during the long rains season) and consequently the air imported into East Africa becomes less stable. This analysis may be used to aid in understanding overestimates of the East African short rains commonly found in coupled models.

scholarly journals Atmospheric Dynamics Feedback: Concept, Simulations, and Climate Implications

2018 ◽  
Vol 31 (8) ◽  
pp. 3249-3264 ◽  
Author(s):  
Michael P. Byrne ◽  
Tapio Schneider
Keyword(s):  
Climate Change ◽  
Atmospheric Circulation ◽  
Radiative Forcing ◽  
Large Scale ◽  
Climate Models ◽  
Atmospheric Dynamics ◽  
Future Climate Change ◽  
Coupled Models ◽  
Near Surface ◽  
Circulation Changes

AbstractThe regional climate response to radiative forcing is largely controlled by changes in the atmospheric circulation. It has been suggested that global climate sensitivity also depends on the circulation response, an effect called the “atmospheric dynamics feedback.” Using a technique to isolate the influence of changes in atmospheric circulation on top-of-the-atmosphere radiation, the authors calculate the atmospheric dynamics feedback in coupled climate models. Large-scale circulation changes contribute substantially to all-sky and cloud feedbacks in the tropics but are relatively less important at higher latitudes. Globally averaged, the atmospheric dynamics feedback is positive and amplifies the near-surface temperature response to climate change by an average of 8% in simulations with coupled models. A constraint related to the atmospheric mass budget results in the dynamics feedback being small on large scales relative to feedbacks associated with thermodynamic processes. Idealized-forcing simulations suggest that circulation changes at high latitudes are potentially more effective at influencing global temperature than circulation changes at low latitudes, and the implications for past and future climate change are discussed.

scholarly journals Validation of IMERG Precipitation in Africa

2017 ◽  
Vol 18 (10) ◽  
pp. 2817-2825 ◽  
Author(s):  
Amin K. Dezfuli ◽  
Charles M. Ichoku ◽  
George J. Huffman ◽  
Karen I. Mohr ◽  
John S. Selker ◽  
...  
Keyword(s):  
East Africa ◽  
Annual Cycle ◽  
Lake Victoria ◽  
Mountainous Regions ◽  
Meteorological Observatory ◽  
Precipitation Analysis ◽  
In Situ Observations ◽  
Short Rains ◽  
Good Agreement

Abstract Understanding of hydroclimatic processes in Africa has been hindered by the lack of in situ precipitation measurements. Satellite-based observations, in particular, the TRMM Multisatellite Precipitation Analysis (TMPA) have been pivotal to filling this void. The recently released Integrated Multisatellite Retrievals for GPM (IMERG) project aims to continue the legacy of its predecessor, TMPA, and provide higher-resolution data. Here, IMERG-V04A precipitation data are validated using in situ observations from the Trans-African Hydro-Meteorological Observatory (TAHMO) project. Various evaluation measures are examined over a select number of stations in West and East Africa. In addition, continent-wide comparisons are made between IMERG and TMPA. The results show that the performance of the satellite-based products varies by season, region, and the evaluation statistics. The precipitation diurnal cycle is relatively better captured by IMERG than TMPA. Both products exhibit a better agreement with gauge data in East Africa and humid West Africa than in the southern Sahel. However, a clear advantage for IMERG is not apparent in detecting the annual cycle. Although all gridded products used here reasonably capture the annual cycle, some differences are evident during the short rains in East Africa. Direct comparison between IMERG and TMPA over the entire continent reveals that the similarity between the two products is also regionally heterogeneous. Except for Zimbabwe and Madagascar, where both satellite-based observations present a good agreement, the two products generally have their largest differences over mountainous regions. IMERG seems to have achieved a reduction in the positive bias evident in TMPA over Lake Victoria.

The Annual Cycle of Fractional Atmospheric Shortwave Absorption in Observations and Models: Spatial Structure, Magnitude, and Timing

2019 ◽  
Vol 32 (20) ◽  
pp. 6729-6748 ◽  
Author(s):  
M. Schwarz ◽  
D. Folini ◽  
S. Yang ◽  
M. Wild
Keyword(s):  
Water Vapor ◽  
Biomass Burning ◽  
Annual Cycle ◽  
Climate Models ◽  
Global Scale ◽  
Shortwave Radiation ◽  
Minor Role ◽  
Annual Cycles ◽  
Regional Feature ◽  
A Minor

