Sensitivity of Dynamical Intraseasonal Prediction Skills to Different Initial Conditions

2011 ◽  
Vol 139 (8) ◽  
pp. 2572-2592 ◽  
Author(s):  
Xiouhua Fu ◽  
Bin Wang ◽  
June-Yi Lee ◽  
Wanqiu Wang ◽  
Li Gao
Keyword(s):  
Southeast Asia ◽  
Initial Conditions ◽  
Lower Boundary ◽  
Intraseasonal Oscillation ◽  
Coupled Model ◽  
Boreal Summer ◽  
Small Scale ◽  
Signal Recovery ◽  
Recovery Method ◽  
Rainfall Prediction

AbstractPredictability of intraseasonal oscillation (ISO) relies on both initial conditions and lower boundary conditions (or atmosphere–ocean interaction). The atmospheric reanalysis datasets are commonly used as initial conditions. Here, the biases of three reanalysis datasets [the NCEP reanalysis 1 and 2 (NCEP-R1 and -R2) and the ECMWF Re-Analysis Interim (ERA-Interim)] in describing ISO were briefly revealed and the impacts of these biases as initial conditions on ISO prediction skills were assessed. A signal-recovery method is proposed to improve ISO prediction.Although all three reanalyses underestimate the intensity of the equatorial eastward-propagating ISO, the overall quality of the ERA-Interim is better than the NCEP-R1 and -R2. When these reanalyses are used as initial conditions in the ECHAM4-University of Hawaii hybrid coupled model (UH-HCM), skillful ISO prediction reaches only about 1 week for both the 850-hPa zonal winds (U850) and rainfall over Southeast Asia and the global tropics. An enhanced nudging of the divergence field is shown to significantly improve the initial conditions, resulting in an extension of the skillful rainfall prediction by 2–4 days and U850 prediction by 5–10 days.After recovering the ISO signals in the original reanalyses, the resultant initial conditions contain ISO strength closer to the observed, whereas the rainfall spatial pattern correlation in the ERA-Interim reanalysis drops. The resultant ISO prediction skills, however, are consistently extended for all the NCEP and ERA-Interim reanalyses. Using these signal-recovered reanalyses as initial conditions, the boreal summer ISO prediction skill measured with the Wheeler–Hendon index reaches 14 days. The U850 and rainfall prediction skills, respectively, reach 23 and 18 days over Southeast Asia. It is also found that small-scale synoptic weather disturbances in initial conditions generally increase ISO prediction skills. Both the UH-HCM and NCEP Climate Forecast System (CFS) suffer the prediction barrier over the Maritime Continent.

scholarly journals Impacts of atmospheric and oceanic initial conditions on boreal summer intraseasonal oscillation forecast in the BCC model

2020 ◽  
Vol 142 (1-2) ◽  
pp. 393-406
Author(s):  
Zhongkai Bo ◽  
Xiangwen Liu ◽  
Weizong Gu ◽  
Anning Huang ◽  
Yongjie Fang ◽  
...  
Keyword(s):  
Indian Ocean ◽  
North Pacific ◽  
Western North Pacific ◽  
Initial Conditions ◽  
Intraseasonal Oscillation ◽  
Tropical Indian Ocean ◽  
Boreal Summer ◽  
Model Errors ◽  
Maritime Continent ◽  
Boreal Summer Intraseasonal Oscillation

Abstract In this paper, we evaluate the capability of the Beijing Climate Center Climate System Model (BCC-CSM) in simulating and forecasting the boreal summer intraseasonal oscillation (BSISO), using its simulation and sub-seasonal to seasonal (S2S) hindcast results. Results show that the model can generally simulate the spatial structure of the BSISO, but give relatively weaker strength, shorter period, and faster transition of BSISO phases when compared with the observations. This partially limits the model’s capability in forecasting the BSISO, with a useful skill of only 9 days. Two sets of hindcast experiments with improved atmospheric and atmosphere/ocean initial conditions (referred to as EXP1 and EXP2, respectively) are conducted to improve the BSISO forecast. The BSISO forecast skill is increased by 2 days with the optimization of atmospheric initial conditions only (EXP1), and is further increased by 1 day with the optimization of both atmospheric and oceanic initial conditions (EXP2). These changes lead to a final skill of 12 days, which is comparable to the skills of most models participated in the S2S Prediction Project. In EXP1 and EXP2, the BSISO forecast skills are improved for most initial phases, especially phases 1 and 2, denoting a better description for BSISO propagation from the tropical Indian Ocean to the western North Pacific. However, the skill is considerably low and insensitive to initial conditions for initial phase 6 and target phase 3, corresponding to the BSISO convection’s active-to-break transition over the western North Pacific and BSISO convection’s break-to-active transition over the tropical Indian Ocean and Maritime Continent. This prediction barrier also exists in many forecast models of the S2S Prediction Project. Our hindcast experiments with different initial conditions indicate that the remarkable model errors over the Maritime Continent and subtropical western North Pacific may largely account for the prediction barrier.

