Seasonal Mean Sea Level Pressure Research Articles

Multi-model projections of twenty-first century North Pacific winter wave climate under the IPCC A2 scenario

A dynamical wave model implemented over the North Pacific Ocean was forced with winds from three coupled global climate models (CGCMs) run under a medium-to-high scenario for greenhouse gas emissions through the twenty-first century. The results are analyzed with respect to changes in upper quantiles of significant wave height (90th and 99th percentile HS) during boreal winter. The three CGCMs produce surprisingly similar patterns of change in winter wave climate during the century, with waves becoming 10–15 % smaller over the lower mid-latitudes of the North Pacific, particularly in the central and western ocean. These decreases are closely associated with decreasing windspeeds along the southern flank of the main core of the westerlies. At higher latitudes, 99th percentile wave heights generally increase, though the patterns of change are less uniform than at lower latitudes. The increased wave heights at high latitudes appear to be due a variety of wind-related factors including both increased windspeeds and changes in the structure of the wind field, these varying from model to model. For one of the CGCMs, a commonly used statistical approach for estimating seasonal quantiles of HS on the basis of seasonal mean sea level pressure (SLP) is used to develop a regression model from 60 years of twentieth century data as a training set, and then applied using twenty-first century SLP data. The statistical model reproduces the general pattern of decreasing twenty-first century wave heights south of ~40 N, but underestimates the magnitude of the changes by ~50–70 %, reflecting relatively weak coupling between sea level pressure and wave heights in the CGCM data and loss of variability in the statistically projected wave heights.

Changes in Present and Future Circulation Types Frequency in Northwest Iberian Peninsula

The aim of the work described herein was to study projection scenarios in order to find changes in the synoptic variability of the northwest Iberian Peninsula in the 21st century. To this end, we investigated the changes in the frequency of the different circulation types computed for the study area using three different models used in the IPCC 4th assessment report. The circulation types were computed using the procedure known as Lamb circulation types. The control simulation for the late 20th century was evaluated objectively from the results obtained using data from the NCEP/NCAR reanalysis, as to evaluate the ability of the model to reproduce the present climate. We have compared not only seasonal mean sea level pressure fields but also the mean seasonal frequency of circulation types. The results for the end of the 21st century show a decrease in the frequency of cyclonic, W, and SW circulation types in the spring and summer months. This trend also appears in the autumn, with a concomitant increase in the anticyclonic types.

Exploring multi-model atmospheric GCM ensembles with ANOVA

Analysis of variance (ANOVA) is a powerful statistical technique for making inferences about experiments that are influenced by multiple factors. Whilst common in many other scientific fields, its use within the climate community has been limited to date. Here we review the basis for ANOVA and how, in particular, it can be applied to partition the variance in a multi-model ensemble of Atmospheric General Circulation Model simulations. We examine an ensemble of four AGCMs forced with observed twentieth century sea surface temperatures (SST). We show that the dominant contributions to the total variance of seasonal mean sea level pressure arise from between-model differences (the bias term) and internal noise (the noise term). However, which term is most important varies from region to region. Of particular interest is the interaction term, which describes differences between the models in their responses to common SST forcing. The interaction term is found to be largest over the Indian Ocean (in all seasons), and over the subtropical Northwest Pacific in boreal summer. The differences between the model responses in these regions suggest differences in their simulation of atmospheric teleconnections, with potentially important implications, e.g. for seasonal predictions of the South and East Asian Monsoons. Examination of these differences may lead to an understanding of the reasons why models respond differently to common forcing, and ultimately to improvements in the performance of climate models.

Projection and Analysis of Extreme Wave Climate

Abstract The nonhomogeneous Poisson process is used to model extreme values of the 40-yr ECMWF Re-Analysis (ERA-40) significant wave height. The parameters of the model are expressed as functions of the seasonal mean sea level pressure anomaly and seasonal squared sea level pressure gradient index. Using projections of the sea level pressure under three different forcing scenarios by the Canadian coupled climate model, projections of the parameters of the nonhomogeneous Poisson process are made, trends in these projections are determined, return-value estimates of significant wave height up to the end of the twenty-first century are projected, and their uncertainties are assessed. The uncertainty of estimates associated with the nonhomogeneous Poisson process estimates is studied and compared with the homologous estimates obtained using a nonstationary generalized extreme value model.