We use the best currently available in situ and satellite-derived surface and top-of-the-atmosphere (TOA) shortwave radiation observations to explore climatological annual cycles of fractional (i.e., normalized by incoming radiation at the TOA) atmospheric shortwave absorption [Formula: see text] on a global scale. The analysis reveals that [Formula: see text] is a rather regional feature where the reported nonexisting [Formula: see text] in Europe is an exception rather than the rule. In several regions, large and distinctively different [Formula: see text] are apparent. The magnitudes of [Formula: see text] reach values up to 10% in some regions, which is substantial given that the long-term global mean atmospheric shortwave absorption is roughly 23%. Water vapor and aerosols are identified as major drivers for [Formula: see text] while clouds seem to play only a minor role for [Formula: see text]. Regions with large annual cycles in aerosol emissions from biomass burning also show the largest [Formula: see text]. As biomass burning is generally related to human activities, [Formula: see text] is likely also anthropogenically intensified or forced in the respective regions. We also test if climate models are able to simulate the observed pattern of [Formula: see text]. In regions where [Formula: see text] is driven by the annual cycle of natural aerosols or water vapor, the models perform well. In regions with large [Formula: see text] induced by biomass-burning aerosols, the models’ performance is very limited.

Surface energy balance and climatology changes from WRF simulations with different horizontal resolutions and soil configurations 

2021 ◽  
Author(s):  
Almudena García-García ◽  
Francisco José Cuesta-Valero ◽  
Hugo Beltrami ◽  
Fidel González-Rouco ◽  
Elena García-Bustamante
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Surface Energy ◽  
Latent Heat ◽  
Surface Energy Balance ◽  
Climate Models ◽  
Horizontal Resolution ◽  
Shortwave Radiation ◽  
Near Surface ◽  
Surface Conditions

<p>Interactions between the lower atmosphere and the shallow continental subsurface govern several surface processes important for ecosystems and society, such as extreme temperature and precipitation events. Transient climate simulations performed with climate models have been employed to study the water, mass and energy exchanges between the atmosphere and the shallow subsurface, obtaining large inter-model differences. Understanding the origin of differences between climate models in the simulation of near-surface conditions is crucial for restricting the inter-model variability of future climate projections. Here, we explore the effect of changes in horizontal resolution on the simulation of the surface energy balance and the climatology of near-surface conditions over North America (NA) using the Weather Research and Forecasting (WRF) model. <br>We analyzed an ensemble of twelve simulations using three different horizontal resolutions (25 km, 50 km and 100 km) and four different Land Surface Model (LSM) configurations over North America from 1980 to 2013. Our results show that increasing horizontal resolution alters the representation of shortwave radiation, affecting near-surface temperatures and consequently the partition of energy into sensible and latent heat fluxes. Thus, finer resolutions lead to higher net shortwave radiation and temperature at high NA latitudes and to lower net shortwave radiation and temperature at low NA latitudes. The use of finer resolutions also leads to an intensification of the terms associated with the surface water balance over coastal areas at low latitudes, generating higher latent heat flux, accumulated precipitation and soil moisture. The effect of the LSM choice is larger than the effect of horizontal resolution on the representation of the surface energy balance, and consequently on near-surface temperature. By contrast, the effect of the LSM configuration on the simulation of precipitation is weaker than the effect of horizontal resolution, showing larger differences among LSM simulations in summer and over regions with high latent heat flux. This ensemble of simulations is then compared against CRU data. Comparison between the CRU data and the simulated climatology of daily maximum and minimum temperatures and accumulated precipitation indicates that enhancing horizontal resolution marginally improves the simulated climatology of minimum and maximum temperatures in summer, while it leads to larger biases in accumulated precipitation. The larger biases in precipitation with the use of finer horizontal resolutions are likely related to the effect of increasing resolution on the atmospheric model component, since precipitation biases are similar using different LSM configurations.</p>

Atlantic Warm-Pool Variability in the IPCC AR4 CGCM Simulations

2012 ◽  
Vol 25 (16) ◽  
pp. 5612-5628 ◽  
Author(s):  
Hailong Liu ◽  
Chunzai Wang ◽  
Sang-Ki Lee ◽  
David Enfield
Keyword(s):  
Twentieth Century ◽  
Decadal Variability ◽  
Local Heating ◽  
Warm Pool ◽  
Shortwave Radiation ◽  
Coupled Models ◽  
Area Index ◽  
Low Level ◽  
Atlantic Warm Pool ◽  
Sst Bias

