Temperature Variability over Africa

2011 ◽  
Vol 24 (14) ◽  
pp. 3649-3666 ◽  
Author(s):  
Jennifer M. Collins
Keyword(s):  
Southern Oscillation ◽  
Surface Air Temperature ◽  
Recent Decade ◽  
Significant Rise ◽  
Tropospheric Temperature ◽  
Near Surface ◽  
The North ◽  
Remote Sensing Systems ◽  
Increasing Temperature ◽  
The University

Abstract The variation of near-surface air temperature anomalies in Africa between 1979 and 2010 is investigated primarily using Microwave Sounding Unit (MSU) total lower-tropospheric temperature data from the Remote Sensing Systems (RSS) and the University of Alabama in Huntsville (UAH) datasets. Significant increasing temperature trends were found in each of the following regions examined: all of Africa, Northern Hemisphere Africa, Southern Hemisphere Africa, tropical Africa, and subtropical Africa. Considering the months June–August, regions in both North and South Africa saw significantly warmer temperatures in the most recent period 1995–2010 than in the period 1979–94. However, for the months December–February, the significant warming was concentrated in the north of Africa. When the two most recent decades are compared with the period 1979–90, warming is observed over these same regions and is concentrated in the most recent decade, from 2001 to 2010. The results presented here indicate that the climate change over Africa is likely not predominantly a result of variations in the El Niño–Southern Oscillation (a teleconnection that has been previously shown to affect climate in some parts of Africa). Instead the climate changes likely occur owing to other natural variability of the climate and/or may be a result of human activity. However, even without ascertaining the specific causes, the most important finding in this work is to demonstrate that a significant rise in African temperatures occurred between 1979 and 2010.

scholarly journals The evolving response of mesopelagic fishes to declining midwater oxygen concentrations in the southern and central California Current

2018 ◽  
Vol 76 (3) ◽  
pp. 626-638 ◽  
Author(s):  
J Anthony Koslow ◽  
Pete Davison ◽  
Erica Ferrer ◽  
S Patricia A Jiménez Rosenberg ◽  
Gerardo Aceves-Medina ◽  
...  
Keyword(s):  
Baja California ◽  
Southern Oscillation ◽  
Global Climate ◽  
California Current ◽  
Deep Ocean ◽  
Near Surface ◽  
Oxygen Minimum Zones ◽  
The North ◽  
The Pacific ◽  
Oxygen Concentrations

Abstract Declining oxygen concentrations in the deep ocean, particularly in areas with pronounced oxygen minimum zones (OMZs), are a growing global concern related to global climate change. Its potential impacts on marine life remain poorly understood. A previous study suggested that the abundance of a diverse suite of mesopelagic fishes off southern California was closely linked to trends in midwater oxygen concentration. This study expands the spatial and temporal scale of that analysis to examine how mesopelagic fishes are responding to declining oxygen levels in the California Current (CC) off central, southern, and Baja California. Several warm-water mesopelagic species, apparently adapted to the shallower, more intense OMZ off Baja California, are shown to be increasing despite declining midwater oxygen concentrations and becoming increasingly dominant, initially off Baja California and subsequently in the CC region to the north. Their increased abundance is associated with warming near-surface ocean temperature, the warm phase of the Pacific Decadal oscillation and Multivariate El Niño-Southern Oscillation Index, and the increased flux of Pacific Equatorial Water into the southern CC.

scholarly journals Timing and extent of late pleistocene glaciation in the arid Central Andes of Argentina and Chile (22°-41°S)

2017 ◽  
Vol 43 (2) ◽  
pp. 697 ◽  
Author(s):  
J. Zech ◽  
C. Terrizzano ◽  
E. García-Morabito ◽  
H. Veit ◽  
R. Zech
Keyword(s):  
Southern Oscillation ◽  
Co2 Concentration ◽  
Late Glacial ◽  
Central Andes ◽  
The North ◽  
Eastern Equatorial Pacific ◽  
Southern Central ◽  
Study Sites ◽  
Increasing Temperature ◽  
Exposure Ages

