scholarly journals Impact of the modulated annual cycle and intraseasonal oscillation on daily-to-interannual rainfall variability across monsoonal India

2011 ◽  
Vol 38 (11-12) ◽  
pp. 2409-2435 ◽  
Author(s):  
Vincent Moron ◽  
Andrew W. Robertson ◽  
Michael Ghil
Keyword(s):  
Annual Cycle ◽  
Rainfall Variability ◽  
Intraseasonal Oscillation ◽  
Interannual Rainfall Variability ◽  
Modulated Annual Cycle

scholarly journals Using Empirical Orthogonal Teleconnections to evaluate interannual rainfall variability over China in the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations

2017 ◽  
Author(s):  
Claudia Christine Stephan ◽  
Nicholas P. Klingaman ◽  
Pier Luigi Vidale ◽  
Andrew G. Turner ◽  
Marie-Estelle Demory ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Rainfall Variability ◽  
Reanalysis Data ◽  
Horizontal Resolution ◽  
Unified Model ◽  
Seasonal Precipitation ◽  
Climate Simulations ◽  
Interannual Rainfall Variability ◽  
The Mean

Abstract. Six climate simulations of the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations are evaluated against observations and reanalysis data for their ability to simulate the mean state and year-to-year variability of precipitation over China. To analyze the sensitivity to air-sea coupling and horizontal resolution, atmosphere-only and coupled integrations at atmospheric horizontal resolutions of N96, N216 and N512 (corresponding to ~ 200, 90, and 40 km in the zonal direction at the equator, respectively) are analyzed. The mean and interannual variance of seasonal precipitation are too high in all simulations over China, but improve with finer resolution and coupling. Empirical Orthogonal Teleconnection (EOT) analysis is applied to simulated and observed precipitation to identify spatial patterns of temporally coherent interannual variability in seasonal precipitation. To connect these patterns to large-scale atmospheric and coupled air-sea processes, atmospheric and oceanic fields are regressed onto the corresponding seasonal-mean timeseries. All simulations reproduce the observed leading pattern of interannual rainfall variability in winter, spring and autumn; the leading pattern in summer is present in all but one simulation. However, only in two simulations are the four leading patterns associated with the observed physical mechanisms. Coupled simulations capture more observed patterns of variability and associate more of them with the correct physical mechanism, compared to atmosphere-only simulations at the same resolution. However, finer resolution does not improve the fidelity of these patterns or their associated mechanisms. This shows that evaluating climate models by only geographical distribution of mean precipitation and its interannual variance is insufficient. The EOT analysis adds knowledge about coherent variability and associated mechanisms.

Erratum to: Historical analysis of interannual rainfall variability and trends in southeastern Brazil based on observational and remotely sensed data

2017 ◽  
Vol 50 (5-6) ◽  
pp. 2283-2283
Author(s):  
Isela L. Vásquez P. ◽  
Lígia Maria Nascimento de Araujo ◽  
Luiz Carlos Baldicero Molion ◽  
Mariana de Araujo Abdalad ◽  
Daniel Medeiros Moreira ◽  
...  
Keyword(s):  
Rainfall Variability ◽  
Historical Analysis ◽  
Remotely Sensed ◽  
Southeastern Brazil ◽  
Remotely Sensed Data ◽  
Interannual Rainfall Variability

scholarly journals Likely Ranges of Climate Change in Bolivia

2013 ◽  
Vol 52 (6) ◽  
pp. 1303-1317 ◽  
Author(s):  
Christian Seiler ◽  
Ronald W. A. Hutjes ◽  
Pavel Kabat
Keyword(s):  
Climate Change ◽  
Amazon Basin ◽  
Rainfall Variability ◽  
Annual Rainfall ◽  
Amazon Forest ◽  
Climate Change Scenarios ◽  
Wet Season ◽  
Global Circulation Models ◽  
The Andes ◽  
Interannual Rainfall Variability

AbstractBolivia is facing numerous climate-related threats, ranging from water scarcity due to rapidly retreating glaciers in the Andes to a partial loss of the Amazon forest in the lowlands. To assess what changes in climate may be expected in the future, 35 global circulation models (GCMs) from the third and fifth phases of the Coupled Model Intercomparison Project (CMIP3/5) were analyzed for the Bolivian case. GCMs were validated against observed surface air temperature, precipitation, and incoming shortwave (SW) radiation for the period 1961–90. Weighted ensembles were developed, and climate change projections for five emission scenarios were assessed for 2070–99. GCMs revealed an overall cold, wet, and positive-SW-radiation bias and showed no substantial improvement from the CMIP3 to the CMIP5 ensemble for the Bolivian case. Models projected an increase in temperature (2.5°–5.9°C) and SW radiation (1%–5%), with seasonal and regional differences. In the lowlands, changes in annual rainfall remained uncertain for CMIP3 whereas CMIP5 GCMs were more inclined to project decreases (−9%). This pattern also applied to most of the Amazon basin, suggesting a higher risk of partial biomass loss for the CMIP5 ensemble. Both ensembles agreed on less rainfall (−19%) during drier months (June–August and September–November), with significant changes in interannual rainfall variability, but disagreed on changes during wetter months (January–March). In the Andes, CMIP3 GCMs tended toward less rainfall (−9%) whereas CMIP5 tended toward more (+20%) rainfall during parts of the wet season. The findings presented here may provide inputs for studies of climate change impact that assess how resilient human and natural systems are under different climate change scenarios.

scholarly journals Orbital precession modulates interannual rainfall variability, as recorded in an Early Pleistocene speleothem

