Wintertime Surface Temperature Research Articles

Sensitivity of Easterly QBO’s Boreal Winter Teleconnections and Surface Impacts to SSWs

Abstract The quasi-biennial oscillation (QBO) is thought to influence boreal winter surface conditions over Asia and around the North Atlantic. Confirming if these responses are robust is complicated by the QBO having multiple pathways to influence surface conditions as well as internal variability. The reanalysis record suggests that sudden stratospheric warmings (SSWs), breakdowns of the polar vortex that can elicit persistent surface impacts, are more frequent during easterly QBO (EQBO). Hence, this modulated frequency of SSWs may account for some of the EQBO surface responses. However, many climate models do not reproduce this QBO–SSW relationship, perhaps because it is noise or because the model QBOs are deficient. We circumvent these issues by using an ensemble of fixed boundary condition branched simulations in which a realistic EQBO is prescribed in control simulations previously devoid of a QBO, allowing us to isolate the transient atmospheric response to EQBO. Imposing EQBO accelerates the tropical upper-tropospheric wind, shifts the subtropical jet poleward, and attenuates the polar vortex. Interestingly, the latter is not entirely dependent on the statistically significant increase in SSW frequency due to EQBO. Corroborating observations, EQBO is associated with warmer surface temperatures over Asia and negative North Atlantic Oscillation (NAO) conditions. We then subsample the branched/control simulations based on which EQBO members have SSWs. The negative NAO response is primarily associated with more frequent SSWs, while the Asia warming develops irrespective of SSWs. These results have implications for wintertime predictability and clarify the pairing of particular QBO teleconnections with certain surface impacts. Significance Statement The QBO is one of the few parts of the Earth system that is predictable months in advance and that also elicits global effects on surface temperature, circulation, and precipitation. Unfortunately, climate models and operational forecast systems do not simulate the QBO well and it is not always clear how robust the global impacts of the QBO are. Here, we impose the QBO in idealized model simulations, which modulates wintertime surface temperature and precipitation over Asia, the North Atlantic, Europe, and Africa in a manner consistent with observations. This work substantiates the importance of climate and forecast models properly simulating the QBO.

Impacts of early-winter Arctic sea-ice loss on wintertime surface temperature in China

Impacts of early-winter Arctic sea-ice loss on wintertime surface temperature in China

Relationship between the East Asian Summer and Winter Monsoons at Obliquity Time Scales

Abstract The relationship between the East Asian summer monsoon (EASM) and East Asian winter monsoon (EAWM) across time scales has been an interesting topic for decades. In this study, we quantitatively investigate the EASM–EAWM relationship at the obliquity time scales using a set of accelerated transient simulations. By comparing different indices defined with different variables, we find that the EASM and EAWM intensities are positively correlated under obliquity forcing. High obliquity leads to warmer summertime and cooler wintertime surface temperatures, with a stronger response observed over land than over the oceans. The warmer summertime and cooler wintertime temperature responses are accompanied by a strengthened Asian low in summer and Siberian high in winter, with enhanced southerlies in summer and northerlies in winter, indicating an enhanced EASM and EAWM. Modulated by ice sheet forcing, however, the evolution of the simulated EAWM shifts toward the ice sheet maximum, such that the circulation-based EASM–EAWM relationship in the realistically forced simulation exhibits a phase shift of approximately 11 kyr, closer to the phase between the composite δ18O and loess grain size in observations. Our results may have implications for better understanding the distinct changes in the proxy-based EASM–EAWM relationship before and after the rapid growth of global ice volume at around 3 Ma. Significance Statement Studying the relationship between the EASM and EAWM can help us understand the characteristics and mechanisms of the regional climate in response to external forcings at different time scales. By investigating the EASM–EAWM relationship over the past 300 000 years, we find that, forced by obliquity variations, the EASM and EAWM are positively correlated at the obliquity time scales. The ice sheet forcing, meanwhile, also influences the circulation over East Asia and modulates the evolutionary phases between the EASM and EAWM. Our results highlight the importance of the combined impacts of orbital parameters and ice sheets on past climate changes over Asia.

