Stratospheric influence on baroclinic lifecycles and its connection to the Arctic Oscillation

Using an idealized primitive equation model, we investigate how stratospheric conditions alter the development of baroclinic instability in the troposphere. Starting from the lifecycle paradigm of Thorncroft et al., we consider the evolution of baroclinic lifecycles resulting from the addition of a stratospheric jet to the LC1 initial condition. We find that the addition of the stratospheric jet yields a net surface geopotential height anomaly that strongly resembles the Arctic Oscillation. With the additional modification of the tropospheric winds to resemble the high-AO climatology, the surface response is amplified by a factor 10 and, though dominated by the tropospheric changes, shows similar sensitivity to the stratospheric conditions.

On the influence of stratospheric water vapor changes on the tropospheric circulation

Observations suggest that the mixing ratio of water vapour in the stratosphere has increased by 20–50% between the 1960s and mid-1990s. Here we show that inclusion of such a stratospheric water vapour (SWV) increase in a state-of-the-art climate model modifies the circulation of the extratropical troposphere: the modeled increase in the North Atlantic Oscillation (NAO) index is 40% of the observed increase in NAO index between 1965 and 1995, suggesting that if the SWV trend is real, it explains a significant fraction of the observed NAO trend. Our results imply that SWV changes provide a novel mechanism for communicating the effects of large tropical volcanic eruptions and ENSO events to the extratropical troposphere over timescales of a few years, which provides a mechanism for interannual climate predictability. Finally, we discuss our results in the context of regional climate change associated with changes in methane emissions.

Effect of ENSO phase on large-scale snow water equivalent distribution in a GCM

Understanding links between the El Nino-Southern Oscillation (ENSO) and snow would be useful for seasonal forecasting, but also for understanding natural variability and interpreting climate change predictions. Here, a 545-year run of the general circulation model HadCM3, with prescribed external forcings and fixed greenhouse gas concentrations, is used to explore the impact of ENSO on snow water equivalent (SWE) anomalies. In North America, positive ENSO events reduce the mean SWE and skew the distribution towards lower values, and vice versa during negative ENSO events. This is associated with a dipole SWE anomaly structure, with anomalies of opposite sign centered in western Canada and the central United States. In Eurasia, warm episodes lead to a more positively skewed distribution and the mean SWE is raised. Again, the opposite effect is seen during cold episodes. In Eurasia the largest anomalies are concentrated in the Himalayas. These correlations with February SWE distribution are seen to exist from the previous June-July-August (JJA) ENSO index onwards, and are weakly detected in 50-year subsections of the control run, but only a shifted North American response can be detected in the anaylsis of 40 years of ERA40 reanalysis data. The ENSO signal in SWE from the long run could still contribute to regional predictions although it would be a weak indicator only

Land surface anomaly simulations and predictions with a climate model: an El Nino Southern Oscillation case study

The ability of climate models to reproduce and predict land surface anomalies is an important but little-studied topic. In this study, an atmosphere and ocean assimilation scheme is used to determine whether HadCM3 can reproduce and predict snow water equivalent and soil moisture during the 1997–1998 El Nino Southern Oscillation event. Soil moisture is reproduced more successfully, though both snow and soil moisture show some predictability at 1- and 4-month lead times. This result suggests that land surface anomalies may be reasonably well initialized for climate model predictions and hydrological applications using atmospheric assimilation methods over a period of time.

A new set of orthogonal patterns in weather and climate: Optimally interpolated patterns.

A new spectral-based approach is presented to find orthogonal patterns from gridded weather/climate data. The method is based on optimizing the interpolation error variance. The optimally interpolated patterns (OIP) are then given by the eigenvectors of the interpolation error covariance matrix, obtained using the cross-spectral matrix. The formulation of the approach is presented, and the application to low-dimension stochastic toy models and to various reanalyses datasets is performed. In particular, it is found that the lowest-frequency patterns correspond to largest eigenvalues, that is, variances, of the interpolation error matrix. The approach has been applied to the Northern Hemispheric (NH) and tropical sea level pressure (SLP) and to the Indian Ocean sea surface temperature (SST). Two main OIP patterns are found for the NH SLP representing respectively the North Atlantic Oscillation and the North Pacific pattern. The leading tropical SLP OIP represents the Southern Oscillation. For the Indian Ocean SST, the leading OIP pattern shows a tripole-like structure having one sign over the eastern and north- and southwestern parts and an opposite sign in the remaining parts of the basin. The pattern is also found to have a high lagged correlation with the Niño-3 index with 6-months lag.

Construction of a historical Water Pollution Index for the Mersey Basin

The Mersey Basin has been significantly polluted for over 200 years. However, there is a lack of quantitative historical water quality data as effective water quality monitoring and data recording only began 30-40 years ago. This paper assesses water pollution in the Mersey Basin using a Water Pollution Index constructed from social and economic data. Methodology, output and the difficulties involved with validation are discussed. With the limited data input available the index approximately reproduces historical water quality. The paper illustrates how historical studies of environmental water quality may provide valuable identification of factors responsible for pollution and a marker set for contemporary and future water quality issues in the context of the past. This is an issue of growing research interest.

