Predictability of Mediterranean climate variables from oceanic variability. Part I: Sea surface temperature regimes

The determination of specific sea surface temperature (SST) patterns from large-scale gridded SST-fields has widely been done. Often principal component analysis (PCA) is used to condense the SST-data to major patterns of variability. In the present study SST-fields for the period 1950?C2003 from the area 20°S to 60°N are analysed with respect to SST-regimes being defined as large-scale oceanic patterns with a regular and at least seasonal occurrence. This has been done in context of investigations on seasonal predictability of Mediterranean regional climate with large-scale SST-regimes as intended predictors in statistical model relationships. The SST-regimes are derived by means of a particular technique including multiple applications of s-mode PCA. Altogether 17 stationary regimes can be identified, eight for the Pacific Ocean, five for the Atlantic Ocean, two for the Indian Ocean, and two regimes which show a distinct co-variability within different ocean basins. Some regimes exist, with varying strength and spatial extent, throughout the whole year, whereas other regimes are only characteristic for a particular season. Several regimes show dominant variability modes, like the regimes associated with El Ni?o, with the Pacific Decadal Oscillation or with the North Atlantic Tripole, whereas other regimes describe little-known patterns of large-scale SST variability. The determined SST-regimes are subsequently used as predictors for monthly precipitation and temperature in the Mediterranean area. This subject is addressed in Part II of this paper.     

Structure of climatic variability of the Mediterranean Sea surface temperature. Part II. Principal modes of variability

The interdecadal and interannual variability of the Mediterranean Sea surface temperature (SST), presented by the first and second modes of empirical orthogonal functions (EOF), respectively, is studied using the 1951–2000 data. It is demonstrated that the spatial and temporal structure of the first EOF mode, reflecting interdecadal SST variations, is similar in all seasons, and, thus, is a manifestation of a global signal that is not subject to significant seasonal changes and whose origin is common for all seasons. On the contrary, the second EOF mode, reflecting the interannual variability of the Mediterranean Sea surface temperature and presented by a zonally oriented dipole, demonstrates its well pronounced seasonality. It is found that the character of temporal variability of this mode is specific for each season. The seasonality is also pronounced in significant variability of the mode contribution to the total SST variability. The above-noted seasonal differences are indicative of various mechanisms of formation of the interannual SST variability in the Mediterranean Sea.     

Twentieth century simulation of the southern hemisphere climate in coupled models. Part II: sea ice conditions and variability

We examine the representation of the mean state and interannual variability of Antarctic sea ice in six simulations of the twentieth century from coupled models participating in the Intergovernmental Panel on Climate Change fourth assessment report. The simulations exhibit a largely seasonal southern hemisphere ice cover, as observed. There is a considerable scatter in the monthly simulated climatological ice extent among different models, but no consistent bias when compared to observations. The scatter in maximum winter ice extent among different models is correlated to the strength of the climatological zonal winds suggesting that wind forced ice transport is responsible for much of this scatter. Observations show that the leading mode of southern hemisphere ice variability exhibits a dipole structure with anomalies of one sign in the Atlantic sector associated with anomalies of the opposite sign in the Pacific sector. The observed ice anomalies also exhibit eastward propagation with the Antarctic circumpolar current, as part of the documented Antarctic circumpolar wave phenomenon. Many of the models do simulate dipole-like behavior in sea ice anomalies as the leading mode of ice variability, but there is a large discrepancy in the eastward propagation of these anomalies among the different models. Consistent with observations, the simulated Antarctic dipole-like variations in the ice cover are led by sea-level pressure anomalies in the Amundsen/ Bellingshausen Sea. These are associated, to different degrees in different models, with both the southern annular mode and the El Nino-Southern Oscillation (ENSO). There are indications that the magnitude of the influence of ENSO on the southern hemisphere ice cover is related to the strength of ENSO events simulated by the different models.     