Geology ◽  
2018 ◽  
Vol 46 (8) ◽  
pp. 731-734 ◽  
Author(s):  
Philip J. Hopley ◽  
Graham P. Weedon ◽  
Chris M. Brierley ◽  
Christopher Thrasivoulou ◽  
Andy I.R. Herries ◽  
...  
Keyword(s):  
South Africa ◽  
Interannual Variability ◽  
Climate Model ◽  
Rainfall Variability ◽  
Early Pleistocene ◽  
Stone Tool ◽  
Climate Projections ◽  
African Rainfall ◽  
Interannual Rainfall Variability ◽  
Instrumental Records

Abstract Interannual variability of African rainfall impacts local and global communities, but its past behavior and response in future climate projections are poorly understood. This is primarily due to short instrumental records and a lack of long high-resolution palaeoclimate proxy records. Here we present an annually resolved 91,000 year Early Pleistocene record of hydroclimate from the early hominin-bearing Makapansgat Valley, South Africa. Changes in speleothem annual band thickness are dominated by precession over four consecutive orbital cycles with strong millennial-scale periodicity. The frequency of interannual variability (2.0–6.5 yr oscillations) does not change systematically, yet its amplitude is modulated by the orbital forcing. These long-term characteristics of interannual variability are reproduced with transient climate model simulations of water balance for South Africa from the Late Pleistocene to Recent. Based on these results, we suggest that the frequency of interannual variations in southern African rainfall is likely to be stable under anthropogenic warming, but that the size of year-to-year variations may increase. We see an orbitally forced increase in the amplitude of interannual climate variability between 1.8 Ma and 1.7 Ma coincident with the first evidence for the Acheulean stone tool technology.

The representation of the boreal summer intraseasonal oscillation in a global convection-permitting simulation

2021 ◽  
Author(s):  
Peter Willetts ◽  
Jennifer Fletcher ◽  
John Marsham
Keyword(s):  
Time Series ◽  
Spatial Scales ◽  
Rainfall Variability ◽  
Intraseasonal Oscillation ◽  
Equatorial Indian Ocean ◽  
Principal Component ◽  
Boreal Summer ◽  
Boreal Summer Intraseasonal Oscillation ◽  
Spatial And Temporal Scales ◽  
Major Mode

<p>The Boreal Summer Intraseasonal Oscillation (BSISO) is a major mode of intraseasonal variability in the Indian summer monsoon. The characteristic pattern includes northward/north-eastward propagating anomalies of convection and circulation over the Indian longitudes, and concurrent eastward propagating anomalies that move through the tropics from the equatorial Indian ocean. In the Indian monsoon region, the BSISO interacts with other processes to affect the rainfall variability on a range of spatial and temporal scales. Convection-permitting simulations are known to improve the representation of some of these smaller-scale processes, but until recently, it has not been feasible to use convection-permitting simulations to model the entire BSISO because of the temporal and spatial scales on which it occurs. Here we assess how well a global multi-year convection-permitting simulation with a coarse grid-spacing of ~10km at the equator models the BSISO. Using Empirical Orthogonal Function (EOF) analysis, we show that overall, the convection-permitting simulation does not give a substantially better representation of the BSISO, when compared with a simulation which parametrises convection. In the observations, the first two EOF eigenvectors and their Principal Component (PC) time series describe the BSISO. The characteristic northwest-to-southeast slope of the observed EOF 1 and 2 patterns is not captured in the parametrised simulation but is better captured in the convection-permitting simulation. However, the convection-permitting simulation does not capture the observed relationship between the PC1 and PC2 time series that describe the strength and phase of the BSISO. The observed pattern is of a fairly constant phase difference between the PC1 and PC2 time series, but in the convection-permitting simulation, there are periods of both negative and positive phase differences. Our results demonstrate that the BSISO is very sensitive to the representation of convection and future higher resolution runs will provide useful routes for understanding scale interactions in the BSISO.</p>

scholarly journals Improved Global Rainfall Retrieval Using the Special Sensor Microwave Imager (SSM/I)

2010 ◽  
Vol 49 (5) ◽  
pp. 1032-1043 ◽  
Author(s):  
Daniel Vila ◽  
Ralph Ferraro ◽  
Hilawe Semunegus
Keyword(s):  
Rainfall Variability ◽  
Substantial Reduction ◽  
Global Precipitation Climatology Project ◽  
Global Scale ◽  
Monthly Rainfall ◽  
Daily Data ◽  
Interannual Rainfall Variability ◽  
Microwave Imager ◽  
Global Precipitation ◽  
Rainfall Estimates

Abstract Global monthly rainfall estimates have been produced from more than 20 years of measurements from the Defense Meteorological Satellite Program series of Special Sensor Microwave Imager (SSM/I). This is the longest passive microwave dataset available to analyze the seasonal, annual, and interannual rainfall variability on a global scale. The primary algorithm used in this study is an 85-GHz scattering-based algorithm over land, while a combined 85-GHz scattering and 19/37-GHz emission is used over ocean. The land portion of this algorithm is one of the components of the blended Global Precipitation Climatology Project rainfall climatology. Because previous SSM/I processing was performed in real time, only a basic quality control (QC) procedure had been employed to avoid unrealistic values in the input data. A more sophisticated, statistical-based QC procedure on the daily data grids (antenna temperature) was developed to remove unrealistic values not detected in the original database and was employed to reprocess the rainfall product using the current version of the algorithm for the period 1992–2007. Discrepancies associated with the SSM/I-derived monthly rainfall products are characterized through comparisons with various gauge-based and other satellite-derived rainfall estimates. A substantial reduction in biases was observed as a result of this QC scheme. This will yield vastly improved global rainfall datasets.

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