Multi-satellite observed responses of precipitation and its extremes to interannual climate variability

The consistency of precipitation variability estimated from the multiple satellite-based observing systems is assessed. There is generally good agreement between TRMM TMI, SSM/I, GPCP and AMSRE datasets for the inter-annual variability of precipitation since 1997 but the HOAPS dataset appears to overestimate the magnitude of variability. Over the tropical ocean the TRMM 3B42 dataset produces unrealistic variabilitys. Based upon deseasonalised GPCP data for the period 1998-2008, the sensitivity of global mean precipitation (P) to surface temperature (T) changes (dP/dT) is about 6%/K, although a smaller sensitivity of 3.6%/K is found using monthly GPCP data over the longer period 1989-2008. Over the tropical oceans dP/dT ranges from 10-30%/K depending upon time-period and dataset while over tropical land dP/dT is -8 to -11%/K for the 1998-2008 period. Analyzing the response of the tropical ocean precipitation intensity distribution to changes in T we find the wetter area P shows a strong positive response to T of around 20%/K. The response over the drier tropical regimes is less coherent and varies with datasets, but responses over the tropical land show significant negative relationships over an interannual time-scale. The spatial and temporal resolutions of the datasets strongly influence the precipitation responses over the tropical oceans and help explain some of the discrepancy between different datasets. Consistency between datasets is found to increase on averaging from daily to 5-day time-scales and considering a 1o (or coarser) spatial resolution. Defining the wet and dry tropical ocean regime by the 60th percentile of P intensity, the 5-day average, 1o TMI data exhibits a coherent drying of the dry regime at the rate of -20%/K and the wet regime becomes wetter at a similar rate with warming.

Seasonality and interannual variability of the westerly jet in the Tibetan Plateau region

In this study, 40-yr ECMWF Re-Analysis (ERA-40) data are used for the description of the seasonal cycle and the interannual variability of the westerly jet in the Tibetan Plateau region. To complement results based on the analysis of monthly mean horizontal wind speeds, an occurrence-based jet climatology is constructed by identifying the locations of the jet axes at 6-hourly intervals throughout 1958–2001. Thus, a dataset describing the highly transient and localized features of jet variability is obtained. During winter and summer the westerly jet is located, respectively, to the south and north of the Tibetan Plateau. During the spring and autumn seasons there are jet transitions from south to north and vice versa. The median dates for these transitions are 28 April and 12 October. The spring transition is associated with large interannual variations, while the fall transition occurs more reliably within a 3-week period. The strength of the jet exhibits a peculiar seasonal cycle. During northward migration in April/May, the jet intensity weakens and its latitudinal position varies largely. In some springs, there are several transitions and split configurations occur before the jet settles in its northern summer position. In June, a well-defined and unusually strong jet reappears at the northern flanks of the Tibetan Plateau. In autumn, the jet gradually but reliably recedes to the south and is typically more intense than in spring. The jet transitions between the two preferred locations follow the seasonal latitudinal migration of the jet in the Northern Hemisphere. An analysis of interannual variations shows the statistical relationship between the strength of the summer jet, the tropospheric meridional temperature gradient, and the all-India rainfall series. Both this analysis and results from previous studies point to the particular dynamical relevance of the onsetting Indian summer monsoon precipitation and the associated diabatic heating for the formation of the strong summer jet. Finally, an example is provided that illustrates the climatological significance of the jet in terms of the covariation between the jet location and the spatial precipitation distribution in central Asia.

Spatial and temporal modeling of community non-timber forest extraction

This paper examines the interaction of spatial and dynamic aspects of resource extraction from forests by local people. Highly cyclical and varied across space and time, the patterns of resource extraction resulting from the spatial–temporal model bear little resemblance to the patterns drawn from focusing either on spatial or temporal aspects of extraction alone. Ignoring this variability inaccurately depicts villagers’ dependence on different parts of the forest and could result in inappropriate policies. Similarly, the spatial links in extraction decisions imply that policies imposed in one area can have unintended consequences in other areas. Combining the spatial–temporal model with a measure of success in community forest management—the ability to avoid open-access resource degradation—characterizes the impact of incomplete property rights on patterns of resource extraction and stocks.

