scholarly journals Uncertainties in the Annual Cycle of Rainfall Characteristics over West Africa in CMIP5 Models

2019 ◽  
Author(s):  
Magatte Sow ◽  
Moussa Diakhaté ◽  
Françoise Guichard ◽  
Diarra Dieng ◽  
Amadou T. Gaye
Keyword(s):  
West Africa ◽  
Annual Cycle ◽  
Late Onset ◽  
Coupled Model ◽  
Daily Rainfall ◽  
Cmip5 Models ◽  
Rainfall Characteristics ◽  
Intercomparison Project ◽  
The Mean ◽  
Annual Scale

This study analyses uncertainties associated with the annual cycle of West African rainfall characteristics in 15 simulations of the Coupled Model Intercomparison Project phase 5 (CMIP5) over the Sahel and Guinean regions. Indices based on daily rainfall such as the frequency and the ntensity of wet days, the consecutive dry days (CDD) and wet days (CWD), the 95th percentile of daily rainfall (R95) and its contribution to the umulative monsoon rainfall (R95PTOT) have been assessed. Over both regions, TRMM, GPCP and CHIRPS observational datasets provide very consistent results on the annual cycle of precipitation but less so on the frequency of wet days. Conversely, higher uncertainties are noted on the intensity of wet days over both study areas, particularly over the Guinean region. Overall, CMIP5 simulations present much higher uncertainties in the representation of the mean precipitation climatology, often provide too early (late) onset dates over the Sahel (the Guinean region) and overestimate rainfall during the early and late monsoon phases. These errors do not compensate at the annual scale nor when considering West Africa as a hole. Results also reveal that over the Guinean region, the difficulty of models to represent the annual structure of the mean precipitation strongly involves biases in the representation of the annual cycle of the frequency of wet days. We found strong uncertainties in the simulation of the CWD and he CDD over both areas. Conversely for R95 and R95PTOT, the ncertainties in CMIP5 models appear somewhat weaker, but the magnitude of R95 is largely underestimated in most models.

scholarly journals Uncertainties in the Annual Cycle of Rainfall Characteristics over West Africa in CMIP5 Models

2019 ◽  
Author(s):  
Magatte Sow ◽  
Moussa Diakhaté ◽  
Françoise Guichard ◽  
Diarra Dieng ◽  
Amadou T. Gaye
Keyword(s):  
West Africa ◽  
Annual Cycle ◽  
Late Onset ◽  
Coupled Model ◽  
Daily Rainfall ◽  
Cmip5 Models ◽  
Rainfall Characteristics ◽  
Intercomparison Project ◽  
The Mean ◽  
Annual Scale

This study analyses uncertainties associated with the annual cycle of West African rainfall characteristics in 15 simulations of the Coupled Model Intercomparison Project phase 5 (CMIP5) over the Sahel and Guinean regions. Indices based on daily rainfall such as the frequency and the ntensity of wet days, the consecutive dry days (CDD) and wet days (CWD), the 95th percentile of daily rainfall (R95) and its contribution to the umulative monsoon rainfall (R95PTOT) have been assessed. Over both regions, TRMM, GPCP and CHIRPS observational datasets provide very consistent results on the annual cycle of precipitation but less so on the frequency of wet days. Conversely, higher uncertainties are noted on the intensity of wet days over both study areas, particularly over the Guinean region. Overall, CMIP5 simulations present much higher uncertainties in the representation of the mean precipitation climatology, often provide too early (late) onset dates over the Sahel (the Guinean region) and overestimate rainfall during the early and late monsoon phases. These errors do not compensate at the annual scale nor when considering West Africa as a hole. Results also reveal that over the Guinean region, the difficulty of models to represent the annual structure of the mean precipitation strongly involves biases in the representation of the annual cycle of the frequency of wet days. We found strong uncertainties in the simulation of the CWD and he CDD over both areas. Conversely for R95p and R95PTOT, the ncertainties in CMIP5 models appear somewhat weaker, but the magnitude f R95 is largely underestimated in most models.

scholarly journals Uncertainties in the Annual Cycle of Rainfall Characteristics over West Africa in CMIP5 Models

