scholarly journals Comparison of simulated and reconstructed variations in East African hydroclimate over the last millennium

2016 ◽  
Vol 12 (7) ◽  
pp. 1499-1518 ◽  
Author(s):  
François Klein ◽  
Hugues Goosse ◽  
Nicholas E. Graham ◽  
Dirk Verschuren
Keyword(s):  
Time Series ◽  
Indian Ocean ◽  
East Africa ◽  
Seasonal Cycle ◽  
General Circulation ◽  
Large Scale ◽  
Internal Variability ◽  
General Circulation Models ◽  
Last Millennium ◽  
East African

Abstract. The multi-decadal to centennial hydroclimate changes in East Africa over the last millennium are studied by comparing the results of forced transient simulations by six general circulation models (GCMs) with published hydroclimate reconstructions from four lakes: Challa and Naivasha in equatorial East Africa, and Masoko and Malawi in southeastern inter-tropical Africa. All GCMs simulate fairly well the unimodal seasonal cycle of precipitation in the Masoko–Malawi region, while the bimodal seasonal cycle characterizing the Challa–Naivasha region is generally less well captured by most models. Model results and lake-based hydroclimate reconstructions display very different temporal patterns over the last millennium. Additionally, there is no common signal among the model time series, at least until 1850. This suggests that simulated hydroclimate fluctuations are mostly driven by internal variability rather than by common external forcing. After 1850, half of the models simulate a relatively clear response to forcing, but this response is different between the models. Overall, the link between precipitation and tropical sea surface temperatures (SSTs) over the pre-industrial portion of the last millennium is stronger and more robust for the Challa–Naivasha region than for the Masoko–Malawi region. At the inter-annual timescale, last-millennium Challa–Naivasha precipitation is positively (negatively) correlated with western (eastern) Indian Ocean SST, while the influence of the Pacific Ocean appears weak and unclear. Although most often not significant, the same pattern of correlations between East African rainfall and the Indian Ocean SST is still visible when using the last-millennium time series smoothed to highlight centennial variability, but only in fixed-forcing simulations. This means that, at the centennial timescale, the effect of (natural) climate forcing can mask the imprint of internal climate variability in large-scale teleconnections.

scholarly journals Comparison of simulated and reconstructed variations in East African hydroclimate over the last millennium

2016 ◽  
Author(s):  
François Klein ◽  
Hugues Goosse ◽  
Nicholas E. Graham ◽  
Dirk Verschuren
Keyword(s):  
Time Series ◽  
Indian Ocean ◽  
East Africa ◽  
Time Scale ◽  
Seasonal Cycle ◽  
General Circulation ◽  
Large Scale ◽  
General Circulation Models ◽  
Last Millennium ◽  
East African

Abstract. The multi-decadal to centennial hydroclimate changes in East Africa over the last millennium are studied by comparing the results of forced transient simulations by six General Circulation Models (GCMs) with published hydroclimate reconstructions from four lakes: Challa and Naivasha in equatorial East Africa, and Masoko and Malawi in southeastern inter-tropical Africa. The GCMs simulate fairly well the unimodal seasonal cycle of precipitation in the Masoko/Malawi region and the bimodal seasonal cycle characterizing the Challa/Naivasha region, except that in the latter the relative magnitude of the two rainy seasons is less well captured. Model results and lake-based hydroclimate reconstructions display very different temporal patterns over the last millennium. Additionally, there is no common signal among the model time series, at least until 1850. This suggests that simulated hydroclimate fluctuations are mostly driven by internal variability rather than by common external forcing. After that, half of the models used simulate a relatively clear response to forcing, but this response is different between the models. Overall, the link between precipitation and tropical sea surface temperatures (SSTs) over the pre-industrial portion of the last millennium is stronger and more robust for the Challa/Naivasha region than for the Masoko/Malawi region. At the inter-annual time scale, last-millennium Challa/Naivasha precipitation is positively (negatively) correlated with western (eastern) Indian Ocean SST, while the influence of the Pacific Ocean appears weak and unclear. Although most often not significant, the same pattern of correlations between the East African rainfall and the Indian Ocean SST is still visible when using the last-millennium time series smoothed to highlight centennial variability, but only in fixed-forcing simulations. This means that, at the centennial time scale, the effect of (natural) climate forcing can overwhelm internal climate variability in large-scale tele-connections.

