scholarly journals Statistics of locally coupled ocean and atmosphere intraseasonal anomalies in Reanalysis and AMIP data

2003 ◽  
Vol 10 (3) ◽  
pp. 245-251 ◽  
Author(s):  
M. Peña ◽  
E. Kalnay ◽  
M. Cai
Keyword(s):  
Phase Relationship ◽  
Reanalysis Data ◽  
Sea Surface ◽  
Strong Reduction ◽  
Atmospheric Research ◽  
Ocean Atmosphere ◽  
Using Data ◽  
The One ◽  
Environmental Prediction ◽  
The Tropics

Abstract. We apply a simple dynamical rule to determine the dominant forcing direction in locally coupled ocean-atmosphere anomalies in the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/ NCAR) reanalysis data. The rule takes into account the phase relationship between the low-level vorticity anomalies and the Sea Surface Temperature (SST) anomalies. Analysis of the frequency of persistent coupled anomalies for five-day average data shows that, in general, the ocean tends to force the atmosphere in the tropics while the atmosphere tends to force the ocean in the extratropics. The results agree well with those obtained independently using lagged correlations between atmospheric and oceanic variables, suggesting that the dynamical rule is generally valid. A similar procedure carried out using data from the NCEP global model run with prescribed SST (in which the coupling is one-way, with the ocean always forcing the atmosphere) produces fewer coupled anomalies in the extratropics. They indicate, not surprisingly, an increase in ocean-driving anomalies in the model. In addition, and very importantly, there is a strong reduction of persistent atmosphere-driving anomalies, indicating that the one-way interaction of the ocean in the model run may provide a spurious negative feedback that damps atmospheric anomalies faster than observed.

scholarly journals Validation of the Aura High Resolution Dynamics Limb Sounder geopotential heights

2014 ◽  
Vol 7 (2) ◽  
pp. 1001-1025
Author(s):  
L. L. Smith ◽  
J. C. Gille
Keyword(s):  
High Resolution ◽  
System Model ◽  
Weather Forecasts ◽  
Atmospheric Research ◽  
Earth Observing System ◽  
Medium Range ◽  
High Bias ◽  
Environmental Prediction ◽  
The Tropics ◽  
Data Screening

Abstract. Global satellite observations from the EOS Aura spacecraft's High Resolution Dynamics Limb Sounder (HIRDLS) of temperature and geopotential height (GPH) are discussed. The accuracy, resolution and precision of the HIRDLS version 7 algorithms are assessed and data screening recommendations are made. Comparisons with GPH from observations, reanalyses and models including European Center for Medium-Range Weather Forecasts Interim Reanalysis (ERA-Interim), National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalysis, Goddard Earth Observing System Model (GEOS) version 5, and EOS Aura Microwave Limb Sounder (MLS) illustrate the HIRDLS GPH have a precision ranging from 2 m to 30 m and an accuracy of ±100 m. Comparisons indicate HIRDLS GPH may have a slight low bias in the tropics and a slight high bias at high latitudes. Geostrophic winds computed with HIRDLS GPH qualitatively agree with winds from other data sources including ERA-Interim, NCEP and GEOS-5.

scholarly journals Validation of the Aura High Resolution Dynamics Limb Sounder geopotential heights

2014 ◽  
Vol 7 (8) ◽  
pp. 2775-2785 ◽  
Author(s):  
L. L. Smith ◽  
J. C. Gille
Keyword(s):  
High Resolution ◽  
High Latitudes ◽  
Weather Forecasts ◽  
Atmospheric Research ◽  
Earth Observing System ◽  
Medium Range ◽  
High Bias ◽  
Environmental Prediction ◽  
The Tropics ◽  
Data Screening

Abstract. The geopotential height (GPH) product created from global observations by the High Resolution Dynamics Limb Sounder (HIRDLS) instrument on NASA's Earth Observing System (EOS) Aura spacecraft is discussed. The accuracy, resolution and precision of the HIRDLS version 7 algorithms are assessed and data screening recommendations are made. Comparisons with GPH from observations, reanalyses and models including European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERA-Interim), and National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalysis illustrate the HIRDLS GPHs have a precision ranging from 2 to 30 m and an accuracy of ±100 m up to 1 hPa. Comparisons indicate HIRDLS GPH may have a slight low bias in the tropics and a slight high bias at high latitudes. Geostrophic winds computed with HIRDLS GPH qualitatively agree with winds from other data sources including ERA-Interim.

