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Qiang Fu and Pu Lin

Abstract

One pronounced feature in observed latitudinal dependence of lower-stratospheric temperature trends is the enhanced cooling near 30° latitude in both hemispheres. The observed phenomenon has not, to date, been explained in the literature. This study shows that the enhanced cooling is a direct response of the lower-stratospheric temperature to the poleward shift of subtropical jets. Furthermore, this enhanced lower-stratospheric cooling can be used to quantify the poleward shift of subtropical jets. Using the lower-stratospheric temperatures observed by satellite-borne microwave sounding units, it is shown that the subtropical jets have shifted poleward by 0.6° ± 0.1° and 1.0° ± 0.3° latitude in the Southern and Northern Hemispheres, respectively, in last 30 years since 1979, indicating a widening of tropical belt by 1.6° ± 0.4° latitude.

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Liao-Fan Lin and Zhaoxia Pu

Abstract

Strongly coupled land–atmosphere data assimilation has not yet been implemented into operational numerical weather prediction (NWP) systems. Up to now, upper-air measurements have been assimilated mainly in atmospheric analyses, while land and near-surface data have been assimilated mainly into land surface models. Thus, this study aims to explore the benefits of assimilating atmospheric and land surface observations within the framework of strongly coupled data assimilation. Specifically, we added soil moisture as a control state within the ensemble Kalman filter (EnKF)-based Gridpoint Statistical Interpolation (GSI) and conducted a series of numerical experiments through the assimilation of 2-m temperature/humidity and in situ surface soil moisture data along with conventional atmospheric measurements such as radiosondes into the Weather Research and Forecasting (WRF) Model with the Noah land surface model. The verification against in situ measurements and analyses show that compared to the assimilation of conventional data, adding soil moisture as a control state and assimilating 2-m humidity can bring additional benefits to analyses and forecasts. The impact of assimilating 2-m temperature (surface soil moisture) data is positive mainly on the temperature (soil moisture) analyses but on average marginal for other variables. On average, below 750 hPa, verification against the NCEP analysis indicates that the respective RMSE reduction in the forecasts of temperature and humidity is 5% and 2% for assimilating conventional data; 10% and 5% for including soil moisture as a control state; and 16% and 11% for simultaneously adding soil moisture as a control state and assimilating 2-m humidity data.

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Liao-Fan Lin and Zhaoxia Pu

Abstract

This study characterizes the spatial and temporal variability of the background error covariance between the land surface soil moisture and atmospheric states for a better understanding of the potentials of assimilating satellite soil moisture data under a framework of strongly coupled land–atmosphere data assimilation. The study uses the Noah land surface model coupled with the Weather Research and Forecasting (WRF) Model and the National Meteorological Center (NMC) method for computing the land–atmosphere background error covariance from 2015 to 2017 over the contiguous United States. The results show that the forecast errors in top-10-cm soil moisture and near-surface air potential temperature and specific humidity are correlated and relatively large during the daytime in the summer. The magnitude of the error correlation between these three states is comparable. For example, in July, the error correlation averaged over all day- and nighttime samples is −0.13 for near-surface temperature and humidity, −0.20 for surface soil moisture and near-surface temperature, and 0.15 for surface soil moisture and near-surface humidity. During the summer, the forecast errors in surface soil moisture are correlated with those of atmospheric states up to the sigma pressure level of 0.9 (approximately 900 hPa for a sea level location) with domain-mean correlations of −0.15 and 0.1 for temperature and humidity, respectively. The results suggest that assimilation of satellite soil moisture data could provide cross-variable impacts comparable to those assimilating conventional near-surface temperature and humidity data. The forecast errors of soil moisture are only marginally correlated with those of the winds.

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Liao-Fan Lin and Zhaoxia Pu

Abstract

Remotely sensed soil moisture data are typically incorporated into numerical weather models under a framework of weakly coupled data assimilation (WCDA), with a land surface analysis scheme independent from the atmospheric analysis component. In contrast, strongly coupled data assimilation (SCDA) allows simultaneous correction of atmospheric and land surface states but has not been sufficiently explored with land surface soil moisture data assimilation. This study implemented a variational approach to assimilate the Soil Moisture Active Passive (SMAP) 9-km enhanced retrievals into the Noah land surface model coupled with the Weather Research and Forecasting (WRF) Model under a framework of both WCDA and SCDA. The goal of the study is to quantify the relative impact of assimilating SMAP data under different coupling frameworks on the atmospheric forecasts in the summer. The results of the numerical experiments during July 2016 show that SCDA can provide additional benefits on the forecasts of air temperature and humidity compared to WCDA. Over the U.S. Great Plains, assimilation of SMAP data under WCDA reduces a warm bias in temperature and a dry bias in humidity by 7.3% and 19.3%, respectively, while the SCDA case contributes an additional bias reduction of 2.2% (temperature) and 3.3% (humidity). While WCDA leads to a reduction of RMSE in temperature forecasts by 4.1%, SCDA results in additional reduction of RMSE by 0.8%. For the humidity, the reduction of RMSE is around 1% for both WCDA and SCDA.

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Pu Lin, Qiang Fu, and Dennis L. Hartmann

Abstract

The impact of tropical sea surface temperature (SST) on stratospheric planetary waves in the Southern Hemisphere (SH) is investigated in austral spring using observed SST and reanalysis data for the past three decades. Maximum covariance analysis indicates that the tropical SST and the SH stratospheric planetary wave activity are primarily coupled through two modes. The leading two modes show the La Niña–like and the central-Pacific El Niño–like SST anomalies in their positive polarities, respectively, which each are related to enhanced stratospheric planetary wave activity. These two modes also introduce phase shifts to the stratospheric stationary planetary waves: a westward shift is seen for La Niña and an eastward shift for warm SST anomalies is seen in the central Pacific. The Eliassen–Palm fluxes associated with the two modes indicate that the anomalous stratospheric wave activity originates in the troposphere and propagates upward over the mid–high latitudes, so that the linkages between tropical SST and extratropical tropospheric circulation appear to play a key role. Furthermore, the observed circulation anomaly patterns for the two modes change rapidly from spring to summer, consistent with a sharp seasonal transition in the SH basic state. Similar SST and circulation anomaly patterns associated with the two modes are simulated in chemistry–climate models.