The arid Central Andes are a key site to study changes in intensity and movement of the three main atmospheric circulation systems over South America: the South American Summer Monsoon (SASM), the Westerlies and the El Niño Southern Oscillation (ENSO). In this semi-arid to arid region glaciers are particularly sensitive to precipitation changes and thus the timing of past glaciation is strongly linked to changes in moisture supply. Surface exposure ages from study sites between 41° and 22°S suggest that glaciers advanced: i) prior to the global Last Glacial Maximum (gLGM) at ~40 ka in the mid (26°- 30°S) and southern Central Andes (35°-41°S), ii) in phase with the gLGM in the northern and southern Central Andes and iii) during the late glacial in the northern Central Andes. Deglaciation started synchronous with the global rise in atmospheric CO2 concentration and increasing temperature starting at ~18 ka. The pre-gLGM glacial advances likely document enhanced precipitation related to the Southern Westerlies, which shifted further to the North at that time than previosuly assumed. During the gLGM glacial advances were favored by decreased temperatures in combination with increased humidity due to a southward shifted Intertropical Convergence Zone (ITCZ) and SASM. During the late-glacial a substantial increase in moisture can be explained by enhanced upper tropospheric easterlies as response to an intensified SASM and sustained La Niña-like conditions over the eastern equatorial Pacific that lead to glacial advances in the northern Central Andes and the lake level highstand Tauca (18-14 ka) on the Altiplano. In the southernmost Central Andes at 39º-41°S, further north at 31°S and in the northernmost Central Andes at 22°S glacial remnants even point to precipitation driven glaciations older than ~115 ka and 260 ka.

scholarly journals Stratospheric Influences on the MJO-Induced Rossby Wave Train: Effects on Intraseasonal Climate

2020 ◽  
Vol 33 (1) ◽  
pp. 365-389 ◽  
Author(s):  
Lon L. Hood ◽  
Malori A. Redman ◽  
Wes L. Johnson ◽  
Thomas J. Galarneau
Keyword(s):  
Solar Cycle ◽  
Rossby Wave ◽  
Southern Oscillation ◽  
Wave Train ◽  
Winter Season ◽  
Surface Air Temperature ◽  
Quasi Biennial Oscillation ◽  
Sea Level Pressure ◽  
The North ◽  
Rossby Wave Train

AbstractThe tropical Madden–Julian oscillation (MJO) excites a northward propagating Rossby wave train that largely determines the extratropical surface weather consequences of the MJO. Previous work has demonstrated a significant influence of the tropospheric El Niño–Southern Oscillation (ENSO) on the characteristics of this wave train. Here, composite analyses of ERA-Interim sea level pressure (SLP) and surface air temperature (SAT) data during the extended northern winter season are performed to investigate the additional role of stratospheric forcings [the quasi-biennial oscillation (QBO) and the 11-yr solar cycle] in modifying the wave train and its consequences. MJO phase composites of 20–100-day filtered data for the two QBO phases show that, similar to the cool phase of ENSO, the easterly phase of the QBO (QBOE) produces a stronger wave train and associated modulation of SLP and SAT anomalies. In particular, during MJO phases 5–7, positive SLP and negative SAT anomalies in the North Atlantic/Eurasian sector are enhanced during QBOE relative to the westerly phase of the QBO (QBOW). The opposite occurs during the earliest MJO phases. SAT anomalies over eastern North America are also more strongly modulated during QBOE. Although less certain because of the short data record, there is some evidence that the minimum phase of the solar cycle (SMIN) produces a similar increased modulation of SLP and SAT anomalies. The strongest modulations of SLP and SAT anomalies are produced when two or more of the forcings are superposed (e.g., QBOE/cool ENSO, SMIN/QBOE, etc.).

Complexity-based approach for El Niño magnitude forecasting before the spring predictability barrier

2020 ◽  
Author(s):  
Jun Meng ◽  
Jingfang Fan ◽  
Josef Ludescher ◽  
Ankit Agarwala ◽  
Xiaosong Chen ◽  
...  
Keyword(s):  
Prediction Models ◽  
Southern Oscillation ◽  
Surface Air Temperature ◽  
Statistical Prediction ◽  
Analysis Tool ◽  
Strong Positive Correlation ◽  
Near Surface ◽  
Spring Predictability Barrier ◽  
Prediction Horizon ◽  
The Individual

