scholarly journals Coupled Climate Model Simulation of Tropical–Extratropical Cloud Bands over Southern Africa

2020 ◽  
Vol 33 (19) ◽  
pp. 8579-8602
Author(s):  
Rachel James ◽  
Neil C. G. Hart ◽  
Callum Munday ◽  
Chris J. C. Reason ◽  
Richard Washington

AbstractThere are increasing efforts to use climate model output for adaptation planning, but meanwhile there is often limited understanding of how models represent regional climate. Here we analyze the simulation in global coupled climate models of a key rainfall-generating mechanism over southern Africa: tropical temperate troughs (TTTs). An image-processing algorithm is applied to outgoing longwave radiation data from satellites and models to create TTT event sets. All models investigated produce TTTs with similar circulation features to observed. However, there are large differences among models in the number, intensity, and preferred longitude of events. Five groups of models are identified. The first group generates too few TTTs, and relatively dry conditions over southern Africa compared to other models. A second group generates more TTTs and wet biases. The contrast between these two groups suggests that the number of TTTs could explain intermodel variations in climatological rainfall. However, there is a third group of models that simulate up to 92% more TTTs than observed, but do not have large rainfall biases, as each TTT event is relatively weak. Finally, there are a further two groups that concentrate TTTs over the subcontinent or the ocean, respectively. These distinctions between models are associated with the amount of convective activity in the Congo Basin, the magnitude of moisture fluxes into southern Africa, and the degree of zonal asymmetry in upper-level westerly flow. Model development focused on tropical convection and the representation of orography is needed for improved simulation of TTTs, and therefore southern African rainfall.

2019 ◽  
Author(s):  
Muhammad Shafqat Mehboob ◽  
Yeonjoo Kim ◽  
Jaehyeong Lee ◽  
Myoung-Jin Um ◽  
Amir Erfanian ◽  
...  

Abstract. This study investigates the projected effect of vegetation feedback on drought conditions in West Africa using a regional climate model coupled to the National Center for Atmospheric Research Community Land Model, the carbon-nitrogen (CN) module, and the dynamic vegetation (DV) module (RegCM-CLM-CN-DV). The role of vegetation feedback is examined based on simulations with and without the DV module. Simulations from four different global climate models are used as lateral boundary conditions (LBCs) for historical and future periods (i.e., historical: 1981–2000; future: 2081–2100). With utilizing the Standardized Precipitation Evapotranspiration Index (SPEI), we quantify the duration, frequency, and severity of droughts over the focal regions of the Sahel, the Gulf of Guinea, and the Congo Basin. With the vegetation dynamics being considered, future droughts become more prolonged and enhanced over the Sahel, whereas for the Guinea Gulf and Congo Basin, the trend is opposite. Additionally, we show that simulated annual leaf greenness (i.e., the Leaf Area Index) well-correlates with annual minimum SPEI, particularly over the Sahel, which is a transition zone, where the feedback between land-atmosphere is relatively strong. Furthermore, we note that our findings based on the ensemble mean are varying, but consistent among three different LBCs except for one LBC. Our results signify the importance of vegetation dynamics in predicting future droughts in West Africa, where the biosphere and atmosphere interactions play an important role in the regional climate setup.


2017 ◽  
Vol 14 ◽  
pp. 261-269 ◽  
Author(s):  
Heike Huebener ◽  
Peter Hoffmann ◽  
Klaus Keuler ◽  
Susanne Pfeifer ◽  
Hans Ramthun ◽  
...  

Abstract. Communication between providers and users of climate model simulation results still needs to be improved. In the German regional climate modeling project ReKliEs-De a midterm user workshop was conducted to allow the intended users of the project results to assess the preliminary results and to streamline the final project results to their needs. The user feedback highlighted, in particular, the still considerable gap between climate research output and user-tailored input for climate impact research. Two major requests from the user community addressed the selection of sub-ensembles and some condensed, easy to understand information on the strengths and weaknesses of the climate models involved in the project.


