scholarly journals Patterns of CO2 Variability from Global Satellite Data

2012 ◽  
Vol 25 (18) ◽  
pp. 6383-6393 ◽  
Author(s):  
Alexander Ruzmaikin ◽  
Hartmut H. Aumann ◽  
Thomas S. Pagano
Keyword(s):  
Spatial Patterns ◽  
Southern Oscillation ◽  
Linear Trend ◽  
Potential Temperature ◽  
Principal Component ◽  
Co2 Concentration ◽  
Time Variability ◽  
Mode Decomposition ◽  
Causative Relationship ◽  
The Tropics

Abstract The authors present an analysis of the global midtropospheric CO2 retrieved for all-sky (clear and cloudy) conditions from measurements by the Atmospheric Infrared Radiation Sounder on board the Aqua satellite in 2003–09. The global data coverage allows the identification of the set of CO2 spatial patterns and their time variability by applying principal component analysis and empirical mode decomposition. The first, dominant pattern represents 93% of the variability and exhibits the linear trend of 2 ± 0.2 ppm yr−1, as well as annual and interannual dependencies. The single-site record of CO2 at Mauna Loa compares well with variability of this pattern. The first principal component is phase shifted relative to the Southern Oscillation, indicating a causative relationship between the atmospheric CO2 and ENSO. The higher-order patterns show regional details of CO2 distribution and display the semiannual oscillation. The CO2 distributions are compared with the distribution of two major characteristics of air transport: the vertical velocity and potential temperature surfaces at the same height. In agreement with modeling, CO2 concentration closely traces the potential temperature surfaces (isentropes) in middle and high latitudes. However, its vertical transport in the tropics, where these surfaces are mostly horizontal, is suppressed. The results are in agreement with the previous results on annual and interannual CO2 time variability obtained by using the network flask data. This knowledge of the global CO2 spatial patterns can be useful in climate analyses and potentially in the challenging task of connecting CO2 sources and sinks with its distribution in the atmosphere.

scholarly journals Trends and variability of midlatitude stratospheric water vapour deduced from the re-evaluated Boulder balloon series and HALOE

2008 ◽  
Vol 8 (5) ◽  
pp. 1391-1402 ◽  
Author(s):  
M. Scherer ◽  
H. Vömel ◽  
S. Fueglistaler ◽  
S. J. Oltmans ◽  
J. Staehelin
Keyword(s):  
Water Vapour ◽  
Linear Trend ◽  
Potential Temperature ◽  
Data Series ◽  
Explanatory Variables ◽  
Time Period ◽  
Corrected Data ◽  
Instrumental Bias ◽  
The Tropics ◽  
Stratospheric Water Vapour

Abstract. This paper presents an updated trend analysis of water vapour in the lower midlatitude stratosphere from the Boulder balloon-borne NOAA frostpoint hygrometer measurements and from the Halogen Occulation Experiment (HALOE). Two corrections for instrumental bias are applied to homogenise the frostpoint data series, and a quality assessment of all soundings after 1991 is presented. Linear trend estimates based on the corrected data for the period 1980–2000 are up to 40% lower than previously reported. Vertically resolved trends and variability are calculated with a multi regression analysis including the quasi-biennal oscillation and equivalent latitude as explanatory variables. In the range of 380 to 640 K potential temperature (≈14 to 25 km), the frostpoint data from 1981 to 2006 show positive linear trends between 0.3±0.3 and 0.7±0.1%/yr. The same dataset shows trends between −0.2±0.3 and 1.0±0.3%/yr for the period 1992 to 2005. HALOE data over the same time period suggest negative trends ranging from −1.1±0.2 to −0.1±0.1%/yr. In the lower stratosphere, a rapid drop of water vapour is observed in 2000/2001 with little change since. At higher altitudes, the transition is more gradual, with slowly decreasing concentrations between 2001 and 2007. This pattern is consistent with a change induced by a drop of water concentrations at entry into the stratosphere. Previously noted differences in trends and variability between frostpoint and HALOE remain for the homogenised data. Due to uncertainties in reanalysis temperatures and stratospheric transport combined with uncertainties in observations, no quantitative inference about changes of water entering the stratosphere in the tropics could be made with the mid latitude measurements analysed here.