scholarly journals Description and Evaluation of the specified-dynamics experiment in the Chemistry-Climate Model Initiative

2020 ◽  
Vol 20 (6) ◽  
pp. 3809-3840 ◽  
Author(s):  
Clara Orbe ◽  
David A. Plummer ◽  
Darryn W. Waugh ◽  
Huang Yang ◽  
Patrick Jöckel ◽  
...  
Keyword(s):  
Seasonal Cycle ◽  
General Circulation ◽  
Large Scale ◽  
Climate Model ◽  
Phase 1 ◽  
General Circulation Models ◽  
Atmospheric Composition ◽  
Cycle Amplitude ◽  
Free Running ◽  
Dynamics Simulations

Abstract. We provide an overview of the REF-C1SD specified-dynamics experiment that was conducted as part of phase 1 of the Chemistry-Climate Model Initiative (CCMI). The REF-C1SD experiment, which consisted of mainly nudged general circulation models (GCMs) constrained with (re)analysis fields, was designed to examine the influence of the large-scale circulation on past trends in atmospheric composition. The REF-C1SD simulations were produced across various model frameworks and are evaluated in terms of how well they represent different measures of the dynamical and transport circulations. In the troposphere there are large (∼40 %) differences in the climatological mean distributions, seasonal cycle amplitude, and trends of the meridional and vertical winds. In the stratosphere there are similarly large (∼50 %) differences in the magnitude, trends and seasonal cycle amplitude of the transformed Eulerian mean circulation and among various chemical and idealized tracers. At the same time, interannual variations in nearly all quantities are very well represented, compared to the underlying reanalyses. We show that the differences in magnitude, trends and seasonal cycle are not related to the use of different reanalysis products; rather, we show they are associated with how the simulations were implemented, by which we refer both to how the large-scale flow was prescribed and to biases in the underlying free-running models. In most cases these differences are shown to be as large or even larger than the differences exhibited by free-running simulations produced using the exact same models, which are also shown to be more dynamically consistent. Overall, our results suggest that care must be taken when using specified-dynamics simulations to examine the influence of large-scale dynamics on composition.

Projected Changes in Mean and Extreme Precipitation in Africa under Global Warming. Part II: East Africa

2011 ◽  
Vol 24 (14) ◽  
pp. 3718-3733 ◽  
Author(s):  
Mxolisi E. Shongwe ◽  
Geert Jan van Oldenborgh ◽  
Bart van den Hurk ◽  
Maarten van Aalst
Keyword(s):  
Indian Ocean ◽  
East Africa ◽  
Extreme Precipitation ◽  
General Circulation ◽  
Tropical Indian Ocean ◽  
General Circulation Models ◽  
Rate Of Change ◽  
Intergovernmental Panel ◽  
Eastern Hemisphere ◽  
Short Rains

Abstract Probable changes in mean and extreme precipitation in East Africa are estimated from general circulation models (GCMs) prepared for the Intergovernmental Panel on Climate Change Fourth Assessment Report (AR4). Bayesian statistics are used to derive the relative weights assigned to each member in the multimodel ensemble. There is substantial evidence in support of a positive shift of the whole rainfall distribution in East Africa during the wet seasons. The models give indications for an increase in mean precipitation rates and intensity of high rainfall events but for less severe droughts. Upward precipitation trends are projected from early this (twenty first) century. As in the observations, a statistically significant link between sea surface temperature gradients in the tropical Indian Ocean and short rains (October–December) in East Africa is simulated in the GCMs. Furthermore, most models project a differential warming of the Indian Ocean during boreal autumn. This is favorable for an increase in the probability of positive Indian Ocean zonal mode events, which have been associated with anomalously strong short rains in East Africa. On top of the general increase in rainfall in the tropics due to thermodynamic effects, a change in the structure of the Eastern Hemisphere Walker circulation is consistent with an increase in East Africa precipitation relative to other regions within the same latitudinal belt. A notable feature of this change is a weakening of the climatological subsidence over eastern Kenya. East Africa is shown to be a region in which a coherent projection of future precipitation change can be made, supported by physical arguments. Although the rate of change is still uncertain, almost all results point to a wetter climate with more intense wet seasons and less severe droughts.