Predictability of extreme events in UFS at subseasonal time scale

2021 ◽  
Author(s):  
Christiana Stan
Keyword(s):  
Extreme Events ◽  
Time Scale ◽  
Initial Conditions ◽  
Coupled Model ◽  
Forecast Skill ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Forecast System ◽  
Cold Events ◽  
Second Category

<p>The predictability of extreme events over the continental United States (CONUS) in the Unified Forecast System (UFS) Couple Model is studied at subseasonal time scale. The benchmark runs of UFS (GFSv15), a coupled model consisting of atmospheric component (FV3GFS) with 28 km resolution and ocean (MOM6) and sea ice (CICE5) components with global 0.25° resolution, for the period April 2011–December 2017 have been assessed. The model’s month-long forecasts initiated on the first and fifteenth of each month are used to examine the predictability of extreme events in precipitation and 2m temperature. The atmospheric and ice initial conditions are from CFSR data, and the ocean initial conditions are from 3Dvar CPC. The errors in the week 1–4 predictions and the corresponding spatial correlation between model and observation over CONUS are presented. The differences in the predictability of the extreme events between the boreal summer and winter are discussed. Two categories of extreme events are evaluated: 95<sup>th</sup> and 99<sup>th</sup> percentile, respectively. The forecast skill of extreme events in the 95<sup>th</sup> percentile is higher than the forecast skill of events in the second category. The forecast skill of warm and cold events in the 95<sup>th</sup> percentile shows seasonal dependence and is higher during the boreal winter.</p>

scholarly journals Tropical Atlantic SST Prediction with Coupled Ocean–Atmosphere GCMs

2006 ◽  
Vol 19 (23) ◽  
pp. 6047-6061 ◽  
Author(s):  
Timothy N. Stockdale ◽  
Magdalena A. Balmaseda ◽  
Arthur Vidard
Keyword(s):  
Initial Conditions ◽  
Coupled Model ◽  
Boreal Summer ◽  
Tropical Atlantic ◽  
Equatorial Atlantic ◽  
Seasonal Forecasts ◽  
Coupled Models ◽  
Equatorial Ocean ◽  
Sst Anomalies

Abstract Variations in tropical Atlantic SST are an important factor in seasonal forecasts in the region and beyond. An analysis is given of the capabilities of the latest generation of coupled GCM seasonal forecast systems to predict tropical Atlantic SST anomalies. Skill above that of persistence is demonstrated in both the northern tropical and equatorial Atlantic, but not farther south. The inability of the coupled models to correctly represent the mean seasonal cycle is a major problem in attempts to forecast equatorial SST anomalies in the boreal summer. Even when forced with observed SST, atmosphere models have significant failings in this area. The quality of ocean initial conditions for coupled model forecasts is also a cause for concern, and the adequacy of the near-equatorial ocean observing system is in doubt. A multimodel approach improves forecast skill only modestly, and large errors remain in the southern tropical Atlantic. There is still much scope for improving forecasts of tropical Atlantic SST.

scholarly journals Assessment of the Ability of CMIP6 GCMS to Simulate the Boreal Summer Intraseasonal Oscillation Over Southeast Asia

2021 ◽  
Vol 3 ◽  
Author(s):  
Abayomi A. Abatan ◽  
Matthew Collins ◽  
Mukand S. Babel ◽  
Dibesh Khadka ◽  
Yenushi K. De Silva
Keyword(s):  
Southeast Asia ◽  
Asian Summer Monsoon ◽  
Intraseasonal Variability ◽  
Intraseasonal Oscillation ◽  
Boreal Summer ◽  
Study Region ◽  
Boreal Summer Intraseasonal Oscillation ◽  
Good Ability ◽  
Wide Range ◽  
Static Energy