Atmosphere ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 216
Author(s):  
Magatte Sow ◽  
Moussa Diakhaté ◽  
Ross D. Dixon ◽  
Françoise Guichard ◽  
Diarra Dieng ◽  
...  
Keyword(s):  
West Africa ◽  
Annual Cycle ◽  
Late Onset ◽  
Daily Rainfall ◽  
Cmip5 Models ◽  
Monthly Precipitation ◽  
Strongly Coupled ◽  
Precipitation Estimates ◽  
Latitudinal Position ◽  
Systematic Biases

We analyse uncertainties associated with the main features of the annual cycle of West African rainfall (amplitude, timing, duration) in 15 CMIP5 simulations over the Sahelian and Guinean regions with satellite daily precipitation estimates. The annual cycle of indices based on daily rainfall such as the frequency and the intensity of wet days, the consecutive dry (CDD) and wet (CWD) days, the 95th percentile of daily rainfall (R95), have been assessed. Over both regions, satellite datasets provide more consistent results on the annual cycle of monthly precipitation than on higher-frequency rainfall indices, especially over the Guinean region. By contrast, CMIP5 simulations display much higher uncertainties in both the mean precipitation climatology and higher-frequency indices. Over both regions, most of them overestimate the frequency of wet days. Over the Guinean region, the difficulty of models to represent the bimodality of the annual cycle of precipitation involves systematic biases in the frequency of wet days. Likewise, we found strong uncertainties in the simulation of the CWD and the CDD over both areas. Finally, models generally provide too early (late) onset dates over the Sahel (the Guinean region) and overestimate rainfall during the early and late monsoon phases. These errors are strongly coupled with errors in the latitudinal position of the ITCZ and do not compensate at the annual scale or when considering West Africa as a whole.

scholarly journals Uncertainties in the Annual Cycle of Rainfall Characteristics Over West Africa in CMIP5 Models

2019 ◽  
Author(s):  
Magatte Sow ◽  
Moussa Diakhaté ◽  
Ross D. Dixon ◽  
Françoise Guichard ◽  
Diarra Dieng ◽  
...  
Keyword(s):  
West Africa ◽  
Annual Cycle ◽  
Late Onset ◽  
Daily Rainfall ◽  
Cmip5 Models ◽  
Monthly Precipitation ◽  
Strongly Coupled ◽  
Precipitation Estimates ◽  
Latitudinal Position ◽  
Systematic Biases

This study analyses uncertainties associated with the main features of the annual cycle of West African rainfall (amplitude, timing, duration) in 15 CMIP5 simulations over the Sahelian and Guinean regions with satellite daily precipitation estimates. The annual cycle of indices based on daily rainfall such as the frequency and the intensity of wet days, the consecutive dry (CDD) and wet days (CWD), the 95th percentile of daily rainfall (R95) have been assessed. Over both regions, satellite datasets provide more consistent results on the annual cycle of monthly precipitation than on higher-frequency rainfall indices, especially over the Guinean region. CMIP5 simulations display much higher uncertainties in both the mean precipitation climatology and higher-frequency indices. Over both regions, most of them overestimate the frequency of wet days. Over the Guinean region, the difficulty of models to represent the bimodality of the annual cycle of precipitation involves systematic biases the frequency of wet days. Likewise, we found strong uncertainties in the simulation of the CWD and the CDD over both areas. Finally, models generally provide too early (late) onset dates over the Sahel (the Guinean region) and overestimate rainfall during the early and late monsoon phases. These errors are strongly coupled errors in the latitudinal position of the ITCZ and do not compensate at the annual scale nor when considering West Africa as a whole. wet days. We found strong uncertainties in the simulation of the CWD and he CDD over both areas. Conversely for R95p and R95PTOT, the ncertainties in CMIP5 models appear somewhat weaker, but the magnitude f R95 is largely underestimated in most models.

scholarly journals DOWNSCALING OF DAILY AVERAGE RAINFALL OF KOTA BHARU KELANTAN, MALAYSIA

2018 ◽  
Vol 30 (1) ◽  
Author(s):  
Muhammad Noor ◽  
Tarmizi Ismail
Keyword(s):  
Coupled Model ◽  
Daily Rainfall ◽  
Circulation Model ◽  
Global Circulation Model ◽  
Global Circulation ◽  
Average Rainfall ◽  
Intercomparison Project ◽  
The Mean ◽  
Grid Points ◽  
Good Relation

