Surface Air Temperature Patterns Research Articles

Decadal Variations in the Meridional Thermal Contrast in East Asia and Its Adjacent Regions: Relative Roles of External Forcing and Internal Variability

Abstract Against the backdrop of global warming, the Eurasian continent and its surrounding areas have experienced ununiform warming in recent decades. Variations in the meridional thermal contrast (MTC) in East Asia and its adjacent regions have a critical influence on the East Asian summer monsoon (EASM); therefore, its forcings were analyzed in this study. The results show that the MTC in East Asia and the surrounding regions showed significant decadal changes during the interval 1960–2014, with a decadal strengthening in the late 1970s and a decadal weakening in the late 1990s. Further investigation showed that internal variability was the dominant control on these two decadal changes of MTC, accounting for 135% and 78.5% of the two observed changes in the 1970s and 1990s, respectively. Based on pacemaker experiments and a method that reconstructs decadal changes in the interdecadal Pacific oscillation (IPO), we found that a positive phase of the IPO tends to cause cooling in the low latitudes and warming in the mid–high latitudes and that a negative phase of the IPO tends to cause warming in the low latitudes and cooling in the mid–high latitudes, which in turn can explain 54.4% and 35.8% of the two internally generated decadal changes in the MTC, respectively. The Atlantic multidecadal oscillation (AMO), when in the same phase as the IPO, exhibits an opposing pattern of surface air temperature. This only had a significant influence in the late 1990s, where it explained 37.9% of the internally generated decadal changes in the MTC. Our findings highlight that internal variability, especially that relating to the IPO and the AMO, should be considered when predicting future changes in thermal conditions in East Asia and its adjacent regions.

A Pan–North Pacific Wintertime Surface Air Temperature Pattern Influenced by the SST Anomalies over the Kuroshio and Oyashio Extension

Abstract A new wintertime surface air temperature (SAT) pattern, called the Asia–Kuroshio and Oyashio Extension–North America (AKNA) pattern, is identified over the pan–North Pacific region (85°E–85°W, 25°–65°N) based on NCEP reanalysis data. The AKNA pattern is likely to influence the climate of the extratropical area of Asia and North America via two SAT dipoles and has a significant impact on the wintertime extremely cold weather along the eastern coastal regions of East Asia. Simulations using an atmospheric general circulation model indicate that wintertime sea surface temperature anomalies (SSTa) in the Kuroshio and Oyashio Extension (KOE) region can force an equivalent barotropic atmospheric ridge downstream and weaken the Siberian high and Alaska atmospheric ridge, resulting in the formation of the AKNA pattern. This circulation pattern tends to intensify the midlatitude (40°–60°N) westerlies over East Asia, which inhibits the southward invasion of the cold air into southern East Asia. Further diagnostic analysis indicates that the KOE SSTa can modulate the variation of storm track and westerlies by affecting baroclinic instability and eddy–mean flow interaction. Moreover, the KOE SSTa can provide a favorable environment for the development of the local atmospheric ascending motion and secondary circulation across the KOE SSTa, thereby affecting variability of the free atmosphere. Significance Statement This study aims to build a connection between the wintertime extratropical climate and the variation of the Kuroshio and Oyashio Extension. This work isolated a new wintertime surface air temperature (SAT) pattern over mid–high-latitude Asia and North America, which explains a considerable proportion of cold extremes over the eastern regions of East Asia. The reanalysis data and model simulations indicate that the temporal variability of the SAT pattern is influenced by the change of sea surface temperature in the Kuroshio and Oyashio Extension. These findings emphasize the important role of midlatitude air–sea interaction in the modulation of the mid–high-latitude climate.

