scholarly journals Comparison of CMIP6 and CMIP5 Models in Simulating Mean and Extreme Precipitation over East Africa

2021 ◽  
Author(s):  
Brian AYUGI ◽  
Jiang Zhidong ◽  
Huanhuan Zhu ◽  
Hamida Ngoma ◽  
Hassen Babaousmail ◽  
...  
Keyword(s):  
East Africa ◽  
Extreme Precipitation ◽  
General Circulation ◽  
General Circulation Models ◽  
Cmip5 Models ◽  
Cycle Simulation ◽  
Systematic Biases ◽  
Improved Performance ◽  
The Individual ◽  
Mean Cycle

This study examines the improvement in coupled intercomparison project phase six (CMIP6) models against the predecessor CMIP5 in simulating mean and extreme precipitation over the East Africa region. The study compares the climatology of the precipitation indices simulated by the CMIP models with the CHIRPS dataset using robust statistical techniques for 1981 – 2005. The results display the varying performance of the general circulation models (GCMs) in the simulation of annual and seasonal precipitation climatology over the study domain. CMIP6-MME shows improved performance in the local annual mean cycle simulation with a better representation of two peaks, especially the MAM rainfall relative to its predecessor. Moreover, simulation of extreme indices is well captured in CMIP6 models relative to its predecessor. The CMIP6-MME performed better than the CMIP5-MME with lesser biases in simulating SDII, CDD, and R20mm over East Africa. Remarkably, most CMIP6 models are unable to simulate extremely wet days (R95p). A few CMIP6 models (e.g., NorESM2-MM and CNRM-CM6-1) depicts robust performance in reproducing the observed indices across all analyses. Conversely, OND season shows the overestimation of some indices (i.e., R95p, PRCPTOT), except for SDII, CDD, and R20mm. Consistent with other studies, the mean ensemble performance for both CMIP5/6 shows better performance due to the cancellation of some systematic errors in the individual models. Generally, the CMIP6 depicts improved performance in the simulation of MAM season akin CMIP5 models. However, the new model generation is still marred with uncertainty, thereby depicting substandard performance over the East Africa domain. This calls for further investigation of attribution studies into the sources of persistent systematic biases and a prerequisite for identifying individual models with robust features that can accurately simulate observed patterns for future usage.

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 Simulation of Extreme Precipitation in Four Climate Regions in China by General Circulation Models (GCMs): Performance and Projections

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1509
Author(s):  
Mengru Zhang ◽  
Xiaoli Yang ◽  
Liliang Ren ◽  
Ming Pan ◽  
Shanhu Jiang ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
General Circulation ◽  
Global Climate ◽  
Summer Precipitation ◽  
General Circulation Models ◽  
Cumulative Distribution ◽  
Extreme Precipitation Events ◽  
Increasing Trend ◽  
The Future ◽  
Semi Arid

In the context of global climate change, it is important to monitor abnormal changes in extreme precipitation events that lead to frequent floods. This research used precipitation indices to describe variations in extreme precipitation and analyzed the characteristics of extreme precipitation in four climatic (arid, semi-arid, semi-humid and humid) regions across China. The equidistant cumulative distribution function (EDCDF) method was used to downscale and bias-correct daily precipitation in eight Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs). From 1961 to 2005, the humid region had stronger and longer extreme precipitation compared with the other regions. In the future, the projected extreme precipitation is mainly concentrated in summer, and there will be large areas with substantial changes in maximum consecutive 5-day precipitation (Rx5) and precipitation intensity (SDII). The greatest differences between two scenarios (RCP4.5 and RCP8.5) are in semi-arid and semi-humid areas for summer precipitation anomalies. However, the area of the four regions with an increasing trend of extreme precipitation is larger under the RCP8.5 scenario than that under the RCP4.5 scenario. The increasing trend of extreme precipitation in the future is relatively pronounced, especially in humid areas, implying a potential heightened flood risk in these areas.

scholarly journals Evaluation of Surface Upward Longwave Radiation in the CMIP6 Models with Ground and Satellite Observations

2021 ◽  
Vol 13 (21) ◽  
pp. 4464
Author(s):  
Jiawen Xu ◽  
Xiaotong Zhang ◽  
Chunjie Feng ◽  
Shuyue Yang ◽  
Shikang Guan ◽  
...  
Keyword(s):  
General Circulation ◽  
Bayesian Model Averaging ◽  
Mean Squared Error ◽  
Radiant Energy ◽  
Coupled Model ◽  
Model Averaging ◽  
Longwave Radiation ◽  
Energy System ◽  
General Circulation Models ◽  
The Individual