Downscaling Global Circulation Model (GCM) output is important in order tounderstand the present climate as well as future climate changes at local scale. In this study,Random Forest (RF) was used to downscale the mean daily rainfall at Kota Bahru meteorologicalstation located in Kelantan Malaysia. The RF model was used to downscale daily rainfall fromGCM of Coupled Model Intercomparison Project Phase 5 (CMIP5), BCC-CSM1.1. The potentialpredictors were selected using stepwise regression at grid points located around the study area.Quantile mapping was used to remove the bias in the prediction. The results showed that the RFmodel was able to establish a good relation between observed and downscaled rainfall. TheQuantile mapping was found to perform well to correct errors in prediction. The statisticalmeasures of performance of downscaling and bias correction approaches show that they are ableto replicate daily observed rainfall with Nash-Schutclif efficiency greater than 0.75 for all themonths. It can be concluded that RF and Quantile mapping are reliable and effective methods fordownscaling rainfall.

scholarly journals An Initial Assessment of Antarctic Sea Ice Extent in the CMIP5 Models

2013 ◽  
Vol 26 (5) ◽  
pp. 1473-1484 ◽  
Author(s):  
John Turner ◽  
Thomas J. Bracegirdle ◽  
Tony Phillips ◽  
Gareth J. Marshall ◽  
J. Scott Hosking
Keyword(s):  
Sea Ice ◽  
Coupled Model ◽  
Initial Assessment ◽  
Cmip5 Models ◽  
Full Time ◽  
Model Intercomparison ◽  
Sea Ice Extent ◽  
Antarctic Sea Ice ◽  
Intercomparison Project ◽  
The Mean

Abstract This paper examines the annual cycle and trends in Antarctic sea ice extent (SIE) for 18 models used in phase 5 of the Coupled Model Intercomparison Project (CMIP5) that were run with historical forcing for the 1850s to 2005. Many of the models have an annual SIE cycle that differs markedly from that observed over the last 30 years. The majority of models have too small of an SIE at the minimum in February, while several of the models have less than two-thirds of the observed SIE at the September maximum. In contrast to the satellite data, which exhibit a slight increase in SIE, the mean SIE of the models over 1979–2005 shows a decrease in each month, with the greatest multimodel mean percentage monthly decline of 13.6% decade−1 in February and the greatest absolute loss of ice of −0.40 × 106 km2 decade−1 in September. The models have very large differences in SIE over 1860–2005. Most of the control runs have statistically significant trends in SIE over their full time span, and all of the models have a negative trend in SIE since the mid-nineteenth century. The negative SIE trends in most of the model runs over 1979–2005 are a continuation of an earlier decline, suggesting that the processes responsible for the observed increase over the last 30 years are not being simulated correctly.

On memory and non-memory parts of surface air temperatures over China: can they be simulated by decadal hindcast experiments in CMIP5?

2021 ◽  
Author(s):  
Feilin Xiong ◽  
Naiming Yuan ◽  
Xiaoyan Ma ◽  
Zhenghui Lu ◽  
Jinhui Gao
Keyword(s):  
Coupled Model ◽  
Cmip5 Models ◽  
Long Term Memory ◽  
Dynamical Models ◽  
Air Temperatures ◽  
New Strategy ◽  
Intercomparison Project ◽  
Open Question ◽  
Annual Scale ◽  
Past Conditions

<p>It has been well recognized that, for most climatic records, their current states are influenced by both past conditions and current dynamical excitations. However, how to properly use this idea to improve the climate predictive skills, is still an open question. In this study, we evaluated the decadal hindcast experiments of 11 models (participating in phase 5 of the Coupled Model Intercomparison Project, CMIP5) in simulating the effects of past conditions (memory part, M(t)) and the current dynamical excitations (non-memory part, ε(t)). Poor skills in simulating the memory part of surface air temperatures (SAT) are found in all the considered models. Over most regions of China, the CMIP5 models significantly overestimated the long-term memory (LTM) of SAT. While in the southwest, the LTM was significantly underestimated. After removing the biased memory part from the simulations using fractional integral statistical model (FISM), the remaining non-memory part, however, was found reasonably simulated in the multi-model means. On annual scale, there were high correlations between the simulated and the observed ε(t) over most regions of the country, and for most cases they had the same sign. These findings indicated that the current errors of dynamical models may be partly due to the unrealistic simulations of the impacts from the past. To improve predictive skills, a new strategy was thus suggested. As FISM is capable of extracting M(t) quantitatively, by combining FISM with dynamical models (which may produce reasonable estimations of ε(t)), improved climate predictions with the effects of past conditions properly considered may become possible.</p>