The boreal summer intraseasonal oscillation (BSISO) plays an important role in the intraseasonal variability of a wide range of weather and climate phenomena across the region modulated by the Asian summer monsoon system. This study evaluates the strengths and weaknesses of 19 Coupled Model Intercomparison Project Phase 6 (CMIP6) models to reproduce the basic characteristics of BSISO. The models' rainfall and largescale climates are evaluated against GPCP and ERA5 reanalysis datasets. All models exhibit intraseasonal variance of 30–60-day bandpass-filtered rainfall and convection anomalies but with diverse magnitude when compared with observations. The CMIP6 models capture the structure of the eastward/northward propagating BSISO at wavenumbers 1 and 2 but struggle with the intensity and location of the convection signal. Nevertheless, the models show a good ability to simulate the power spectrum and coherence squared of the principal components of the combined empirical orthogonal function (CEOF) and can capture the distinction between the CEOF modes and red noise. Also, the result shows that some CMIP6 models can capture the coherent intraseasonal propagating features of the BSISO as indicated by the Hovmöller diagram. The contribution of latent static energy to the relationship between the moist static energy and intraseasonal rainfall over Southeast Asia is also simulated by the selected models, albeit the signals are weak. Taking together, some of the CMIP6 models can represent the summertime climate and intraseasonal variability over the study region, and can also simulate the propagating features of BSISO, but biases still exist.

Eastern Pacific Intraseasonal Variability: A Predictability Perspective

2014 ◽  
Vol 27 (23) ◽  
pp. 8869-8883 ◽  
Author(s):  
J. M. Neena ◽  
Xianan Jiang ◽  
Duane Waliser ◽  
June-Yi Lee ◽  
Bin Wang
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Initial Conditions ◽  
Intraseasonal Variability ◽  
Coupled Model ◽  
Eastern Pacific ◽  
Prediction Skill ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Weather And Climate

Abstract The eastern Pacific (EPAC) warm pool is a region of strong intraseasonal variability (ISV) during boreal summer. While the EPAC ISV is known to have large-scale impacts that shape the weather and climate in the region (e.g., tropical cyclones and local monsoon), simulating the EPAC ISV is still a great challenge for present-day global weather and climate models. In the present study, the predictive skill and predictability of the EPAC ISV are explored in eight coupled model hindcasts from the Intraseasonal Variability Hindcast Experiment (ISVHE). Relative to the prediction skill for the boreal winter Madden–Julian oscillation (MJO) in the ISVHE (~15–25 days), the skill for the EPAC ISV is considerably lower in most models, with an average skill around 10 days. On the other hand, while the MJO exhibits a predictability of 35–45 days, the predictability estimate for the EPAC ISV is 20–30 days. The prediction skill was found to be higher when the hindcasts were initialized from the convective phase of the EPAC ISV as opposed to the subsidence phase. Higher prediction skill was also found to be associated with active MJO initial conditions over the western Pacific (evident in four out of eight models), signaling the importance of exploring the dynamic link between the MJO and the EPAC ISV. The results illustrate the possibility and need for improving dynamical prediction systems to facilitate more accurate and longer-lead predictions of the EPAC ISV and associated weather and short-term climate variability.

scholarly journals Sea Surface Temperature Feedback Extends the Predictability of Tropical Intraseasonal Oscillation

2008 ◽  
Vol 136 (2) ◽  
pp. 577-597 ◽  
Author(s):  
Xiouhua Fu ◽  
Bo Yang ◽  
Qing Bao ◽  
Bin Wang
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Mixed Layer ◽  
Meridional Circulation ◽  
Lower Boundary ◽  
Intraseasonal Oscillation ◽  
Sea Surface ◽  
Boreal Summer ◽  
Mixed Layer Ocean ◽  
Tropical Intraseasonal Oscillation