On the coupled interdecadal variations of the extra‐tropical surface air temperature and the isentropic meridional airmass transport in Northern winter

AbstractBased on the ERA5 reanalysis since the 1950s, this study investigates the coherent inter‐decadal variations of the winter continental surface air temperature (SAT) between the Eurasian (EUA) and the North American continents in the past 70 years. The SAT variation over the two continents can be characterized with five typical periods successively from a ‘both‐warmer’ (1950s–1960s), to a ‘both‐colder’ (1960s–1980s), and then a ‘EUA‐warmer’ (1980s–1990s) followed by another ‘both‐warmer’ (1990s–2000s) and a ‘EUA‐colder’ (2000s–2010s) period. Such periodic variation of the SAT is closely coupled with changes of the low isentropic‐level meridional mass transport (IMMT), as manifested by the coupling relationship between the midlatitude SAT and the net IMMT out of the polar circle, in terms of their zonal patterns and geographical patterns. The SAT variation can be well reconstructed with the first two leading maximum covariance analysis (MCA) modes between the SAT and IMMT. The first leading MCA mode (MCA1) mainly dominates a ‘EUA‐warmer/colder’ pattern, while the second (MCA2) dominates the ‘both‐warmer/colder’ pattern. There exists a significant lead–lag correlation between the MCA1 and MCA2, which determines the changing SAT pattern in the five successive periods. Furthermore, the MCA1 and MCA2, especially their lead–lag coupling after the 1975 is significantly associated with the Pacific decadal oscillation (PDO) which dominates the much‐intensified MCA1 and the related ‘EUA‐warmer/colder’ SAT pattern since then. The Atlantic multi‐decadal oscillation mainly dominates the third leading MCA mode with it's effects on the SAT over Europe coincidently to amplify the PDO‐related SAT changes.

The increase in intensity and frequency of surface air temperature extremes throughout the western South Atlantic coast

The climate is changing. At this stage, it is important to specify an ‘extreme’ climate and identify patterns that indicate its potential harm worldwide, including the coastal zones. Herein, we considered extremes based on the “Peaks Over Threshold” method from the “Extreme Value Theory”. We looked after geographical patterns of surface air temperature (SAT) extremes (e.g., Tmax, Tmin, daily temperature range (DTR), and inter-daily temperature range) over the last 40 years throughout the Brazilian coast. Overall, we found a trend increase in intensity and frequency, but the duration was barely affected. The latitudinal pattern of extremes and the temperatures considered extremes followed the settled perception that areas in higher latitudes will be more affected by the extent of warming. Additionally, the seasonal pattern of DTR demonstrated to be a good approach to make inferences about air mass changes, but joint analyses on extremes with other atmospheric variables are desirable. Given the potential effects of extreme climates on society and natural systems over the world, our study highlights the urge for action to mitigate the effects of the increase in SAT in coastal zones.

Contrasting effects of lake breeze and urbanization on heat stress in Chicago metropolitan area

This study used the latest Weather Research and Forecasting (WRF) model coupled with multilayer urban canopy models to investigate contrasting effects from urbanization and lake breeze on summer heat stress over the Chicago metropolitan area (CMA). Comparisons between the model and in situ observations show that this coupled modeling system better captures urban locations' diurnal pattern of surface air temperature, skin temperature and relative humidity, with root mean square error reduced from 1.58 to 1.80 °C to 1.14–1.31 °C, 3.11–3.55 °C to 1.81–2.21 °C, and 10.73–11.35% to 7.84–8.60%, respectively, compared to WRF without coupling the urban canopy models. Two sensitivity experiments were conducted to isolate the influence of lake breeze and urbanization: one replaced the urban land use with cropland over the CMA, and the other filled all of Lake Michigan with cropland. Three different heat stress indices were computed to assess the uncertainties of heat stress response to changes in air temperature, relative humidity, and wind conditions. Results show that, when the lake has the largest cooling effect on air temperature, it also increases the relative humidity the most, and vice versa for urban warming and drying effects. Urbanization intensifies heat stress at night, and extends the heat caution period by up to 4 h over inland urban grids; the lake breeze relieves heat stress during afternoon (when the heat stress is the worst), and shortens the heat caution period by 1–3 h over inland urban grids and 3–4 h over coastal urban grids. The intensification of heat stress over the CMA due to urbanization is more than four times greater than the reduction from the lake breeze in the late afternoon and evening.