2018 ◽  
Vol 31 (18) ◽  
pp. 7533-7548 ◽  
Author(s):  
C. Munday ◽  
R. Washington

An important challenge for climate science is to understand the regional circulation and rainfall response to global warming. Unfortunately, the climate models used to project future changes struggle to represent present-day rainfall and circulation, especially at a regional scale. This is the case in southern Africa, where models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) overestimate summer rainfall by as much as 300% compared to observations and tend to underestimate rainfall in Madagascar and the southwest Indian Ocean. In this paper, we explore the climate processes associated with the rainfall bias, with the aim of assessing the reliability of the CMIP5 ensemble and highlighting important areas for model development. We find that the high precipitation rates in models that are wet over southern Africa are associated with an anomalous northeasterly moisture transport (~10–30 g kg−1 s−1) that penetrates across the high topography of Tanzania and Malawi and into subtropical southern Africa. This transport occurs in preference to a southeasterly recurvature toward Madagascar that is seen in drier models and reanalysis data. We demonstrate that topographically related model biases in low-level flow are important for explaining the intermodel spread in rainfall; wetter models have a reduced tendency to block the oncoming northeasterly flow compared to dry models. The differences in low-level flow among models are related to upstream wind speed and model representation of topography, both of which should be foci for model development.


2007 ◽  
Vol 20 (16) ◽  
pp. 4227-4242 ◽  
Author(s):  
B. Pohl ◽  
Y. Richard ◽  
N. Fauchereau

Abstract Composite maps of outgoing longwave radiation (OLR) anomalies over the Madden–Julian oscillation (MJO) cycle show marked intraseasonal fluctuations over southern Africa (south of 15°S). Large-scale convective clusters are seen to propagate eastward and then northward over the continent, mainly between 10° and 20°S. The corresponding response of the rainfall field presents the alternation, over the cycle, of dry and humid phases, which are both significant. Moisture flux anomalies indicate an intraseasonal modulation of the midtropospheric easterly flow over the Congo basin at 700 hPa; these fluctuations are coupled to meridional flux anomalies that extend from the tropical to the subtropical austral latitudes, and favor occurrences of wet or dry conditions over the domain. Though statistically significant, the influence of the MJO on southern Africa is however not homogeneous spatially, and only the tropical areas exhibit sharp periodicities in the 30–60-day period range. The OLR dipole observed in previous studies at the interannual and synoptic time scales between the hinterland parts of southern Africa and the southwestern Indian Ocean in the north of Madagascar is investigated next, as it also shows strong fluctuations at the intraseasonal time scale. The study points out that the dipole is partly influenced by the MJO, though the strongest periodicities are found for slightly longer periods (35–80 days) than those typically associated with the oscillation. The forcing of the MJO on the OLR dipole, though significant, remains thus partial.


2021 ◽  
pp. 1-69
Author(s):  
Alain T. Tamoffo ◽  
Leonard K. Amekudzi ◽  
Torsten Weber ◽  
Derbetini A. Vondou ◽  
Edmund I. Yamba ◽  
...  

Abstract Two regional climate models (RCMs) participating in the CORDEX-Coordinated Output for Regional Evaluations (CORDEX-CORE) project feature a dipole-type rainfall bias during March-May (MAM) and September-November (SON) over Central Equatorial Africa (CEA), consisting in positive bias in West Central Equatorial Africa (WCEA) and negative bias in East Central Equatorial Africa (ECEA). One is the REgional MOdel version 2015 (REMO2015), and the other is the fourth version of the Regional Climate Model (RegCM4-v7). RCMs are nested in three Earth System Models (ESMs) from the Coupled Model Intercomparison Project phase 5 (CMIP5), and in the reanalysis ERA-Interim, at ~25 Km spacing-grid resolution. This study highlights misrepresented underlying physical processes associated with these rainfall biases through a process-based evaluation. Both RCMs produce a weaker Congo basin cell, associated with a weaker land-ocean zonal surface pressure gradient. Consequently, less water vapour enters the region, and little amount is transported from WCEA to ECEA, resulting in higher moisture availability in the west than in the east. This leads to an unevenly distributed moisture across the region, favouring a stronger atmospheric instability in WCEA where the moist static energy (MSE) anomalously increases through an enhanced latent static energy (LSE). Moisture arrives at a slower pace in ECEA, associated with the weak cell's strength. The intensity of ascent motions in response to the orographic constraint is weak to destabilise atmospheric stability in the lower layers, necessary for initiating deep convection. Therefore, the convection is shallow in ECEA related to underestimating the MSE due to the reduced LSE.


