Using idealized snow forcing to test teleconnections with the Indian summer monsoon in the Hadley Centre GCM

Anomalous heavy snow during winter or spring has long been regarded as a possible precursor of deficient Indian monsoon rainfall during the subsequent summer. However previous work in this field is inconclusive, in terms of the mechanism that communicates snow anomalies to the monsoon summer, and even the region from which snow has the most impact. In this study we explore these issues in coupled and atmosphere-only versions of the Hadley Centre model. A 1050-year control integration of the HadCM3 coupled model, which well represents the seasonal cycle of snow cover over the Eurasian continent, is analysed and shows evidence for weakened monsoons being preceded by strong snow forcing (in the absence of ENSO) over either the Himalaya/Tibetan Plateau or north/west Eurasia regions. However, empirical orthogonal function (EOF) analysis of springtime interannual variability in snow depth shows the leading mode to have opposite signs between these two regions, suggesting that competing mechanisms may be possible. To determine the dominant region, ensemble integrations are carried out using HadAM3, the atmospheric component of HadCM3, and a variety of anomalous snow forcing initial conditions obtained from the control integration of the coupled model. Forcings are applied during spring in separate experiments over the Himalaya/Tibetan Plateau and north/west Eurasia regions, in conjunction with climatological SSTs in order to avoid the direct effects of ENSO. With the aid of idealized forcing conditions in sensitivity tests, we demonstrate that forcing from the Himalaya region is dominant in this model via a Blanford-type mechanism involving reduced surface sensible heat and longwave fluxes, reduced heating of the troposphere over the Tibetan Plateau and consequently a reduced meridional tropospheric temperature gradient which weakens the monsoon during early summer. Snow albedo is shown to be key to the mechanism, explaining around 50% of the perturbation in sensible heating over the Tibetan Plateau, and accounting for the majority of cooling through the troposphere.

Past, present and future precipitation in the Middle East: insights from models and observations

Anthropogenic changes in precipitation pose a serious threat to society—particularly in regions such as the Middle East that already face serious water shortages. However, climate model projections of regional precipitation remain highly uncertain. Moreover, standard resolution climate models have particular difficulty representing precipitation in the Middle East, which is modulated by complex topography, inland water bodies and proximity to the Mediterranean Sea. Here we compare precipitation changes over the twenty-first century against both millennial variability during the Holocene and interannual variability in the present day. In order to assess the climate model and to make consistent comparisons, this study uses new regional climate model simulations of the past, present and future in conjunction with proxy and historical observations. We show that the pattern of precipitation change within Europe and the Middle East projected by the end of the twenty-first century has some similarities to that which occurred during the Holocene. In both cases, a poleward shift of the North Atlantic storm track and a weakening of the Mediterranean storm track appear to cause decreased winter rainfall in southern Europe and the Middle East and increased rainfall further north. In contrast, on an interannual time scale, anomalously dry seasons in the Middle East are associated with a strengthening and focusing of the storm track in the north Mediterranean and hence wet conditions throughout southern Europe.

Two Independent Triggers for the Indian Ocean Dipole/Zonal Mode in a Coupled GCM

The question of whether and how tropical Indian Ocean dipole or zonal mode (IOZM) interannual variability is independent of El Nino-Southern Oscillation (ENSO) variability in the Pacific is addressed in a comparison of twin 200-yr runs of a coupled climate model. The first is a reference simulation, and the second has ENSO-scale variability suppressed with a constraint on the tropical Pacific wind stress. The IOZM can exist in the model without ENSO, and the composite evolution of the main anomalies in the Indian Ocean in the two simulations is virtually identical. Its growth depends on a positive feedback between anomalous equatorial easterly winds, upwelling equatorial and coastal Kelvin waves reducing the thermocline depth and sea surface temperature off the coast of Sumatra, and the atmospheric dynamical response to the subsequently reduced convection. Two IOZM triggers in the boreal spring are found. The first is an anomalous Hadley circulation over the eastern tropical Indian Ocean and Maritime Continent, with an early northward penetration of the Southern Hemisphere southeasterly trades. This situation grows out of cooler sea surface temperatures in the southeastern tropical Indian Ocean left behind by a reinforcement of the late austral summer winds. The second trigger is a consequence of a zonal shift in the center of convection associated with a developing El Nino, a Walker cell anomaly. The first trigger is the only one present in the constrained simulation and is similar to the evolution of anomalies in 1994, when the IOZM occurred in the absence of a Pacific El Nino state. The presence of these two triggers-the first independent of ENSO and the second phase locking the IOZM to El Nino-allows an understanding of both the existence of IOZM events when Pacific conditions are neutral and the significant correlation between the IOZM and El Nino.