Surface upward longwave radiation (SULR) is an indicator of thermal conditions over the Earth’s surface. In this study, we validated the simulated SULR from 51 Coupled Model Intercomparison Project (CMIP6) general circulation models (GCMs) through a comparison with ground measurements and satellite-retrieved SULR from the Clouds and the Earth’s Radiant Energy System, Energy Balanced and Filled (CERES EBAF). Moreover, we improved the SULR estimations by a fusion of multiple CMIP6 GCMs using multimodel ensemble (MME) methods. Large variations were found in the monthly mean SULR among the 51 CMIP6 GCMs; the bias and root mean squared error (RMSE) of the individual CMIP6 GCMs at 133 sites ranged from −3 to 24 W m−2 and 22 to 38 W m−2, respectively, which were higher than those found between the CERES EBAF and GCMs. The CMIP6 GCMs did not improve the overestimation of SULR compared to the CMIP5 GCMs. The Bayesian model averaging (BMA) method showed better performance in simulating SULR than the individual GCMs and simple model averaging (SMA) method, with a bias of 0 W m−2 and an RMSE of 19.29 W m−2 for the 133 sites. In terms of the global annual mean SULR, our best estimation for the CMIP6 GCMs using the BMA method was 392 W m−2 during 2000–2014. We found that the SULR varied between 386 and 393 W m−2 from 1850 to 2014, exhibiting an increasing tendency of 0.2 W m−2 per decade (p < 0.05).

scholarly journals Precipitation in the Amazon and its relationship with moisture transport and tropical Pacific and Atlantic SST from the CMIP5 simulation

2015 ◽  
Vol 12 (1) ◽  
pp. 671-704 ◽  
Author(s):  
G. Martins ◽  
C. von Randow ◽  
G. Sampaio ◽  
A. J. Dolman
Keyword(s):  
Moisture Transport ◽  
General Circulation ◽  
Regional Analysis ◽  
Coupled Model ◽  
General Circulation Models ◽  
Moisture Convergence ◽  
Cmip5 Models ◽  
Wet Season ◽  
The Pacific ◽  
Eastern Edge

Abstract. Studies on numerical modeling in Amazonia show that the models fail to capture important aspects of climate variability in this region and it is important to understand the reasons that cause this drawback. Here, we study how the general circulation models of the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulate the inter-relations between regional precipitation, moisture convergence and Sea Surface Temperature (SST) in the adjacent oceans, to assess how flaws in the representation of these processes can translate into biases in simulated rainfall in Amazonia. Using observational data (GPCP, CMAP, ERSST.v3, ERAI and evapotranspiration) and 21 numerical simulations from CMIP5 during the present climate (1979–2005) in June, July and August (JJA) and December, January and February (DJF), respectively, to represent dry and wet season characteristics, we evaluate how the models simulate precipitation, moisture transport and convergence, and pressure velocity (omega) in different regions of Amazonia. Thus, it is possible to identify areas of Amazonia that are more or less influenced by adjacent ocean SSTs. Our results showed that most of the CMIP5 models have poor skill in adequately representing the observed data. The regional analysis of the variables used showed that the underestimation in the dry season (JJA) was twice in relation to rainy season as quantified by the Standard Error of the Mean (SEM). It was found that Atlantic and Pacific SSTs modulate the northern sector of Amazonia during JJA, while in DJF Pacific SST only influences the eastern sector of the region. The analysis of moisture transport in JJA showed that moisture preferentially enters Amazonia via its eastern edge. In DJF this occurs both via its northern and eastern edge. The moisture balance is always positive, which indicates that Amazonia is a source of moisture to the atmosphere. Additionally, our results showed that during DJF the simulations in northeast sector of Amazonia have a strong bias in precipitation and an underestimation of moisture convergence due to the higher influence of biases in the Pacific SST. During JJA, a strong precipitation bias was observed in the southwest sector associated, also with a negative bias of moisture convergence, but with weaker influence of SSTs of adjacent oceans. The poor representation of precipitation-producing systems in Amazonia by the models and the difficulty of adequately representing the variability of SSTs in the Pacific and Atlantic oceans may be responsible for these underestimates in Amazonia.

scholarly journals Skillful Climate Forecasts of the Tropical Indo-Pacific Ocean Using Model-Analogs

2018 ◽  
Vol 31 (14) ◽  
pp. 5437-5459 ◽  
Author(s):  
Hui Ding ◽  
Matthew Newman ◽  
Michael A. Alexander ◽  
Andrew T. Wittenberg
Keyword(s):  
General Circulation ◽  
General Circulation Models ◽  
Coarse Grained ◽  
Seasonal Forecasts ◽  
Multimodel Ensemble ◽  
Initial State ◽  
The North ◽  
Eastern Equatorial Pacific ◽  
Spread Model ◽  
The Individual