scholarly journals Hierarchy of climate and hydrological uncertainties in transient low flow projections

2015 ◽  
Vol 12 (12) ◽  
pp. 12649-12701 ◽  
Author(s):  
J.-P. Vidal ◽  
B. Hingray ◽  
C. Magand ◽  
E. Sauquet ◽  
A. Ducharne
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Internal Variability ◽  
General Circulation Models ◽  
Low Flow ◽  
Small Scale ◽  
Total Uncertainty ◽  
Low Flows ◽  
The Difference ◽  
Flow Variables

Abstract. This paper proposes a methodology for estimating the transient probability distribution of yearly hydrological variables conditional to an ensemble of projections built from multiple general circulation models (GCMs), multiple statistical downscaling methods (SDMs) and multiple hydrological models (HMs). The methodology is based on the quasi-ergodic analysis of variance (QE-ANOVA) framework that allows quantifying the contributions of the different sources of total uncertainty, by critically taking account of large-scale internal variability stemming from the transient evolution of multiple GCM runs, and of small-scale internal variability derived from multiple realizations of stochastic SDMs. The QE-ANOVA framework was initially developed for long-term climate averages and is here extended jointly to (1) yearly anomalies and (2) low flow variables. It is applied to better understand possible transient futures of both winter and summer low flows for two snow-influenced catchments in the southern French Alps. The analysis takes advantage of a very large dataset of transient hydrological projections that combines in a comprehensive way 11 runs from 4 different GCMs, 3 SDMs with 10 stochastic realizations each, as well as 6 diverse HMs. The change signal is a decrease in yearly low flows of around −20 % in 2065, except for the most elevated catchment in winter where low flows barely decrease. This signal is largely masked by both large- and small-scale internal variability, even in 2065. The time of emergence of the change signal on 30 year low-flow averages is however around 2035, i.e. for time slices starting in 2020. The most striking result is that a large part of the total uncertainty – and a higher one than that due to the GCMs – stems from the difference in HM responses. An analysis of the origin of this substantial divergence in HM responses for both catchments and in both seasons suggests that both evapotranspiration and snowpack components of HMs should be carefully checked for their robustness in a changed climate in order to provide reliable outputs for informing water resource adaptation strategies.

scholarly journals Present and future trends in winds and SST off central East Africa

2021 ◽  
pp. 63-70
Author(s):  
Marisol García-Reyes ◽  
Shigalla B. Mahongo
Keyword(s):  
East Africa ◽  
General Circulation ◽  
General Circulation Models ◽  
Coastal Current ◽  
Future Trends ◽  
East African ◽  
Related Services ◽  
Water Column Stability ◽  
The Past ◽  
Regional Dynamics

The coast of central East Africa (CEA) is a dynamic region in terms of climate, in which fisheries and marine-related services impact a large portion of the population. The main driver of regional dynamics is the seasonal alternation of the Northeast (NE) and Southeast (SE) monsoons. Winds associated with these monsoons modulate the prevalent, remotely-forced East African Coastal Current (EACC). Here, present and future trends in winds and sea surface temperature (SST) of the CEA and adjacent regions are investigated using reanalysis and reconstructed data, and an ensemble of General Circulation Models. It was found that the winds and SST show unidirectional trends, with magnitude and spatial differences between the NE and SE monsoons. Winds show weakening trends during the NE monsoon, in the past and future, of the Somali region; with no significant trends during the SE monsoon. SST shows increasing trends in the entire region in the past and future, with stronger warming during the NE monsoon off Somalia; SST trends are smaller in the CEA. These trends could impact the CEA through increased water-column stability and decreased upwelling due to shifting of the EACC separation from the continent. However, given the coarse resolution of data analyzed, regional modeling is still necessary to understand the impacts on local dynamics and productivity in the CEA.

scholarly journals Brief communication: Drought likelihood for East Africa

2018 ◽  
Vol 18 (2) ◽  
pp. 491-497 ◽  
Author(s):  
Hui Yang ◽  
Chris Huntingford
Keyword(s):  
East Africa ◽  
Bias Correction ◽  
General Circulation ◽  
Climate Models ◽  
Extreme Rainfall ◽  
General Circulation Models ◽  
Medical Assistance ◽  
East African ◽  
Climatological Variability ◽  
Drought Occurrence