Predictability and skill of boreal winter forecasts made with the ECMWF Seasonal Forecasting System II

The performance of boreal winter forecasts made with the European Centre for Medium-Range Weather Forecasts (ECMWF) System 11 Seasonal Forecasting System is investigated through analyses of ensemble hindcasts for the period 1987-2001. The predictability, or signal-to-noise ratio, associated with the forecasts, and the forecast skill are examined. On average, forecasts of 500 hPa geopotential height (GPH) have skill in most of the Tropics and in a few regions of the extratropics. There is broad, but not perfect, agreement between regions of high predictability and regions of high skill. However, model errors are also identified, in particular regions where the forecast ensemble spread appears too small. For individual winters the information provided by t-values, a simple measure of the forecast signal-to-noise ratio, is investigated. For 2 m surface air temperature (T2m), highest t-values are found in the Tropics but there is considerable interannual variability, and in the tropical Atlantic and Indian basins this variability is not directly tied to the El Nino Southern Oscillation. For GPH there is also large interannual variability in t-values, but these variations cannot easily be predicted from the strength of the tropical sea-surface-temperature anomalies. It is argued that the t-values for 500 hPa GPH can give valuable insight into the oceanic forcing of the atmosphere that generates predictable signals in the model. Consequently, t-values may be a useful tool for understanding, at a mechanistic level, forecast successes and failures. Lastly, the extent to which t-values are useful as a predictor of forecast skill is investigated. For T2m, t-values provide a useful predictor of forecast skill in both the Tropics and extratropics. Except in the equatorial east Pacific, most of the information in t-values is associated with interannual variability of the ensemble-mean forecast rather than interannual variability of the ensemble spread. For GPH, however, t-values provide a useful predictor of forecast skill only in the tropical Pacific region.

The meteorology of the Western Indian Ocean, and the influence of the east African highlands

This paper reviews the meteorology of the Western Indian Ocean and uses a state–of–the–art atmospheric general circulation model to investigate the influence of the East African Highlands on the climate of the Indian Ocean and its surrounding regions. The new 44–year re–analysis produced by the European Centre for Medium range Weather Forecasts (ECMWF) has been used to construct a new climatology of the Western Indian Ocean. A brief overview of the seasonal cycle of the Western Indian Ocean is presented which emphasizes the importance of the geography of the Indian Ocean basin for controlling the meteorology of the Western Indian Ocean. The principal modes of inter–annual variability are described, associated with El Niño and the Indian Ocean Dipole or Zonal Mode, and the basic characteristics of the subseasonal weather over the Western Indian Ocean are presented, including new statistics on cyclone tracks derived from the ECMWF re–analyses. Sensitivity experiments, in which the orographic effects of East Africa are removed, have shown that the East African Highlands, although not very high, play a significant role in the climate of Africa, India and Southeast Asia, and in the heat, salinity and momentum forcing of the Western Indian Ocean. The hydrological cycle over Africa is systematically enhanced in all seasons by the presence of the East African Highlands, and during the Asian summer monsoon there is a major redistribution of the rainfall across India and Southeast Asia. The implied impact of the East African Highlands on the ocean is substantial. The East African Highlands systematically freshen the tropical Indian Ocean, and act to focus the monsoon winds along the coast, leading to greater upwelling and cooler sea–surface temperatures.

Key features of the IPSL ocean atmosphere model and its sensitivity to atmospheric resolution

This paper presents the major characteristics of the Institut Pierre Simon Laplace (IPSL) coupled ocean–atmosphere general circulation model. The model components and the coupling methodology are described, as well as the main characteristics of the climatology and interannual variability. The model results of the standard version used for IPCC climate projections, and for intercomparison projects like the Paleoclimate Modeling Intercomparison Project (PMIP 2) are compared to those with a higher resolution in the atmosphere. A focus on the North Atlantic and on the tropics is used to address the impact of the atmosphere resolution on processes and feedbacks. In the North Atlantic, the resolution change leads to an improved representation of the storm-tracks and the North Atlantic oscillation. The better representation of the wind structure increases the northward salt transports, the deep-water formation and the Atlantic meridional overturning circulation. In the tropics, the ocean–atmosphere dynamical coupling, or Bjerknes feedback, improves with the resolution. The amplitude of ENSO (El Niño-Southern oscillation) consequently increases, as the damping processes are left unchanged.