On the ability of the regional climate model RIEMS to simulate the present climate over Asia

A continuous 10-year simulation in Asia for the period of 1 July 1988 to 31 December 1998 was conducted using the Regional Integrated Environmental Model System (RIEMS) with NCEP Reanalysis II data as the driving fields. The model processes include surface physics state package (BATS 1e), a Holtslag explicit planetary boundary layer formulation, a Grell cumulus parameterization, and a modified radiation package (CCM3). Model-produced surface temperature and precipitation are compared with observations from 1001 meteorology stations distributed over Asia and with the 0.5° × 0.5° CRU gridded dataset. The analysis results show that: (1) RIEMS reproduces well the spatial pattern and the seasonal cycle of surface temperature and precipitation; (2) When regionally averaged, the seasonal mean temperature biases are within 1–2°C. For precipitation, the model tends to give better simulation in winter than in summer, and seasonal precipitation biases are mostly in the range of −12%–50%; (3) Spatial correlation coefficients between observed and simulated seasonal precipitation are higher in north of the Yangtze River than in the south and higher in winter than in summer; (4) RIEMS can well reproduce the spatial pattern of seasonal mean sea level pressure. In winter, the model-simulated Siberian high is stronger than the observed. In summer, the simulated subtropical high is shifted northwestwards: (5) The temporal evolution of the East Asia summer monsoon rain belt, with steady phases separated by more rapid transitions, is reproduced.

Interpretation of Enhanced Integrated Water Vapor Bands Associated with Extratropical Cyclones: Their Formation and Connection to Tropical Moisture

Abstract Trajectory analysis using a weather prediction model is performed for five cases to interpret the formation of enhanced bands of vertically integrated water vapor (IWV) in the central and eastern Pacific that are frequently seen in satellite images from the Special Sensor Microwave Imager. The connection of these enhanced bands with poleward water vapor transport from the Tropics is also examined. It is shown that the leading end of the enhanced IWV bands (defined as the most eastward and poleward end) is the manifestation of moisture convergence in the warm conveyor belt associated with extratropical cyclones, while the bands away from the leading end result mainly from moisture convergence along the trailing cold fronts. There is evidence that some enhanced IWV bands may be associated with a direct poleward transport of tropical moisture along the IWV bands from the Tropics all the way to the extratropics. The trajectory analysis, together with the seasonal mean sea level pressure analysis, indicates that a favorable condition for the occurrence of a direct, along-IWV band transport of tropical (defined as south of 23.5°N) moisture to the U.S. West Coast in the eastern Pacific is a weakened subtropical ridge in the central Pacific with an enhanced southwesterly low-level flow. The authors hypothesize that the direct poleward transport of tropical moisture within an enhanced IWV band in the eastern Pacific is most possible in the neutral El Niño–Southern Oscillation (ENSO) phase and is least possible in the El Niño phase.

New Zealand climate change information derived by multivariate statistical and artificial neural networks approaches

AbstractClimate change impact assessment requires data at the spatial and the temporal resolution at which impacts occur. The outputs of the current global climate models (GCMs) cannot be used directly in the development of desired climate change scenarios due to their coarse resolution. Artificial neural network (ANN) and multivariate statistics (MST) models were adapted to derive changes of site precipitation and temperature characteristics in a comparative study of their potential in downscaling GCM outputs. They were calibrated and verified using observed site temperature and precipitation over New Zealand and circulation variables from the National Center for Environment Prediction (NCEP) reanalysis.Subsequently, the models were used to derive changes of mean monthly precipitation and temperature characteristics from circulation variables projected in a transient climate change experiment performed by the Hadley Centre Global Climate Model (HadCM2). HadCM2 validated well with respect to NCEP reanalysis for its ‘present climate’ simulation. The predicted changes in seasonal mean sea level pressure fields over the ‘New Zealand region’ include intensified westerly flow particularly in winter. Therefore, the HadCM2 outputs contain information that can be used to derive localized climate change characteristics.Both downscaling models capture similar general patterns of change from the same GCM output, although they show substantial differences in localized characteristics, particularly for precipitation. The MST model suggests greater warming than the ANN model but both show larger temperature rises in summer and spring than in other seasons. Precipitation changes have marked spatial variation in their magnitude and direction; although by 2070–2099 more sites show precipitation increases than decreases, except for spring, and precipitation increases are more common in the North Island than the South Island. This intercomparison of two downscaling methods demonstrates an important source of uncertainty in regional climate change scenarios in addition to differing regional responses of GCMs. Copyright © 2001 Royal Meteorological Society