A modelling study on quantifying the impact of urbanization and regional effects on the wintertime surface temperature over a rapidly-growing tropical city

Climate change and sustainability are among the most widely used terms among policymakers and the scientific community in recent times. However, climate action or steps to sustainable growth in cities in the global south are mostly borrowed from general studies at a few large urban agglomerations in the developed world. There are very few modeling studies over south Asia to understand and quantify the impact of climate change and urbanization on even the most primary meteorological variable, such as temperature. Such quantifications are difficult to estimate due to the non-availability of relevant long-term observational datasets. In this modeling study, an attempt is made to understand the urban heat island (UHI), its transition, and the segregation of regional climate change effects and urbanization over the rapidly growing tier 2 tropical smart city Bhubaneswar in India. The model is able to simulate the UHI for both land surface temperature, called the SUHI, and 2-m air temperature, called UHI, reasonably well. Their magnitudes were ~ 5 and 2.5°C, respectively. It is estimated that nearly 60–70% of the overall air and 70–80% of the land surface temperature increase during nighttime over the city between the period 2004 and 2015 is due to urbanization, with the remaining due to the regional/non-local effects.

On the Importance of Representing Snow Over Sea‐Ice for Simulating the Arctic Boundary Layer

AbstractCorrectly representing the snow on sea‐ice has great potential to improve cryosphere‐atmosphere coupling in forecasting and monitoring (e.g., reanalysis) applications, via improved modeling of surface temperature, albedo and emissivity. This can also enhance the all‐weather all‐surface coupled data assimilation for atmospheric satellite radiances. Using wintertime observations from two Arctic field campaigns, SHEBA and N‐ICE2015, and satellite data, we explore the merits of different approaches to represent the snow over sea‐ice in a set of 5‐day coupled forecasts. Results show that representing the snow insulation effects is essential for capturing the wintertime surface temperature variability over sea‐ice and its response to changes in the atmospheric forcing. Modeling the snow over sea‐ice improves the representation of strong cooling events, reduces surface temperature biases in clear‐sky conditions and improves the simulation of surface‐based temperature inversions. In clear‐sky conditions, when using a multi‐layer snow scheme the root‐mean‐squared error in the surface temperature is reduced by about 60% for both N‐ICE2015 and SHEBA. This study also highlights the role of compensating errors in different components of the surface energy budget in the Arctic boundary layer. During warm air intrusions, errors in the surface temperature increase when cloud phase and cloud radiative processes are misrepresented in the model, inducing large errors in the net radiative energy at the surface. This work indicates that numerical weather prediction systems can fully benefit from a better representation of snow over sea‐ice, for example, with multi‐layer snow schemes, combined with improvements to other boundary layer processes including mixed phase clouds.

Improvements in Wintertime Surface Temperature Variability in the Community Earth System Model Version 2 (CESM2) Related to the Representation of Snow Density

AbstractThe Community Earth System Model (CESM) is widely used for the prediction and understanding of climate variability and change. Accurate simulation of the behavior of near surface air temperature (T2m) is critical in such a model for addressing societally relevant problems. However, previous versions of CESM suffered from an overestimation of wintertime T2m variability in Northern Hemisphere (NH) land regions. Here, it is shown that the latest version of CESM (CESM2) exhibits a much improved representation of wintertime T2m variability compared to its predecessor and it now compares well with observations. A series of targeted experiments reveal that an important contributor to this improvement is the local effects of changes to the representation of snow density within the land surface component. Increased snow densities in CESM2 lead to enhanced conductance of the snow layer. As a result, larger heat fluxes across the snow layer are induced in the presence of T2m anomalies, leading to a greater dampening of surface and near surface atmospheric temperature anomalies. The implications for future projections with CESM2 are also considered through comparison of the CESM1 and CESM2 large ensembles. Aligned with the reduction in surface temperature variability, compared to CESM1, CESM2 exhibits reduced ensemble spread in future projections of NH winter mean temperature and a smaller decline in daily wintertime T2m variability under climate change. Overall, this improvement has increased the accuracy of CESM2 as a tool for the study of wintertime T2m variability and change.

Advancing interpretability of machine-learning prediction models

Abstract This paper proposes an approach to diagnosing the skill of a machine-learning prediction model based on finding combinations of variables that minimize the normalized mean square error of the predictions. This technique is attractive because it compresses the positive skill of a forecast model into the smallest number of components. The resulting components can then be analyzed much like principal components, including the construction of regression maps for investigating sources of skill. The technique is illustrated with a machine-learning model of week 3–4 predictions of western US wintertime surface temperatures. The technique reveals at least two patterns of large-scale temperature variations that are skillfully predicted. The predictability of these patterns is generally consistent between climate model simulations and observations. The predictability is determined largely by sea surface temperature variations in the Pacific, particularly the region associated with the El Nino-Southern Oscillation. This result is not surprising, but the fact that it emerges naturally from the technique demonstrates that the technique can be helpful in “explaining” the source of predictability in machine-learning models.