<p>The El Niño Southern Oscillation (ENSO) is one of the most prominent interannual climate phenomena. An early and reliable ENSO forecasting remains a crucial goal, due to its serious implications for economy, society, and ecosystem. Despite the development of various dynamical and statistical prediction models in the recent decades, the “spring predictability barrier” (SPB) remains a great challenge for long (over 6-month) lead-time forecasting. To overcome this barrier, here we develop an analysis tool, the System Sample Entropy (SysSampEn), to measure the complexity (disorder) of the system composed of temperature anomaly time series in the Niño 3.4 region. When applying this tool to several near surface air temperature and sea surface temperature datasets, we find that in all datasets a strong positive correlation exists between the magnitude of El Niño and the previous calendar year’s SysSampEn (complexity). We show that this correlation allows to forecast the magnitude of an El Niño with a prediction horizon of 1 year and high accuracy (i.e., Root Mean Square Error = 0.23°C for the average of the individual datasets forecasts). For the 2018 El Niño event, our method forecasts a weak El Niño with a magnitude of 1.11±0.23°C.  Our framework presented here not only facilitates a long–term forecasting of the El Niño magnitude but can potentially also be used as a measure for the complexity of other natural or engineering complex systems.</p>

scholarly journals The Internal Multidecadal Variability of SST in the Pacific and Its Impact on Air Temperature and Rainfall over Land in the Northern Hemisphere

Atmosphere ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 153
Author(s):  
Hua Chen ◽  
Donglin He ◽  
Zhiwei Zhu
Keyword(s):  
Northern Hemisphere ◽  
Air Temperature ◽  
Critical Role ◽  
Surface Air Temperature ◽  
Ensemble Empirical Mode Decomposition ◽  
Near Surface ◽  
Multidecadal Variability ◽  
The North ◽  
Mode Decomposition ◽  
The Pacific

Based on the centennial-scale observations and re-analyses, this paper employs the ensemble empirical mode decomposition to separate the internal multidecadal variability (IMV) from the externally-forced variability of sea surface temperature (SST), and then defines new indices that represent the IMV of SST in the North Pacific (NPIMV) and South Pacific (SPIMV), respectively. The spatial structure of NPIMV/SPIMV shows remarkably positive SST anomaly only in the index-defined region; meanwhile, the temporal evolutions of NPIMV and SPIMV are uncorrelated, indicating their independence of each other. Both NPIMV and SPIMV play a critical role in the near-surface air temperature and rainfall over land in the Northern hemisphere, especially in the season when their intensity is the strongest. It is through teleconnection wave trains that NPIMV and SPIMV exert influences on remote regions. Results from another two rainfall datasets are found to be consistent in the majority of the Northern hemisphere in response to NPIMV/SPIMV, yet disagreement exists in certain regions due to large uncertainties of rainfall datasets.

scholarly journals Changes of Variability in Response to Increasing Greenhouse Gases. Part I: Temperature

2007 ◽  
Vol 20 (21) ◽  
pp. 5455-5467 ◽  
Author(s):  
R. J. Stouffer ◽  
R. T. Wetherald
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Annual Data ◽  
Tropospheric Temperature ◽  
High Latitudes ◽  
Near Surface ◽  
Temperature Variance ◽  
General Reduction

Abstract This study documents the temperature variance change in two different versions of a coupled ocean–atmosphere general circulation model forced with estimates of future increases of greenhouse gas (GHG) and aerosol concentrations. The variance changes are examined using an ensemble of 8 transient integrations for the older model version and 10 transient integrations for the newer one. Monthly and annual data are used to compute the mean and variance changes. Emphasis is placed upon computing and analyzing the variance changes for the middle of the twenty-first century and compared with those found in a control integration. The large-scale variance of lower-tropospheric temperature (including surface air temperature) generally decreases in high latitudes particularly during fall due to a delayed onset of sea ice as the climate warms. Sea ice acts to insolate the atmosphere from the much larger heat capacity of the ocean. Therefore, the near-surface temperature variance tends to be larger over the sea ice–covered regions, than the nearby ice-free regions. The near-surface temperature variance also decreases during the winter and spring due to a general reduction in the extent of sea ice during winter and spring. Changes in storminess were also examined and were found to have relatively little effect upon the reduction of temperature variance. Generally small changes of surface air temperature variance occurred in low and midlatitudes over both land and oceanic areas year-round. An exception to this was a general reduction of variance in the equatorial Pacific Ocean for the newer model. Small increases in the surface air temperature variance occur in mid- to high latitudes during the summer months, suggesting the possibility of more frequent and longer-lasting heat waves in response to increasing GHGs.

scholarly journals Seasonal-to-Interannual Prediction Skills of Near-Surface Air Temperature in the CMIP5 Decadal Hindcast Experiments