Sensitivity of MJO Simulation and Predictability to Sea Surface Temperature Variability

2008 ◽  
Vol 21 (20) ◽  
pp. 5304-5317 ◽  
Author(s):  
Hye-Mi Kim ◽  
Carlos D. Hoyos ◽  
Peter J. Webster ◽  
In-Sik Kang
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
General Circulation ◽  
Phase Relationship ◽  
Circulation Model ◽  
Forecast Skill ◽  
Sea Surface ◽  
Coupled Processes ◽  
Forecast Lead Time ◽  
Ocean Atmosphere

Abstract The influence of sea surface temperature (SST) on the simulation and predictability of the Madden–Julian oscillation (MJO) is examined using the Seoul National University atmospheric general circulation model (SNU AGCM). Forecast skill was examined using serial climate simulations spanning eight different winter seasons with 30-day forecasts commencing every 5 days, giving a total of 184 thirty-day simulations. The serial runs were repeated using prescribing observed SST with monthly, weekly, and daily temporal resolutions. The mean SST was the same for all cases so that differences between experiments result from the different temporal resolutions of the SST boundary forcing. It is shown that high temporal SST frequency acts to improve 1) the MJO activity of 200-hPa velocity potential field over the entire Asian monsoon region at all lead times; 2) the percentage of filtered variance of the two leading EOF modes that explain the eastward propagation of MJO; 3) the power of the wavenumber 1 eastward propagating mode; and 4) the forecast skill of MJO, maintaining it for longer periods. However, the MJO phase relationship between MJO convection and SST, as is often the case with many atmosphere-only models, although well simulated at the beginning of forecast period becomes distorted rapidly as the forecast lead time increases, even with the daily SST forcing case. Comparison of AGCM simulations with coupled GCM (CGCM) integrations shows that ocean–atmosphere coupling improves considerably the phase relationship between SST and convection. The CGCM results reinforce that the MJO is a coupled phenomenon and suggest strongly the need of the ocean–atmosphere coupled processes to extend predictability.

Local Atmosphere–Ocean Predictability: Dynamical Origins, Lead Times, and Seasonality

2019 ◽  
Vol 32 (21) ◽  
pp. 7507-7519 ◽  
Author(s):  
Eviatar Bach ◽  
Safa Motesharrei ◽  
Eugenia Kalnay ◽  
Alfredo Ruiz-Barradas
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Phase Relationship ◽  
Sea Surface ◽  
Low Frequencies ◽  
Model Studies ◽  
Almost Everywhere ◽  
Summer Hemisphere ◽  
Coupled Data Assimilation ◽  
The Tropics

Abstract Due to the physical coupling between atmosphere and ocean, information about the ocean helps to better predict the future of the atmosphere, and in turn, information about the atmosphere helps to better predict the ocean. Here, we investigate the spatial and temporal nature of this predictability: where, for how long, and at what frequencies does the ocean significantly improve prediction of the atmosphere, and vice versa? We apply Granger causality, a statistical test to measure whether a variable improves prediction of another, to local time series of sea surface temperature (SST) and low-level atmospheric variables. We calculate the detailed spatial structure of the atmosphere-to-ocean and ocean-to-atmosphere predictability. We find that the atmosphere improves prediction of the ocean most in the extratropics, especially in regions of large SST gradients. This atmosphere-to-ocean predictability is weaker but longer-lived in the tropics, where it can last for several months in some regions. On the other hand, the ocean improves prediction of the atmosphere most significantly in the tropics, where this predictability lasts for months to over a year. However, we find a robust signature of the ocean on the atmosphere almost everywhere in the extratropics, an influence that has been difficult to demonstrate with model studies. We find that both the atmosphere-to-ocean and ocean-to-atmosphere predictability are maximal at low frequencies, and both are larger in the summer hemisphere. The patterns we observe generally agree with dynamical understanding and the results of the Kalnay dynamical rule, which diagnoses the direction of forcing between the atmosphere and ocean by considering the local phase relationship between simultaneous sea surface temperature and vorticity anomaly signals. We discuss applications to coupled data assimilation.

