Long-range precipitation forecasts are useful when managing water supplies.Oceanicatmospheric oscillations have been shown to influence precipitation.Due to a longer cycle of some of the oscillations,a short instrumental record is a limitation in using them for long-range precipitation forecasts.The influence of oscillations over precipitation is observable within paleoclimate reconstructions;however,there have been no attempts to utilize these reconstructions in precipitation forecasting.A data-driven model,KStar,is used for obtaining long-range precipitation forecasts by extending the period of record through the use of reconstructions of oscillations.KStar is a nearest neighbor algorithm with an entropy-based distance function.Oceanic-atmospheric oscillation reconstructions include the El Nino-Southern Oscillation(ENSO),the Pacific Decadal Oscillation(PDO),the North Atlantic Oscillation(NAO),and the Atlantic Multi-decadal Oscillation(AMO).Precipitation is forecasted for 20 climate divisions in the western United States.A 10-year moving average is applied to aid in the identification of oscillation phases.A lead time approach is used to simulate a one-year forecast,with a 10-fold cross-validation technique to test the models.Reconstructions are used from 1658-1899,while the observed record is used from 1900-2007.The model is evaluated using mean absolute error(MAE),root mean squared error(RMSE),RMSE-observations standard deviation ratio(RSR),Pearson's correlation coefficient(R),NashSutcliffe coefficient of efficiency(NSE),and linear error in probability space(LEPS) skill score(SK).The role of individual and coupled oscillations is evaluated by dropping oscillations in the model.The results indicate 'good' precipitation estimates using the KStar model.This modeling technique is expected to be useful for long-term water resources planning and management.
The analytical expressions for the average intensity,root mean square(RMS)beam width and angular spread of Gaussian Schell-model(GSM)beams propagating under slant atmospheric turbulence are derived,and they are used to study the influence of different propagation paths on the propagation of laser beams in atmospheric turbulence.It is shown that under the same condition,the influence of atmospheric turbulence along a downlink path on the GSM beam propagation is the smallest among the three paths.Therefore,the downlink propagation is more beneficial to the beam propagation through atmospheric turbulence compared with the uplink propagation and horizontal propagation.
Variations in global atmospheric oscillations during the last millennium are simulated using the climate system model FGOALS_gl. The model was driven by reconstructions of both natural forcing (solar variability and volcanic aerosol) and anthropogenic forcing (greenhouse gases and sulfate aerosol). The model results are compared against proxy reconstruction data. The reconstructed North Atlantic Oscillation (NAO) was out of phase with the Pacific Decadal Oscillation (PDO) in the last millennium. During the Medieval Warm Period (MWP), the NAO was strong while the PDO was weak. During the Little Ice Age (LIA), the NAO was weak while the PDO was strong. A La Ni a-like state prevailed in the MWP, while an El Ni o-like state dominated in the LIA. This phenomenon is particularly obvious in the 15th, 17th and 19th centuries. Analysis of the model output indicates that the NAO was generally positive during 1000-1400 AD and negative during 1650-1900 AD. There is a discrepancy between the sim- ulation and reconstruction during 1400-1650 AD. The simulated PDO generally varies in parallel with the reconstruction, which has a negative phase during the MWP and a positive phase during the LIA. The correlation coefficient between the reconstruction and simulation is 0.61, and the correlation is statistically significant at the 1% level. Neither the La Ni a-like state of the MWP nor the El Ni o-like state of the LIA is reproduced in the model. Both the reconstructed and the simulated Antarctic Oscillations had a negative phase in the early period of the last millennium and a positive phase in the late period of the last millennium. The Asian-Pacific Oscillation was generally strong during the WMP and weak during the LIA, and the correlation coefficient between the simulation and reconstruction is 0.50 for the period 1000 -1985 AD. The analysis suggests that the specified external forcings significantly affected the evolution of atmospheric oscillation during the last millennium.
