Relationships between California rainfall variability and large-scale climate drivers

2014 ◽  
Vol 34 (13) ◽  
pp. 3626-3640 ◽  
Author(s):  
Alexandre O. Fierro
Keyword(s):  
Large Scale ◽  
Rainfall Variability

scholarly journals Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in the EC-Earth global climate model

2017 ◽  
Vol 10 (3) ◽  
pp. 1383-1402 ◽  
Author(s):  
Paolo Davini ◽  
Jost von Hardenberg ◽  
Susanna Corti ◽  
Hannah M. Christensen ◽  
Stephan Juricke ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Rainfall Variability ◽  
Global Climate Model ◽  
Small Scale ◽  
Low Resolution ◽  
The Impact ◽  
Stochastic Physics

Abstract. The Climate SPHINX (Stochastic Physics HIgh resolutioN eXperiments) project is a comprehensive set of ensemble simulations aimed at evaluating the sensitivity of present and future climate to model resolution and stochastic parameterisation. The EC-Earth Earth system model is used to explore the impact of stochastic physics in a large ensemble of 30-year climate integrations at five different atmospheric horizontal resolutions (from 125 up to 16 km). The project includes more than 120 simulations in both a historical scenario (1979–2008) and a climate change projection (2039–2068), together with coupled transient runs (1850–2100). A total of 20.4 million core hours have been used, made available from a single year grant from PRACE (the Partnership for Advanced Computing in Europe), and close to 1.5 PB of output data have been produced on SuperMUC IBM Petascale System at the Leibniz Supercomputing Centre (LRZ) in Garching, Germany. About 140 TB of post-processed data are stored on the CINECA supercomputing centre archives and are freely accessible to the community thanks to an EUDAT data pilot project. This paper presents the technical and scientific set-up of the experiments, including the details on the forcing used for the simulations performed, defining the SPHINX v1.0 protocol. In addition, an overview of preliminary results is given. An improvement in the simulation of Euro-Atlantic atmospheric blocking following resolution increase is observed. It is also shown that including stochastic parameterisation in the low-resolution runs helps to improve some aspects of the tropical climate – specifically the Madden–Julian Oscillation and the tropical rainfall variability. These findings show the importance of representing the impact of small-scale processes on the large-scale climate variability either explicitly (with high-resolution simulations) or stochastically (in low-resolution simulations).

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.

scholarly journals Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in climate simulations

2016 ◽  
Author(s):  
Paolo Davini ◽  
Jost von Hardenberg ◽  
Susanna Corti ◽  
Hannah M. Christensen ◽  
Stephan Juricke ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Rainfall Variability ◽  
Pilot Project ◽  
Small Scale ◽  
Low Resolution ◽  
Climate Simulations ◽  
Advanced Computing ◽  
The Impact ◽  
Stochastic Physics

Abstract. The Climate SPHINX (Stochastic Physics HIgh resolutioN eXperiments) project is a comprehensive set of ensemble simulations aimed at evaluating the sensitivity of present and future climate to model resolution and stochastic parameterisation. The EC-Earth Earth-System Model is used to explore the impact of stochastic physics in a large ensemble of 30-year climate integrations at five different atmospheric horizontal resolutions (from 125 km up to 16 km). The project includes more than 120 simulations in both a historical scenario (1979–2008) and a climate change projection (2039–2068), together with coupled transient runs (1850–2100). A total of 20.4 million core hours have been used, made available from a single year grant from PRACE (the Partnership for Advanced Computing in Europe), and close to 1.5 PBytes of output data have been produced on SuperMUC IBM Petascale System at the Leibniz Supercomputing Center (LRZ) in Garching, Germany. About 140 TBytes of post-processed data are stored on the CINECA supercomputing center archives and are freely accessible to the community thanks to an EUDAT Data Pilot project. This paper presents the technical and scientific setup of the experiments, including the details on the forcing used for the simulations performed, defining the SPHINX v1.0 protocol. In addition, an overview of preliminary results is given: an improvement in the simulation of Euro-Atlantic atmospheric blocking following resolution increases is observed. It is also shown that including stochastic parameterisation in the low resolution runs helps to improve some aspects of the tropical climate – specifically the Madden-Julian Oscillation and the tropical rainfall variability. These findings show the importance of representing the impact of small scale processes on the large scale climate variability either explicitly (with high resolution simulations) or stochastically (in low resolution simulations).