scholarly journals An Intercomparison of the Spatiotemporal Variability of Satellite- and Ground-Based Cloud Datasets Using Spectral Analysis Techniques

2015 ◽  
Vol 28 (14) ◽  
pp. 5716-5736 ◽  
Author(s):  
Jing Li ◽  
Barbara E. Carlson ◽  
William B. Rossow ◽  
Andrew A. Lacis ◽  
Yuanchong Zhang
Keyword(s):  
Spectral Analysis ◽  
Spatial Patterns ◽  
Southern Oscillation ◽  
Cloud Amount ◽  
Principal Component ◽  
Spatiotemporal Variability ◽  
Indian Ocean Dipole Mode ◽  
Climate Modes ◽  
Analysis Techniques ◽  
Sahel Region

Abstract Because of the importance of clouds in modulating Earth’s energy budget, it is critical to understand their variability in space and time for climate and modeling studies. This study examines the consistency of the spatiotemporal variability of cloud amount (CA) and cloud-top pressure (CTP) represented by five 7-yr satellite datasets from the Global Energy and Water Cycle Experiment (GEWEX) cloud assessment project, and total cloud fraction observation from the Extended Edited Cloud Reports Archive (EECRA). Two spectral analysis techniques, namely combined maximum covariance analysis (CMCA) and combined principal component analysis (CPCA), are used to extract the dominant modes of variability from the combined datasets, and the resulting spatial patterns are compared in parallel. The results indicate that the datasets achieve overall excellent agreement on both seasonal and interannual scales of variability, with the correlations between the spatial patterns mostly above 0.6 and often above 0.8. For seasonal variability, the largest differences are found in the Northern Hemisphere high latitudes and near the South African coast for CA and in the Sahel region for CTP, where some differences in the phase and strength of the seasonal cycle are found. On interannual scales, global cloud variability is mostly associated with major climate modes, including El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), and the Indian Ocean dipole mode (IODM), and the datasets also agree reasonably well. The good agreement across the datasets supports the conclusion that they are describing cloud variations with these climate modes.

scholarly journals Trends and variability of midlatitude stratospheric water vapour deduced from the re-evaluated Boulder balloon series and HALOE

2007 ◽  
Vol 7 (5) ◽  
pp. 14511-14542 ◽  
Author(s):  
M. Scherer ◽  
H. Vömel ◽  
S. Fueglistaler ◽  
S. J. Oltmans ◽  
J. Staehelin
Keyword(s):  
Water Vapour ◽  
Linear Trend ◽  
Potential Temperature ◽  
Data Series ◽  
Explanatory Variables ◽  
Time Period ◽  
Corrected Data ◽  
Instrumental Bias ◽  
The Tropics ◽  
Stratospheric Water Vapour

Abstract. This paper presents an updated trend analysis of water vapour in the lower midlatitude stratosphere from the Boulder balloon-borne NOAA frostpoint hygrometer measurements and from the Halogen Occulation Experiment (HALOE). Two corrections for instrumental bias are applied to homogenise the frostpoint data series, and a quality assessment of all soundings after 1991 is presented. Linear trend estimates based on the corrected data for the period 1980–2000 are up to 40% lower than previously reported. Vertically resolved trends and variability are calculated with a multi regression analysis including the quasi-biennal oscillation and equivalent latitude as explanatory variables. In the range of 380 to 640 K potential temperature (≈14 to 25 km), the frostpoint data from 1981 to 2006 show positive linear trends between 0.3± 0.3 and 0.7±0.1%/yr. The same dataset shows trends between −0.2±0.3 and 1.0±0.3%/yr for the period 1992 to 2005. HALOE data over the same time period suggest negative trends ranging from −1.1±0.2 to −0.1±0.1%/yr. In the lower stratosphere, a rapid drop of water vapour is observed in 2000/2001 with little change since. At higher altitudes, the transition is more gradual, with slowly decreasing concentrations between 2001 and 2007. This pattern is consistent with a change induced by a drop of water concentrations at entry into the stratosphere. Previously noted differences in trends and variability between frostpoint and HALOE remain for the homogenised data. Due to uncertainties in reanalysis temperatures and stratospheric transport combined with uncertainties in observations, no quantitative inference about changes of water entering the stratosphere in the tropics could be made with the mid latitude measurements analysed here.

