scholarly journals Interannual variability in hindcasts of atmospheric chemistry: the role of meteorology

2009 ◽  
Vol 9 (14) ◽  
pp. 5261-5280 ◽  
Author(s):  
P. Hess ◽  
N. Mahowald
Keyword(s):  
Water Vapor ◽  
Surface Temperature ◽  
Interannual Variability ◽  
Atmospheric Chemistry ◽  
El Niño ◽  
Hydrological Cycle ◽  
Transport Model ◽  
El Nino ◽  
Climate Simulation ◽  
Relative Variability

Abstract. Two 40-year meteorological datasets are used to drive the Model of Ozone and Related Tracers chemical transport model, version 2 (MOZART2) in hindcast simulations. One dataset is from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis, the second dataset uses meteorology from the Community Atmosphere Model (CAM3) forced with observed interannually varying sea surface temperatures. All emissions, except those from lightning are annually constant. Analysis of these simulations focuses on the period between 1979–1999, due to meteorological discontinuities in the NCEP reanalysis during the 1970s. The meteorology using CAM3 captures observed trends in temperature and water vapor; the simulation using NCEP meteorology does not. This paper examines the regional and global interannual variability of various chemical and meteorological fields: CO, OH, O3 and HNO3, the surface photolysis rate of NO2 (as a proxy for overhead cloudiness), lightning NO emissions, water vapor, planetary boundary layer height, and temperature. The variability due to changes in emissions is not considered in this analysis. In both the NCEP and CAM3 simulations the relative variability of CO, OH, O3 and HNO3 are qualitatively similar, with variability maxima both in the tropics and the high latitudes. Locally, relative variability generally ranges between 3 and 10%; globally the tropospheric variability generally ranges from half to one percent, but can be higher. For most fields the leading global Empirical Orthogonal Function explains approximately 10% of the variability and correlates significantly with El Niño. In both simulations the first principal component of a multiple tracer, globally averaged analysis shows a strong coupling between surface temperature, measures of the hydrological cycle, CO and OH, but is not correlated with El Niño. In both simulations we examine the global response of the selected variables to changes in global surface temperature, and compare with a climate simulation over the 21st century.

scholarly journals Interannual variability in hindcasts of atmospheric chemistry: the role of meteorology

2009 ◽  
Vol 9 (1) ◽  
pp. 3485-3534
Author(s):  
P. Hess ◽  
N. Mahowald
Keyword(s):  
Water Vapor ◽  
Surface Temperature ◽  
Interannual Variability ◽  
Atmospheric Chemistry ◽  
El Niño ◽  
Hydrological Cycle ◽  
Transport Model ◽  
El Nino ◽  
Climate Simulation ◽  
Relative Variability

Abstract. Two 40-year meteorological datasets are used to drive the Model of Ozone and Related Tracers chemical transport model, version 2 (MOZART2) in hindcast simulations. One dataset is from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis, the second dataset uses meteorology from the Community Atmosphere Model (CAM3) forced with observed interannually varying sea surface temperatures. All emissions, except those from lightning are annually constant. Analysis of these simulations is from 1979–1999, due to meteorological discontinuities in the NCEP reanalysis during the 1970s. The meteorology using CAM3 captures observed trends in temperature, water vapor, precipitation and cloudiness; the simulation using NCEP meteorology does not. This paper examines the regional and global interannual variability of various chemical and meteorological fields: CO, OH, O3 and HNO3, the surface photolysis rate of NO2 (as a proxy for overhead cloudiness), lightning NO emissions, water vapor, planetary boundary layer height, and temperature. The variability due to changes in emissions is not considered in this analysis. In both the NCEP and CAM3 simulations the relative variability of CO, OH, O3 and HNO3 are qualitatively similar, with variability maxima both in the tropics and the high latitudes. Locally, relative variability generally ranges between 3 and 10%; globally the tropospheric variability generally ranges from half to one percent, but can be higher. For most fields the leading Empirical Orthogonal Function explains approximately 10% of the variability and correlates significantly with El Niño. In both simulations the first principal component of a multiple tracer, globally averaged analysis shows a strong coupling between surface temperature, measures of the hydrological cycle, CO and OH, but is not correlated with El Niño. In both simulations we examine the global response of the selected variables to changes in global surface temperature, and compare with a climate simulation over the 21st century.

The role of El Niño Southern Oscillation on the patterns of cycling rates observed over India during the monsoon season

2014 ◽  
Vol 5 (4) ◽  
pp. 696-706 ◽  
Author(s):  
T. V. Lakshmi Kumar ◽  
K. Koteswara Rao ◽  
R. Uma ◽  
K. Aruna
Keyword(s):  
Water Vapor ◽  
El Niño ◽  
Hydrological Cycle ◽  
El Nino ◽  
Southern Oscillation ◽  
Monsoon Season ◽  
Precipitable Water ◽  
Spatiotemporal Variability ◽  
Monsoon Period ◽  
Sw Monsoon

