scholarly journals Role of monsoon interannual variability on the climate model prediction of seasonal rainfall over Indonesia

2019 ◽  
Vol 1307 ◽  
pp. 012005
Author(s):  
Suaydhi
Keyword(s):  
Interannual Variability ◽  
Model Prediction ◽  
Climate Model ◽  
Seasonal Rainfall

scholarly journals Modeling the Hydroclimatology of Kuwait: The Role of Subcloud Evaporation in Semiarid Climates

2008 ◽  
Vol 21 (12) ◽  
pp. 2976-2989 ◽  
Author(s):  
Marc P. Marcella ◽  
Elfatih A. B. Eltahir
Keyword(s):  
Boundary Conditions ◽  
Interannual Variability ◽  
Large Scale ◽  
Climate Model ◽  
Regional Climate ◽  
Critical Role ◽  
Rain Gauge ◽  
Annual Rainfall ◽  
Semiarid Region

Abstract A new subcloud layer evaporation scheme is incorporated into Regional Climate Model, version 3 (RegCM3), to better simulate the rainfall distribution over a semiarid region around Kuwait. The new scheme represents subcloud layer evaporation of convective as well as large-scale rainfall. Model results are compared to observations from rain gauge data networks and satellites. The simulations show significant response to the incorporation of subcloud layer evaporation as a reduction by as much as 20% in annual rainfall occurs over the region. As a result, the new model simulations of annual rainfall are within 15% of observations. In addition, results indicate that the interannual variability of rainfall simulated by RegCM3 is sensitive to the specification of boundary conditions. For example, forcing RegCM3’s lateral boundary conditions with the 40-yr ECMWF Re-Analysis (ERA-40) data, instead of NCEP–NCAR’s Reanalysis Project 2 (NNRP2), reduces interannual variability by over 25%. Moreover, with subcloud layer evaporation incorporated and ERA-40 boundary conditions implemented, the model’s bias and root-mean-square error are significantly reduced. Therefore, the model’s ability to reproduce observed annual rainfall and the year-to-year variation of rainfall is greatly improved. Thus, these results elucidate the critical role of this natural process in simulating the hydroclimatology of semiarid climates. Last, a large discrepancy between observation datasets over the region is observed. It is believed that the inherent characteristics that are used to construct these datasets explain the differences observed in the annual and interannual variability of Kuwait’s rainfall.

Potential predictability of Southwest US rainfall : role of tropical and high-latitude variability

2021 ◽  
pp. 1-45
Keyword(s):  
Time Scale ◽  
Climate Model ◽  
Southern Oscillation ◽  
Seasonal Prediction ◽  
Seasonal Rainfall ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Potential Predictability ◽  
Subseasonal Variability ◽  
The Tropics

Abstract This study explores the potential predictability of Southwest US (SWUS) precipitation for the November-March season in a set of numerical experiments performed with the Whole Atmospheric Community Climate Model. In addition to the prescription of observed sea surface temperature and sea ice concentration, observed variability from the MERRA-2 reanalysis is prescribed in the tropics and/or the Arctic through nudging of wind and temperature. These experiments reveal how a perfect prediction of tropical and/or Arctic variability in the model would impact the prediction of seasonal rainfall over the SWUS, at various time scales. Imposing tropical variability improves the representation of the observed North Pacific atmospheric circulation, and the associated SWUS seasonal precipitation. This is also the case at the subseasonal time scale due to the inclusion of the Madden-Julian Oscillation (MJO) in the model. When additional nudging is applied in the Arctic, the model skill improves even further, suggesting that improving seasonal predictions in high latitudes may also benefit prediction of SWUS precipitation. An interesting finding of our study is that subseasonal variability represents a source of noise (i.e., limited predictability) for the seasonal time scale. This is because when prescribed in the model, subseasonal variability, mostly the MJO, weakens the El Niño Southern Oscillation (ENSO) teleconnection with SWUS precipitation. Such knowledge may benefit S2S and seasonal prediction as it shows that depending on the amount of subseasonal activity in the tropics on a given year, better skill may be achieved in predicting subseasonal rather than seasonal rainfall anomalies, and conversely.

scholarly journals Oceanic Overturning and Heat Transport: The Role of Background Diffusivity

2019 ◽  
Vol 32 (3) ◽  
pp. 701-716 ◽  
Author(s):  
Magnus Hieronymus ◽  
Jonas Nycander ◽  
Johan Nilsson ◽  
Kristofer Döös ◽  
Robert Hallberg
Keyword(s):  
Heat Transport ◽  
Large Scale ◽  
Energy Transport ◽  
Climate Model ◽  
Potential Temperature ◽  
Meridional Heat Transport ◽  
Sea Ice Extent ◽  
Antarctic Sea Ice ◽  
Meridional Overturning

The role of oceanic background diapycnal diffusion for the equilibrium climate state is investigated in the global coupled climate model CM2G. Special emphasis is put on the oceanic meridional overturning and heat transport. Six runs with the model, differing only by their value of the background diffusivity, are run to steady state and the statistically steady integrations are compared. The diffusivity changes have large-scale impacts on many aspects of the climate system. Two examples are the volume-mean potential temperature, which increases by 3.6°C between the least and most diffusive runs, and the Antarctic sea ice extent, which decreases rapidly as the diffusivity increases. The overturning scaling with diffusivity is found to agree rather well with classical theoretical results for the upper but not for the lower cell. An alternative empirical scaling with the mixing energy is found to give good results for both cells. The oceanic meridional heat transport increases strongly with the diffusivity, an increase that can only partly be explained by increases in the meridional overturning. The increasing poleward oceanic heat transport is accompanied by a decrease in its atmospheric counterpart, which keeps the increase in the planetary energy transport small compared to that in the ocean.