National Centers for Environmental Prediction – National Center for Atmospheric Research (NCEP–NCAR) reanalyses data for hydrologic modelling on a basin scale

2010 ◽  
Vol 37 (4) ◽  
pp. 611-623 ◽  
Author(s):  
Tarana A. Solaiman ◽  
Slobodan P. Simonovic
Keyword(s):  
Hydraulic Modeling ◽  
Reanalysis Data ◽  
Hydrologic Model ◽  
Maximum Temperature ◽  
Reanalysis Dataset ◽  
Hydrologic Modelling ◽  
Stream Flows ◽  
Atmospheric Research ◽  
Basin Scale ◽  
Environmental Prediction

This paper evaluates the National Centers for Environmental Prediction – National Center for Atmospheric Research (NCEP–NCAR) reanalyses hydroclimatic data as an initial check for assessment of hydrologic impacts of climate change at the basin scale. A reanalysis dataset for daily precipitation, maximum temperature, and minimum temperature from the NCEP–NCAR global (NNGR) and regional (North American Regional Reanalysis or NARR) reanalysis project has been used as input into the semidistributed hydrologic model (Hydrologic Engineering Center Hydraulic Modeling System or HEC–HMS) for the period 1980–2005. An extensive analysis has been performed for assessing the performance of the reanalysis data generated flows compared with the observed inputs during May–November. The stream flows generated from the NARR dataset show encouraging results in simulating summertime low flows with less variability and fewer errors. The results indicate that NNGR results are less accurate and highly variable. This study suggests that NARR can be adequately used as an alternative in data-scarce regions.

scholarly journals Reanalysis data of wind fields above the caspian sea for Calculation of wind-induced waves

2019 ◽  
Vol 46 (6) ◽  
pp. 598-604 ◽  
Author(s):  
L. I. Lopatoukhin ◽  
N. A. Yaitskaya
Keyword(s):  
Caspian Sea ◽  
Input Data ◽  
Reanalysis Data ◽  
Wind Fields ◽  
Hydrodynamic Models ◽  
The Caspian Sea ◽  
Atmospheric Research ◽  
Study Results ◽  
The World ◽  
Environmental Prediction

A database covering at least 30 years is required for calculation of the wind-induced waves mode in accordance with recommendations of the World Meteorological Organization. Continuous measurements of wind-induced waves for this period of time are missing or available only for a limited number of offshore strips. Typically this information is a result of calculations based on numerical (spectral) hydrodynamic models of the wind-induced waves while input data is information regarding wind from reanalyzes. Reanalysis can be used for calculation of wind-induced waves without any preliminary processing but not for all offshore zones. The Caspian Sea is used as an example to demonstrate an approach to revision of the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis data and study results are provided.

scholarly journals Reservoir Inflow Prediction under GCM Scenario Downscaled by Wavelet Transform and Support Vector Machine Hybrid Models

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Gusfan Halik ◽  
Nadjadji Anwar ◽  
Budi Santosa ◽  
Edijatno
Keyword(s):  
Support Vector Machine ◽  
General Circulation ◽  
Circulation Model ◽  
Support Vector ◽  
Reservoir Inflow ◽  
Using Data ◽  
The One ◽  
Environmental Prediction ◽  
Inflow Prediction ◽  
Technical Guideline

Climate change has significant impacts on changing precipitation patterns causing the variation of the reservoir inflow. Nowadays, Indonesian hydrologist performs reservoir inflow prediction according to the technical guideline of Pd-T-25-2004-A. This technical guideline does not consider the climate variables directly, resulting in significant deviation to the observation results. This research intends to predict the reservoir inflow using the statistical downscaling (SD) of General Circulation Model (GCM) outputs. The GCM outputs are obtained from the National Center for Environmental Prediction/National Center for Atmospheric Research Reanalysis (NCEP/NCAR Reanalysis). A new proposed hybrid SD model named Wavelet Support Vector Machine (WSVM) was utilized. It is a combination of the Multiscale Principal Components Analysis (MSPCA) and nonlinear Support Vector Machine regression. The model was validated at Sutami Reservoir, Indonesia. Training and testing were carried out using data of 1991–2008 and 2008–2012, respectively. The results showed that MSPCA produced better extracting data than PCA. The WSVM generated better reservoir inflow prediction than the one of technical guideline. Moreover, this research also applied WSVM for future reservoir inflow prediction based on GCM ECHAM5 and scenario SRES A1B.

scholarly journals Weakening of Antarctic Stratospheric Planetary Wave Activities in Early Austral Spring Since the Early 2000s: A Response to Sea Surface Temperature Trends

2021 ◽  
Author(s):  
Yihang Hu ◽  
Wenshou Tian ◽  
Jiankai Zhang ◽  
Tao Wang ◽  
Mian Xu
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Numerical Simulations ◽  
Southern Hemisphere ◽  
Planetary Wave ◽  
Stratospheric Ozone ◽  
Reanalysis Data ◽  
Sea Surface ◽  
Austral Spring ◽  
The Tropics