A model study of oceanic mechanisms affecting Equatorial Pacific sea surface temperature during the 1997-98 El Niño

In this study, the processes affecting sea surface temperature variability over the 1992–98 period, encompassing the very strong 1997–98 El Niño event, are analyzed. A tropical Pacific Ocean general circulation model, forced by a combination of weekly ERS1–2 and TAO wind stresses, and climatological heat and freshwater fluxes, is first validated against observations. The model reproduces the main features of the tropical Pacific mean state, despite a weaker than observed thermal stratification, a 0.1 m s−1 too strong (weak) South Equatorial Current (North Equatorial Countercurrent), and a slight underestimate of the Equatorial Undercurrent. Good agreement is found between the model dynamic height and TOPEX/Poseidon sea level variability, with correlation/rms differences of 0.80/4.7 cm on average in the 10°N–10°S band. The model sea surface temperature variability is a bit weak, but reproduces the main features of interannual variability during the 1992–98 period. The model compares well with the TAO current variability at the equator, with correlation/rms differences of 0.81/0.23 m s−1 for surface currents. The model therefore reproduces well the observed interannual variability, with wind stress as the only interannually varying forcing. This good agreement with observations provides confidence in the comprehensive three-dimensional circulation and thermal structure of the model. A close examination of mixed layer heat balance is thus undertaken, contrasting the mean seasonal cycle of the 1993–96 period and the 1997–98 El Niño. In the eastern Pacific, cooling by exchanges with the subsurface (vertical advection, mixing, and entrainment), the atmospheric forcing, and the eddies (mainly the tropical instability waves) are the three main contributors to the heat budget. In the central–western Pacific, the zonal advection by low-frequency currents becomes the main contributor. Westerly wind bursts (in December 1996 and March and June 1997) were found to play a decisive role in the onset of the 1997–98 El Niño. They contributed to the early warming in the eastern Pacific because the downwelling Kelvin waves that they excited diminished subsurface cooling there. But it is mainly through eastward advection of the warm pool that they generated temperature anomalies in the central Pacific. The end of El Niño can be linked to the large-scale easterly anomalies that developed in the western Pacific and spread eastward, from the end of 1997 onward. In the far-western Pacific, because of the shallower than normal thermocline, these easterlies cooled the SST by vertical processes. In the central Pacific, easterlies pushed the warm pool back to the west. In the east, they led to a shallower thermocline, which ultimately allowed subsurface cooling to resume and to quickly cool the surface layer.

Probabilistic simulations of crop yield over western India using the DEMETER seasonal hindcast ensembles

Process-based integrated modelling of weather and crop yield over large areas is becoming an important research topic. The production of the DEMETER ensemble hindcasts of weather allows this work to be carried out in a probabilistic framework. In this study, ensembles of crop yield (groundnut, Arachis hypogaea L.) were produced for 10 2.5 degrees x 2.5 degrees grid cells in western India using the DEMETER ensembles and the general large-area model (GLAM) for annual crops. Four key issues are addressed by this study. First, crop model calibration methods for use with weather ensemble data are assessed. Calibration using yield ensembles was more successful than calibration using reanalysis data (the European Centre for Medium-Range Weather Forecasts 40-yr reanalysis, ERA40). Secondly, the potential for probabilistic forecasting of crop failure is examined. The hindcasts show skill in the prediction of crop failure, with more severe failures being more predictable. Thirdly, the use of yield ensemble means to predict interannual variability in crop yield is examined and their skill assessed relative to baseline simulations using ERA40. The accuracy of multi-model yield ensemble means is equal to or greater than the accuracy using ERA40. Fourthly, the impact of two key uncertainties, sowing window and spatial scale, is briefly examined. The impact of uncertainty in the sowing window is greater with ERA40 than with the multi-model yield ensemble mean. Subgrid heterogeneity affects model accuracy: where correlations are low on the grid scale, they may be significantly positive on the subgrid scale. The implications of the results of this study for yield forecasting on seasonal time-scales are as follows. (i) There is the potential for probabilistic forecasting of crop failure (defined by a threshold yield value); forecasting of yield terciles shows less potential. (ii) Any improvement in the skill of climate models has the potential to translate into improved deterministic yield prediction. (iii) Whilst model input uncertainties are important, uncertainty in the sowing window may not require specific modelling. The implications of the results of this study for yield forecasting on multidecadal (climate change) time-scales are as follows. (i) The skill in the ensemble mean suggests that the perturbation, within uncertainty bounds, of crop and climate parameters, could potentially average out some of the errors associated with mean yield prediction. (ii) For a given technology trend, decadal fluctuations in the yield-gap parameter used by GLAM may be relatively small, implying some predictability on those time-scales.

