scholarly journals Causes of the Uncertainty in Projections of Tropical Terrestrial Rainfall Change: East Africa

2018 ◽  
Vol 31 (15) ◽  
pp. 5977-5995 ◽  
Author(s):  
David P. Rowell ◽  
Robin Chadwick

Understanding the causes of regional climate projection uncertainty is a critical component toward establishing reliability of these projections. Here, four complementary experimental and decomposition techniques are synthesized to begin to understand which mechanisms differ most between models. These tools include a variety of multimodel ensembles, a decomposition of rainfall into tropics-wide or region-specific processes, and a separation of within-domain versus remote contributions to regional model projection uncertainty. Three East African regions are identified and characterized by spatially coherent intermodel projection behavior, which interestingly differs from previously identified regions of coherent interannual behavior. For the “Short Rains” regions, uncertainty in projected seasonal mean rainfall change is primarily due to uncertainties in the regional response to both the uniform and pattern components of SST warming (but not uncertainties in the global mean warming itself) and a small direct CO2 impact. These primarily derive from uncertain regional dynamics over both African and remote regions, rather than globally coherent (thermo)dynamics. For the “Long Rains” region, results are similar, except that uncertain atmospheric responses to a fixed SST pattern change are a little less important, and some key regional uncertainties are primarily located beyond Africa. The latter reflects the behavior of two outlying models that experience exceptional warming in the southern subtropical oceans, from which large lower-tropospheric moisture anomalies are advected by the mean flow to contribute to exceptional increases in the Long Rains totals. Further research could lead to a useful assessment of the reliability of these exceptional projections.

2016 ◽  
Vol 29 (7) ◽  
pp. 2493-2509 ◽  
Author(s):  
Robin Chadwick

Abstract The sources of intermodel uncertainty in regional tropical rainfall projections are examined using a framework of atmosphere-only experiments. Uncertainty is dominated by model disagreement on shifts in convective regions, but the drivers of this uncertainty differ between land and ocean. Over the tropical oceans SST pattern uncertainty plays a substantial role, although it is not the only cause of uncertainty. Over land SST pattern uncertainty appears to be much less influential, and the largest source of uncertainty comes from the response to uniform SST warming, with a secondary contribution from the response to direct CO2 forcing. This may be because a larger number of processes can cause rainfall change in response to uniform SST warming than direct CO2 forcing, and so there is more potential for models to disagree. However, new experiments designed to more accurately decompose the regional climate responses of coupled models, combined with results from high-resolution climate modeling, are needed before these results can be considered robust. The pattern of present-day rainfall does not in general provide emergent constraints on future regional rainfall change. Correlations between relative humidity (RH) change and spatial shifts in convection over many land regions suggest that a proposed causal influence of RH change on dynamical rainfall change is plausible, although causality is not demonstrated here.


2015 ◽  
Vol 28 (15) ◽  
pp. 6249-6266 ◽  
Author(s):  
Christian Kerkhoff ◽  
Hans R. Künsch ◽  
Christoph Schär

Abstract A Bayesian hierarchical model for heterogeneous multimodel ensembles of global and regional climate models is presented. By applying the methodology herein to regional and seasonal temperature averages from the ENSEMBLES project, probabilistic projections of future climate are derived. Intermodel correlations that are particularly strong between regional climate models and their driving global climate models are explicitly accounted for. Instead of working with time slices, a data archive is investigated in a transient setting. This enables a coherent treatment of internal variability on multidecadal time scales. Results are presented for four European regions to highlight the feasibility of the approach. In particular, the methodology is able to objectively identify patterns of variability changes, in ways that previously required subjective expert knowledge. Furthermore, this study underlines that assumptions about bias changes have an effect on the projected warming. It is also shown that validating the out-of-sample predictive performance is possible on short-term prediction horizons and that the hierarchical model herein is competitive. Additionally, the findings indicate that instead of running a large suite of regional climate models all forced by the same driver, priority should be given to a rich diversity of global climate models that force a number of regional climate models in the experimental design of future multimodel ensembles.