Assessing and understanding the impact of stratospheric dynamics and variability on the earth system

Advances in weather and climate research have demonstrated the role of the stratosphere in the Earth system across a wide range of temporal and spatial scales. Stratospheric ozone loss has been identified as a key driver of Southern Hemisphere tropospheric circulation trends, affecting ocean currents and carbon uptake, sea ice, and possibly even the Antarctic ice sheets. Stratospheric variability has also been shown to affect short term and seasonal forecasts, connecting the tropics and midlatitudes and guiding storm track dynamics. The two-way interactions between the stratosphere and the Earth system have motivated the World Climate Research Programme's (WCRP) Stratospheric Processes and Their Role in Climate (SPARC) DynVar activity to investigate the impact of stratospheric dynamics and variability on climate. This assessment will be made possible by two new multi-model datasets. First, roughly 10 models with a well resolved stratosphere are participating in the Coupled Model Intercomparison Project 5 (CMIP5), providing the first multi-model ensemble of climate simulations coupled from the stratopause to the sea floor. Second, the Stratosphere Historical Forecasting Project (SHFP) of WCRP's Climate Variability and predictability (CLIVAR) program is forming a multi-model set of seasonal hindcasts with stratosphere resolving models, revealing the impact of both stratospheric initial conditions and dynamics on intraseasonal prediction. The CMIP5 and SHFP model-data sets will offer an unprecedented opportunity to understand the role of the stratosphere in the natural and forced variability of the Earth system and to determine whether incorporating knowledge of the middle atmosphere improves seasonal forecasts and climate projections. Capsule New modeling efforts will provide unprecedented opportunities to harness our knowledge of the stratosphere to improve weather and climate prediction.

Arctic Oscillation and Antarctic Oscillation in internal atmospheric variability

n this study, we investigated the features of Arctic Oscillation (AO) and Antarctic Oscillation (AAO), that is, the annular modes in the extratropics, in the internal atmospheric variability attained through an ensemble of integrations by an atmospheric general circulation model (AGCM) forced with the global observed SSTs. We focused on the interannual variability of AO/AAO, which is dominated by internal atmospheric variability. In comparison with previous observed results, the AO/AAO in internal atmospheric variability bear some similar characteristics, but exhibit a much clearer spatial structure: significant correlation between the North Pacific and North Atlantic centers of action, much stronger and more significant associated precipitation anomalies, and the meridional displacement of upper-tropospheric westerly jet streams in the Northern/Southern Hemisphere. In addition, we examined the relationship between the North Atlantic Oscillation (NAO)/AO and East Asian winter monsoon (EAWM). It has been shown that in the internal atmospheric variability, the EAWM variation is significantly related to the NAO through upper-tropospheric atmospheric teleconnection patterns.

Cloud bands over southern Africa: seasonality, contribution to rainfall variability, and modulation by the MJO

Tropical-extratropical cloud band systems over southern Africa, known as tropical temperate troughs (TTTs), are known to contribute substantially to South African summer rainfall. This study performs a comprehensive assessment of the seasonal cycle and rainfall contribution of TTTs by using a novel object-based strategy that explicitly tracks these systems for their full life cycle. The methodology incorporates a simple assignment of station rainfall data to each event, thereby creating a database containing detailed rainfall characteristics for each TTT. This is used to explore the importance of TTTs for rain days and climatological rainfall totals in October–March. Average contributions range from 30 to 60 % with substantial spatial heterogeneity observed. TTT rainfall contributions over the Highveld and eastern escarpment are lower than expected. A short analysis of TTT rainfall variability indicates TTTs provide substantial, but not dominant, intraseasonal and interannual variability in station rainfall totals. TTTs are however responsible for a high proportion of heavy rainfall days. Of 52 extreme rainfall events in the 1979–1999 period, 30 are associated with these tropical-extratropical interactions. Cut-off lows were included in the evolution of 6 of these TTTs. The study concludes with an analysis of the question: does the Madden-Julian Oscillation influence the intensity of TTT rainfall over South Africa? Results suggest a weak but significant suppression (enhancement) of intensity during phase 1(6).

Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability

Systematic climate shifts have been linked to multidecadal variability in observed sea surface temperatures in the North Atlantic Ocean1. These links are extensive, influencing a range of climate processes such as hurricane activity2 and African Sahel3, 4, 5 and Amazonian5 droughts. The variability is distinct from historical global-mean temperature changes and is commonly attributed to natural ocean oscillations6, 7, 8, 9, 10. A number of studies have provided evidence that aerosols can influence long-term changes in sea surface temperatures11, 12, but climate models have so far failed to reproduce these interactions6, 9 and the role of aerosols in decadal variability remains unclear. Here we use a state-of-the-art Earth system climate model to show that aerosol emissions and periods of volcanic activity explain 76 per cent of the simulated multidecadal variance in detrended 1860–2005 North Atlantic sea surface temperatures. After 1950, simulated variability is within observational estimates; our estimates for 1910–1940 capture twice the warming of previous generation models but do not explain the entire observed trend. Other processes, such as ocean circulation, may also have contributed to variability in the early twentieth century. Mechanistically, we find that inclusion of aerosol–cloud microphysical effects, which were included in few previous multimodel ensembles, dominates the magnitude (80 per cent) and the spatial pattern of the total surface aerosol forcing in the North Atlantic. Our findings suggest that anthropogenic aerosol emissions influenced a range of societally important historical climate events such as peaks in hurricane activity and Sahel drought. Decadal-scale model predictions of regional Atlantic climate will probably be improved by incorporating aerosol–cloud microphysical interactions and estimates of future concentrations of aerosols, emissions of which are directly addressable by policy actions.

Stratosphere‐troposphere coupling and annular mode variability in chemistry‐climate models

The internal variability and coupling between the stratosphere and troposphere in CCMVal‐2 chemistry‐climate models are evaluated through analysis of the annular mode patterns of variability. Computation of the annular modes in long data sets with secular trends requires refinement of the standard definition of the annular mode, and a more robust procedure that allows for slowly varying trends is established and verified. The spatial and temporal structure of the models’ annular modes is then compared with that of reanalyses. As a whole, the models capture the key features of observed intraseasonal variability, including the sharp vertical gradients in structure between stratosphere and troposphere, the asymmetries in the seasonal cycle between the Northern and Southern hemispheres, and the coupling between the polar stratospheric vortices and tropospheric midlatitude jets. It is also found that the annular mode variability changes little in time throughout simulations of the 21st century. There are, however, both common biases and significant differences in performance in the models. In the troposphere, the annular mode in models is generally too persistent, particularly in the Southern Hemisphere summer, a bias similar to that found in CMIP3 coupled climate models. In the stratosphere, the periods of peak variance and coupling with the troposphere are delayed by about a month in both hemispheres. The relationship between increased variability of the stratosphere and increased persistence in the troposphere suggests that some tropospheric biases may be related to stratospheric biases and that a well‐simulated stratosphere can improve simulation of tropospheric intraseasonal variability.

Climatology and variability in the ECHO coupled GCM

ECHO is a new global coupled ocean-atmosphere general circulation model (GCM), consisting of the Hamburg version of the European Centre atmospheric GCM (ECHAM) and the Hamburg Primitive Equation ocean GCM (HOPE). We performed a 20-year integration with ECHO. Climate drift is significant, but typical annual mean errors in sea surface temperature (SST) do not exceed 2° in the open oceans. Near the boundaries, however, SST errors are considerably larger. The coupled model simulates an irregular ENSO cycle in the tropical Pacific, with spatial patterns similar to those observed. The variability, however, is somewhat weaker relative to observations. ECHO also simulates significant interannual variability in mid-latitudes. Consistent with observations, variability over the North Pacific can be partly attributed to remote forcing from the tropics. In contrast, the interannual variability over the North Atlantic appears to be generated locally.