Dynamical evidence for causality between Northern Hemisphere annular mode and winter surface air temperature over Northeast Asia

Past results [Thompson and Wallace in Geophys Res Lett 25(9):1297–1300, 1998; Science 293(5527):85–89, 2001; Wallace and Thompson in J Clim 15(14):1987–1991, 2002a] indicate that over the Eurasian continent, North America, and East Asia, wintertime surface temperatures tend to be warmer (colder) on high-index (low-index) Northern Hemisphere annular mode (NAM). However, a linear correlation is neither necessary nor sufficient to establish causality between them. Here, we apply a recently developed method, convergent cross mapping (CCM), to examine the causal connections between NAM and wintertime surface air temperature (SAT) over Northeast Asia. Our analysis indicates that both NAM and SAT exhibit nonlinear dynamical structure and that NAM information is encoded in the SAT data but not the other way around. This indicates a causality between them in the direction NAM → SAT. This result opens the possibility to use the NAM index as the external driving factor to forecast winter SAT over Northeast Asia.

Coherent changes of wintertime surface air temperatures over North Asia and North America

The surface temperature variance and its potential change with global warming are most prominent in winter over Northern Hemisphere mid-high latitudes. Consistent wintertime surface temperature variability has been observed over large areas in Eurasia and North America on a broad range of time scales. However, it remains a challenge to quantify where and how the coherent change of temperature anomalies occur over the two continents. Here we demonstrate the coherent change of wintertime surface temperature anomalies over North Asia and the central-eastern parts of North America for the period from 1951 to 2015. This is supported by the results from the empirical orthogonal function analysis of surface temperature and temperature trend anomalies over the Northern Hemisphere extratropical lands and the timeseries analysis of the regional averaged temperature anomalies over North Asia and the Great Plains and Great Lakes. The Asian-Bering-North American (ABNA) teleconnection provides a pathway to connect the regional temperature anomalies over the two continents. The ABNA is also responsible for the decadal variation of the temperature relationship between North Asia and North America.

Exploring the combined effects of the Arctic Oscillation and ENSO on the wintertime climate over East Asia using self‐organizing maps

AbstractTo examine the combined effects of the different spatial patterns of the Arctic Oscillation (AO)‐related sea level pressure (SLP) anomalies and the El Niño–Southern Oscillation (ENSO)‐related sea surface temperature (SST) anomalies on the wintertime surface temperature anomalies over East Asia, a nonlinear method based on self‐organizing maps is employed. Investigation of identified regimes reveals that the AO can affect East Asian temperature anomalies when there are significant SLP anomalies over the Arctic Ocean and northern parts of Eurasian continent. Analogously, ENSO is found to affect East Asian temperature anomalies when significant SST anomalies are present over the tropical central Pacific. The regimes with the warmest and coldest temperature anomalies over East Asia are both associated with the negative phase of the AO. The ENSO‐activated, Pacific‐East Asian teleconnection pattern could affect the higher latitude continental regions when the impact of the AO is switched off. When the spatial patterns of the AO and ENSO have significant, but opposite, impacts on the coastal winds, no obvious temperature anomalies can be observed over south China. Further, the circulation state with nearly the same AO and Niño3 indices may drive rather different responses in surface temperature over East Asia. The well‐known continuous weakening (recovery) of the East Asian winter monsoon that occurred around 1988 (2009) can be attributed to the transitions of the spatial patterns of the SLP anomalies over the Arctic Ocean and Eurasian continent, through their modulation on the occurrences of the Ural and central Siberian blocking events.

A dynamical systems approach to studying midlatitude weather extremes

AbstractExtreme weather occurrences carry enormous social and economic costs and routinely garner widespread scientific and media coverage. The ability to predict these events is therefore a topic of crucial importance. Here we propose a novel predictability pathway for extreme events, by building upon recent advances in dynamical systems theory. We show that simple dynamical systems metrics can be used to identify sets of large‐scale atmospheric flow patterns with similar spatial structure and temporal evolution on time scales of several days to a week. In regions where these patterns favor extreme weather, they afford a particularly good predictability of the extremes. We specifically test this technique on the atmospheric circulation in the North Atlantic region, where it provides predictability of large‐scale wintertime surface temperature extremes in Europe up to 1 week in advance.