Including climatic variability in stochastic rainfall for flood catastrophe modelling – The effect of ENSO and SOI in China

2020 ◽  
Author(s):  
Jose Luis Salinas ◽  
Rebecca Smith ◽  
Shuangcai Li ◽  
Ludovico Nicotina ◽  
Arno Hilberts
Keyword(s):  
Tropical Cyclone ◽  
Large Scale ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Climatic Variability ◽  
Extreme Rainfall ◽  
Extreme Rainfall Events ◽  
Natural Catastrophes ◽  
Socio Economic Impact ◽  
Catastrophe Modelling

<p>Damages from flooding in China account on average for 60-70% of the total Annual Losses derived from natural catastrophes. The extreme rainfall events responsible for these inundations can be broadly categorised in two well differentiated mechanisms: Tropical Cyclone (TC) induced, and non Tropical Cyclone induced (nonTC) precipitation. Between 2001 and 2015, inland nonTC rainfall flood events occurred roughly with double the frequency as TC events. While TC events can be highly destructive for coastal locations, over the entire China territory nonTC flooding accounted for more than half of the total economic flood loss for events with significant socio-economic impact, highlighting the importance of the nonTC flooding mechanism on the regional and national scale.</p><p>Large-scale modes of climate variability modulate in different ways TC and nonTC induced precipitation, both in the frequency and the magnitude of the events. In a stochastic rainfall generation framework, it becomes therefore useful to model these two mechanisms separately and include their differentiated long-term climatic influences in order to fully reproduce the overall observed rainfall variability. This work presents results on the effect of ENSO and Southern Oscillation Index (SOI) values on seasonal rainfall in China, and how to include this climatic variability in stochastic rainfall for flood catastrophe modelling.</p>

Regional Impacts of Irrigation in Mexico and the Southwestern United States on Hydrometeorological Fields in the North American Monsoon Region

2016 ◽  
Vol 17 (12) ◽  
pp. 2981-2995 ◽  
Author(s):  
Alex Mahalov ◽  
Jialun Li ◽  
Peter Hyde
Keyword(s):  
North American ◽  
Land Surface ◽  
Large Scale ◽  
Rainfall Variability ◽  
Convective Available Potential Energy ◽  
North American Monsoon ◽  
Western Slope ◽  
Surface Model ◽  
Southern Mexico ◽  
The Impact

Abstract In this study, the impacts of Mexican and southwestern U.S. agricultural and urban irrigation on North American monsoon (NAM) rainfall and other hydrometeorological fields are investigated using the Weather Research and Forecasting (WRF) Model by implementing an irrigation scheme into the WRF–land surface model. Taking the 2000–12 monsoon seasons as examples, multiple WRF simulations with irrigation are conducted by designing different crops’ maximum allowable water depletions (SWm). In comparison with gridded rainfall observations in urban and rural area, the WRF simulations with/without irrigation generally capture the observations very well, but with underestimation along the western slope of the Sierra Madre Occidental (SMO) and overestimation over southern Mexico. The simulations of WRF with irrigation are slightly improved over those without irrigation, compared with rainfall and sounding observations. Sensitivity studies reveal that the impact of irrigation on rainfall varies with location and NAM rainfall variability. Irrigation increases rainfall in eastern Arizona–western New Mexico and in northwestern Mexico because of the irrigation-induced increases of convective available potential energy (CAPE) and precipitable water. Overall, irrigation decreases rainfall in western Arizona, along the western slope of the SMO, and in central Mexico because of irrigation-induced increases of convective inhibition (CIN), decreases of CAPE, and/or large-scale water vapor divergence.

scholarly journals Tropical Atlantic Variability Modes (1979–2002). Part I: Time-Evolving SST Modes Related to West African Rainfall

2008 ◽  
Vol 21 (24) ◽  
pp. 6457-6475 ◽  
Author(s):  
Irene Polo ◽  
Belén Rodríguez-Fonseca ◽  
Teresa Losada ◽  
Javier García-Serrano
Keyword(s):  
Large Scale ◽  
Monsoon Season ◽  
Rainfall Variability ◽  
Principal Component ◽  
West African ◽  
Tropical Atlantic ◽  
Kelvin Wave ◽  
Sst Variability ◽  
The Mediterranean ◽  
Sst Anomalies

Abstract This work presents a description of the 1979–2002 tropical Atlantic (TA) SST variability modes coupled to the anomalous West African (WA) rainfall during the monsoon season. The time-evolving SST patterns, with an impact on WA rainfall variability, are analyzed using a new methodology based on maximum covariance analysis. The enhanced Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) dataset, which includes measures over the ocean, gives a complete picture of the interannual WA rainfall patterns for the Sahel dry period. The leading TA SST pattern, related to the Atlantic El Niño, is coupled to anomalous precipitation over the coast of the Gulf of Guinea, which corresponds to the second WA rainfall principal component. The thermodynamics and dynamics involved in the generation, development, and damping of this mode are studied and compared with previous works. The SST mode starts at the Angola/Benguela region and is caused by alongshore wind anomalies. It then propagates westward via Rossby waves and damps because of latent heat flux anomalies and Kelvin wave eastward propagation from an off-equatorial forcing. The second SST mode includes the Mediterranean and the Atlantic Ocean, showing how the Mediterranean SST anomalies are those that are directly associated with the Sahelian rainfall. The global signature of the TA SST patterns is analyzed, adding new insights about the Pacific–Atlantic link in relation to WA rainfall during this period. Also, this global picture suggests that the Mediterranean SST anomalies are a fingerprint of large-scale forcing. This work updates the results given by other authors, whose studies are based on different datasets dating back to the 1950s, including both the wet and the dry Sahel periods.

scholarly journals Early Portuguese meteorological records (18th century)