Is there regime behavior in monsoon convection in the late 20th century?

Mixture model techniques are applied to a daily index of monsoon convection from ERA‐40 reanalysis to show regime behavior. The result is the existence of two significant regimes showing preferred locations of convection within the Asia/Western‐North Pacific domain, with some resemblance to active‐break events over India. Simple trend analysis over 1958–2001 shows that the first regime has become less frequent while the second becomes much more dominant. Both undergo a change in structure contributing to the total OLR trend over the ERA‐40 period. Stratifying the data according to a large‐scale dynamical index of monsoon interannual variability, we show the regime occurrence to be strongly perturbed by the seasonal condition, in agreement with conceptual ideas. This technique could be used to further examine predictability issues relating the seasonal mean and intraseasonal monsoon variability or to explore changes in monsoon behavior in centennial‐scale model integrations.

Processes governing the predictability of the Atlantic meridional overturning circulation in a coupled GCM

The processes that govern the predictability of decadal variations in the North Atlantic meridional overturning circulation (MOC) are investigated in a long control simulation of the ECHO-G coupled atmosphere–ocean model. We elucidate the roles of local stochastic forcing by the atmosphere, and other potential ocean processes, and use our results to build a predictive regression model. The primary influence on MOC variability is found to come from air–sea heat fluxes over the Eastern Labrador Sea. The maximum correlation between such anomalies and the variations in the MOC occurs at a lead time of 2 years, but we demonstrate that the MOC integrates the heat flux variations over a period of 10 years. The corresponding univariate regression model accounts for 74.5% of the interannual variability in the MOC (after the Ekman component has been removed). Dense anomalies to the south of the Greenland-Scotland ridge are also shown to precede the overturning variations by 4–6 years, and provide a second predictor. With the inclusion of this second predictor the resulting regression model explains 82.8% of the total variance of the MOC. This final bivariate model is also tested during large rapid decadal overturning events. The sign of the rapid change is always well represented by the bivariate model, but the magnitude is usually underestimated, suggesting that other processes are also important for these large rapid decadal changes in the MOC.

Evaluating the potential for statistical decadal predictions of sea surface temperatures with a perfect model approach

We explore the potential for making statistical decadal predictions of sea surface temperatures (SSTs) in a perfect model analysis, with a focus on the Atlantic basin. Various statistical methods (Lagged correlations, Linear Inverse Modelling and Constructed Analogue) are found to have significant skill in predicting the internal variability of Atlantic SSTs for up to a decade ahead in control integrations of two different global climate models (GCMs), namely HadCM3 and HadGEM1. Statistical methods which consider non-local information tend to perform best, but which is the most successful statistical method depends on the region considered, GCM data used and prediction lead time. However, the Constructed Analogue method tends to have the highest skill at longer lead times. Importantly, the regions of greatest prediction skill can be very different to regions identified as potentially predictable from variance explained arguments. This finding suggests that significant local decadal variability is not necessarily a prerequisite for skillful decadal predictions, and that the statistical methods are capturing some of the dynamics of low-frequency SST evolution. In particular, using data from HadGEM1, significant skill at lead times of 6–10 years is found in the tropical North Atlantic, a region with relatively little decadal variability compared to interannual variability. This skill appears to come from reconstructing the SSTs in the far north Atlantic, suggesting that the more northern latitudes are optimal for SST observations to improve predictions. We additionally explore whether adding sub-surface temperature data improves these decadal statistical predictions, and find that, again, it depends on the region, prediction lead time and GCM data used. Overall, we argue that the estimated prediction skill motivates the further development of statistical decadal predictions of SSTs as a benchmark for current and future GCM-based decadal climate predictions.

Clear-sky biases in satellite infrared estimates of upper tropospheric humidity and its trends

We use microwave retrievals of upper tropospheric humidity (UTH) to estimate the impact of clear-sky-only sampling by infrared instruments on the distribution, variability and trends in UTH. Our method isolates the impact of the clear-sky-only sampling, without convolving errors from other sources. On daily time scales IR-sampled UTH contains large data gaps in convectively active areas, with only about 20-30 % of the tropics (30 S­ 30 N) being sampled. This results in a dry bias of about -9 %RH in the area-weighted tropical daily UTH time series. On monthly scales, maximum clear-sky bias (CSB) is up to -30 %RH over convectively active areas. The magnitude of CSB shows significant correlations with UTH itself (-0.5) and also with the variability in UTH (-0.6). We also show that IR-sampled UTH time series have higher interannual variability and smaller trends compared to microwave sampling. We argue that a significant part of the smaller trend results from the contrasting influence of diurnal drift in the satellite measurements on the wet and dry regions of the tropics.