scholarly journals Southern Ocean Wind Stress in CMIP5 Models: Role of Wind Fluctuations

2020 ◽  
Vol 33 (4) ◽  
pp. 1209-1226 ◽  
Author(s):  
Xia Lin ◽  
Xiaoming Zhai ◽  
Zhaomin Wang ◽  
David R. Munday
Keyword(s):  
Southern Ocean ◽  
Time Scales ◽  
Wind Stress ◽  
Surface Wind ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Coupled Models ◽  
Surface Wind Stress ◽  
Stress Changes ◽  
The Mean

AbstractThe Southern Ocean (SO) surface wind stress is a major atmospheric forcing for driving the Antarctic Circumpolar Current and the global overturning circulation. Here the effects of wind fluctuations at different time scales on SO wind stress in 18 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are investigated. It is found that including wind fluctuations, especially on time scales associated with synoptic storms, in the stress calculation strongly enhances the mean strength, modulates the seasonal cycle, and significantly amplifies the trends of SO wind stress. In 11 out of the 18 CMIP5 models, the SO wind stress has strengthened significantly over the period of 1960–2005. Among them, the strengthening trend of SO wind stress in one CMIP5 model is due to the increase in the intensity of wind fluctuations, while in all the other 10 models the strengthening trend is due to the increasing strength of the mean westerly wind. These discrepancies in SO wind stress trend in CMIP5 models may explain some of the diverging behaviors in the model-simulated SO circulation. Our results suggest that to reduce the uncertainty in SO responses to wind stress changes in the coupled models, both the mean wind and wind fluctuations need to be better simulated.

scholarly journals Simulations of changes to Glaciar Zongo, Bolivia (16° S), over the 21st century using a 3-D full-Stokes model and CMIP5 climate projections

2015 ◽  
Vol 56 (70) ◽  
pp. 89-97 ◽  
Author(s):  
Marion Réveillet ◽  
Antoine Rabatel ◽  
Fabien Gillet-Chaulet ◽  
Alvaro Soruco
Keyword(s):  
Mass Balance ◽  
21St Century ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Climate Projections ◽  
Surface Mass Balance ◽  
Equilibrium Line Altitude ◽  
Surface Mass ◽  
Temperature Changes ◽  
Intercomparison Project

AbstractBolivian glaciers are an essential source of fresh water for the Altiplano, and any changes they may undergo in the near future due to ongoing climate change are of particular concern. Glaciar Zongo, Bolivia, located near the administrative capital La Paz, has been extensively monitored by the GLACIOCLIM observatory in the last two decades. Here we model the glacier dynamics using the 3-D full-Stokes model Elmer/Ice. The model was calibrated and validated over a recent period (1997–2010) using four independent datasets: available observations of surface velocities and surface mass balance were used for calibration, and changes in surface elevation and retreat of the glacier front were used for validation. Over the validation period, model outputs are in good agreement with observations (differences less than a small percentage). The future surface mass balance is assumed to depend on the equilibrium-line altitude (ELA) and temperature changes through the sensitivity of ELA to temperature. The model was then forced for the 21st century using temperature changes projected by nine Coupled Model Intercomparison Project phase 5 (CMIP5) models. Here we give results for three different representative concentration pathways (RCPs). The intermediate scenario RCP6.0 led to 69 ± 7% volume loss by 2100, while the two extreme scenarios, RCP2.6 and RCP8.5, led to 40 ± 7% and 89 ± 4% loss of volume, respectively.

scholarly journals The impact of air–sea coupling and ocean biases on the seasonal cycle of southern West African precipitation