Trend and interannual variability of total integrated precipitable water vapor (PWV) has been studied over India for the period 1979–2004 using NCEP/National Centre for Atmospheric Research reanalysis data with 2.5° × 2.5° resolution. The spatiotemporal variability of cycling rates (CR; units: per day), obtained from the ratio of rainfall to the PWV were presented not only for the long term (1979–2004) but also during El Niño (EN) and La Niña (LN) years of the study period to understand the intensity of hydrological cycle. The paper then dwells on obtaining the monthly atmospheric residences times over India to infer the stay of water vapor before it precipitates. The results of the present study are: all India PWV shows decreasing trend in association with the increasing/decreasing trends of Niño 3 SST/Southern Oscillation Index (SOI) for the southwest (SW) monsoon period of 1979–2004; the spatial pattern of temporal correlations of CR with SOI and Niño 3 SST displayed the significant positive and negative values in peninsular and central Indian portions of India respectively; all India atmospheric residence times varied from 9 to 2 days from premonsoon/post monsoon to SW monsoon over India.

Spatial and temporal trends and variabilities of hailstones in the United States Northern Great Plains and their possible attributions

2021 ◽  
pp. 1-53
Author(s):  
Jong-Hoon Jeong ◽  
Jiwen Fan ◽  
Cameron R. Homeyer
Keyword(s):  
United States ◽  
Water Vapor ◽  
Interannual Variability ◽  
Great Plains ◽  
El Niño ◽  
El Nino ◽  
Vapor Transport ◽  
Water Vapor Transport ◽  
Northern Great Plains ◽  
Contributing Factors

AbstractFollowing on our study of hail for the Southern Great Plains (SGP), we investigated the spatial and temporal hail trends and variabilities for the Northern Great Plains (NGP) and the contributing factors for summers (June–August) focusing on the period of 2004–2016 using two independent hail datasets. Analysis for an extended period (1994–2016) with the hail reports was also conducted to more reliably investigate the contributing factors. Both severe hail (1″ < diameter ≤ 2″) and significant severe hail (SSH; diameter > 2″) were examined and similar results were obtained. The occurrence of hail over the NGP demonstrated a large interannual variability, with a positive slope overall. Spatially, the increase is mainly located in the western part of Nebraska, South Dakota, and North Dakota. We find the three major dynamical factors that most likely contribute to the hail interannual variability in the NGP are the El Niño-Southern Oscillation (ENSO), North Atlantic subtropical high (NASH), and low-level jet (LLJ). With a thermodynamical variable integrated water vapor transport that is strongly controlled by LLJ, the four factors can explain 78% of the interannual variability in the number of SSH reports. Hail occurrences in the La Niña years are higher than the El Niño years since the jet stream is stronger and NASH extends further into the southeastern United States, thereby strengthening the LLJ and in turn water vapor transport. Interestingly, the important factors impacting hail interannual variability over the NGP are quite different from those for the SGP, except for ENSO.

Process-Based Decomposition of the Global Surface Temperature Response to El Niño in Boreal Winter

2012 ◽  
Vol 69 (5) ◽  
pp. 1706-1712 ◽  
Author(s):  
Yi Deng ◽  
Tae-Won Park ◽  
Ming Cai
Keyword(s):  
Water Vapor ◽  
Surface Temperature ◽  
El Niño ◽  
Heat Storage ◽  
Temperature Anomaly ◽  
El Nino ◽  
Mean Amplitude ◽  
Temperature Pattern ◽  
The Mean ◽  
Sst Anomalies

Abstract This paper reports an attribution analysis that quantifies addible contributions to the observed temperature anomalies from radiative and nonradiative processes in terms of both amplitude and spatial pattern for the two most prominent surface temperature patterns in an El Niño winter. One is the El Niño SST pattern consisting of warming SST anomalies over the eastern equatorial Pacific basin surrounded by cooling SST anomalies in the western and subtropical Pacific, and the other is a tripole surface temperature anomaly characteristic of a positive Pacific–North American (PNA) teleconnection pattern. The decomposition of the observed temperature anomalies is achieved with the coupled atmosphere–surface climate feedback-responses analysis method (CFRAM), which is formulated utilizing energy balance in the atmosphere–surface columns and linearization of radiative energy perturbation. Out of the mean amplitude of 0.78 K of the El Niño SST pattern, the oceanic dynamics and heat storage term alone contributes to 2.34 K. Water vapor feedback adds another 1.6 K whereas both cloud and atmospheric dynamical feedbacks are negative, reducing the mean amplitude by 2.02 and 1.07 K, respectively. Atmospheric dynamical feedback contributes more than 50% (0.73 K) of the mean amplitude (1.32 K) of the PNA surface temperature pattern. Water vapor and surface albedo feedbacks contribute 0.34 and 0.13 K, respectively. The surface processes, including oceanic dynamics in the North Pacific, heat storage anomalies, and surface sensible/latent heat flux anomalies of ocean and land also contribute positively to the PNA surface temperature pattern (about 0.14 K). Cloud and ozone feedback, although very weak, act to oppose the PNA surface temperature anomaly.