Statistical bias correction for daily precipitation in regional climate models over Europe

We design, apply, and validate a methodology for correcting climate model output to produce internally consistent fields that have the same statistical intensity distribution as the observations. We refer to this as a statistical bias correction. Validation of the methodology is carried out using daily precipitation fields, defined over Europe, from the ENSEMBLES climate model dataset. The bias correction is calculated using data from 1961 to 1970, without distinguishing between seasons, and applied to seasonal data from 1991 to 2000. This choice of time periods is made to maximize the lag between calibration and validation within the ERA40 reanalysis period. Results show that the method performs unexpectedly well. Not only are the mean and other moments of the intensity distribution improved, as expected, but so are a drought and a heavy precipitation index, which depend on the autocorrelation spectra. Given that the corrections were derived without seasonal distinction and are based solely on intensity distributions, a statistical quantity oblivious of temporal correlations, it is encouraging to find that the improvements are present even when seasons and temporal statistics are considered. This encourages the application of this method to multi-decadal climate projections.     

Multi-year fluctuations of temperature and precipitation: The gray area of climate change

The issue of whether the secular climate (twentieth century) is stationary or changing to some new semi-permanent state is clouded by the presence of so-called climate fluctuations. The twentieth century climate record of the United States reveals a substantial number of decadal fluctuations which occur in all seasons for both temperature and precipitation. Recent examples of such behavior include changes in winter and summer temperature variability and increases in transition season precipitation. Statistical evidence suggests that a substantial portion of these fluctuations, even those which are remarkably unusual, are merely manifestations of a stochastic process which possesses weak year-to-year persistence as viewed from an a posteriori perspective. The implications of this result are particularly important with respect to the formulation of physical causes of the fluctuations. The results emphasize the desirability of well-founded clearly-stated a priori theories of climate change as well as the limited usefulness of widely used climate normals.     

Statistical significance of trends in monthly heavy precipitation over the US

Trends in monthly heavy precipitation, defined by a return period of one year, are assessed for statistical significance in observations and Global Climate Model (GCM) simulations over the contiguous United States using Monte Carlo non-parametric and parametric bootstrapping techniques. The results from the two Monte Carlo approaches are found to be similar to each other, and also to the traditional non-parametric Kendall’s τ test, implying the robustness of the approach. Two different observational data-sets are employed to test for trends in monthly heavy precipitation and are found to exhibit consistent results. Both data-sets demonstrate upward trends, one of which is found to be statistically significant at the 95% confidence level. Upward trends similar to observations are observed in some climate model simulations of the twentieth century, but their statistical significance is marginal. For projections of the twenty-first century, a statistically significant upwards trend is observed in most of the climate models analyzed. The change in the simulated precipitation variance appears to be more important in the twenty-first century projections than changes in the mean precipitation. Stochastic fluctuations of the climate-system are found to be dominate monthly heavy precipitation as some GCM simulations show a downwards trend even in the twenty-first century projections when the greenhouse gas forcings are strong.     

Projections of high resolution climate changes for South Korea using multiple-regional climate models based on four RCP scenarios. Part 2: precipitation

Precipitation changes over South Korea were projected using five regional climate models (RCMs) with a horizontal resolution of 12.5 km for the mid and late 21st century (2026-2050, 2076- 2100) under four Representative Concentration Pathways (RCP) scenarios against present precipitation (1981-2005). The simulation data of the Hadley Centre Global Environmental Model version 2 coupled with the Atmosphere-Ocean (HadGEM2-AO) was used as boundary data of RCMs. In general, the RCMs well simulated the spatial and seasonal variations of present precipitation compared with observation and HadGEM2-AO. Equal Weighted Averaging without Bias Correction (EWA_NBC) significantly reduced the model biases to some extent, but systematic biases in results still remained. However, the Weighted Averaging based on Taylor’s skill score (WEA_Tay) showed a good statistical correction in terms of the spatial and seasonal variations, the magnitude of precipitation amount, and the probability density. In the mid-21st century, the spatial and interannual variabilities of precipitation over South Korea are projected to increase regardless of the RCP scenarios and seasons. However, the changes in area-averaged seasonal precipitation are not significant due to mixed changing patterns depending on locations. Whereas, in the late 21st century, the precipitation is projected to increase proportionally to the changes of net radiative forcing. Under RCP8.5, WEA_Tay projects the precipitation to be increased by about +19.1, +20.5, +33.3% for annual, summer and winter precipitation at 1-5% significance levels, respectively. In addition, the probability of strong precipitation (≥ 15 mm d^-1) is also projected to increase significantly, particularly in WEA_Tay under RCP8.5.     