Abstract This study investigates Atlantic warm pool (AWP) variability in the twentieth century and preindustrial simulations of coupled GCMs submitted to the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). In the twentieth-century simulations, most coupled models show very weak AWP variability, represented by an AWP area index, because of the cold SST bias in the AWP. Among the IPCC models, a higher AWP SST index corresponds to increased net downward shortwave radiation and decreased low-level cloud fraction during the AWP peak season. This suggests that the cold SST bias in the AWP region is at least partly caused by an excessive amount of simulated low-level cloud, which blocks shortwave radiation from reaching the sea surface. AWP natural variability is examined in preindustrial simulations. Spectral analysis reveals that only multidecadal band variability of the AWP is significant in observations. All models successfully capture the multidecadal band, but they show that interannual and/or decadal variability is also significant. On the multidecadal time scale, the global SST difference pattern between large AWP years and small AWP years resembles the geographic pattern of the AMO for most coupled models. Observational analysis indicates that both positive ENSO phase and negative NAO phase in winter correspond to reduced trade winds in the AWP region. The westerly anomalies induced by positive ENSO and negative NAO lead to local heating and warm SST from March to May and February to April, respectively. This behavior as a known feature of anomalous AWP growth is well captured by only five models.

scholarly journals The location of the thermodynamic atmosphere–ice interface in fully-coupled models

2015 ◽  
Vol 8 (11) ◽  
pp. 9707-9739
Author(s):  
A. E. West ◽  
A. J. McLaren ◽  
H. T. Hewitt ◽  
M. J. Best
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Sensible Heat Flux ◽  
Surface Air Temperature ◽  
Coupled Models ◽  
Surface Exchange ◽  
Near Surface ◽  
Fully Coupled ◽  
Coupling Frequency ◽  
Ice Model

Abstract. In fully-coupled climate models, it is now normal to include a sea ice component with multiple layers, each having their own temperature. When coupling this component to an atmosphere model, it is more common for surface variables to be calculated in the sea ice component of the model, the equivalent of placing an interface immediately above the surface. This study uses a one-dimensional (1-D) version of the Los Alamos sea ice model (CICE) thermodynamic solver and the Met Office atmospheric surface exchange solver (JULES) to compare this method with that of allowing the surface variables to be calculated instead in the atmosphere, the equivalent of placing an interface immediately below the surface. The model is forced with a sensible heat flux derived from a sinusoidally varying near-surface air temperature. The two coupling methods are tested first with a 1-h coupling frequency, and then a 3-h coupling frequency, both commonly-used. With an above-surface interface, the resulting surface temperature and flux cycles contain large phase and amplitude errors, as well as having a very "blocky" shape. The simulation of both quantities is greatly improved when the interface is instead placed within the top ice layer, allowing surface variables to be calculated on the shorter timescale of the atmosphere. There is also an unexpected slight improvement in the simulation of the top-layer ice temperature by the ice model. The study concludes with a discussion of the implications of these results to three-dimensional modelling. An appendix examines the stability of the alternative method of coupling under various physically realistic scenarios.

scholarly journals The location of the thermodynamic atmosphere–ice interface in fully coupled models – a case study using JULES and CICE

2016 ◽  
Vol 9 (3) ◽  
pp. 1125-1141 ◽  
Author(s):  
Alex E. West ◽  
Alison J. McLaren ◽  
Helene T. Hewitt ◽  
Martin J. Best
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Sensible Heat Flux ◽  
Snow Layer ◽  
Coupled Models ◽  
Surface Exchange ◽  
Near Surface ◽  
Fully Coupled ◽  
Coupling Frequency ◽  
Ice Model

Abstract. In fully coupled climate models, it is now normal to include a sea ice component with multiple layers, each having their own temperature. When coupling this component to an atmosphere model, it is more common for surface variables to be calculated in the sea ice component of the model, the equivalent of placing an interface immediately above the surface. This study uses a one-dimensional (1-D) version of the Los Alamos sea ice model (CICE) thermodynamic solver and the Met Office atmospheric surface exchange solver (JULES) to compare this method with that of allowing the surface variables to be calculated instead in the atmosphere, the equivalent of placing an interface immediately below the surface. The model is forced with a sensible heat flux derived from a sinusoidally varying near-surface air temperature. The two coupling methods are tested first with a 1 h coupling frequency, and then a 3 h coupling frequency, both commonly used. With an above-surface interface, the resulting surface temperature and flux cycles contain large phase and amplitude errors, and have a very blocky shape. The simulation of both quantities is greatly improved when the interface is instead placed within the top ice layer, allowing surface variables to be calculated on the shorter timescale of the atmosphere. There is also an unexpected slight improvement in the simulation of the top-layer ice temperature by the ice model. The surface flux improvement remains when a snow layer is added to the ice, and when the wind speed is increased. The study concludes with a discussion of the implications of these results to three-dimensional modelling. An appendix examines the stability of the alternative method of coupling under various physically realistic scenarios.