Abstract. The East Africa drought in autumn of year 2016 caused malnutrition, illness and death. Close to 16 million people across Somalia, Ethiopia and Kenya needed food, water and medical assistance. Many factors influence drought stress and response. However, inevitably the following question is asked: are elevated greenhouse gas concentrations altering extreme rainfall deficit frequency? We investigate this with general circulation models (GCMs). After GCM bias correction to match the climatological mean of the CHIRPS data-based rainfall product, climate models project small decreases in probability of drought with the same (or worse) severity as 2016 ASO (August to October) East African event. This is by the end of the 21st century compared to the probabilities for present day. However, when further adjusting the climatological variability of GCMs to also match CHIRPS data, by additionally bias-correcting for variance, then the probability of drought occurrence will increase slightly over the same period.

Quantifying chaos in the atmosphere

2000 ◽  
Vol 24 (4) ◽  
pp. 499-514 ◽  
Author(s):  
Richard Washington
Keyword(s):  
Boundary Layer ◽  
Land Surface ◽  
General Circulation ◽  
Large Scale ◽  
Internal Variability ◽  
General Circulation Models ◽  
Model Atmosphere ◽  
Heat Fluxes ◽  
Sea Surface Temperature Anomalies ◽  
The Uk

The atmosphere is known to be forced by a variety of energy sources, including radiation and heat fluxes emanating from the boundary layer associated with sea-surface temperature anomalies and land-surface features. The atmosphere is also subject to internal variability which is essentially unforced and is thought to be a basic characteristic of fluids. Whereas much work has been done in quantifying the links between external forcing of the atmosphere and its long-term response as well as the influence of boundary layer forcing in determining organized, large-scale modes of planetary-scale circulation, less is known about the importance of internal variability or chaos in determining the evolution of weather and climate. General circulation models (GCMs) now provide for this possibility. Multiple evolutions of the climate system may be computed in GCM simulations. Where these simulations are identical except for the conditions by which the model is initialized, the degree of departure in the evolution of climate from one model run to the next corresponds precisely to the degree of internal variability or chaos present in the model atmosphere. A methodology for quantifying this chaotic forcing is considered and is applied to century-long integrations of the UK Meteorological Office model HADAM2A.

scholarly journals Description and Evaluation of the Specified-Dynamics Experiment in the Chemistry-Climate Model Initiative (CCMI)

2019 ◽  
Author(s):  
Clara Orbe ◽  
David A. Plummer ◽  
Darryn W. Waugh ◽  
Huang Yang ◽  
Patrick Jöckel ◽  
...  
Keyword(s):  
Seasonal Cycle ◽  
General Circulation ◽  
Large Scale ◽  
Climate Model ◽  
Phase 1 ◽  
General Circulation Models ◽  
Atmospheric Composition ◽  
Cycle Amplitude ◽  
Free Running ◽  
Dynamics Simulations

Abstract. Here we provide an overview of the REF-C1SD Specified-Dynamics experiment that was conducted as part of Phase 1 of the Chemistry-Climate Model Initiative (CCMI). The REF-C1SD experiment, which consisted of mainly online general circulation models (GCMs) constrained with (re)analysis fields, was designed to examine the influence of the large-scale circulation on past trends in atmospheric composition. The REF-C1SD simulations were produced across various model frameworks and we evaluate how well the simulations represent different measures of the dynamical and transport circulations. In the troposphere there are large (~ 40 %) differences in the climatological mean distributions and seasonal cycle amplitude of the meridional and vertical winds. In the stratosphere there are similarly large (~ 50 %) differences in the magnitude and seasonal cycle amplitude of the Transformed Eulerian Mean circulation and among various chemical and idealized tracers. For nearly all variables these differences are not related to the use of different reanalysis products; rather, we show they are associated with how the simulations were implemented, by which we refer both to how the large-scale flow was prescribed and to biases in the underlying free-running models. Furthermore, in most cases these differences are shown to be as large or even larger than the differences exhibited by free-running simulations produced using the exact same models. Overall, our results suggest that care must be taken when using specified-dynamics simulations to examine the influence of large-scale dynamics on composition.