Abstract The possible impacts of different sea surface temperature (SST) configurations on the predictability of the boreal summer tropical intraseasonal oscillation (TISO) are assessed with a series of ensemble forecasts. The five different lower boundary conditions examined in this study are, respectively, (i) the fully interactive ocean–atmosphere coupling, (ii) “smoothed” SST, which excludes the intraseasonal signal from sea surface forcing, (iii) damped persistent SST, (iv) coupling to a slab mixed-layer ocean, and (v) daily SST from the coupled forecast. The full atmosphere–ocean coupling generates an interactive SST that results in the highest TISO predictability of about 30 days over Southeast Asia. The atmosphere-only model is capable of reaching this predictability if the ensemble mean daily SST forecast by the coupled model is used as the lower boundary condition, which suggests that, in principle, the so-called tier-one and tier-two systems have the same predictability for the boreal summer TISO. The atmosphere-only model driven by either smoothed or damped persistent SSTs, however, has the lowest predictability (∼20 days). The atmospheric model coupled to a slab mixed-layer ocean achieves a predictability of 25 days. The positive SST anomalies in the northern Indo–western Pacific Oceans trigger convective disturbances by moistening and warming up the atmospheric boundary layer. The seasonal mean easterly shear intensifies the anomalous convection by enhancing the surface convergence. An overturning meridional circulation driven by the off-equatorial anomalous convection suppresses the near-equatorial convection and enhances the northward flows, which further intensify the off-equatorial surface convergence and the TISO-related convection. Thus, the boreal summer mean easterly shear and the overturning meridional circulation in the northern Indo–western Pacific sector act as “amplifiers” for the SST feedback to the convection of the TISO.

scholarly journals Sources of Subseasonal Predictability over CONUS during Boreal Summer

2021 ◽  
pp. 1-52
Author(s):  
V. Krishnamurthy ◽  
Jessica Meixner ◽  
Lydia Stefanova ◽  
Jiande Wang ◽  
Denise Worthen ◽  
...  
Keyword(s):  
Time Scale ◽  
Southern Oscillation ◽  
Intraseasonal Oscillation ◽  
Coupled Model ◽  
Warming Trend ◽  
Adaptive Method ◽  
Horizontal Wind ◽  
Boreal Summer ◽  
Forecast Errors ◽  
Modes Of Variability

AbstractThe predictability of the Unified Forecast System (UFS) Coupled Model Prototype 2 developed by the National Centers for Environmental Prediction is assessed for the boreal summer over the continental United States (CONUS). The retrospective forecasts of low-level horizontal wind, precipitation and 2m temperature for 2011–2017 are examined to determine the predictability at subseasonal time scale. Using a data-adaptive method, the leading modes of variability are obtained and identified to be related to El Niño-Southern Oscillation (ENSO), intraseasonal oscillation (ISO) and warming trend. In a new approach, the sources of enhanced predictability are identified by examining the forecast errors and correlations in the weekly averages of the leading modes of variability. During the boreal summer, the ISO followed by the trend in UFS are found to provide better predictability in weeks 1–4 compared to the ENSO mode and the total anomaly. The western CONUS seems to have better predictability on weekly time scale in all the three modes.

scholarly journals Real-Time Digital Signal Recovery for a Low-Pass Transfer Function System with Multiple Complex Poles

2018 ◽  
Author(s):  
Jhinhwan Lee
Keyword(s):  
Transfer Function ◽  
Real Time ◽  
Initial Conditions ◽  
Digital Signal ◽  
Signal Recovery ◽  
Signal Delay ◽  
Recovery Method ◽  
Resonant Amplitude ◽  
Resonance Frequencies ◽  
Low Pass

In order to solve the problems of waveform distortion and signal delay by many physical and electrical systems with linear low-pass transfer characteristics with multiple complex poles, a general digital-signal-processing (DSP)-based method of real-time recovery of the original source waveform from the distorted output waveform is proposed. From the convolution kernel representation of a multiple-pole low-pass transfer function with an arbitrary denominator polynomial with real valued coefficients, it is shown that the source waveform can be accurately recovered in real time using a particular moving average algorithm with real-valued DSP computations only, even though some or all of the poles are complex. The proposed digital signal recovery method is DC-accurate and unaffected by initial conditions, transient signals, and resonant amplitude enhancement. This method can be applied to most sensors and amplifiers operating close to their frequency response limits or around their resonance frequencies to accurately deconvolute the multiple-pole characteristics and to improve the overall performances of data acquisition systems and digital feedback control systems.

scholarly journals The Boreal-Summer Intraseasonal Oscillations Simulated in a Hybrid Coupled Atmosphere–Ocean Model*