2011 ◽  
Vol 7 (5) ◽  
pp. 3399-3448
Author(s):  
M. J. Alcoforado ◽  
J. M. Vaquero ◽  
R. M. Trigo ◽  
J. P. Taborda
Keyword(s):  
Rio De Janeiro ◽  
Large Scale ◽  
18Th Century ◽  
Rainfall Variability ◽  
Nao Index ◽  
Late 18Th Century ◽  
Southern Portugal ◽  
Haze Days ◽  
Measurement Period

Abstract. Natural proxies, documentary evidence and instrumental data are the main sources used to reconstruct past climates. In this paper, we present the 18th century meteorologists (either Portuguese or foreigners), who made the first observations at several sites in Continental Portugal, Madeira Island and Rio de Janeiro (Brazil), from 1749 until 1802. Information is given concerning observation site, variables observed, measurement period, methodologies and sources (both manuscript and printed). Some examples from the data usefulness are given: rainfall variability in Madeira (1749–1753) and in Continental Portugal (1781–1793) was reconstructed, allowing to extend towards the late 18th century the well known negative correlation between the NAO index and seasonal rainfall. Furthermore, previously unpublished data for 1783–1784 has allowed analysing the consequences of the Laki eruption in Portugal: foggy and haze days are referred to in summer 1783, but unlike the hot summer observed in Northern and Central Europe, temperatures in Portugal were lower than average. Additionally, observations from Rio de Janeiro in Brazil show that the Laki consequences may well have spread to sectors of the Southern Hemisphere. Although the series are short, the data will be used for climate reconstruction studies focused in Southern Portugal and are also useful to improve the quality of large scale reconstruction datasets.

scholarly journals Detecting the impact of land cover change on observed rainfall

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7523 ◽  
Author(s):  
Chun Xia Liang ◽  
Floris F. van Ogtrop ◽  
R. Willem Vervoort
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Large Scale ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Tree Cover ◽  
Trend Test ◽  
South Central ◽  
The Impact ◽  
Step Trend

Analysis of observational data to pinpoint impact of land cover change on local rainfall is difficult due to multiple environmental factors that cannot be strictly controlled. In this study we use a statistical approach to identify the relationship between removal of tree cover and rainfall with data from best available sources for two large areas in Australia. Gridded rainfall data between 1979 and 2015 was used for the areas, while large scale (exogenous) effects were represented by mean rainfall across a much larger area and climatic indicators, such as Southern Oscillation Index and Indian Ocean Dipole. Both generalised additive modelling and step trend tests were used for the analysis. For a region in south central Queensland, the reported change in tree clearing between 2002–2005 did not result in strong statistically significant precipitation changes. On the other hand, results from a bushfire affected region on the border of New South Wales and Victoria suggest significant changes in the rainfall due to changes in tree cover. This indicates the method works better when an abrupt change in the data can be clearly identified. The results from the step trend test also mainly identified a positive relationship between the tree cover and the rainfall at p < 0.1 at the NSW/Victoria region. High rainfall variability and possible regrowth could have impacted the results in the Queensland region.

scholarly journals Intraseasonal summer rainfall variability over China in the MetUM GA6 and GC2 configurations

2018 ◽  
Vol 11 (8) ◽  
pp. 3215-3233
Author(s):  
Claudia Christine Stephan ◽  
Nicholas P. Klingaman ◽  
Pier Luigi Vidale ◽  
Andrew G. Turner ◽  
Marie-Estelle Demory ◽  
...  
Keyword(s):  
Large Scale ◽  
Southern China ◽  
Yangtze River Basin ◽  
Rainfall Variability ◽  
Intraseasonal Variability ◽  
Coastal Region ◽  
Late Summer ◽  
Horizontal Resolution ◽  
Configuration Model ◽  
The Impact

Abstract. The simulation of intraseasonal precipitation variability over China in extended summer (May–October) is evaluated based on six climate simulations of the Met Office Unified Model. Two simulations use the Global Atmosphere 6.0 (GA6) and four the Global Coupled 2.0 (GC2) configuration. Model biases are large such that mean precipitation and intraseasonal variability reach twice their observed values, particularly in southern China. To test the impact of air–sea coupling and horizontal resolution, GA6 and GC2 at horizontal resolutions corresponding to ∼25, 60, and 135 km at 50∘ N are analyzed. Increasing the horizontal resolution and adding air–sea coupling have little effect on these biases. Pre-monsoon rainfall in the Yangtze River basin is too strong in all simulations. Simulated rainfall amounts in June are too high along the southern coast and persist in the coastal region through July, with only a weak northward progression. The observed northward propagation of the Meiyu–Baiu–Changma rainband from spring to late summer is poor in all GA6 and GC2 simulations. To assess how well the MetUM simulates spatial patterns of temporally coherent precipitation, empirical orthogonal teleconnection (EOT) analysis is applied to pentad-mean precipitation. Patterns are connected to large-scale processes by regressing atmospheric fields onto the EOT pentad time series. Most observed patterns of intraseasonal rainfall variability are found in all simulations, including the associated observed mechanisms. This suggests that GA6 and GC2 may provide useful predictions of summer intraseasonal variability despite their substantial biases in mean precipitation and overall intraseasonal variance.

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