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Pu Lin, Isaac Held, and Yi Ming

Abstract

An unprecedented disruption of the quasi-biennial oscillation (QBO) started to develop from late 2015. The early development of this event is analyzed using the space–time spectra of eddies from reanalysis data. While the extratropical waves propagating horizontally into the tropics were assumed to be the main driver for the disruption, it was not clear why these waves dissipated near the jet core instead of near the jet edge as linear theory predicts. This study shows that the drastic deceleration of the equatorial jet was largely brought about by a single strong wave packet, and the local winds experienced by the wave packet served as a better indicator of the wave breaking latitude than the zonal mean winds. Surprisingly, tropical mixed Rossby–gravity waves also made an appreciable contribution to the deceleration of the equatorial westerly jet by the horizontal eddy momentum fluxes, especially before January 2016. The horizontal eddy momentum fluxes associated with the tropical waves arise from the deformation of the wave structure when background westerlies increase with height. These horizontal eddy momentum anomalies from the tropical waves are commonly observed in the reanalysis data but are typically much weaker than those in the 2015/16 winter. The possibility exists that exceptionally strong equatorially trapped waves precondition the flow to disruption by an extratropical disturbance.

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Pu Lin, Qiang Fu, Susan Solomon, and John M. Wallace
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Brian V. Smoliak, John M. Wallace, Pu Lin, and Qiang Fu

Abstract

The influence of atmospheric circulation changes reflected in spontaneously occurring sea level pressure (SLP) anomalies upon surface air temperature (SAT) variability and trends is investigated using partial least squares (PLS) regression, a statistical method that seeks to maximally explain covariance between a predictand time series or field and a predictor field. Applying PLS regression in any one of the three variants described in this study (pointwise, PC-wise, and fieldwise), the method yields a dynamical adjustment to the observed NH SAT field that accounts for approximately 50% of the variance in monthly mean, cold season data. It is shown that PLS regression provides a more parsimonious and statistically robust dynamical adjustment than an adjustment method based on the leading principal components of the extratropical SLP field. The usefulness of dynamical adjustment is demonstrated by applying it to the attribution of cold season SAT trends in two reference intervals: 1965–2000 and 1920–2011. The adjustment is shown to reconcile much of the spatial structure and seasonal differences in the observed SAT trends. The dynamically adjusted SAT fields obtained from this analysis provide datasets capable of being analyzed for residual variability and trends associated with thermodynamic and radiative processes.

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Pu Lin, David Paynter, Yi Ming, and V. Ramaswamy

Abstract

This paper investigates changes in the tropical tropopause layer (TTL) in response to carbon dioxide increase and surface warming separately in an atmospheric general circulation model, finding that both effects lead to a warmer tropical tropopause. Surface warming also results in an upward shift of the tropopause. A detailed heat budget analysis is performed to quantify the contributions from different radiative and dynamic processes to changes in the TTL temperature. When carbon dioxide increases with fixed surface temperature, a warmer TTL mainly results from the direct radiative effect of carbon dioxide increase. With surface warming, the largest contribution to the TTL warming comes from the radiative effect of the warmer troposphere, which is partly canceled by the radiative effect of the moistening at the TTL. Strengthening of the stratospheric circulation following surface warming cools the lower stratosphere dynamically and radiatively via changes in ozone. These two effects are of comparable magnitudes. This circulation change is the main cause of temperature changes near 63 hPa but is weak near 100 hPa. Contributions from changes in convection and clouds are also quantified. These results illustrate the heat budget analysis as a useful tool to disentangle the radiative–dynamical–chemical–convective coupling at the TTL and to facilitate an understanding of intermodel difference.

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Pu Lin, Qiang Fu, Susan Solomon, and John M. Wallace

Abstract

Robust stratospheric temperature trend patterns are suggested in the winter and spring seasons in the Southern Hemisphere high latitudes from the satellite-borne Microwave Sounding Unit (MSU) measurement for 1979–2007. These patterns serve as indicators of key processes governing temperature and ozone changes in the Antarctic. The observed patterns are characterized by cooling and warming regions of comparable magnitudes, with the strongest local trends occurring in September and October. In September, ozone depletion induces radiative cooling, and strengthening of the Brewer–Dobson circulation (BDC) induces dynamical warming. Because the trends induced by these two processes are centered in different locations in September, they do not cancel each other, but rather produce a wavelike structure. In contrast, during October, the ozone-induced radiative cooling and the BDC-induced warming exhibit a more zonally symmetric structure than in September, and hence largely cancel each other. However, the October quasi-stationary planetary wavenumber 1 has shifted eastward from 1979 to 2007, producing a zonal wavenumber-1 trend structure, which dominates the observed temperature trend pattern.

Simulated temperature changes for 1979–2007 from coupled atmosphere–ocean general circulation model (AOGCM) experiments run for the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) are compared with the observations. In general, the simulated temperature changes are dominated by zonally symmetric ozone-induced radiative cooling. The models fail to simulate the warming in the southern polar stratosphere, implying a lack of the BDC strengthening in these models. They also fail to simulate the quasi-stationary planetary wave changes observed in October and November.

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