A Pan-North Pacific Wintertime Surface Air Temperature Pattern Contributed by the SST Anomalies over the Kuroshio and Oyashio Extension

A Pan-North Pacific Wintertime Surface Air Temperature Pattern Contributed by the SST Anomalies over the Kuroshio and Oyashio Extension

Surface air temperature changes over the Tibetan Plateau: Historical evaluation and future projection based on CMIP6 models

With its amplification simultaneously emerging in cryospheric regions, especially in the Tibetan Plateau, global warming is undoubtedly occurring. In this study, we utilized 28 global climate models to assess model performance regarding surface air temperature over the Tibetan Plateau from 1961 to 2014, reported spatiotemporal variability in surface air temperature in the future under four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), and further quantified the timing of warming levels (1.5, 2, and 3 °C) in the region. The results show that the multimodel ensemble means depicted the spatiotemporal patterns of surface air temperature for the past decades well, although with differences across individual models. The projected surface air temperature, by 2099, would warm by 1.9, 3.2, 5.2, and 6.3 °C relative to the reference period (1981–2010), with increasing rates of 0.11, 0.31, 0.53, and 0.70 °C/decade under the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios for the period 2015–2099, respectively. Compared with the preindustrial periods (1850–1900), the mean annual surface air temperature over the Tibetan Plateau has hit the 1.5 °C threshold and will break 2 °C in the next decade, but there is still a chance to limit the temperature below 3 °C in this century. Our study provides a new understanding of climate warming in high mountain areas and implies the urgent need to achieve carbon neutrality.

A Dynamical Systems Perspective to Characterize the El Niño Diversity in Spatiotemporal Patterns

El Niño is the long-lasting anomalous warming of sea surface temperature (SST) and surface air temperature (SAT) over the tropical Pacific. Each El Niño event has its unique impact on the overlaying atmosphere, where the warming exhibits diversity in spatiotemporal patterns. It still remains an open question for discriminating the El Niño diversity, since the single area-averaging SST index often fails to distinguish the impact of the event diversity, which is partially due to the nonlinear and non-uniform variations of the warming patterns. Here, we introduced the Dynamical Systems metrics (DSMs) to measure instantaneous dimensions and persistence of the SAT warming patterns over the tropical Pacific. Our results show that different SAT warming patterns can be discriminated by their corresponding values of dimension and persistence, then the central Pacific and eastern Pacific El Niño events can be discriminated by DSM. Particularly, through the analyses of El Niño events, we can interpret the physical meaning of DSM parameters applied to the space-time SAT field: an instantaneous dimension reflects whether the sub-regions of the SAT field are consistently varying and to what degree the spatial pattern of anomalies is homogeneous, while the instantaneous persistence indicates how long an anomalous SAT pattern can be maintained. This work analyzes the spatiotemporal variability of El Niño from a dynamical system perspective, and DSM may also serve as a useful tool to study extreme events related to SST anomalies.