Simple indices of global climate variability and change Part II: attribution of climate change during the twentieth century

Five simple indices of surface temperature are used to investigate the influence of anthropogenic and natural (solar irradiance and volcanic aerosol) forcing on observed climate change during the twentieth century. These indices are based on spatial fingerprints of climate change and include the global-mean surface temperature, the land-ocean temperature contrast, the magnitude of the annual cycle in surface temperature over land, the Northern Hemisphere meridional temperature gradient and the hemispheric temperature contrast. The indices contain information independent of variations in global-mean temperature for unforced climate variations and hence, considered collectively, they are more useful in an attribution study than global mean surface temperature alone. Observed linear trends over 1950–1999 in all the indices except the hemispheric temperature contrast are significantly larger than simulated changes due to internal variability or natural (solar and volcanic aerosol) forcings and are consistent with simulated changes due to anthropogenic (greenhouse gas and sulfate aerosol) forcing. The combined, relative influence of these different forcings on observed trends during the twentieth century is investigated using linear regression of the observed and simulated responses of the indices. It is found that anthropogenic forcing accounts for almost all of the observed changes in surface temperature during 1946–1995. We found that early twentieth century changes (1896–1945) in global mean temperature can be explained by a combination of anthropogenic and natural forcing, as well as internal climate variability. Estimates of scaling factors that weight the amplitude of model simulated signals to corresponding observed changes using a combined normalized index are similar to those calculated using more complex, optimal fingerprint techniques.     

Twentieth century simulation of the southern hemisphere climate in coupled models. Part 1: large scale circulation variability

The ability of five, global coupled climate models to simulate important atmospheric circulation characteristics in the Southern Hemisphere for the period 1960–1999 is assessed. The circulation features examined are the Southern Hemisphere annular mode (SAM), the semi-annual oscillation (SAO) and the quasi-stationary zonal wave 3 (ZW3). The models assessed are the National Center for Atmospheric Research Community Climate System Model Version 3 (CCSM3), the Commonwealth Scientific and Industrial Research Organisation Mark 3, the Geophysical Fluid Dynamics Laboratory Model, the Goddard Institute for Space Studies Model ER (GISS-ER) and the UK Meteorological Office Hadley Center Coupled Model Version 3. The simulations were compared to the NCAR–NCEP reanalyses. The models simulate a SAO which differs spatially from the observed over the Pacific and Indian oceans. The amplitudes are too high over the southern ocean and too low over the midlatitudes. These differences are attributed to a circumpolar trough which is too deep and extends too far north, and to the inability of the models to simulate the middle to high latitude temperature gradient. The SAM is well-represented spatially by most models but there are important differences which may influence the flow over the Pacific and in the region extending from the Ross to Weddell Seas. The observed trend towards positive polarity in the SAM is apparent in the ensemble averages of the GISS-ER and CCSM3 simulations, suggesting that the trend is due to external forcing by changes in the concentration of ozone and greenhouse gases. ZW3 is well-represented by the models but the observed trend towards positive phases of ZW3 is not apparent in the simulations suggesting that the observed trend may be due to natural variability, not external forcing.     

Structure of climatic variability of the Mediterranean sea surface temperature. Part I. Standard deviations and linear trends

Interannual and longer-period variability of the Mediterranean sea surface temperature is studied in terms of standard deviations and linear trends based on the 1951–2000 data. It is shown that both standard deviations and linear SST trends in the Mediterranean Sea are clearly season-dependent. Seasonality of standard deviations is characterized by a zonally-oriented seesaw with opposite changes in standard deviations in the western and eastern parts of the basin from season to season. The SST trend seasonality is pronounced in winter in predominant negative SST trends, and in summer in positive trends. Such seasonal differences indicate that long-term Mediterranean SST variability has different mechanisms of formation.     