2004 ◽  
Vol 132 (11) ◽  
pp. 2628-2649 ◽  
Author(s):  
Xiouhua Fu ◽  
Bin Wang
Keyword(s):  
Three Dimensional ◽  
Intraseasonal Oscillation ◽  
Coupled Model ◽  
Coupled System ◽  
Ocean Model ◽  
Sea Surface ◽  
Boreal Summer ◽  
Surface Cooling ◽  
Internal Dynamics ◽  
Intraseasonal Oscillations

Abstract The boreal-summer intraseasonal oscillation (BSISO) simulated by an atmosphere–ocean coupled model is validated with the long-term observations [Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) rainfall, ECMWF analysis, and Reynolds' SST]. This validation focuses on the three-dimensional water vapor cycle associated with the BSISO and its interaction with underlying sea surface. The advantages of a coupled approach over stand-alone atmospheric approaches on the simulation of the BSISO are revealed through an intercomparison between a coupled run and two atmosphere-only runs. This coupled model produces a BSISO that mimics the one presented in the observations over the Asia– western Pacific region. The similarities with the observations include 1) the coherent spatiotemporal evolutions of rainfall, surface winds, and SST associated with the BSISO; 2) the intensity and period (or speed) of the northward-propagating BSISO; and 3) the tropospheric moistening (or drying) and overturning circulations of the BSISO. However, the simulated tropospheric moisture fluctuations in the extreme phases (both wet and dry) are larger than those in the ECMWF analysis. The simulated sea surface cooling during the wet phase is weaker than the observed cooling. Better representations of the interaction between convection and boundary layer in the GCM and including salinity effects in the ocean model are expected to further improve the simulation of the BSISO. The intercomparison between a coupled run and two atmospheric runs suggests that the air–sea coupled system is the ultimate tool needed to realistically simulate the BSISO. Though the major characteristics of the BSISO are very likely determined by the internal atmospheric dynamics, the correct interaction between the internal dynamics and underlying sea surface can only be sustained by a coupled system. The atmosphere-only approach, when forced with high-frequency (e.g., daily) SST, introduces an erroneous boundary interference on the internal dynamics associated with the BSISO. The implications for the predictability of the BSISO are discussed.

Impact of Subdaily Air–Sea Interaction on Simulating Intraseasonal Oscillations over the Tropical Asian Monsoon Region

2015 ◽  
Vol 28 (3) ◽  
pp. 1057-1073 ◽  
Author(s):  
Wenting Hu ◽  
Anmin Duan ◽  
Guoxiong Wu
Keyword(s):  
General Circulation ◽  
Asian Monsoon ◽  
Intraseasonal Oscillation ◽  
Phase Relationship ◽  
Coupled Model ◽  
Circulation Model ◽  
Boreal Summer ◽  
Lag Phase ◽  
Asian Monsoon Region ◽  
Coupling Frequency

Abstract The off-equatorial boreal summer intraseasonal oscillation (ISO) is closely linked to the onset, active, and break phases of the tropical Asian monsoon, but the accurate simulation of the eastward-propagating low-frequency ISO by current models remains a challenge. In this study, an atmospheric general circulation model (AGCM)–ocean mixed layer coupled model with high (10 min) coupling frequency (DC_10m) shows improved skill in simulating the ISO signal in terms of period, intensity, and propagation direction, compared with the coupled runs with low (1 and 12 h) coupling frequency and a stand-alone AGCM driven by the daily sea surface temperature (SST) fields. In particular, only the DC_10m is able to recreate the observed lead–lag phase relationship between SST (SST tendency) and precipitation at intraseasonal time scales, indicating that the ISO signal is closely linked to the subdaily air–sea interaction. During the ISO life cycle, air–sea interaction reduces the SST underlying the convection via wind–evaporation and cloud–radiation feedbacks, as well as wind-induced oceanic mixing, which in turn restrains convection. However, to the east of the convection, the heat-induced atmospheric Gill-type response leads to downward motion and a reduced surface westerly background flow because of the easterly anomalies. The resultant decreased oceanic mixing, together with the increased shortwave flux, tends to warm the SST and subsequently trigger convection. Therefore, the eastward-propagating ISO may result from an asymmetric east–west change in SST induced mainly by multiscale air–sea interactions.

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