Seasonal circulation regimes in the North Atlantic: Towards a new seasonality

AbstractEuropean climate variability is shaped by atmospheric dynamics over the North Atlantic and local processes. Better understanding their future seasonality is essential to anticipate changes in weather conditions for human and natural systems. We explore atmospheric seasonality over 1979–2017 and 1979–2100 with seasonal circulation regimes (SCRs), by clustering year‐round daily fields of Z500 from the ERA‐Interim reanalysis and 12 Coupled Model Intercomparison Project phase 5 (CMIP5) climate models (historical and RCP8.5 runs). The spatial and temporal variability of SCR structures and associated patterns of surface air temperature are investigated. Climate models have biases but reproduce structures and evolutions of SCRs similar to the reanalysis over 1979–2017: decreasing frequency of winter conditions (starting later and ending earlier in the year) and the opposite for summer conditions. These changes are stronger over 1979–2100 than over 1979–2017, associated with a large increase of North Atlantic seasonal mean Z500 and temperature. When using more SCRs (more freedom in definition of seasonality), the changes over 1979–2100 correspond to a long‐term swap between SCRs, resulting in similar structures (annual cycle and spatial patterns) relative to the evolution of seasonal mean Z500 and temperature. To understand whether the evolution of SCRs is linked to uniform warming, or to changes in circulation patterns, we remove the calendar trend in the Z500 regional average to define SCRs based on detrended data (d‐SCRs). The temporal properties of d‐SCRs appear almost constant whereas their spatial patterns change, indicating that the calendar Z500 regional trend drives the evolutions of SCRs, and that changing spatial patterns in d‐SCRs account for the heterogeneity of this trend. Our study suggests that historical winter conditions will continue to decrease in the future while historical summer conditions continue to increase. However, it also suggests that the spatial and temporal patterns of SCRs would remain similar, relatively to the year‐round Z500 increase.

Variations of widespread extreme cold and warm days in winter over China and their possible causes

The two leading modes of winter surface air temperature (SAT) over China during 1961–2017 are a spatially consistent pattern and a north-south dipole pattern. Based on the two leading modes, the characteristics of the extreme cold and warm days in the two patterns, defined by the standard deviation larger than 1.28 or smaller than −1.28 in the time series of the two leading modes, are analyzed. With the increase of winter SAT during 1961–2017, the number of spatially consistent extreme cold days decreased and their occurrence was restricted to late December to early January, whereas the number of spatially consistent extreme warm days increased significantly in January and February. Global warming is associated with an increase in the spatially consistent extreme warm days and a decrease in spatially consistent extreme cold days, but has little relation to the sum of extreme cold and warm days of either the spatially consistent or north-south dipole pattern. The Siberian High (SH) is the main factor controlling the sum of spatially consistent extreme warm and cold days. The strong (weak) SH before (after) the 1990s corresponds to an increase (decrease) in the sum of the spatially consistent extreme warm and cold days. The occurrences of extreme south-cold-north-warm and extreme south-warm-north-cold days are related to the north-south difference of the SH. When the center of the SH is in mid-high latitudes, the extreme south-warm-north-cold (south-cold-north-warm) days occur more (less) often. During the winters of 1961–2017, the total number of extreme cold and warm days of the north-south dipole pattern changes negligibly. The North Atlantic meridional overturning circulation (AMOC) may be the main factor affecting the sum of the extreme cold and warm days of the two types of SAT pattern in China.

Regional differences in surface air temperature changing patterns from 1960 to 2016 of China

A thorough understanding of regional differences in change patterns of surface air temperature (SAT) at various spatial scales can help people cope well with global warming. In this study, a SAT change pattern recognition method was firstly established based on k-mean++ algorithm. By creating a clustering effect evaluation index (DBWk) to select the optimal cluster number k, the pattern of SAT change in 1960–2016 of China was recognized at national and regional scales. Results showed that China’s SAT change patterns were grouped into 3 clusters, namely, Clusters I, II and III, at the national scale. These clusters were further divided into 3, 7, and 4 subclusters at the regional scale, respectively. The SAT change in Cluster I was intense, with a relatively cold period (1960–1987) and a relatively warm period (1988–2016). The SAT of Cluster II decreased slightly in the first phase (1960–1983), minimally increased in the third phase (1999–2016), but rose strongly in the second phase (1984–1998). The linear trend (LT) of SAT increase of Cluster III was high and statistically significant, especially in 1983–2016. The analysis of the SAT change pattern of subclusters showed that the SAT fluctuations of the Altai Mountains and Junggar Basin were the strongest. The Northern Qinghai–Tibet Plateau had the highest warming rate, and the LT of warming was statistically the most significant in China.