scholarly journals Observed Multi-Timescale Differences between Summertime Near-Surface Equivalent Temperature and Temperature for China and Their Linkage with Global Sea Surface Temperatures

Atmosphere ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 447
Author(s):  
Jingping Li ◽  
Xiao Li ◽  
Xing Li ◽  
Lian Chen ◽  
Likun Jin
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Spatial Patterns ◽  
Southern Oscillation ◽  
Linear Trend ◽  
Sea Surface ◽  
Multiple Time ◽  
Equivalent Temperature ◽  
Near Surface ◽  
Temperature Variations

Based on the ensemble empirical mode decomposition method, this study explores the differences and similarities in multiple time-scale characteristics of summer air temperature (T) and equivalent temperature (Te) over China during 1961–2017, using daily meteorological observations collected at 412 stations in China. Their relationships to global sea surface temperature variations is also discussed. Results show that both T and Te can be decomposed into five components, which includes multiple timescales, from interannual to long-term trends. The spatial patterns of each timescale’s leading mode show that the variations of Te are generally larger than that of T. Meanwhile, both T and Te are dominated by their inter-annual, multi-decadal variations and the non-linear trend. High correlations of T and Te can also be found in these major scales. The related sea surface temperature variations in these major scales also show consistent patterns, which correspond to El Niño–Southern Oscillation, Atlantic Multidecadal Oscillation and the global warming trend in the sea, respectively. In other scales, both spatial patterns of T and Te and the corresponding correlation patterns with sea surface temperature are distinguishable. The current results explore the compound changes of surface temperature-humidity during the past five decades from a new perspective, which provides some insights for a better understanding of the possible causes of climate change over China.

scholarly journals Interpreting the time variability of world-wide GPS and GOME/SCIAMACHY integrated water vapour retrievals, using reanalyses as auxiliary tools

2018 ◽  
Author(s):  
Roeland Van Malderen ◽  
Eric Pottiaux ◽  
Gintautas Stankunavicius ◽  
Steffen Beirle ◽  
Thomas Wagner ◽  
...  
Keyword(s):  
Time Series ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Water Vapour ◽  
Southern Oscillation ◽  
Linear Trend ◽  
Time Variability ◽  
The North ◽  
Integrated Water Vapour

Abstract. This study investigates different aspects of the Integrated Water Vapour (IWV) variability at 118 globally distributed Global Positioning System (GPS) sites, using additionally UV/VIS satellite retrievals by GOME, SCIAMACHY and GOME-2 (denoted as GOMESCIA below), and ERA-Interim reanalysis output at these site locations. Apart from some spatial representativeness issues at especially coastal and island sites, those three datasets correlate rather well, the lowest correlation found between GPS and GOMESCIA (0.865 on average). In this paper, we first study the geographical distribution of the frequency distributions of the IWV time series, and subsequently analyse the seasonal IWV cycle and linear trend differences among the three different datasets. Finally, both the seasonal behaviour and the long-term variability are fitted together by means of a stepwise multiple linear regression of the station’s time series, with a selection of regionally dependent candidate explanatory variables. Overall, the variables that are most frequently used and explain the largest fractions of the IWV variability are the surface temperature and precipitation. Also the surface pressure and tropopause pressure (in particular for higher latitude sites) are important contributors to the IWV time variability. All these variables also seem to account for the sign of long-term trend in the IWV time series to a large extent, when considered as explanatory variable. Furthermore, the multiple linear regression linked the IWV variability at some particular regions to teleconnection patterns or climate/oceanic indices like the North Oscillation index for West USA, the El Niňo Southern Oscillation (ENSO) for East Asia, the East Atlantic (associated with the North Atlantic Oscillation, NAO) index for Europe.

