Analyses of Global Monthly Precipitation Using Gauge Observations, Satellite Estimates, and Numerical Model Predictions

Xie, Pingping; Arkin, Phillip A.

doi:10.1175/1520-0442(1996)009<0840:aogmpu>2.0.co;2

Cited by 1,246 publications

(784 citation statements)

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“…Model results are verified against ERA-Interim for MSLP and other atmospheric fields, HadISST for SST (Rayner et al, 2003), SOC datasets (Josey et al, 1996) for sea surface heat fluxes and CMAP observations (Xie and Arkin, 1996) for precipitation. Results are tested for statistical significance with a t test (Von Storch and Zwiers, 1999) at 95 % significance level, where normal distribution is involved (namely for mean climatological fields), and with a non-parametric Kolmogorov-Smirnov test (Von Storch and Zwiers, 1999) at 90 % significance level, where cyclone distributions are analyzed.…”

Section: Methodsmentioning

confidence: 94%

Coupled atmosphere ocean climate model simulations in the Mediterranean region: effect of a high-resolution marine model on cyclones and precipitation

Sanna¹,

Lionello²,

Gualdi³

2013

Nat. Hazards Earth Syst. Sci.

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In this study we investigate the importance of an eddy-permitting Mediterranean Sea circulation model on the simulation of atmospheric cyclones and precipitation in a climate model. This is done by analyzing results of two fully coupled GCM (general circulation models) simulations, differing only for the presence/absence of an interactive marine module, at very high-resolution (~ 1/16°), for the simulation of the 3-D circulation of the Mediterranean Sea. Cyclones are tracked by applying an objective Lagrangian algorithm to the MSLP (mean sea level pressure) field. On annual basis, we find a statistically significant difference in vast cyclogenesis regions (northern Adriatic, Sirte Gulf, Aegean Sea and southern Turkey) and in lifetime, giving evidence of the effect of both land–sea contrast and surface heat flux intensity and spatial distribution on cyclone characteristics. Moreover, annual mean convective precipitation changes significantly in the two model climatologies as a consequence of differences in both air–sea interaction strength and frequency of cyclogenesis in the two analyzed simulations

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Section: Methodsmentioning

confidence: 94%

Coupled atmosphere ocean climate model simulations in the Mediterranean region: effect of a high-resolution marine model on cyclones and precipitation

Sanna¹,

Lionello²,

Gualdi³

2013

Nat. Hazards Earth Syst. Sci.

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“…2). Minimum average SST are 24.6 • C, meaning there is a mean seasonal range of 4.1 • C. Highest rainfall occurs between January and March, while lowest rainfall occurs between September and November (Xie and Arkin, 1996). Average rainfall levels reach 300 mm month −1 during the wet season (January to March) and 50 mm month −1 in the dry season.…”

Section: Research Area and Climate Settingmentioning

confidence: 99%

Spatial linkages between coral proxies of terrestrial runoff across a large embayment in Madagascar

et al. 2012

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Abstract. Coral cores provide vital climate reconstructions for site-specific temporal variability in river flow and sediment load. Yet, their ability to record spatial differences across multiple catchments is relatively unknown. Here, we investigate spatial linkages between four coral proxies of terrestrial runoff and their relationships between sites. Coral cores were drilled in and around Antongil Bay, the largest bay in Madagascar, and individually analysed for fifteen years of continuous luminescence (G / B), Ba / Ca, δ 18 O sw and δ 13 C data. Each coral core was drilled close to individual river mouths (≤ 7 km), and proxy data were compared to modelled river discharge and sediment runoff data for the three corresponding catchments. A reasonable agreement between terrestrial runoff proxies with modelled river discharge and sediment yield was observed. Some inconsistencies between proxy and modelled data are likely linked to proxy behaviour, watershed size and local environmental physiochemical parameters. In general, the further a coral resided from its river source, the weaker the proxy relationship was with modelled data and other corals, due to mixing gradients and currents. Nevertheless, we demonstrate that two coral Ba / Ca and luminescence (G / B) records influenced by the same watershed are reproducible. Furthermore, a strong Ba / Ca relationship was observed between two cores from distant watersheds, with baseline averages in agreement with modelled sediment runoff data. As humic acids behave conservatively in the water column, luminescence (G / B) data gave the highest regional correlations between cores, and showed the most consistent relationship with site specific modelled discharge. No statistical relationship was observed between cores in terms of interannual δ 18 O sw and δ 13 C, meaning corals were recording a localised signal at their respective sites, confounded by vital effects. Comparing proxy baseline averages and mean seasonal cycles provided a good overview of the runoff dynamics of the bay system.