Modelling and forecasting for monthly surface air temperature patterns in India, 1951–2016: Structural time series approach

Surface air temperature (SAT) is a key meteorological parameter. Modelling and forecasting of the SAT has vital importance to understand the ecological and agricultural changes. We utilized all India monthly mean SAT, which covers a time span of 1951–2016. We used structural time series (STS) analysis to model and forecast the monthly mean SAT. Forecast during 2006–2016 well matched with the observational data. Further, the forecast of monthly mean surface air temperature patterns for 2017–2019 shows a good agreement with climatological behaviour. Note that we observed an increasing trend 0.0009°C per year in monthly mean surface air. Further, we noticed slight chance of rise in temperature about 0.1°C specially for the months of April, May and December in the years 2017–2019.

Subseasonal Forecast of Surface Air Temperature Using Superensemble Approaches: Experiments over Northeast Asia for 2018

AbstractBridging the gap between weather forecasting and climate prediction, subseasonal to seasonal (S2S) forecasts are of great importance yet currently of relatively poor quality. Using the S2S Prediction Project database, the study evaluates products derived from four operational centers of CMA, KMA, NCEP, and UKMO, and superensemble experiments including the straightforward ensemble mean (EMN), bias-removed ensemble mean (BREM), error-based superensemble (ESUP), and Kalman filter superensemble (KF), in forecasts of surface air temperature with lead times of 6–30 days over northeast Asia in 2018. Validations after the preprocessing of a 5-day running mean suggest that the KMA model shows the highest skill for either the control run or the ensemble mean. The nonequal weighted ESUP is slightly superior to BREM, whereas they both show larger biases than EMN after a lead time of 22 days. The KF forecast constantly outperforms the others, decreasing mean absolute errors by 0.2°–0.5°C relative to EMN. Forecast experiments of the 2018 northeast Asia heat wave reveal that the superensembles remarkably improve the raw forecasts featuring biases of >4°C. The prominent advancement of KF is further confirmed, showing the regionally averaged bias of ≤2°C and the hit rate of 2°C reaching up to 60% at a lead time of 22 days. The superensemble techniques, particularly the KF method of dynamically adjusting the weights in accordance with the latest information available, are capable of improving forecasts of spatiotemporal patterns of surface air temperature on the subseasonal time scale, which could extend the skillful prediction lead time of extreme events such as heat waves to about 3 weeks.

Structural time-series modelling for seasonal surface air temperature patterns in India 1951–2016

To investigate variability patterns, to predict short-term and long-term changes of weather, time-series data analysis is considered to be a valuable tool. The paper presents modelling and forecasting the seasonal surface air temperature patterns in India for the period 1951–2016 using the structural time-series modelling. The structural time-series model (STSM) with the hidden components of deterministic linear time trend, trigonometric seasonal, and stochastic autoregression for cycle is selected from the parsimonious models. The model selection can be done based on Bayesian Information Criteria (BIC), significant tests, and statistical fit. The model parameters of the noise terms and the damping coefficient in the autoregression are determined using maximizing the likelihood function. The diagnostics of the selected STSM is determined with normal diagnostics checked by examining the histogram and Q–Q plot of residuals; the whiteness checked by autocorrelation function (ACF), partial autocorrelation function (PACF), and p values of LJung–Box portmanteau test of residuals. Furthermore, the forecast of seasonal surface air temperature patterns in India during the years 2017–2019 has been forecasted from the selected STSM. Statistically significant increase is noticed in annual average surface air temperature over India. The increase in surface temperature is about 0.0132 °C per year for the period 1951–2016. The study also showed slow and steady increase in the mean surface air temperature over India during the recent years.