scholarly journals Interannual Variability of Tropical Cyclones in the Australian Region: Role of Large-Scale Environment

2008 ◽  
Vol 21 (5) ◽  
pp. 1083-1103 ◽  
Author(s):  
Hamish A. Ramsay ◽  
Lance M. Leslie ◽  
Peter J. Lamb ◽  
Michael B. Richman ◽  
Mark Leplastrier
Keyword(s):  
Interannual Variability ◽  
Large Scale ◽  
Vertical Wind Shear ◽  
Principal Component ◽  
Relative Vorticity ◽  
Vertical Shear ◽  
Scale Parameters ◽  
Australian Region ◽  
Sst Variability

Abstract This study investigates the role of large-scale environmental factors, notably sea surface temperature (SST), low-level relative vorticity, and deep-tropospheric vertical wind shear, in the interannual variability of November–April tropical cyclone (TC) activity in the Australian region. Extensive correlation analyses were carried out between TC frequency and intensity and the aforementioned large-scale parameters, using TC data for 1970–2006 from the official Australian TC dataset. Large correlations were found between the seasonal number of TCs and SST in the Niño-3.4 and Niño-4 regions. These correlations were greatest (−0.73) during August–October, immediately preceding the Australian TC season. The correlations remain almost unchanged for the July–September period and therefore can be viewed as potential seasonal predictors of the forthcoming TC season. In contrast, only weak correlations (<+0.37) were found with the local SST in the region north of Australia where many TCs originate; these were reduced almost to zero when the ENSO component of the SST was removed by partial correlation analysis. The annual frequency of TCs was found to be strongly correlated with 850-hPa relative vorticity and vertical shear of the zonal wind over the main genesis areas of the Australian region. Furthermore, correlations between the Niño SST and these two atmospheric parameters exhibited a strong link between the Australian region and the Niño-3.4 SST. A principal component analysis of the SST dataset revealed two main modes of Pacific Ocean SST variability that match very closely with the basinwide patterns of correlations between SST and TC frequencies. Finally, it is shown that the correlations can be increased markedly (e.g., from −0.73 to −0.80 for the August–October period) by a weighted combination of SST time series from weakly correlated regions.

scholarly journals On the role of trend and variability in the hydroxyl radical (OH) in the global methane budget

2020 ◽  
Vol 20 (21) ◽  
pp. 13011-13022
Author(s):  
Yuanhong Zhao ◽  
Marielle Saunois ◽  
Philippe Bousquet ◽  
Xin Lin ◽  
Antoine Berchet ◽  
...  
Keyword(s):  
Hydroxyl Radical ◽  
El Niño ◽  
Climate Model ◽  
El Nino ◽  
Interannual Variations ◽  
Atmospheric Methane ◽  
Tropical Regions ◽  
Ch4 Emissions ◽  
Methane Budget

Abstract. Decadal trends and interannual variations in the hydroxyl radical (OH), while poorly constrained at present, are critical for understanding the observed evolution of atmospheric methane (CH4). Through analyzing the OH fields simulated by the model ensemble of the Chemistry–Climate Model Initiative (CCMI), we find (1) the negative OH anomalies during the El Niño years mainly corresponding to the enhanced carbon monoxide (CO) emissions from biomass burning and (2) a positive OH trend during 1980–2010 dominated by the elevated primary production and the reduced loss of OH due to decreasing CO after 2000. Both two-box model inversions and variational 4D inversions suggest that ignoring the negative anomaly of OH during the El Niño years leads to a large overestimation of the increase in global CH4 emissions by up to 10 ± 3 Tg yr−1 to match the observed CH4 increase over these years. Not accounting for the increasing OH trends given by the CCMI models leads to an underestimation of the CH4 emission increase by 23 ± 9 Tg yr−1 from 1986 to 2010. The variational-inversion-estimated CH4 emissions show that the tropical regions contribute most to the uncertainties related to OH. This study highlights the significant impact of climate and chemical feedbacks related to OH on the top-down estimates of the global CH4 budget.

scholarly journals Recent changes of relative humidity: regional connection with land and ocean processes

2017 ◽  
Author(s):  
Sergio M. Vicente-Serrano ◽  
Raquel Nieto ◽  
Luis Gimeno ◽  
Cesar Azorin-Molina ◽  
Anita Drumond ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Interannual Variability ◽  
Air Temperature ◽  
Spatial Scales ◽  
Global Scale ◽  
Sea Surface ◽  
Positive Trend ◽  
Source Regions ◽  
Strong Agreement

Abstract. We analyzed changes in surface relative humidity (RH) at the global scale from 1979 to 2014 using both observations and ERA-Interim dataset. We compared the variability and trends of RH with those of land evapotranspiration and ocean evaporation in moisture source areas across a range of selected regions worldwide. The sources of moisture for each particular region were identified by integrating different observational data and model outputs into a lagrangian approach. The aim was to account for the possible role of changes in air temperature over land, in comparison to sea surface temperature (SST), on RH variability. Results demonstrate a strong agreement between the interannual variability of RH and the interannual variability of precipitation and land evapotranspiration in regions with continentally-originated humidity. In contrast, albeit with the dominant positive trend of air temperature/SST ratio in the majority of the analyzed regions, the interannual variability of RH in the target regions did not show any significant correlation with this ratio over the source regions. Also, we did not find any significant association between the interannual variability of oceanic evaporation in the oceanic humidity source regions and RH in the target regions. Our findings stress the need for further investigation of the role of both dynamic and radiative factors in the evolution of RH over continental regions at different spatial scales.

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