NON-DIMENSIONAL MEASURES OF CLIMATE MODEL PERFORMANCE

The characteristics of several non-dimensional measures of skill, which can be readily used to quantify the accuracy of simulated climatologica l fields, are examined. The correlation coefficient, the ‘SITES1’ measure, and two forms of Willmott's ‘index of agreement’ are compared with Mielke's measure of agreement, ρ=1−δ/μ, where δ is either mean square or mean absolute error, and μ is the expected value of δ if the simulated values are distributed randomly over the global grid-points. It is shown that, after certain transformations, the measures converge similarly to unity, for small errors. Fields simulated by the CSIRO9 general circulation model are used to illustrate the behaviour of the measures. Although all the measures can be useful, it is shown that the transformation M of the mean square ρ, where M= arcsin(ρ)/π, is especially practical. Three examples of its use are given. In comparing the skill of several climate models in simulating the global distribution of seasonal mean sea-level pressure, M ranged from 0·02 to 0·75. In comparing the skill of CSIRO9 in simulating various climatological quantities, M values ranged from 0·23 for cloud cover to 0·85 for surface air temperature. In comparing present and doubled CO2; climates simulated by CSIRO9, the quantity with the largest change, relative to its spatial variation, is the water vapour column (M=0·67) and that with the smallest change is sea-level pressure (M=0·90).

Prediction of ENSO Episodes Using Canonical Correlation Analysis

Abstract Canonical correlation analysis (CCA) is explored as a multivariate linear statistical methodology with which to forecast fluctuations of the El Nino/Southern Oscillation (ENSO) in real time. CCA is capable of identifying critical sequence of predictor patterns that tend to evolve into subsequent patterns that can be used to form a forecast. The CCA model is used to forecast the 3-month mean sea surface temperature (SST) in several regions of the tropical Pacific and Indian oceans for projection times of 0 to 4 seasons beyond the immediately forthcoming season. The predictor variables, representing the climate situation in the four consecutive 3-month periods ending at the time of the forecast, are 1) quasi-global seasonal mean sea level pressure (SLP) and 2) SST in the predictand regions themselves. Forecast skill is estimated using cross-validation, and persistence is used as the primary skill control measure. Results indicate that a large region in the eastern equatorial Pacific (120°−170°W lon...

Provisionally Corrected Surface Wind Data, Worldwide Ocean-Atmosphere Surface Fields, and Sahellan Rainfall Variability

Abstract Worldwide ship datasets of sea surface temperature (SST), sea level pressure (SLP), and surface vector wind are analyzed for a July-September composite of five Sabelian wet years (1950, 1952, 1953, 1954, 1958) minus five Sahelian dry years (1972, 1973, 1982, 1983, 1984) (W – D). The results are compared with fields for a number of individual years and for 1988 minus 1987 (88 – 87); Sahelian rainfall in 1988 was near the 1951–80 normal, whereas 1987 was very dry. Before performing the analyses, an extensive study of the geostrophic consistency of trends in pressure gradients and observed wind was undertaken, motivated by the suggestion that changes in observational practice on board ships have introduced an upward trend in reported wind speed during the last 40 years. The results suggest that, during the period 1949–88, there is a mean increase in reported wind speed of about 16% that cannot be explained by trends in geostrophic winds derived from seasonal mean SLP. Estimates of the wind bias are ...

Interannual Variability and Seasonal Climate Predictability

Abstract A twenty-year integration of an atmospheric general circulation model with identically evolving prescribed surface boundary conditions each year is employed to provide a measure of the interannual variability obtainable from internal atmospheric dynamics alone. In particular, the variability of seasonal mean sea level pressure and 700-mb geopotential height is considered by means of a sampled climate ensemble approach. This model-generated internal dynamics variability is assumed to be identical to that resulting from the real atmosphere if it operated without anomalous boundary conditions and is considered unpredictable since the time scales involved are beyond the traditional limits of deterministic predictability. By means of objective statistical tests, sampled model variances for these fields are compared to sampled variances of observed seasonal means (which have contributions from anomalous boundary conditions as well) for all four seasons in order to ascertain if, in an infinite populatio...

Spatial Variability of Seasonal Sea Level Pressure and 500 mb Height Anomalies

Abstract The spatial variability of seasonal mean sea level pressure (SLP) and 500 mb height anomalies are determined using eigenvector analysis. Previously, spatial variability had only been analyzed in such a manner during winter months, and the time coefficients of the eigenvectors of SLP and 500 mb heights were not compared. The eigenvectors of SLP and 500 mb heights obtained here are compared during each season, and the vectors are compared between seasons. Surface and 500 mb level eigenvector coefficients are found to be correlated and they are correlated in some seasons to air temperatures at surface stations. The data used were National Meteorological Center analyses of daily SLP and 500 mb heights between 1946 and 1977. The eigenvectors are determined for the covariance matrices of seasonal mean pressure and height departures from the 31 or 32 year long term normal over a 132 grid-point network. The coefficients of the first eigenvector of 500 mb heights are most highly correlated to the coeffici...