An isoline separating relatively warm from relatively cool wintertime forest surface temperatures for the southeastern United States

Forest-oriented climate mitigation policies promote forestation as a means to increase uptake of atmospheric carbon to counteract global warming. Some have pointed out that a carbon-centric forest policy may be overstated because it discounts biophysical aspects of the influence of forests on climate. In extra-tropical regions, many climate models have shown that forests tend to be warmer than grasslands and croplands because forest albedos tend to be lower than non-forest albedos. A lower forest albedo results in higher absorption of solar radiation and increased sensible warming that is not offset by the cooling effects of carbon uptake in extra-tropical regions. However, comparison of forest warming potential in the context of climate models is based on a coarse classification system of tropical, temperate, and boreal. There is considerable variation in climate within the broad latitudinal zonation of tropical, temperate, and boreal, and the relationship between biophysical (albedo) and biogeochemical (carbon uptake) mechanisms may not be constant within these broad zones. We compared wintertime forest and non-forest surface temperatures for the southeastern United States and found that forest surface temperatures shifted from being warmer than non-forest surface temperatures north of approximately 36°N to cooler south of 36°N. Our results suggest that the biophysical aspects of forests' influence on climate reinforce the biogeochemical aspects of forests' influence on climate south of 36°N. South of 36°N, both biophysical and biogeochemical properties of forests appear to support forestation as a climate mitigation policy. We also provide some quantitative evidence that evergreen forests tend to have cooler wintertime surface temperatures than deciduous forests that may be attributable to greater evapotranspiration rates.

QBO‐dependent relation between electron precipitation and wintertime surface temperature

Recent research has shown that energetic particle precipitation into the upper atmosphere can change ion and neutral chemistry, e.g., by enhancing NOxconcentration in the mesosphere, which, in turn, can affect stratospheric ozone balance under appropriate conditions. It has been suggested that this may affect the surface temperatures at high latitudes by modulating tropospheric circulation. Motivated by such results, we compare here the wintertime energetic electron precipitation (EEP) with North Atlantic Oscillation (NAO) and surface air temperature (SAT) in the Northern Hemisphere. We use the recently recalibrated energetic electron data from the Medium Energy Proton and Electron Detector instrument of the National Oceanic and Atmospheric Administration (NOAA)/Polar Orbiting Environment Satellites in two energy ranges (30–100 keV and 100–300 keV), the NAO index from NOAA, and the NASA Goddard Institute for Space Studies surface temperature analysis for years 1980–2010. We find a statistically significant correlation between EEP and the NAO index and also between EEP and SAT in certain geographic regions. The strongest negative correlation is found in Northeast Canada/Greenland, while the strongest positive correlation is found in North Siberia/Barents Sea, in agreement with similar studies using global geomagnetic activity as a proxy for particle precipitation. We find higher correlation when the two winters (1984/1985 and 2003/2004) of unprecedentedly strong sudden stratospheric warmings are excluded. We also find that the different phases of quasi‐biennial oscillation (QBO; observed at 30 hPa) lead to dramatically different correlation patterns, with easterly QBO producing considerably stronger and spatially wider correlation and larger temperature response than westerly QBO.

Wintertime Temperature Variability over Kingdom of Saudi Arabia

Mean wintertime temperature (December, January, February) recorded at 26 weather stations distributed across Kingdom of Saudi Arabia (KSA) were analyzed to reveal spatial and temporal patterns of long-term trends. The behavior of wintertime temperature since 1979 is examined with regard to the persistence, non-linear trends and inter-decadal variations. The coefficient of variability (COV) of winter temperature decreases gradually from north to south of KSA. The higher values of COV occur north and northeast of KSA. The higher values of winter COV over north and north east of KSA is due to the effect of the Traveling Mediterranean depressions and its interaction with the inverted-V shape trough of the Sudan low. Relationship between COV and latitudes is highly significant, while with longitudes is not significant. The Mann-Kendal statistical rank test illustrates that positive trends (warming) in winter temperature series occur over the all stations and the trends are significant at mid and southern region of the KSA. Recent warming has only occurred during the last two decades at most stations. While cooling in wintertime surface temperature appears for the short period of about 5 years, 1979-1983 and 1988-1993. These trends are in general consistence with trends in the global mean surface temperature.