Seasonal linkage of the Southern Hemisphere extratropical climate variability to two types of ENSO

This study uses the Climate Forecast System Reanalysis (CFSR) to investigate the responses of the Southern Hemisphere (SH) extratropical climate to two types of El Nino-Southern Oscillation (ENSO)—the eastern Pacific (EP) type and the central Pacific (CP) type in different seasons. The responses are denoted by the anomalies of climate variables associated with one-standard-deviation increase in the Nino3 or Nino4 index. The results show that in austral spring the differences in the ENSO-related anomaly (ERA) patterns of atmospheric circulation between the EP ENSO period (1979–1998) and CP ENSO period (1999–2010) are mainly associated with the change in the ENSO-PSA2 relationship. Such differences affect the ERA fields of surface air temperature and mixed layer temperature, and finally result in significant differences in sea-ice concentration anomalies in the Atlantic sector. In austral summer, significant correlation exists between the variations of SAM and both of the variations of Nino3 and Nino4 in 1979–1998, while the correlation between SAM and Nino4 disappears in 1999–2010. For all seasons, the strength of the climate ERAs depend on if there are close relationship between ENSO and the major climate variation modes of the SH extratropics. For the climate variables, the ERA patterns of surface air temperature are generally controlled by surface wind anomalies and mirrored by the mixed layer temperature anomalies. The mixed layer depth anomalies are primarily modulated by surface heat flux anomalies and occasionally by anomalous wind. There are strikingly strong anomalies of surface heat flux in the autumn of 1979–1998 related to the Nino3 variation, the period when there is only significant correlation between ENSO and PSA2. There are no evidence that the SH extratropical climate variability induced by Nino3 variations are stronger in the EP-ENSO period, and that variability induced by Nino4 variations are stronger in the CP-ENSO period.

The sensitivity of Northern Hemisphere ice sheets to atmospheric forcing during the last glacial cycle using PMIP3 models

ABSTRACTThe evolution of Northern Hemisphere ice sheets through the last glacial cycle is simulated with the glacial index method by using the climate forcing from one General Circulation Model, COSMOS. By comparing the simulated results to geological reconstructions, we first show that the modelled climate is capable of capturing the main features of the ice-sheet evolution. However, large deviations exist, likely due to the absence of nonlinear interactions between ice sheet and other climate components. The model uncertainties of the climate forcing are examined using the output from nine climate models from the Paleoclimate Modelling Intercomparison Project Phase III. The results show a large variability in simulated ice sheets between the different models. We find that the ice-sheet extent pattern resembles summer surface air temperature pattern at the Last Glacial Maximum, confirming the dominant role of surface ablation process for high-latitude Northern Hemisphere ice sheets. This study shows the importance of the upper boundary condition for ice-sheet modelling, and implies that careful constraints on climate output is essential for simulating realistic glacial Northern Hemisphere ice sheets.

CMIP5 vs. CORDEX over the Indian region: how much do we benefit from dynamical downscaling?

Given the general notion that dynamical downscaling leads to added accuracy in both historical simulations as well as climate change projections, this paper investigates its validity over India using historical data (1975–2005) from the CORDEX models and their driving global climate models (GCMs) from Coupled Model Intercomparison Project Phase 5 (CMIP5), and comparing them against observed temperature and rainfall. We find that downscaling invariably leads to an improvement in the spatial pattern of surface air temperature, but compared to the driving GCMs, the errors in magnitude after downscaling are even worse in some cases. In regard to JJAS rainfall simulations, the CMIP5 driving GCMs are found to be superior to their dynamically downscaled counterparts both in terms of spatial patterns as well as magnitude of errors. Both CMIP5 driving GCMs as well as the CORDEX models underestimate rainfall during JJAS; however, negative bias in CORDEX models is worse. Unlike the driving CMIP5 GCMs, their dynamically downscaled counterparts simulate an early onset followed by a slow and late withdrawal of the Indian summer monsoon rainfall. The frequency of occurrence of rainfall intensities is simulated well by both sets of models in the lower intensity regime (0–20 mm/day); however, for higher intensities, the driving CMIP5 GCMs underestimate whereas the CORDEX models overestimate.