Have aerosols caused the observed Atlantic multidecadal variability?

Identifying the prime drivers of the twentieth-century multidecadal variability in the Atlantic Ocean is crucial for predicting how the Atlantic will evolve in the coming decades and the resulting broad impacts on weather and precipitation patterns around the globe. Recently, Booth et al. showed that the Hadley Centre Global Environmental Model, version 2, Earth system configuration (HadGEM2-ES) closely reproduces the observed multidecadal variations of area-averaged North Atlantic sea surface temperature in the twentieth century. The multidecadal variations simulated in HadGEM2-ES are primarily driven by aerosol indirect effects that modify net surface shortwave radiation. On the basis of these results, Booth et al. concluded that aerosols are a prime driver of twentieth-century North Atlantic climate variability. However, here it is shown that there are major discrepancies between the HadGEM2-ES simulations and observations in the North Atlantic upper-ocean heat content, in the spatial pattern of multidecadal SST changes within and outside the North Atlantic, and in the subpolar North Atlantic sea surface salinity. These discrepancies may be strongly influenced by, and indeed in large part caused by, aerosol effects. It is also shown that the aerosol effects simulated in HadGEM2-ES cannot account for the observed anticorrelation between detrended multidecadal surface and subsurface temperature variations in the tropical North Atlantic. These discrepancies cast considerable doubt on the claim that aerosol forcing drives the bulk of this multidecadal variability.

The impact of diurnal variability in sea surface temperature on the atlantic air-sea CO2 flux

The effect of diurnal variations in sea surface temperature (SST) on the air-sea flux of CO2 over the central Atlantic ocean and Mediterranean Sea (60 S–60 N, 60 W–45 E) is evaluated for 2005–2006. We use high spatial resolution hourly satellite ocean skin temperature data to determine the diurnal warming (ΔSST). The CO2 flux is then computed using three different temperature fields – a foundation temperature (Tf, measured at a depth where there is no diurnal variation), Tf, plus the hourly ΔSST and Tf, plus the monthly average of the ΔSSTs. This is done in conjunction with a physically-based parameterisation for the gas transfer velocity (NOAA-COARE). The differences between the fluxes evaluated for these three different temperature fields quantify the effects of both diurnal warming and diurnal covariations. We find that including diurnal warming increases the CO2 flux out of this region of the Atlantic for 2005–2006 from 9.6 Tg C a−1 to 30.4 Tg C a−1 (hourly ΔSST) and 31.2 Tg C a−1 (monthly average of ΔSST measurements). Diurnal warming in this region, therefore, has a large impact on the annual net CO2 flux but diurnal covariations are negligible. However, in this region of the Atlantic the uptake and outgassing of CO2 is approximately balanced over the annual cycle, so although we find diurnal warming has a very large effect here, the Atlantic as a whole is a very strong carbon sink (e.g. −920 Tg C a−1 Takahashi et al., 2002) making this is a small contribution to the Atlantic carbon budget.

A spatial view of ensemble spread in convection permitting ensembles

With movement toward kilometer-scale ensembles, new techniques are needed for their characterization. A new methodology is presented for detailed spatial ensemble characterization using the fractions skill score (FSS). To evaluate spatial forecast differences, the average and standard deviation are taken of the FSS calculated over all ensemble member–member pairs at different scales and lead times. These methods were found to give important information about the ensemble behavior allowing the identification of useful spatial scales, spinup times for the model, and upscale growth of errors and forecast differences. The ensemble spread was found to be highly dependent on the spatial scales considered and the threshold applied to the field. High thresholds picked out localized and intense values that gave large temporal variability in ensemble spread: local processes and undersampling dominate for these thresholds. For lower thresholds the ensemble spread increases with time as differences between the ensemble members upscale. Two convective cases were investigated based on the Met Office United Model run at 2.2-km resolution. Different ensemble types were considered: ensembles produced using the Met Office Global and Regional Ensemble Prediction System (MOGREPS) and an ensemble produced using different model physics configurations. Comparison of the MOGREPS and multiphysics ensembles demonstrated the utility of spatial ensemble evaluation techniques for assessing the impact of different perturbation strategies and the need for assessing spread at different, believable, spatial scales.