scholarly journals Hierarchy of climate and hydrological uncertainties in transient low-flow projections

2016 ◽  
Vol 20 (9) ◽  
pp. 3651-3672 ◽  
Author(s):  
Jean-Philippe Vidal ◽  
Benoît Hingray ◽  
Claire Magand ◽  
Eric Sauquet ◽  
Agnès Ducharne
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Large Data ◽  
Internal Variability ◽  
General Circulation Models ◽  
Low Flow ◽  
Small Scale ◽  
Data Set ◽  
Total Uncertainty ◽  
Low Flows

Abstract. This paper proposes a methodology for estimating the transient probability distribution of yearly hydrological variables conditional to an ensemble of projections built from multiple general circulation models (GCMs), multiple statistical downscaling methods (SDMs), and multiple hydrological models (HMs). The methodology is based on the quasi-ergodic analysis of variance (QE-ANOVA) framework that allows quantifying the contributions of the different sources of total uncertainty, by critically taking account of large-scale internal variability stemming from the transient evolution of multiple GCM runs, and of small-scale internal variability derived from multiple realizations of stochastic SDMs. This framework thus allows deriving a hierarchy of climate and hydrological uncertainties, which depends on the time horizon considered. It was initially developed for long-term climate averages and is here extended jointly to (1) yearly anomalies and (2) low-flow variables. It is applied to better understand possible transient futures of both winter and summer low flows for two snow-influenced catchments in the southern French Alps. The analysis takes advantage of a very large data set of transient hydrological projections that combines in a comprehensive way 11 runs from four different GCMs, three SDMs with 10 stochastic realizations each, as well as six diverse HMs. The change signal is a decrease in yearly low flows of around −20  % in 2065, except for the more elevated catchment in winter where low flows barely decrease. This signal is largely masked by both large- and small-scale internal variability, even in 2065. The time of emergence of the change signal is however detected for low-flow averages over 30-year time slices starting as early as 2020. The most striking result is that a large part of the total uncertainty – and a higher one than that due to the GCMs – stems from the difference in HM responses. An analysis of the origin of this substantial divergence in HM responses for both catchments and in both seasons suggests that both evapotranspiration and snowpack components of HMs should be carefully checked for their robustness in a changed climate in order to provide reliable outputs for informing water resource adaptation strategies.

scholarly journals Quantification of Uncertainty in High-Resolution Temperature Scenarios for North America

2012 ◽  
Vol 25 (9) ◽  
pp. 3373-3389 ◽  
Author(s):  
Guilong Li ◽  
Xuebin Zhang ◽  
Francis Zwiers ◽  
Qiuzi H. Wen
Keyword(s):  
High Resolution ◽  
North America ◽  
General Circulation ◽  
Large Scale ◽  
Climate Models ◽  
Internal Variability ◽  
General Circulation Models ◽  
First Century ◽  
Small Scale ◽  
Twenty First Century

A framework for the construction of probabilistic projections of high-resolution monthly temperature over North America using available outputs of opportunity from ensembles of multiple general circulation models (GCMs) and multiple regional climate models (RCMs) is proposed. In this approach, a statistical relationship is first established between RCM output and that from the respective driving GCM and then this relationship is applied to downscale outputs from a larger number of GCM simulations. Those statistically downscaled projections were used to estimate empirical quantiles at high resolution. Uncertainty in the projected temperature was partitioned into four sources including differences in GCMs, internal variability simulated by GCMs, differences in RCMs, and statistical downscaling including internal variability at finer spatial scale. Large spatial variability in projected future temperature changes is found, with increasingly larger changes toward the north in winter temperature and larger changes in the central United States in summer temperature. Under a given emission scenario, downscaling from large scale to small scale is the most important source of uncertainty, though structural errors in GCMs become equally important by the end of the twenty-first century. Different emission scenarios yield different projections of temperature change. This difference increases with time. The difference between the IPCC’s Special Report on Emissions Scenarios (SRES) A2 and B1 in the median values of projected changes in 30-yr mean temperature is small for the coming 30 yr, but can become almost as large as the total variance due to internal variability and modeling errors in both GCM and RCM later in the twenty-first century.

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