Author(s):  
Weijia Qian ◽  
Howard H. Chang

Health impact assessments of future environmental exposures are routinely conducted to quantify population burdens associated with the changing climate. It is well-recognized that simulations from climate models need to be bias-corrected against observations to estimate future exposures. Quantile mapping (QM) is a technique that has gained popularity in climate science because of its focus on bias-correcting the entire exposure distribution. Even though improved bias-correction at the extreme tails of exposure may be particularly important for estimating health burdens, the application of QM in health impact projection has been limited. In this paper we describe and apply five QM methods to estimate excess emergency department (ED) visits due to projected changes in warm-season minimum temperature in Atlanta, USA. We utilized temperature projections from an ensemble of regional climate models in the North American-Coordinated Regional Climate Downscaling Experiment (NA-CORDEX). Across QM methods, we estimated consistent increase in ED visits across climate model ensemble under RCP 8.5 during the period 2050 to 2099. We found that QM methods can significantly reduce between-model variation in health impact projections (50–70% decreases in between-model standard deviation). Particularly, the quantile delta mapping approach had the largest reduction and is recommended also because of its ability to preserve model-projected absolute temporal changes in quantiles.


Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 174
Author(s):  
Günther Heinemann ◽  
Sascha Willmes ◽  
Lukas Schefczyk ◽  
Alexander Makshtas ◽  
Vasilii Kustov ◽  
...  

The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.


2007 ◽  
Vol 88 (3) ◽  
pp. 375-384 ◽  
Author(s):  
E. S. Takle ◽  
J. Roads ◽  
B. Rockel ◽  
W. J. Gutowski ◽  
R. W. Arritt ◽  
...  

A new approach, called transferability intercomparisons, is described for advancing both understanding and modeling of the global water cycle and energy budget. Under this approach, individual regional climate models perform simulations with all modeling parameters and parameterizations held constant over a specific period on several prescribed domains representing different climatic regions. The transferability framework goes beyond previous regional climate model intercomparisons to provide a global method for testing and improving model parameterizations by constraining the simulations within analyzed boundaries for several domains. Transferability intercomparisons expose the limits of our current regional modeling capacity by examining model accuracy on a wide range of climate conditions and realizations. Intercomparison of these individual model experiments provides a means for evaluating strengths and weaknesses of models outside their “home domains” (domain of development and testing). Reference sites that are conducting coordinated measurements under the continental-scale experiments under the Global Energy and Water Cycle Experiment (GEWEX) Hydrometeorology Panel provide data for evaluation of model abilities to simulate specific features of the water and energy cycles. A systematic intercomparison across models and domains more clearly exposes collective biases in the modeling process. By isolating particular regions and processes, regional model transferability intercomparisons can more effectively explore the spatial and temporal heterogeneity of predictability. A general improvement of model ability to simulate diverse climates will provide more confidence that models used for future climate scenarios might be able to simulate conditions on a particular domain that are beyond the range of previously observed climates.


2017 ◽  
Vol 30 (20) ◽  
pp. 8275-8298 ◽  
Author(s):  
Melissa S. Bukovsky ◽  
Rachel R. McCrary ◽  
Anji Seth ◽  
Linda O. Mearns

Abstract Global and regional climate model ensembles project that the annual cycle of rainfall over the southern Great Plains (SGP) will amplify by midcentury. Models indicate that warm-season precipitation will increase during the early spring wet season but shift north earlier in the season, intensifying late summer drying. Regional climate models (RCMs) project larger precipitation changes than their global climate model (GCM) counterparts. This is particularly true during the dry season. The credibility of the RCM projections is established by exploring the larger-scale dynamical and local land–atmosphere feedback processes that drive future changes in the simulations, that is, the responsible mechanisms or processes. In this case, it is found that out of 12 RCM simulations produced for the North American Regional Climate Change Assessment Program (NARCCAP), the majority are mechanistically credible and consistent in the mean changes they are producing in the SGP. Both larger-scale dynamical processes and local land–atmosphere feedbacks drive an earlier end to the spring wet period and deepening of the summer dry season in the SGP. The midlatitude upper-level jet shifts northward, the monsoon anticyclone expands, and the Great Plains low-level jet increases in strength, all supporting a poleward shift in precipitation in the future. This dynamically forced shift causes land–atmosphere coupling to strengthen earlier in the summer, which in turn leads to earlier evaporation of soil moisture in the summer, resulting in extreme drying later in the summer.


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