A reconstructed Siberian High index since A. D. 1599 from Eurasian and North American tree rings

The long-term variability of the Siberian High, the dominant Northern Hemisphere anticyclone during winter, is largely unknown. To investigate how this feature varied prior to the instrumental record, we present a reconstruction of a Dec-Feb Siberian High (SH) index based on Eurasian and North American tree rings. Spanning 1599-1980, it provides information on SH variability over the past four centuries. A decline in the instrumental SH index since the late 1970s, related to Eurasian warming, is the most striking feature over the past four hundred years. It is associated with a highly significant (p < 0.0001) step change in 1989. Significant similar to 3-4 yr spectral peaks in the reconstruction fall within the range of variability of the East Asian winter monsoon (which has also declined recently) and lend further support to proposed relationships between these largescale features of the climate system.

On the long-term interannual variability of the east Asian winter monsoon

The East Asian Winter Monsoon (EAWM) and Siberian High (SH) are inherently related, based on prior studies of instrumental data available for recent decades (since 1958). Here we develop an extended instrumental EAWM index since 1871 that correlates significantly with the SH. These two indices show common modes of variation on the biennial (2-3 year) time scale. We also develop an index of the pressure gradient between the SH and the Aleutian Low, a gradient which critically impacts EAWM variability. This difference series, based on tree-ring reconstructions of the SH and the North Pacific Index (NPI) over the past 400 years, shows that the weakening of this gradient in recent decades has not been unusual in a long-term context. Correlations between the SH series and a tree-ring reconstruction of the El Nino-Southern Oscillation (ENSO) suggest a variable tropical-higher latitude teleconnection.

Uncertainties in annual riverine phosphorus load estimation: Impact of load estimation methodology, sampling frequency, baseflow index and catchment population density

Models developed to identify the rates and origins of nutrient export from land to stream require an accurate assessment of the nutrient load present in the water body in order to calibrate model parameters and structure. These data are rarely available at a representative scale and in an appropriate chemical form except in research catchments. Observational errors associated with nutrient load estimates based on these data lead to a high degree of uncertainty in modelling and nutrient budgeting studies. Here, daily paired instantaneous P and flow data for 17 UK research catchments covering a total of 39 water years (WY) have been used to explore the nature and extent of the observational error associated with nutrient flux estimates based on partial fractions and infrequent sampling. The daily records were artificially decimated to create 7 stratified sampling records, 7 weekly records, and 30 monthly records from each WY and catchment. These were used to evaluate the impact of sampling frequency on load estimate uncertainty. The analysis underlines the high uncertainty of load estimates based on monthly data and individual P fractions rather than total P. Catchments with a high baseflow index and/or low population density were found to return a lower RMSE on load estimates when sampled infrequently than those with a tow baseflow index and high population density. Catchment size was not shown to be important, though a limitation of this study is that daily records may fail to capture the full range of P export behaviour in smaller catchments with flashy hydrographs, leading to an underestimate of uncertainty in Load estimates for such catchments. Further analysis of sub-daily records is needed to investigate this fully. Here, recommendations are given on load estimation methodologies for different catchment types sampled at different frequencies, and the ways in which this analysis can be used to identify observational error and uncertainty for model calibration and nutrient budgeting studies. (c) 2006 Elsevier B.V. All rights reserved.

Greening the United Nations' Human Development Index?

The Human Development Index (HDI) introduced by the United Nations Development Programme (UNDP) in 1990 has helped facilitate widespread debate amongst development researchers, practitioners and policy makers. The HDI is an aggregate index, calculated on an annual basis by the UNDP and published in its Human Development Reports, comprising measures of three components deemed by them to be central to development: W income (the gross domestic product per capita), (ii) education (adult literacy rate) and (iii) health (life expectancy at birth). The results of calculating the HDI are typically presented as country/regional league tables, and provide a quick means for policy makers and others to judge performance. Perhaps partly because of the relative simplicity of the index, the HDI has managed to achieve a level of acceptance and use amongst politicians and policy makers that has yet to emerge with any indicator of sustainability. Indeed, despite its existence for 11 years, including nine years after the Rio Earth Summit, the HDI has not even been modified to take on board wider issues of sustainability. This paper will critically examine the potential for 'greening' the HDI so as to include environmental and resource-consumption dimensions. Copyright (C) 2003 John Wiley & Sons, Ltd and ERP Environment.

For better or for worse, till the human development index do us part?

This paper describes the results of research intended to explore the volatility inherent in the United Nations Development Programme's (UNDP) Human Development Index (HDI). The HDI is intended to be a simple and transparent device for comparing progress in human development, and is an aggregate of life expectancy, education and GDP per capita. Values of the HDI for each country are presented in the Human Development Reports (HDRs), the first being published in 1990. However, while the methodology is consistent for all countries in each year there are notable differences between years that make temporal comparisons of progress difficult. The paper presents the results of recalculating the HDI for a simplified sample of 114 countries using various methodologies employed by the UNDP. The results are a set of deviations of recalculated HDI ranks compared to the original ranks given in the HDRs. The volatility that can result from such recalculation is shown to be substantial (+/-10-15 ranks), yet reports in the popular press are frequently sensitive to movements of only a few ranks. Such movement can easily be accounted for by changes in the HDI methodology rather than genuine progress in human development. While the HDRs often carry warnings about the inadvisability of such year-on-year comparisons, it is argued that the existence of such a high-profile index and the overt presentation within league tables do encourage such comparison. Assuming that the HDI will be retained as a focal point within the HDRs, then it is suggested that greater focus be upon more meaningful and robust categories of human development (e.g. low, medium and high) rather than league tables where shifts of a few places, perhaps as a result of nothing more than a methodological or data artefact, may be highlighted in the press and by policy makers. (C) 2003 Elsevier Science B.V. All rights reserved.