Seasonal forecasts made by coupled atmosphere–ocean general circulation models (CGCMs) undergo strong climate drift and initialization shock, driving the model state away from its long-term attractor. Here we explore initializing directly on a model’s own attractor, using an analog approach in which model states close to the observed initial state are drawn from a “library” obtained from prior uninitialized CGCM simulations. The subsequent evolution of those “model-analogs” yields a forecast ensemble, without additional model integration. This technique is applied to four of the eight CGCMs comprising the North American Multimodel Ensemble (NMME) by selecting from prior long control runs those model states whose monthly tropical Indo-Pacific SST and SSH anomalies best resemble the observations at initialization time. Hindcasts are then made for leads of 1–12 months during 1982–2015. Deterministic and probabilistic skill measures of these model-analog hindcast ensembles are comparable to those of the initialized NMME hindcast ensembles, for both the individual models and the multimodel ensemble. In the eastern equatorial Pacific, model-analog hindcast skill exceeds that of the NMME. Despite initializing with a relatively large ensemble spread, model-analogs also reproduce each CGCM’s perfect-model skill, consistent with a coarse-grained view of tropical Indo-Pacific predictability. This study suggests that with little additional effort, sufficiently realistic and long CGCM simulations provide the basis for skillful seasonal forecasts of tropical Indo-Pacific SST anomalies, even without sophisticated data assimilation or additional ensemble forecast integrations. The model-analog method could provide a baseline for forecast skill when developing future models and forecast systems.

Diagnosing Cloud Feedbacks in General Circulation Models

2007 ◽  
Vol 20 (11) ◽  
pp. 2602-2622 ◽  
Author(s):  
Ping Zhu ◽  
James J. Hack ◽  
Jeffrey T. Kiehl
Keyword(s):  
Radiative Forcing ◽  
General Circulation ◽  
Cloud Amount ◽  
General Circulation Models ◽  
Cloud Feedback ◽  
Radiative Fluxes ◽  
Cloud Feedbacks ◽  
Flux Change ◽  
Gfdl Model ◽  
The Individual

Abstract In this study, it is shown that the NCAR and GFDL GCMs exhibit a marked difference in climate sensitivity of clouds and radiative fluxes in response to doubled CO2 and ±2-K SST perturbations. The GFDL model predicted a substantial decrease in cloud amount and an increase in cloud condensate in the warmer climate, but produced a much weaker change in net cloud radiative forcing (CRF) than the NCAR model. Using a multiple linear regression (MLR) method, the full-sky radiative flux change at the top of the atmosphere was successfully decomposed into individual components associated with the clear sky and different types of clouds. The authors specifically examined the cloud feedbacks due to the cloud amount and cloud condensate changes involving low, mid-, and high clouds between 60°S and 60°N. It was found that the NCAR and GFDL models predicted the same sign of individual longwave and shortwave feedbacks resulting from the change in cloud amount and cloud condensate for all three types of clouds (low, mid, and high) despite the different cloud and radiation schemes used in the models. However, since the individual longwave and shortwave feedbacks resulting from the change in cloud amount and cloud condensate generally have the opposite signs, the net cloud feedback is a subtle residual of all. Strong cancellations between individual cloud feedbacks may result in a weak net cloud feedback. This result is consistent with the findings of the previous studies, which used different approaches to diagnose cloud feedbacks. This study indicates that the proposed MLR approach provides an easy way to efficiently expose the similarity and discrepancy of individual cloud feedback processes between GCMs, which are hidden in the total cloud feedback measured by CRF. Most importantly, this method has the potential to be applied to satellite measurements. Thus, it may serve as a reliable and efficient method to investigate cloud feedback mechanisms on short-term scales by comparing simulations with available observations, which may provide a useful way to identify the cause for the wide spread of cloud feedbacks in GCMs.

scholarly journals Extreme Precipitation Spatial Analog: In Search of an Alternative Approach for Future Extreme Precipitation in Urban Hydrological Studies

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 1032 ◽  
Author(s):  
Ariel Wang ◽  
Francina Dominguez ◽  
Arthur Schmidt
Keyword(s):  
Extreme Precipitation ◽  
General Circulation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Regional Climate Models ◽  
General Circulation Models ◽  
Precipitation Frequency ◽  
Spatio Temporal ◽  
Climate Change Assessment