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“…Chaves et al (2005) evaluated the performance of the FSU model for South America, in which seasonal means were compared with observations. The model reproduces the rainfall patterns over the continent and neighbouring areas reasonably for the austral summertime and the wintertime when compared with observational rainfall data from Xie and Arkin (1997) and NCEP/NCAR reanalysis. Chaves et al (2005) used the suite of FSU-coupled models in the FSUSSE technique to assess their integrity for climate prediction over South America, specifically their ability to faithfully represent seasonal mean climatological features such as the monsoon circulation.…”

Section: Model Validation For South Americamentioning

confidence: 82%

“…Actual values, rather than anomalies, of precipitation and surface temperature are used in the determination of the FSUSSE. Observed rainfall is from Xie and Arkin (1997) and observed surface temperature is from the NCEP/NCAR reanalysis.…”

Section: Florida State University Synthetic Superensemble (Fsusse) Mementioning

confidence: 99%

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Weather and seasonal climate prediction for South America using a multi-model superensemble

2005

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This work examines the feasibility of weather and seasonal climate predictions for South America using the multi-model synthetic superensemble approach for climate, and the multi-model conventional superensemble approach for numerical weather prediction, both developed at Florida State University (FSU). The effect on seasonal climate forecasts of the number of models used in the synthetic superensemble is investigated. It is shown that the synthetic superensemble approach for climate and the conventional superensemble approach for numerical weather prediction can reduce the errors over South America in seasonal climate prediction and numerical weather prediction.For climate prediction, a suite of 13 models is used. The forecast lead-time is 1 month for the climate forecasts, which consist of precipitation and surface temperature forecasts. The multi-model ensemble is comprised of four versions of the FSU-Coupled Ocean-Atmosphere Model, seven models from the Development of a European Multi-model Ensemble System for Seasonal to Interannual Prediction (DEMETER), a version of the Community Climate Model (CCM3), and a version of the predictive Ocean Atmosphere Model for Australia (POAMA). The results show that conditions over South America are appropriately simulated by the Florida State University Synthetic Superensemble (FSUSSE) in comparison to observations and that the skill of this approach increases with the use of additional models in the ensemble. When compared to observations, the forecasts are generally better than those from both a single climate model and the multi-model ensemble mean, for the variables tested in this study.For numerical weather prediction, the conventional Florida State University Superensemble (FSUSE) is used to predict the mass and motion fields over South America. Predictions of mean sea level pressure, 500 hPa geopotential height, and 850 hPa wind are made with a multi-model superensemble comprised of six global models for the period January, February, and December of 2000. The six global models are from the following forecast centers: FSU, Bureau of Meteorology Research Center (BMRC), Japan Meteorological Agency (JMA), National Centers for Environmental Prediction (NCEP), Naval Research Laboratory (NRL), and Recherche en Prevision Numerique (RPN). Predictions of precipitation are made for the period January, February, and December of 2001 with a 'multi-analysis-multi-model' superensemble where, in addition to the six forecast models just mentioned, five additional versions of the FSU model are used in the ensemble, each with a different initialization (analysis) based on different physical initialization procedures. On the basis of observations, the results show that the FSUSE provides the best forecasts of the mass and motion field variables to forecast day 5, when compared to both the models comprising the ensemble and the multi-model ensemble mean during the wet season of December-February over South America. Individual case studies show that the FSUSE provides excellent ...

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Analyses of Global Monthly Precipitation Using Gauge Observations, Satellite Estimates, and Numerical Model Predictions

Cited by 1,246 publications

References 0 publications

Coupled atmosphere ocean climate model simulations in the Mediterranean region: effect of a high-resolution marine model on cyclones and precipitation

Coupled atmosphere ocean climate model simulations in the Mediterranean region: effect of a high-resolution marine model on cyclones and precipitation

Spatial linkages between coral proxies of terrestrial runoff across a large embayment in Madagascar

Weather and seasonal climate prediction for South America using a multi-model superensemble

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