scholarly journals Using a Groundwater Adjusted Water Balance Approach and Copulas to Evaluate Spatial Patterns and Dependence Structures in Remote Sensing Derived Evapotranspiration Products

2021 ◽  
Vol 13 (5) ◽  
pp. 853
Author(s):  
Mohsen Soltani ◽  
Julian Koch ◽  
Simon Stisen
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
Spatial Pattern ◽  
Spatial Patterns ◽  
Principal Component ◽  
Small Scale ◽  
Dependence Structure ◽  
Test Case ◽  
Catchment Scale ◽  
Balance Approach

This study aims to improve the standard water balance evapotranspiration (WB ET) estimate, which is typically used as benchmark data for catchment-scale ET estimation, by accounting for net intercatchment groundwater flow in the ET calculation. Using the modified WB ET approach, we examine errors and shortcomings associated with the long-term annual mean (2002–2014) spatial patterns of three remote-sensing (RS) MODIS-based ET products from MODIS16, PML_V2, and TSEB algorithms at 1 km spatial resolution over Denmark, as a test case for small-scale, energy-limited regions. Our results indicate that the novel approach of adding groundwater net in water balance ET calculation results in a more trustworthy ET spatial pattern. This is especially relevant for smaller catchments where groundwater net can be a significant component of the catchment water balance. Nevertheless, large discrepancies are observed both amongst RS ET datasets and compared to modified water balance ET spatial pattern at the national scale; however, catchment-scale analysis highlights that difference in RS ET and WB ET decreases with increasing catchment size and that 90%, 87%, and 93% of all catchments have ∆ET < ±150 mm/year for MODIS16, PML_V2, and TSEB, respectively. In addition, Copula approach captures a nonlinear structure of the joint relationship with multiple densities amongst the RS/WB ET products, showing a complex dependence structure (correlation); however, among the three RS ET datasets, MODIS16 ET shows a closer spatial pattern to the modified WB ET, as identified by a principal component analysis also. This study will help improve the water balance approach by the addition of groundwater net in the ET estimation and contribute to better understand the true correlations amongst RS/WB ET products especially over energy-limited environments.

scholarly journals The Response of Tropical Atmospheric Energy Budgets to ENSO*

2013 ◽  
Vol 26 (13) ◽  
pp. 4710-4724 ◽  
Author(s):  
Michael Mayer ◽  
Kevin E. Trenberth ◽  
Leopold Haimberger ◽  
John T. Fasullo
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Warm Pool ◽  
Smooth Transition ◽  
Energy Budgets ◽  
Enso Events ◽  
El Niño Modoki ◽  
Static Energy ◽  
The Tropics

Abstract The variability of zonally resolved tropical energy budgets in association with El Niño–Southern Oscillation (ENSO) is investigated. The most recent global atmospheric reanalyses from 1979 to 2011 are employed with removal of apparent discontinuities to obtain best possible temporal homogeneity. The growing length of record allows a more robust analysis of characteristic patterns of variability with cross-correlation, composite, and EOF methods. A quadrupole anomaly pattern is found in the vertically integrated energy divergence associated with ENSO, with centers over the Indian Ocean, the Indo-Pacific warm pool, the eastern equatorial Pacific, and the Atlantic. The smooth transition, particularly of the main maxima of latent and dry static energy divergence, from the western to the eastern Pacific is found to require at least two EOFs to be adequately described. The canonical El Niño pattern (EOF-1) and a transition pattern (EOF-2; referred to as El Niño Modoki by some authors) form remarkably coherent ENSO-related anomaly structures of the tropical energy budget not only over the Pacific but throughout the tropics. As latent and dry static energy divergences show strong mutual cancellation, variability of total energy divergence is smaller and more tightly coupled to local sea surface temperature (SST) anomalies and is mainly related to the ocean heat discharge and recharge during ENSO peak phases. The complexity of the structures throughout the tropics and their evolution during ENSO events along with their interactions with the annual cycle have often not been adequately accounted for; in particular, the El Niño Modoki mode is but part of the overall evolutionary patterns.