In this paper, extreme precipitation spatial analog is examined as an alternative method to adapt extreme precipitation projections for use in urban hydrological studies. The idea for this method is that real climate records from some cities can serve as “analogs” that behave like potential future precipitation for other locations at small spatio-temporal scales. Extreme precipitation frequency quantiles of a 3.16 km 2 catchment in the Chicago area, computed using simulations from North American Regional Climate Change Assessment Program (NARCCAP) Regional Climate Models (RCMs) with L-moment method, were compared to National Oceanic and Atmospheric Administration (NOAA) Atlas 14 (NA14) quantiles at other cities. Variances in raw NARCCAP historical quantiles from different combinations of RCMs, General Circulation Models (GCMs), and remapping methods are much larger than those in NA14. The performance for NARCCAP quantiles tend to depend more on the RCMs than the GCMs, especially at durations less than 24-h. The uncertainties in bias-corrected future quantiles of NARCCAP are still large compared to those of NA14, and increase with rainfall duration. Results show that future 3-h and 30-day rainfall in Chicago will be similar to historical rainfall from Memphis, TN and Springfield, IL, respectively. This indicates that the spatial analog is potentially useful, but highlights the fact that the analogs may depend on the duration of the rainfall of interest.

scholarly journals Representing the Australian Heat Low in a GCM Using Different Surface and Cloud Schemes

2016 ◽  
Vol 2016 ◽  
pp. 1-16 ◽  
Author(s):  
Matthew M. Allcock ◽  
Duncan Ackerley
Keyword(s):  
General Circulation ◽  
Thermal Inertia ◽  
Coupled Model ◽  
General Circulation Models ◽  
Significant Feature ◽  
Monsoon Circulation ◽  
North West ◽  
Australian Monsoon ◽  
The Individual ◽  
Heat Low

The high insolation during the Southern Hemisphere summer leads to the development of a heat low over north-west Australia, which is a significant feature of the monsoon circulation. It is therefore important that General Circulation Models (GCMs) are able to represent this feature well in order to adequately represent the Australian Monsoon. Given that there are many different configurations of GCMs used globally (such as those used as part of the Coupled Model Intercomparison Project), it is difficult to assess the underlying causes of the differences in circulation between such GCMs. In order to address this problem, the work presented here makes use of three different configurations of the Australian Community Climate and Earth System Simulator (ACCESS). The configurations incorporate changes to the surface parameterization, cloud parameterization, and both together (surface and cloud) while keeping all other parameterized processes unchanged. The work finds that the surface scheme has a larger impact on the heat low than the cloud scheme, which is caused by differences in the soil thermal inertia. This study also finds that the differences in the circulation caused by changing the cloud and surface schemes together are the linear sum of the individual perturbations (i.e., no nonlinear interaction).

scholarly journals How Well Do the CMIP5 Models Simulate the Antarctic Atmospheric Energy Budget?

2015 ◽  
Vol 28 (20) ◽  
pp. 7933-7942 ◽  
Author(s):  
Michael Previdi ◽  
Karen L. Smith ◽  
Lorenzo M. Polvani
Keyword(s):  
Sea Ice ◽  
Energy Budget ◽  
General Circulation ◽  
Climate Model ◽  
General Circulation Models ◽  
Cmip5 Models ◽  
Secondary Importance ◽  
Sea Ice Extent ◽  
Atmospheric Energy ◽  
The Antarctic

Abstract The authors evaluate 23 coupled atmosphere–ocean general circulation models from phase 5 of CMIP (CMIP5) in terms of their ability to simulate the observed climatological mean energy budget of the Antarctic atmosphere. While the models are shown to capture the gross features of the energy budget well [e.g., the observed two-way balance between the top-of-atmosphere (TOA) net radiation and horizontal convergence of atmospheric energy transport], the simulated TOA absorbed shortwave (SW) radiation is too large during austral summer. In the multimodel mean, this excessive absorption reaches approximately 10 W m−2, with even larger biases (up to 25–30 W m−2) in individual models. Previous studies have identified similar climate model biases in the TOA net SW radiation at Southern Hemisphere midlatitudes and have attributed these biases to errors in the simulated cloud cover. Over the Antarctic, though, model cloud errors are of secondary importance, and biases in the simulated TOA net SW flux are instead driven mainly by biases in the clear-sky SW reflection. The latter are likely related in part to the models’ underestimation of the observed annual minimum in Antarctic sea ice extent, thus underscoring the importance of sea ice in the Antarctic energy budget. Finally, substantial differences in the climatological surface energy fluxes between existing observational datasets preclude any meaningful assessment of model skill in simulating these fluxes.

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