Analyzing projected changes and trends of temperature and precipitation in the southern USA from 16 downscaled global climate models

This study aims to examine how future climate, temperature and precipitation specifically, are expected to change under the A2, A1B, and B1 emission scenarios over the six states that make up the Southern Climate Impacts Planning Program (SCIPP): Oklahoma, Texas, Arkansas, Louisiana, Tennessee, and Mississippi. SCIPP is a member of the National Oceanic and Atmospheric Administration-funded Regional Integrated Sciences and Assessments network, a program which aims to better connect climate-related scientific research with in-the-field decision-making processes. The results of the study found that the average temperature over the study area is anticipated to increase by 1.7°C to 2.4°C in the twenty-first century based on the different emission scenarios with a rate of change that is more pronounced during the second half of the century. Summer and fall seasons are projected to have more significant temperature increases, while the northwestern portions of the region are projected to experience more significant increases than the Gulf coast region. Precipitation projections, conversely, do not exhibit a discernible upward or downward trend. Late twenty-first century exhibits slightly more precipitation than the early century, based on the A1B and B1 scenario, and fall and winter are projected to become wetter than the late twentieth century as a whole. Climate changes on the city level show that greater warming will happened in inland cities such as Oklahoma City and El Paso, and heavier precipitation in Nashville. These changes have profound implications for local water resources management as well as broader regional decision making. These results represent an initial phase of a broader study that is being undertaken to assist SCIPP regional and local water planning efforts in an effort to more closely link climate modeling to longer-term water resources management and to continue assessing climate change impacts on regional hazards management in the South.     

Postprocessing of simulated precipitation for impact research in West Africa. Part I: model output statistics for monthly data

Rainfall represents an important factor in agriculture and food security, particularly, in the low latitudes. Climatological and hydrological studies which attempt to diagnose the hydrological cycle, require high-quality precipitation data. In West Africa, like in many parts of the world, the density of observational data is low and climate models are needed in order to perform homogeneous and complete data sets. However, climate models tend to produce systematic errors, especially, in terms of rainfall and cloud processes, which are usually approximated by physical parameterizations. In this study, a 25-year climatology of monthly precipitation in West Africa is presented, derived from a regional climate model simulation, and evaluated with respect to observational data. It is found that the model systematically underestimates the rainfall amount and variability and does not capture some details of the seasonal cycle in sub-Saharan West Africa. Thus, in its present form the precipitation climatology is not appropriate to draw a realistic picture of the hydrological cycle in West Africa nor to serve as input data for impact research. Therefore, a statistical model is developed in order to adjust the simulated rainfall data to the characteristics of observed precipitation. Assuming that the regional climate model is much more reliable in terms of atmospheric circulation and thermodynamics, model output statistics is used to correct simulated rainfall by means of other simulated parameters of the near-surface climate like temperature, sea level pressure and wind components. Monthly data is adjusted by a cross-validated multiple regression model. The resulting adjusted rainfall climatology reveals a substantial improvement in terms of the model deficiencies mentioned above. In part II of this publication, the characteristics of simulated daily precipitation is adapted to station data by applying a weather generator. Once the postprocessing approach is trained, it can be extrapolated to simulation periods, for which observational data do not exist like for instance future climate.     