2018 ◽  
Vol 31 (16) ◽  
pp. 6611-6631 ◽  
Author(s):  
Linda Hirons ◽  
Andrew Turner

The role of the Indian Ocean dipole (IOD) in controlling interannual variability in the East African short rains, from October to December, is examined in state-of-the-art models and in detail in one particular climate model. In observations, a wet short-rainy season is associated with the positive phase of the IOD and anomalous easterly low-level flow across the equatorial Indian Ocean. A model’s ability to capture the teleconnection to the positive IOD is closely related to its representation of the mean state. During the short-rains season, the observed low-level wind in the equatorial Indian Ocean is westerly. However, half of the models analyzed exhibit mean-state easterlies across the entire basin. Specifically, those models that exhibit mean-state low-level equatorial easterlies in the Indian Ocean, rather than the observed westerlies, are unable to capture the latitudinal structure of moisture advection into East Africa during a positive IOD. Furthermore, the associated anomalous easterly surface wind stress causes upwelling in the eastern Indian Ocean. This upwelling draws up cool subsurface waters, enhancing the zonal sea surface temperature gradient between west and east and strengthening the positive IOD pattern, further amplifying the easterly wind stress. This positive Bjerknes coupled feedback is stronger in easterly mean-state models, resulting in a wetter East African short-rain precipitation bias in those models.


2019 ◽  
Vol 32 (22) ◽  
pp. 7989-8001 ◽  
Author(s):  
David MacLeod ◽  
Cyril Caminade

Abstract El Niño–Southern Oscillation (ENSO) has large socioeconomic impacts worldwide. The positive phase of ENSO, El Niño, has been linked to intense rainfall over East Africa during the short rains season (October–December). However, we show here that during the extremely strong 2015 El Niño the precipitation anomaly over most of East Africa during the short rains season was less intense than experienced during previous El Niños, linked to less intense easterlies over the Indian Ocean. This moderate impact was not indicated by reforecasts from the ECMWF operational seasonal forecasting system, SEAS5, which instead forecast large probabilities of an extreme wet signal, with stronger easterly anomalies over the surface of the Indian Ocean and a colder eastern Indian Ocean/western Pacific than was observed. To confirm the relationship of the eastern Indian Ocean to East African rainfall in the forecast for 2015, atmospheric relaxation experiments are carried out that constrain the east Indian Ocean lower troposphere to reanalysis. By doing so the strong wet forecast signal is reduced. These results raise the possibility that link between ENSO and Indian Ocean dipole events is too strong in the ECMWF dynamical seasonal forecast system and that model predictions for the East African short rains rainfall during strong El Niño events may have a bias toward high probabilities of wet conditions.


2020 ◽  
Vol 59 (6) ◽  
pp. 1077-1090
Author(s):  
Xiao Peng ◽  
Scott Steinschneider ◽  
John Albertson

AbstractWe investigate the predictability of East African short rains at long (up to 12 month) lead times by relating seasonal rainfall anomalies to climate anomalies associated with the predominant Walker circulation, including sea surface temperatures (SST), geopotential heights, zonal and meridional winds, and vertical velocities. The underlying teleconnections are examined using a regularized regression model that shows two periods of high model skill (0–3-month lead and 7–9-month lead) with similar spatial patterns of predictability. We observe large-scale circulation anomalies consistent with the Walker circulation at short lead times (0–3 months) and dipoles of SST and height anomalies over the Mascarene high region at longer lead times (7–9 months). These two patterns are linked in time by anticyclonic winds in the dipole region associated with a perturbed meridional circulation (4–6-month lead). Overall, these results suggest that there is potential to extend forecast lead times beyond a few months for drought impact mitigation applications.


2016 ◽  
Vol 121 (16) ◽  
pp. 9441-9457 ◽  
Author(s):  
Dao-Yi Gong ◽  
Dong Guo ◽  
Rui Mao ◽  
Jing Yang ◽  
Yongqi Gao ◽  
...  

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