Influence of Lake Malawi on regional climate from a double-nested regional climate model experiment

We evaluate the performance of the regional climate model (RCM) RegCM4 coupled to a one dimensional lake model for Lake Malawi (also known as Lake Nyasa in Tanzania and Lago Niassa in Mozambique) in simulating the main characteristics of rainfall and near surface air temperature patterns over the region. We further investigate the impact of the lake on the simulated regional climate. Two RCM simulations, one with and one without Lake Malawi, are performed for the period 1992–2008 at a grid spacing of 10 km by nesting the model within a corresponding 25 km resolution run (“mother domain”) encompassing all Southern Africa. The performance of the model in simulating the mean seasonal patterns of near surface air temperature and precipitation is good compared with previous applications of this model. The temperature biases are generally less than 2.5 °C, while the seasonal cycle of precipitation over the region matches observations well. Moreover, the one-dimensional lake model reproduces fairly well the geographical pattern of observed (from satellite measurements) lake surface temperature as well as its mean month-to-month evolution. The Malawi Lake-effects on the moisture and atmospheric circulation of the surrounding region result in an increase of water vapor mixing ratio due to increased evaporation in the presence of the lake, which combines with enhanced rising motions and low-level moisture convergence to yield a significant precipitation increase over the lake and neighboring areas during the whole austral summer rainy season.

Evaluation of simulated decadal variations over the Euro-Mediterranean region from ENSEMBLES to Med-CORDEX

Med-CORDEX simulations over the period 1979–2011 are evaluated with regard to their capability to represent observed decadal variations over the Euro-Mediterranean region and improve upon previous generation simulations from the ENSEMBLES project in their various experimental set-ups. Such an evaluation is needed to inform the use of these simulations and also future model development. For temperature, both Med-CORDEX and ENSEMBLES simulations tend to provide comparable results: they generally capture the sign and timing of the anomalies but not the amplitude. In general, no clear stratification appears when considering different types of Med-CORDEX regional modeling systems. Rather, it is remarkable that certain periods are poorly represented by all systems with a general underestimation of the observed long-term temperature trend, mostly in the summer season, even with respect to the corresponding global drivers. For precipitation, the Med-CORDEX simulations are closer to observations than the other datasets, with some improvement with respect to ENSEMBLES dataset. In general, all the systems experience difficulties in representing anomalies during specific periods or for specific regions. These appear in part due to limitations in the reanalysis boundary forcing data. For instance, in the second part of 1980s, the spatial patterns of surface air temperature during DJF/MAM are generally poorly represented, as well as the regionally averaged MAM/JJA surface air temperature decadal anomalies. Overall, the evaluation suggests limited improvement in Med-CORDEX simulations compared to ENSEMBLES, and a lack of sensitivity to resolution or coupling configuration, with persisting problems in part likely related to the representation of surface processes that could also affect the viability of future projections (e.g. the estimation of temperature trends). A set of decadal variability evaluation metrics, as applied in this study, could be useful in the context of a broader evaluation framework.

Topographic effects on spatial pattern of surface air temperature in complex mountain environment

Understanding topographic effects on surface air temperature (SAT) is essential in developing an accurate prediction model in complex mountain environment. A nonlinear topographic regression model is developed to predict the spatial SAT pattern using latitude, elevation, slope, and aspect. Monthly SAT data have been collected from 14 meteorological stations between 1960 and 2010 in the Daqing Mountains of China. Topographic data are acquired from a 30 m resolution digital elevation model of the study region. Results show that: (1) the SAT models are able to explain 89–95.8 % of the spatial variation in different months. Elevation has the strongest effect on the SAT variation in all months (average 84.78 %). (2) The combined contribution of slope and aspect to SAT variations is larger (average 9.14 %) than that of latitude (average 6.07 %). (3) The combined effect of slope and aspect on SAT variations is higher in winter than in summer. The introduction of slope and aspect optimizes the SAT modeling in different months. In further studies, the accuracy of SAT model might be improved by introducing alternative topographic factors to capture the vegetation and weather condition.