Abstract. Using multiple reanalysis datasets and modeling simulations, the trends of Antarctic stratospheric planetary wave activities in early austral spring since the early 2000s are investigated in this study. We find that the stratospheric planetary wave activities in September have weakened significantly since 2000, which is related to the weakening of the tropospheric wave sources in the extratropical southern hemisphere. Further analysis indicates that the trend of September sea surface temperature (SST) over 20° N–70° S is statistically linked to the weakening of stratospheric planetary wave activities. Numerical simulations support the result that the SST trend in the extratropical southern hemisphere (20° S–70° S) and the tropics (20° N–20° S) induce the weakening of wave-1 component of tropospheric geopotential height in the extratropical southern hemisphere, which subsequently leads to the decrease in stratospheric wave flux. The responses of stratospheric wave activities in the southern hemisphere to stratospheric ozone recovery is not significant in simulations. In addition, both reanalysis data and numerical simulations indicate that the Brewer-Dobson circulation (BDC) related to wave activities in the stratosphere has also been weakening in early austral spring since 2000 due to the trend of September SST in the tropics and extratropical southern hemisphere.

Long-term variation of water vapor content and precipitation in the Haihe river basin

2014 ◽  
Vol 6 (2) ◽  
pp. 341-351 ◽  
Author(s):  
Chun Chang ◽  
Ping Feng ◽  
Fawen Li ◽  
Yunming Gao
Keyword(s):  
Water Vapor ◽  
River Basin ◽  
Reanalysis Data ◽  
Water Vapor Content ◽  
Haihe River Basin ◽  
Haihe River ◽  
Annual Water ◽  
Environmental Prediction ◽  
High Consistency ◽  
The Haihe River Basin

Based on the Haihe river basin National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis data from 1948 to 2010 and the precipitation data of 53 hydrological stations during 1957–2010, this study analyzed the variation of water vapor content and precipitation, and investigated the correlation between them using several statistical methods. The results showed that the annual water vapor content decreased drastically from 1948 to 2010. It was comparatively high from the late 1940s to the late 1960s and depreciated from the early 1970s. From the southeast to the northwest of the Haihe river basin, there was a decrease in water vapor content. For vertical distribution, water vapor content from the ground to 700 hPa pressure level accounted for 72.9% of the whole atmospheric layer, which indicated that the water vapor of the Haihe river basin was mainly in the air close to the ground. The precipitation in the Haihe river basin during 1957–2010 decreased very slightly. According to the correlation analysis, the precipitation and water vapor content changes showed statistically positive correlation, in addition, their break points were both in the 1970s. Furthermore, the high consistency between the precipitation efficiency and precipitation demonstrates that water vapor content is one of the important factors in the formation of precipitation.

scholarly journals Interannual Variability and Trends in Sea Surface Temperature, Lower and Middle Atmosphere Temperature at Different Latitudes for 1980–2019

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 454
Author(s):  
Andrew R. Jakovlev ◽  
Sergei P. Smyshlyaev ◽  
Vener Y. Galin
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Lower Stratosphere ◽  
Middle Atmosphere ◽  
Southern Oscillation ◽  
Lower Troposphere ◽  
Reanalysis Data ◽  
Sea Surface ◽  
The Arctic ◽  
The Impact

The influence of sea-surface temperature (SST) on the lower troposphere and lower stratosphere temperature in the tropical, middle, and polar latitudes is studied for 1980–2019 based on the MERRA2, ERA5, and Met Office reanalysis data, and numerical modeling with a chemistry-climate model (CCM) of the lower and middle atmosphere. The variability of SST is analyzed according to Met Office and ERA5 data, while the variability of atmospheric temperature is investigated according to MERRA2 and ERA5 data. Analysis of sea surface temperature trends based on reanalysis data revealed that a significant positive SST trend of about 0.1 degrees per decade is observed over the globe. In the middle latitudes of the Northern Hemisphere, the trend (about 0.2 degrees per decade) is 2 times higher than the global average, and 5 times higher than in the Southern Hemisphere (about 0.04 degrees per decade). At polar latitudes, opposite SST trends are observed in the Arctic (positive) and Antarctic (negative). The impact of the El Niño Southern Oscillation phenomenon on the temperature of the lower and middle atmosphere in the middle and polar latitudes of the Northern and Southern Hemispheres is discussed. To assess the relative influence of SST, CO2, and other greenhouse gases’ variability on the temperature of the lower troposphere and lower stratosphere, numerical calculations with a CCM were performed for several scenarios of accounting for the SST and carbon dioxide variability. The results of numerical experiments with a CCM demonstrated that the influence of SST prevails in the troposphere, while for the stratosphere, an increase in the CO2 content plays the most important role.

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