Investigation of the accuracy of historical irradiance products and interannual variability of solar irradiance using Met Office ground data

Met Office station data from 1980 to 2012 has been used to characterise the interannual variability of incident solar irradiance across the UK. The same data are used to evaluate four popular historical irradiance products to determine which are most suitable for use by the UK PV industry for site selection and system design. The study confirmed previous findings that interannual variability is typically 3–6% and weighted average probability of a particular percentage deviation from the mean at an average site in the UK was calculated. This weighted average showed that fewer than 2% of site-years could be expected to fall below 90% of the long-term site mean. The historical irradiance products were compared against Met Office station data from the input years of each product. This investigation has found that all products perform well. No products have a strong spatial trend. Meteonorm 7 is most conservative (MBE = −2.5%), CMSAF is most optimistic (MBE = +3.4%) and an average of all four products performs better than any one individual product (MBE = 0.3%)

Climate variability and human impact in South America during the last 2000 years: synthesis and perspectives from pollen records

An improved understanding of present-day climate variability and change relies on high-quality data sets from the past 2 millennia. Global efforts to model regional climate modes are in the process of being validated against, and integrated with, records of past vegetation change. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to an absence of information on the spatial and temporal coverage of study sites. This paper therefore serves as a guide to high-quality pollen records that capture environmental variability during the last 2 millennia. We identify 60 vegetation (pollen) records from across South America which satisfy geochronological requirements set out for climate modelling, and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local-scale responses to climate modes; thus, it is necessary to understand how vegetation–climate interactions might diverge under variable settings. We provide a qualitative translation from pollen metrics to climate variables. Additionally, pollen is an excellent indicator of human impact through time. We discuss evidence for human land use in pollen records and provide an overview considered useful for archaeological hypothesis testing and important in distinguishing natural from anthropogenically driven vegetation change. We stress the need for the palynological community to be more familiar with climate variability patterns to correctly attribute the potential causes of observed vegetation dynamics. This manuscript forms part of the wider LOng-Term multi-proxy climate REconstructions and Dynamics in South America – 2k initiative that provides the ideal framework for the integration of the various palaeoclimatic subdisciplines and palaeo-science, thereby jump-starting and fostering multidisciplinary research into environmental change on centennial and millennial timescales.

Spatial and temporal variations of the seasonal sea level cycle in the northwest Pacific

The seasonal sea level variations observed from tide gauges over 1900-2013 and gridded satellite altimeter product AVISO over 1993-2013 in the northwest Pacific have been explored. The seasonal cycle is able to explain 60-90% of monthly sea level variance in the marginal seas, while it explains less than 20% of variance in the eddy-rich regions. The maximum annual and semi-annual sea level cycles (30cm and 6cm) are observed in the north of the East China Sea and the west of the South China Sea respectively. AVISO was found to underestimate the annual amplitude by 25% compared to tide gauge estimates along the coasts of China and Russia. The forcing for the seasonal sea level cycle was identified. The atmospheric pressure and the steric height produce 8-12cm of the annual cycle in the middle continental shelf and in the Kuroshio Current regions separately. The removal of the two attributors from total sea level permits to identify the sea level residuals that still show significant seasonality in the marginal seas. Both nearby wind stress and surface currents can explain well the long-term variability of the seasonal sea level cycle in the marginal seas and the tropics because of their influence on the sea level residuals. Interestingly, the surface currents are a better descriptor in the areas where the ocean currents are known to be strong. Here, they explain 50-90% of inter-annual variability due to the strong links between the steric height and the large-scale ocean currents.