Wet season Mediterranean precipitation variability: influence of large-scale dynamics and trends

The influence of the large-scale atmospheric circulation at several tropospheric levels on wet season precipitation over 292 sites across the Mediterranean area is assessed. A statistical downscaling model is designed with an objective methodology based on empirical orthogonal functions and canonical correlation analysis (CCA) and tested by means of cross-validation. In all 30% of the total Mediterranean October to March precipitation variability can be accounted for by the combination of four large-scale geopotential height fields and sea level pressure. The Mediterranean sea surface temperatures seem to be less relevant to explain precipitation variability at interannual time scale. It is shown that interdecadal changes in the first CCA mode are related to variations in the North Atlantic Oscillation index and responsible for comparable time scale variations of the Mediterranean precipitation throughout the twentieth century. The analysis reveals that since the mid-nineteenth century precipitation steadily increased with a maximum in the 1960s and decreased since then. The second half of the twentieth century shows a general downward trend of 2.2 mm·month^–1·decade^–1.     

Linear methods for the statistical transformation of daily precipitation sums from regional climate models

This paper presents two new methods for the linear transformation of climate model precipitation data. For verification of the developed methods, daily precipitation sums from the REMO climate model were transformed to observed data from the meteorological stations in the Malse River basin in the Czech Republic. Both methods are based on an analysis of the gamma distribution. The comparison between the observed and transformed data indicates their suitable applicability. The precipitation amounts of transformed data comply with an equivalent probability distribution as the observed data, a distribution of dry days in time drifts towards realistic values. In addition, the efficiency of the formerly published method for nonlinear transformation and newly introduced linear methods is compared.     

Low-frequency variability of the arctic climate: the role of oceanic and atmospheric heat transport variations

Changes in meridional heat transports, carried either by the atmosphere (HTRA) or by the ocean (HTRO), have been proposed to explain the decadal to multidecadal climate variations in the Arctic. On the other hand, model simulations indicate that, at high northern latitudes, variations in HTRA and HTRO are strongly coupled and may even compensate each other. A multi-century control integration with the Max Planck Institute global atmosphere-ocean model is analyzed to investigate the relative role of the HTRO and HTRA variations in shaping the Arctic climate and the consequences of their possible compensation. In the simulation, ocean heat transport anomalies modulate sea ice cover and surface heat fluxes mainly in the Barents Sea/Kara Sea region and the atmosphere responds with a modified pressure field. In response to positive HTRO anomalies there are negative HTRA anomalies associated with an export of relatively warm air southward to Western Siberia and a reduced inflow of heat over Alaska and northern Canada. While the compensation mechanism is prominent in this model, its dominating role is not constant over long time scales. The presence or absence of the compensation is determined mainly by the atmospheric circulation in the Pacific sector of the Arctic where the two leading large-scale atmospheric circulation patterns determine the lateral fluxes with varying contributions. The degree of compensation also determines the heat available to modulate the large-scale Arctic climate. The combined effect of atmospheric and oceanic contributions has to be considered to explain decadal-scale warming or cooling trends.     

Intra-seasonal climate variability of Madagascar. Part 1: Mean summer conditions

Summary Variability of the summer climate of Madagascar is studied using area-averaged rainfall (1961–1992) and ECMWF meteorological data (1987–1992). Rainfall time series illustrate a seasonal onset in late December, a convective peak in mid-February and cessation near the end of March. Convective cycles with periods of 10–20 and 40 days are common. The former are contributed by easterly waves and the latter by monsoon surges which may resonate with the Madden Julian Oscillation. Using ECMWF January–February means, the summer climate of the Madagascar region is described. Characteristics of the region include SST>28°C, a quasi-permanent, topographic trade wind trough, sudden cyclogenesis, and distinct circulation regimes with easterly (westerly) shear to the north (south). The most poleward limit of deep convection and sustained uplift is near 20°S, 45°E. A convective vortex embedded in the ITCZ is a prevalent feature owing to the interaction of the NW monsoon and local topography.With 11 Figures     

Decadal climate variability in the Mediterranean region: roles of large-scale forcings and regional processes