Higher precision estimates of regional polar warming by ensemble regression of climate model projections

This study presents projections of twenty-first century wintertime surface temperature changes over the high-latitude regions based on the third Coupled Model Inter-comparison Project (CMIP3) multi-model ensemble. The state-dependence of the climate change response on the present day mean state is captured using a simple yet robust ensemble linear regression model. The ensemble regression approach gives different and more precise estimated mean responses compared to the ensemble mean approach. Over the Arctic in January, ensemble regression gives less warming than the ensemble mean along the boundary between sea ice and open ocean (sea ice edge). Most notably, the results show 3 °C less warming over the Barents Sea (~7 °C compared to ~10 °C). In addition, the ensemble regression method gives projections that are 30 % more precise over the Sea of Okhostk, Bering Sea and Labrador Sea. For the Antarctic in winter (July) the ensemble regression method gives 2 °C more warming over the Southern Ocean close to the Greenwich Meridian (~7 °C compared to ~5 °C). Projection uncertainty was almost half that of the ensemble mean uncertainty over the Southern Ocean between 30° W to 90° E and 30 % less over the northern Antarctic Peninsula. The ensemble regression model avoids the need for explicit ad hoc weighting of models and exploits the whole ensemble to objectively identify overly influential outlier models. Bootstrap resampling shows that maximum precision over the Southern Ocean can be obtained with ensembles having as few as only six climate models.

The Changing Relationship between Surface Temperatures and Indian Monsoon Rainfall with the Phase of ESI Tendency

Effective Strength Index (ESI) is the relative strength of NAO and SO. ESI tendency is the algebraic difference between April-ESI and January-ESI and it represents the simultaneous evolution of NAO and SO from winter to spring. During positive (negative) phase of ESI tendency, NAO restores positive (negative) phase and SO restores negative (positive) phase before the beginning of summer season. Thus during contrasting phases (positive and negative) of ESI tendency, the evolution of NAO and SO is out of phase. In this paper we have studied the spatial and temporal variability of winter-time temperature field over Europe, Arabian Sea and Bay of Bengal during contrasting phases of ESI tendency. The study reveals that during positive (negative) ESI tendency, smaller (larger) region of Europe is showing significant winter-time cooling (warming) at surface. The relationship between winter-time surface temperature over above regions and Indian summer monsoon rainfall (ISMR) also shows spatial and temporal variability. The probable explanation for this change in the relationship is discussed in the paper. Two sets of temperature parameters for two different phases of ESI tendency are found out. Multiple regression equations are developed for the prediction of ISMR in each phase of ESI tendency. The performance of these equations is also discussed in this paper.

Causes of early Holocene desertification in arid central Asia

Paleoclimate records of effective moisture (precipitation minus evaporation, or P–E) show a dry (low effective moisture) period in mid-latitude arid/semi-arid central Asia during the early Holocene (11,000–8,000 years ago) relative to the middle and late Holocene, in contrast to evidence for greater-than-present precipitation at the same time in the south and east Asian monsoonal areas. To investigate the spatial differences in climate response over mid-latitude central Asia and monsoonal Asia we conducted a series of simulations with the Community Climate System Model version 3 coupled climate model for the early, middle and late Holocene. The simulations test the climatic impact of all important forcings for the early Holocene, including changes in orbital parameters, the presence of the remnant Laurentide ice sheet and deglacial freshening of the North Atlantic. Model results clearly show the early Holocene patterns indicated by proxy records, including both the decreased effective moisture in arid central Asia, which occurs in the model primarily during the winter months, and the increase in summer monsoon precipitation in south and east Asia. The model results suggest that dry conditions in the early Holocene in central Asia are closely related to decreased water vapor advection due to reduced westerly wind speed and less evaporation upstream from the Mediterranean, Black, and Caspian Seas in boreal winter. As an extra forcing to the early Holocene climate system, the Laurentide ice sheet and meltwater fluxes have a substantial cooling effect over high latitudes, especially just over and downstream of the ice sheets, but contribute only to a small degree to the early Holocene aridity in central Asia. Instead, most of the effective moisture signal can be explained by orbital forcing decreasing the early Holocene latitudinal temperature gradient and wintertime surface temperature. We find little evidence for regional subsidence related to a stronger summer Asian monsoon in forcing early Holocene aridity in central Asia, as has been previously hypothesized.