scholarly journals Biases in CMIP5 Sea Surface Temperature and the Annual Cycle of East African Rainfall

2020 ◽  
Vol 33 (19) ◽  
pp. 8209-8223
Author(s):  
Bradfield Lyon
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Annual Cycle ◽  
General Circulation ◽  
Regional Scale ◽  
Sea Surface ◽  
East African ◽  
Coupled Models ◽  
African Rainfall ◽  
Short Rains

AbstractIn much of East Africa, climatological rainfall follows a bimodal distribution characterized by the long rains (March–May) and short rains (October–December). Most CMIP5 coupled models fail to properly simulate this annual cycle, typically reversing the amplitudes of the short and long rains relative to observations. This study investigates how CMIP5 climatological sea surface temperature (SST) biases contribute to simulation errors in the annual cycle of East African rainfall. Monthly biases in CMIP5 climatological SSTs (50°S–50°N) are first identified in historical runs (1979–2005) from 31 models and examined for consistency. An atmospheric general circulation model (AGCM) is then forced with observed SSTs (1979–2005) generating a set of control runs and observed SSTs plus the monthly, multimodel mean SST biases generating a set of “bias” runs for the same period. The control runs generally capture the observed annual cycle of East African rainfall while the bias runs capture prominent CMIP5 annual cycle biases, including too little (much) precipitation during the long rains (short rains) and a 1-month lag in the peak of the long rains relative to observations. Diagnostics reveal the annual cycle biases are associated with seasonally varying north–south- and east–west-oriented SST bias patterns in Indian Ocean and regional-scale atmospheric circulation and stability changes, the latter primarily associated with changes in low-level moist static energy. Overall, the results indicate that CMIP5 climatological SST biases are the primary driver of the improper simulation of the annual cycle of East African rainfall. Some implications for climate change projections are discussed.

scholarly journals Impact of increased resolution on long-standing biases in HighResMIP-PRIMAVERA climate models

2021 ◽  
Author(s):  
Eduardo Moreno-Chamarro ◽  
Louis-Philippe Caron ◽  
Saskia Loosveldt Tomas ◽  
Oliver Gutjahr ◽  
Marie-Pierre Moine ◽  
...  
Keyword(s):  
General Circulation ◽  
Cloud Cover ◽  
Climate Models ◽  
General Circulation Models ◽  
Coupled Models ◽  
Near Surface ◽  
Warm Bias ◽  
Zonal Winds ◽  
Cloud Radiative Effect ◽  
Improved Model

Abstract. We examine the impacts of increased resolution on four long-standing biases using five different climate models developed within the PRIMAVERA project. Atmospheric resolution is increased from ~100–200 km to ~25–50 km, and ocean resolution is increased from ~1° (i.e., eddy-parametrized) to ~0.25° (i.e., eddy-present). For one model, ocean resolution is also increased to 1/12° (i.e., eddy-rich). Fully-coupled general circulation models and their atmosphere-only versions are compared with observations and reanalysis of near-surface temperature, precipitation, cloud cover, net cloud radiative effect, and zonal wind over the period 1980–2014. Both the ensemble mean and individual models are analyzed. Increased resolution especially in the atmosphere helps reduce the surface warm bias over the tropical upwelling regions in the coupled models, with further improvements in the cloud cover and precipitation biases particularly over the tropical South Atlantic. Related to this and to the improvement in the precipitation distribution over the western tropical Pacific, the double Intertropical Convergence Zone bias also weakens with resolution. Overall, increased ocean resolution from ~1° to ~0.25° offers limited improvements or even bias degradation in some models, although an eddy-rich ocean resolution seems beneficial for reducing the biases in North Atlantic temperatures and Gulf Stream path. Despite the improvements, however, large biases in precipitation and cloud cover persist over the whole tropics as well as in the upper-troposphere zonal winds at mid-latitudes in coupled and atmosphere-only models at higher resolutions. The Southern Ocean warm bias also worsens or persists in some coupled models. And a new warm bias emerges in the Labrador Sea in all the high-resolution coupled models. The analysis of the PRIMAVERA models therefore suggests that, to reduce biases, i) increased atmosphere resolution up to ~25–50 km alone might not be sufficient and ii) an eddy-rich ocean resolution might be needed. The study thus adds to evidence that further improved model physics and tuning might be necessary in addition to increased resolution to mitigate biases.

Sign in / Sign up

Export Citation Format

Share Document