We analyze decadal climate variability in the Mediterranean region using observational datasets over the period 1850–2009 and a regional climate model simulation for the period 1960–2000, focusing in particular on the winter (DJF) and summer (JJA) seasons. Our results show that decadal variability associated with the winter and summer manifestations of the North Atlantic Oscillation (NAO and SNAO respectively) and the Atlantic Multidecadal Oscillation (AMO) significantly contribute to decadal climate anomalies over the Mediterranean region during these seasons. Over 30% of decadal variance in DJF and JJA precipitation in parts of the Mediterranean region can be explained by NAO and SNAO variability respectively. During JJA, the AMO explains over 30% of regional surface air temperature anomalies and Mediterranean Sea surface temperature anomalies, with significant influence also in the transition seasons. In DJF, only Mediterranean SST still significantly correlates with the AMO while regional surface air temperature does not. Also, there is no significant NAO influence on decadal Mediterranean surface air temperature anomalies during this season. A simulation with the PROTHEUS regional ocean–atmosphere coupled model is utilized to investigate processes determining regional decadal changes during the 1960–2000 period, specifically the wetter and cooler 1971–1985 conditions versus the drier and warmer 1986–2000 conditions. The simulation successfully captures the essence of observed decadal changes. Model set-up suggests that AMO variability is transmitted to the Mediterranean/European region and the Mediterranean Sea via atmospheric processes. Regional feedbacks involving cloud cover and soil moisture changes also appear to contribute to observed changes. If confirmed, the linkage between Mediterranean temperatures and the AMO may imply a certain degree of regional decadal climate predictability. The AMO and other decadal influences outlined here should be considered along with those from long-term increases in greenhouse gas forcings when making regional climate out-looks for the Mediterranean 10–20?years out.     

Atlantic multidecadal oceanic variability and its influence on the atmosphere in a climate model

The mechanisms controlling the decadal to multidecadal variability of the Atlantic Meridional Overturning Circulation (MOC) and its influence on the atmosphere are investigated using a control simulation with the IPSL-CM4 climate model. The multidecadal fluctuations of the MOC are mostly driven by deep convection in the subpolar gyre, which occurs south of Iceland in the model. The latter is primarily influenced by the anomalous advection of salinity due to changes in the East Atlantic Pattern (EAP), which is the second mode of atmospheric variability in the North Atlantic region. The North Atlantic Oscillation is the dominant mode, but it plays a secondary role in the MOC fluctuations. During summer, the MOC variability is shown to have a significant impact on the atmosphere in the North Atlantic–European sector. The MOC influence is due to an interhemispheric sea surface temperature (SST) anomaly with opposite signs in the two hemispheres but largest amplitude in the northern one. The SST pattern driven by the MOC mostly resembles the model Atlantic Multidecadal Oscillation (AMO) and bears some similarity with the observed one. It is shown that the AMO reflects both the MOC influence and the local atmospheric forcing. Hence, the MOC influence on climate is best detected using lagged relations between climatic fields. The atmospheric response resembles the EAP, in a phase that might induce a weak positive feedback on the MOC.     

Statistical downscaling of daily mean temperature, pan evaporation and precipitation for climate change scenarios in Haihe River, China

A statistical downscaling method (SDSM) was evaluated by simultaneously downscaling air temperature, evaporation, and precipitation in Haihe River basin, China. The data used for evaluation were large-scale atmospheric data encompassing daily NCEP/NCAR reanalysis data and the daily mean climate model results for scenarios A2 and B2 of the HadCM3 model. Selected as climate variables for downscaling were measured daily mean air temperature, pan evaporation, and precipitation data (1961–2000) from 11 weather stations in the Haihe River basin. The results obtained from SDSM showed that: (1) the pattern of change in and numerical values of the climate variables can be reasonably simulated, with the coefficients of determination between observed and downscaled mean temperature, pan evaporation, and precipitation being 99%, 93%, and 73%, respectively; (2) systematic errors existed in simulating extreme events, but the results were acceptable for practical applications; and (3) the mean air temperature would increase by about 0.7°C during 2011~2040; the total annual precipitation would decrease by about 7% in A2 scenario but increase by about 4% in B2 scenario; and there were no apparent changes in pan evaporation. It was concluded that in the next 30 years, climate would be warmer and drier, extreme events could be more intense, and autumn might be the most distinct season among all the changes.