Physical Mechanisms of the Wintertime Surface Air Temperature Variability in South Korea and the near-7-Day Oscillations

Abstract The first three principal modes of wintertime surface temperature variability in Seoul, South Korea (37.33°N, 126.59°E), are extracted from the 1979–2008 observed records via cyclostationary EOF (CSEOF) analysis. The first mode represents the seasonal cycle, the principle physical mechanism of which is associated with the continent–ocean sea level pressure contrast. The second mode mainly describes the overall wintertime warming or cooling. The third mode depicts subseasonal fluctuations of surface temperature. Sea level pressure anomalies to the west of South Korea (eastern China) and those with an opposite sign to the east of South Korea (Japan) are a major physical factor both for the second mode and the third mode. These sea level pressure anomalies with opposite signs alter the amount of warm air to the south of South Korea, which changes the surface temperature in South Korea. The PC time series of the seasonal cycle is significantly correlated with the East Asian winter monsoon index and exhibits a conspicuous downward trend. The PC time series of the second mode exhibits a positive trend. These trends imply that the wintertime surface temperature in South Korea has increased and the seasonal cycle has weakened gradually over the past 30 yr; the sign of greenhouse warming is clear in both PC time series. The ∼7-day oscillations are a major component of high-frequency variability in much of the analysis domain and are a manifestation of Rossby waves. Rossby waves aloft result in the concerted variation of physical variables in the atmospheric column. Due to the stronger mean zonal wind, the disturbances by Rossby waves propagate eastward at ∼8–12 m s−1; the passing of Rossby waves with alternating signs produces the ∼7-day temperature oscillations in South Korea.

An Improved Parameterization for Simulating Arctic Cloud Amount in the CCSM3 Climate Model

Abstract A simple alternative parameterization for predicting cloud fraction in the Community Climate System Model, version 3 (CCSM3) global climate model is presented. This formula, dubbed “freeezedry,” is designed to alleviate the bias of excessive low clouds during polar winter by reducing the cloud amount under very dry conditions. During winter, freezedry decreases the low cloud amount over the coldest regions in high latitudes by over 50% locally and more than 30% averaged across the Arctic. The cloud reduction causes an Arctic-wide drop of 15 W m−2 in surface cloud radiative forcing (CRF) during winter and about a 50% decrease in mean annual Arctic CRF. Consequently, wintertime surface temperatures fall by up to 4 K on land and 2–8 K over the Arctic Ocean, thus significantly reducing the model’s pronounced warm bias. Freezedry also affects CCSM3’s sensitivity to greenhouse forcing. In a transient-CO2 experiment, the model version with freezedry warms up to 20% less in the North Polar and South Polar regions (1.5- and 0.5-K-smaller warming, respectively). Paradoxically, the muted high-latitude response occurs despite a much larger increase in cloud amount with freezedry during nonsummer months (when clouds warm the surface), apparently because of the colder modern reference climate. While improving the polar climate simulation in CCSM3, freezedry has virtually no influence outside of very cold regions and has already been implemented in another climate model, the Global Environmental and Ecological Simulation of Ecological Systems, version 1 (GENESIS1). Furthermore, the simplicity of this parameterization allows it to be readily incorporated into other GCMs, many of which also suffer from excessive wintertime polar cloudiness.

Wintertime surface temperature in Egypt in relation to the associated atmospheric circulation

AbstractMean wintertime temperatures (December, January, February) recorded during the period 1905–2000 at 18 weather stations distributed across Egypt were analysed to reveal spatial and temporal patterns of long‐term trends. The relationship between winter atmospheric circulation indices and winter temperature in Egypt is examined using correlation analysis. The atmospheric circulation is represented by four indices: the well‐known El Niño–southern oscillation (ENSO), North Atlantic oscillation (NAO) index, East Atlantic–West Russia (EAWR) index, and East Atlantic (EA) index.Surface temperature is a stable climatic element whose coefficient of variation (COV) is lower during winter. A statistically significant relation between COV and latitude indicates that stations in the south, Upper Egypt, are more variable than stations in the north, Lower Egypt. Increasing and decreasing winter surface temperature trends were found. In general, wintertime temperature has increased (warming) at most stations. Decreasing trends (cooling) are observed mainly over Upper Egypt. The upward trends in mean winter temperature during the 1910s–30s, mid 1970s, and early 1980s–2000 and the downward trends during the 1940s and 1960s are prominent features of the temporal distributions. The warming period that occurred early in the century may be explained by changes in circulation. Striking upward trends are most remarkable during the last 20 years. This could be attributed not only to human activities, but also to atmospheric circulation changes. No detectable connection between Egypt temperature and either ENSO or EA index was found during winter. A statistically significant negative relationship between winter temperature and winter NAO index can be observed. The NAO index is more dominant in determining winter temperature than ENSO circulation. A significantly stronger negative relationship between temperature over Egypt and the winter EAWR index values is detected. Copyright © 2004 Royal Meteorological Society