2016 ◽  
Vol 29 (4) ◽  
pp. 1511-1527 ◽  
Author(s):  
Jung Choi ◽  
Seok-Woo Son ◽  
Yoo-Geun Ham ◽  
June-Yi Lee ◽  
Hye-Mi Kim
Keyword(s):  
Air Temperature ◽  
Climate Models ◽  
Southern Oscillation ◽  
Surface Air Temperature ◽  
Equatorial Pacific ◽  
Prediction Skill ◽  
Good Opportunity ◽  
Near Surface ◽  
Global Mean

Abstract This study explores the seasonal-to-interannual near-surface air temperature (TAS) prediction skills of state-of-the-art climate models that were involved in phase 5 of the Coupled Model Intercomparison Project (CMIP5) decadal hindcast/forecast experiments. The experiments are initialized in either November or January of each year and integrated for up to 10 years, providing a good opportunity for filling the gap between seasonal and decadal climate predictions. The long-lead multimodel ensemble (MME) prediction is evaluated for 1981–2007 in terms of the anomaly correlation coefficient (ACC) and mean-squared skill score (MSSS), which combines ACC and conditional bias, with respect to observations and reanalysis data, paying particular attention to the seasonal dependency of the global-mean and equatorial Pacific TAS predictions. The MME shows statistically significant ACCs and MSSSs for the annual global-mean TAS for up to two years, mainly because of long-term global warming trends. When the long-term trends are removed, the prediction skill is reduced. The prediction skills are generally lower in boreal winters than in other seasons regardless of lead times. This lack of winter prediction skill is attributed to the failure of capturing the long-term trend and interannual variability of TAS over high-latitude continents in the Northern Hemisphere. In contrast to global-mean TAS, regional TAS over the equatorial Pacific is predicted well in winter. This is mainly due to a successful prediction of the El Niño–Southern Oscillation (ENSO). In most models, the wintertime ENSO index is reasonably well predicted for at least one year in advance. The sensitivity of the prediction skill to the initialized month and method is also discussed.

scholarly journals El Niño–Global Atmospheric Oscillation as the Main Mode of Interannual Climate Variability

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1443
Author(s):  
Ilya V. Serykh ◽  
Dmitry M. Sonechkin
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Surface Air Temperature ◽  
The Arctic ◽  
Northern Eurasia ◽  
Main Mode ◽  
Trade Winds ◽  
Near Surface ◽  
Atmospheric Oscillation

The interannual variability of the global mean monthly anomalies of near-surface air temperature, sea-level pressure, wind speed near the surface, amount of precipitation and total cloudiness was investigated. The amplitudes of the anomalies of these hydrometeorological characteristics between opposite phases of the Global Atmospheric Oscillation (GAO) were calculated. The regional element of the GAO in the tropics of the Indian and Pacific Oceans is the Southern Oscillation. The results show that the oscillations of these characteristics are associated with the GAO not only in the tropical belt of the Earth but also in the middle and high latitudes, especially in the Arctic and northern Eurasia. The physical mechanism by which the transition of the GAO from the negative to the positive phase influences the weakening of the Pacific trade winds, and, as a consequence, the onset of El Niño is described.

scholarly journals How large does a large ensemble need to be?

2020 ◽  
Vol 11 (4) ◽  
pp. 885-901
Author(s):  
Sebastian Milinski ◽  
Nicola Maher ◽  
Dirk Olonscheck
Keyword(s):  
Southern Oscillation ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
Forced Response ◽  
Ensemble Size ◽  
Max Planck ◽  
Large Ensemble ◽  
Acceptable Error ◽  
Near Surface ◽  
Temperature And Precipitation

Abstract. Initial-condition large ensembles with ensemble sizes ranging from 30 to 100 members have become a commonly used tool for quantifying the forced response and internal variability in various components of the climate system. However, there is no consensus on the ideal or even sufficient ensemble size for a large ensemble. Here, we introduce an objective method to estimate the required ensemble size that can be applied to any given application and demonstrate its use on the examples of global mean near-surface air temperature, local temperature and precipitation, and variability in the El Niño–Southern Oscillation (ENSO) region and central United States for the Max Planck Institute Grand Ensemble (MPI-GE). Estimating the required ensemble size is relevant not only for designing or choosing a large ensemble but also for designing targeted sensitivity experiments with a model. Where possible, we base our estimate of the required ensemble size on the pre-industrial control simulation, which is available for every model. We show that more ensemble members are needed to quantify variability than the forced response, with the largest ensemble sizes needed to detect changes in internal variability itself. Finally, we highlight that the required ensemble size depends on both the acceptable error to the user and the studied quantity.

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