The precipitation climate of Central Asia: intercomparison of observational and numerical data sources in a remote semiarid region

In this study, we systematically compare a wide range of observational and numerical precipitation datasets for Central Asia. Data considered include two re-analyses, three datasets based on direct observations, and the output of a regional climate model simulation driven by a global re-analysis. These are validated and intercompared with respect to their ability to represent the Central Asian precipitation climate. In each of the datasets, we consider the mean spatial distribution and the seasonal cycle of precipitation, the amplitude of interannual variability, the representation of individual yearly anomalies, the precipitation sensitivity (i.e. the response to wet and dry conditions), and the temporal homogeneity of precipitation. Additionally, we carried out part of these analyses for datasets available in real time. The mutual agreement between the observations is used as an indication of how far these data can be used for validating precipitation data from other sources. In particular, we show that the observations usually agree qualitatively on anomalies in individual years while it is not always possible to use them for the quantitative validation of the amplitude of interannual variability. The regional climate model is capable of improving the spatial distribution of precipitation. At the same time, it strongly underestimates summer precipitation and its variability, while interannual variations are well represented during the other seasons, in particular in the Central Asian mountains during winter and spring

Hydrological cycle in the Danube basin in present-day and XXII century simulations by IPCCAR4 global climate models

We present an intercomparison and verification analysis of 20 GCMs (Global Circulation Models) included in the 4th IPCC assessment report regarding their representation of the hydrological cycle on the Danube river basin for 1961–2000 and for the 2161–2200 SRESA1B scenario runs. The basin-scale properties of the hydrological cycle are computed by spatially integrating the precipitation, evaporation, and runoff fields using the Voronoi-Thiessen tessellation formalism. The span of the model- simulated mean annual water balances is of the same order of magnitude of the observed Danube discharge of the Delta; the true value is within the range simulated by the models. Some land components seem to have deficiencies since there are cases of violation of water conservation when annual means are considered. The overall performance and the degree of agreement of the GCMs are comparable to those of the RCMs (Regional Climate Models) analyzed in a previous work, in spite of the much higher resolution and common nesting of the RCMs. The reanalyses are shown to feature several inconsistencies and cannot be used as a verification benchmark for the hydrological cycle in the Danubian region. In the scenario runs, for basically all models the water balance decreases, whereas its interannual variability increases. Changes in the strength of the hydrological cycle are not consistent among models: it is confirmed that capturing the impact of climate change on the hydrological cycle is not an easy task over land areas. Moreover, in several cases we find that qualitatively different behaviors emerge among the models: the ensemble mean does not represent any sort of average model, and often it falls between the models’ clusters.

Co-variation of temperature and precipitation in CMIP5 models and satellite observations

Current variability of precipitation (P) and its response to surface temperature (T) are analysed using coupled(CMIP5) and atmosphere-only (AMIP5) climate model simulations and compared with observational estimates. There is striking agreement between Global Precipitation Climatology Project (GPCP) observed and AMIP5 simulated P anomalies over land both globally and in the tropics suggesting that prescribed sea surface temperature and realistic radiative forcings are sufficient for simulating the interannual variability in continental P. Differences between the observed and simulated P variability over the ocean, originate primarily from the wet tropical regions, in particular the western Pacific, but are reduced slightly after 1995. All datasets show positive responses of P to T globally of around 2 %/K for simulations and 3-4 %/K in GPCP observations but model responses over the tropical oceans are around 3 times smaller than GPCP over the period 1988-2005. The observed anticorrelation between land and ocean P, linked with El Niño Southern Oscillation, is captured by the simulations. All data sets over the tropical ocean show a tendency for wet regions to become wetter and dry regions drier with warming. Over the wet region (75% precipitation percentile), the precipitation response is ~13-15%/K for GPCP and ~5%/K for models while trends in P are 2.4%/decade for GPCP, 0.6% /decade for CMIP5 and 0.9%/decade for AMIP5 suggesting that models are underestimating the precipitation responses or a deficiency exists in the satellite datasets.