scholarly journals Relationships between Southeast Australian Temperature Anomalies and Large-Scale Climate Drivers

2014 ◽  
Vol 27 (4) ◽  
pp. 1395-1412 ◽  
Author(s):  
Alexandre O. Fierro ◽  
Lance M. Leslie
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Power Spectra ◽  
Warm Season ◽  
Principal Component ◽  
Temperature Variability ◽  
Maximum Temperature ◽  
Past Century ◽  
Tasman Sea ◽  
Australian Continent

Abstract Over the past century, particularly after the 1960s, observations of mean maximum temperatures reveal an increasing trend over the southeastern quadrant of the Australian continent. Correlation analysis of seasonally averaged mean maximum temperature anomaly data for the period 1958–2012 is carried out for a representative group of 10 stations in southeast Australia (SEAUS). For the warm season (November–April) there is a positive relationship with the El Niño–Southern Oscillation (ENSO) and the Pacific decadal oscillation (PDO) and an inverse relationship with the Antarctic Oscillation (AAO) for most stations. For the cool season (May–October), most stations exhibit similar relationships with the AAO, positive correlations with the dipole mode index (DMI), and marginal inverse relationships with the Southern Oscillation index (SOI) and the PDO. However, for both seasons, the blocking index (BI, as defined by M. Pook and T. Gibson) in the Tasman Sea (160°E) clearly is the dominant climate mode affecting maximum temperature variability in SEAUS with negative correlations in the range from r = −0.30 to −0.65. These strong negative correlations arise from the usual definition of BI, which is positive when blocking high pressure systems occur over the Tasman Sea (near 45°S, 160°E), favoring the advection of modified cooler, higher-latitude maritime air over SEAUS. A point-by-point correlation with global sea surface temperatures (SSTs), principal component analysis, and wavelet power spectra support the relationships with ENSO and DMI. Notably, the analysis reveals that the maximum temperature variability of one group of stations is explained primarily by local factors (warmer near-coastal SSTs), rather than teleconnections with large-scale drivers.

Potential predictability of Southwest US rainfall : role of tropical and high-latitude variability

2021 ◽  
pp. 1-45
Keyword(s):  
Time Scale ◽  
Climate Model ◽  
Southern Oscillation ◽  
Seasonal Prediction ◽  
Seasonal Rainfall ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Potential Predictability ◽  
Subseasonal Variability ◽  
The Tropics

Abstract This study explores the potential predictability of Southwest US (SWUS) precipitation for the November-March season in a set of numerical experiments performed with the Whole Atmospheric Community Climate Model. In addition to the prescription of observed sea surface temperature and sea ice concentration, observed variability from the MERRA-2 reanalysis is prescribed in the tropics and/or the Arctic through nudging of wind and temperature. These experiments reveal how a perfect prediction of tropical and/or Arctic variability in the model would impact the prediction of seasonal rainfall over the SWUS, at various time scales. Imposing tropical variability improves the representation of the observed North Pacific atmospheric circulation, and the associated SWUS seasonal precipitation. This is also the case at the subseasonal time scale due to the inclusion of the Madden-Julian Oscillation (MJO) in the model. When additional nudging is applied in the Arctic, the model skill improves even further, suggesting that improving seasonal predictions in high latitudes may also benefit prediction of SWUS precipitation. An interesting finding of our study is that subseasonal variability represents a source of noise (i.e., limited predictability) for the seasonal time scale. This is because when prescribed in the model, subseasonal variability, mostly the MJO, weakens the El Niño Southern Oscillation (ENSO) teleconnection with SWUS precipitation. Such knowledge may benefit S2S and seasonal prediction as it shows that depending on the amount of subseasonal activity in the tropics on a given year, better skill may be achieved in predicting subseasonal rather than seasonal rainfall anomalies, and conversely.

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