scholarly journals Improvement of ENSO Simulation Based on Intermodel Diversity

2015 ◽  
Vol 28 (3) ◽  
pp. 998-1015 ◽  
Author(s):  
Yoo-Geun Ham ◽  
Jong-Seong Kug
Keyword(s):  
Interannual Variability ◽  
El Niño ◽  
Climate Models ◽  
El Nino ◽  
Southern Oscillation ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Climate Simulation ◽  
Central Pacific

Abstract In this study, a new methodology is developed to improve the climate simulation of state-of-the-art coupled global climate models (GCMs), by a postprocessing based on the intermodel diversity. Based on the close connection between the interannual variability and climatological states, the distinctive relation between the intermodel diversity of the interannual variability and that of the basic state is found. Based on this relation, the simulated interannual variabilities can be improved, by correcting their climatological bias. To test this methodology, the dominant intermodel difference in precipitation responses during El Niño–Southern Oscillation (ENSO) is investigated, and its relationship with climatological state. It is found that the dominant intermodel diversity of the ENSO precipitation in phase 5 of the Coupled Model Intercomparison Project (CMIP5) is associated with the zonal shift of the positive precipitation center during El Niño. This dominant intermodel difference is significantly correlated with the basic states. The models with wetter (dryer) climatology than the climatology of the multimodel ensemble (MME) over the central Pacific tend to shift positive ENSO precipitation anomalies to the east (west). Based on the model’s systematic errors in atmospheric ENSO response and bias, the models with better climatological state tend to simulate more realistic atmospheric ENSO responses. Therefore, the statistical method to correct the ENSO response mostly improves the ENSO response. After the statistical correction, simulating quality of the MME ENSO precipitation is distinctively improved. These results provide a possibility that the present methodology can be also applied to improving climate projection and seasonal climate prediction.

scholarly journals A quasi chemistry-transport model mode for EMAC

2011 ◽  
Vol 4 (1) ◽  
pp. 195-206 ◽  
Author(s):  
R. Deckert ◽  
P. Jöckel ◽  
V. Grewe ◽  
K.-D. Gottschaldt ◽  
P. Hoor
Keyword(s):  
Water Vapor ◽  
Nitric Acid ◽  
Atmospheric Chemistry ◽  
Transport Model ◽  
Climate Simulation ◽  
Chemistry Transport Model ◽  
Mixing Ratios ◽  
Reference Simulation ◽  
The Difference ◽  
Chemical Water

Abstract. A quasi chemistry-transport model mode (QCTM) is presented for the numerical chemistry-climate simulation system ECHAM/MESSy Atmospheric Chemistry (EMAC). It allows for a quantification of chemical signals through suppression of any feedback between chemistry and dynamics. Noise would otherwise interfere too strongly. The signal is calculated from the difference of two QCTM simulations, a reference simulation and a sensitivity simulation. In order to avoid the feedbacks, the simulations adopt the following offline chemical fields: (a) offline mixing ratios of radiatively active substances enter the radiation scheme, (b) offline mixing ratios of nitric acid enter the scheme for re-partitioning and sedimentation from polar stratospheric clouds, (c) and offline methane oxidation is the exclusive source of chemical water-vapor tendencies. Any set of offline fields suffices to suppress the feedbacks, though may be inconsistent with the simulation setup. An adequate set of offline climatologies can be produced from a non-QCTM simulation using the setup of the reference simulation. Test simulations reveal the particular importance of adequate offline fields associated with (a). Inconsistencies from (b) are negligible when using adequate fields of nitric acid. Acceptably small inconsistencies come from (c), but should vanish for an adequate prescription of chemical water vapor tendencies. Toggling between QCTM and non-QCTM is done via namelist switches and does not require a source code re-compilation.

scholarly journals Spatial and Temporal Variability of Sea Surface Temperature in Eastern Marginal Seas of China

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Renhao Wu ◽  
Jianmin Lin ◽  
Bo Li
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Interannual Variability ◽  
El Niño ◽  
Temporal Variability ◽  
El Nino ◽  
Mean Value ◽  
Sea Surface ◽  
Marginal Seas

Spatial mean value evolution, long-term mean pattern, and seasonal as well as interannual variability of sea surface temperature (SST) in Eastern Marginal Seas of China (EMSC) are reanalyzed based on thirty years’ NOAA optimum interpolation (OI) 1/4 degrees’ daily SST data. Temporal evolution of the spatial mean value shows a very marked annual cycle and a weak warming tendency (0.03437°C/year). Spatial distribution of the long-term mean value shows some more fine spatial structure of SST compared to previous studies. Over 90% of the temporal variability can be explained by the annual harmonic whose amplitude is one order larger than that of the semiannual harmonic. In addition, the annual harmonic amplitude distribution is consistent with that of the value of standard deviation. In order to investigate the interannual variation of SST, the EMSC SST interannual index was constructed. Based on wavelet analysis, a significant peak around 3.3 years was found in the EMSC SST interannual index. Further analysis demonstrated that the interannual variability of SST is linked with El Niño-Southern Oscillation (ENSO) teleconnection, through which anomalous surface heat flux warms or cools the EMSC during El Niño or La Niña events.

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