2019 ◽  
Vol 53 (11) ◽  
pp. 7027-7044
Author(s):  
Caroline M. Wainwright ◽  
Linda C. Hirons ◽  
Nicholas P. Klingaman ◽  
Richard P. Allan ◽  
Emily Black ◽  
...  
Keyword(s):  
West Africa ◽  
Atlantic Ocean ◽  
Crop Yields ◽  
Coupled Model ◽  
Dry Season ◽  
Global Ocean ◽  
Cmip5 Models ◽  
Rainfall Regime ◽  
Climate Projections ◽  
The Impact

Abstract The biannual seasonal rainfall regime over the southern part of West Africa is characterised by two wet seasons, separated by the ‘Little Dry Season’ in July–August. Lower rainfall totals during this intervening dry season may be detrimental for crop yields over a region with a dense population that depends on agricultural output. Coupled Model Intercomparison Project Phase 5 (CMIP5) models do not correctly capture this seasonal regime, and instead generate a single wet season, peaking at the observed timing of the Little Dry Season. Hence, the realism of future climate projections over this region is questionable. Here, the representation of the Little Dry Season in coupled model simulations is investigated, to elucidate factors leading to this misrepresentation. The Global Ocean Mixed Layer configuration of the Met Office Unified Model is particularly useful for exploring this misrepresentation, as it enables separating the effects of coupled model ocean biases in different ocean basins while maintaining air–sea coupling. Atlantic Ocean SST biases cause the incorrect seasonal regime over southern West Africa. Upper level descent in August reduces ascent along the coastline, which is associated with the observed reduction in rainfall during the Little Dry Season. When coupled model Atlantic Ocean biases are introduced, ascent over the coastline is deeper and rainfall totals are higher during July–August. Hence, this study indicates detrimental impacts introduced by Atlantic Ocean biases, and highlights an area of model development required for production of meaningful climate change projections over the West Africa region.

scholarly journals Intercomparison of temperature trends in IPCC CMIP5 simulations with observations, reanalyses and CMIP3 models

2013 ◽  
Vol 6 (5) ◽  
pp. 1705-1714 ◽  
Author(s):  
J. Xu ◽  
L. Zhao ◽  
Keyword(s):  
Coupled Model ◽  
Temperature Trend ◽  
The Arctic ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Model Simulations ◽  
Temperature Trends ◽  
Intercomparison Project ◽  
Stratospheric Cooling ◽  
The Tropics

Abstract. On the basis of the fifth Coupled Model Intercomparison Project (CMIP5) and the climate model simulations covering 1979 through 2005, the temperature trends and their uncertainties have been examined to note the similarities or differences compared to the radiosonde observations, reanalyses and the third Coupled Model Intercomparison Project (CMIP3) simulations. The results show noticeable discrepancies for the estimated temperature trends in the four data groups (radiosonde, reanalysis, CMIP3 and CMIP5), although similarities can be observed. Compared to the CMIP3 model simulations, the simulations in some of the CMIP5 models were improved. The CMIP5 models displayed a negative temperature trend in the stratosphere closer to the strong negative trend seen in the observations. However, the positive tropospheric trend in the tropics is overestimated by the CMIP5 models relative to CMIP3 models. While some of the models produce temperature trend patterns more highly correlated with the observed patterns in CMIP5, the other models (such as CCSM4 and IPSL_CM5A-LR) exhibit the reverse tendency. The CMIP5 temperature trend uncertainty was significantly reduced in most areas, especially in the Arctic and Antarctic stratosphere, compared to the CMIP3 simulations. Similar to the CMIP3, the CMIP5 simulations overestimated the tropospheric warming in the tropics and Southern Hemisphere and underestimated the stratospheric cooling. The crossover point where tropospheric warming changes into stratospheric cooling occurred near 100 hPa in the tropics, which is higher than in the radiosonde and reanalysis data. The result is likely related to the overestimation of convective activity over the tropical areas in both the CMIP3 and CMIP5 models. Generally, for the temperature trend estimates associated with the numerical models including the reanalyses and global climate models, the uncertainty in the stratosphere is much larger than that in the troposphere, and the uncertainty in the Antarctic is the largest. In addition, note that the reanalyses show the largest uncertainty in the lower tropical stratosphere, and the CMIP3 simulations show the largest uncertainty in both the south and north polar regions.

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