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Summer 2010 saw two simultaneous extremes linked by an atmospheric wave train: a record-breaking heatwave in Russia and severe floods in Pakistan. Here, we study this wave event using a large ensemble climate model experiment. First, we show that the circulation in 2010 reflected a recurrent wave train connecting the heatwave and flooding events. Second, we show that the occurrence of the wave train is favored by three drivers: (1) 2010 sea surface temperature anomalies increase the probability of this wave train by a factor 2-to-4 relative to the model's climatology, (2) early-summer soil moisture deficit in Russia not only increases the probability of local heatwaves, but also enhances rainfall extremes over Pakistan by forcing an atmospheric wave response, and (3) high-latitude land warming favors wave-train occurrence and therefore rainfall and heat extremes. These findings highlight the complexity and synergistic interactions between different drivers, reconciling some seemingly contradictory results from previous studies. [ABSTRACT FROM AUTHOR]

The hydrological response to climate change in mountainous basins manifests itself at varying spatial and temporal scales, ranging from catchment to large river basin scale and from sub‐daily to decade and century scale. To robustly assess the 21st century climate change impact for hydrology in entire High Mountain Asia (HMA) at a wide range of scales, we use a high resolution cryospheric‐hydrological model covering 15 upstream HMA basins to quantify the compound effects of future changes in precipitation and temperature based on the range of climate change projections in the Coupled Model Intercomparison Project Phase 6 climate model ensemble. Our analysis reveals contrasting responses for HMA's rivers, dictated by their hydrological regimes. At the seasonal scale, the earlier onset of melting causes a shift in the magnitude and peak of water availability, to earlier in the year. At the decade to century scale, after an initial increase, the glacier melt declines by the mid or end of the century except for the Tarim river basin, where it continues to increase. Despite a large variability in hydrological regimes across HMA's rivers, our results indicate relatively consistent climate change responses across HMA in terms of total water availability at decadal time scales. Although total water availability increases for the headwaters, changes in seasonality and magnitude may diverge widely between basins and need to be addressed while adapting to future changes in a region where food security, energy security as well as biodiversity, and the livelihoods of many depend on water from HMA. Plain Language Summary: The mountains of Asia have large reservoirs of snow and ice, which are the source of water to the people living in the mountains and downstream, mainly during the dry season. However, due to recent warming, these reserves are melting faster and depleting year by year. We use a computer model to understand what will happen to these volumes of snow and ice and the total volume of water, which also includes rain and groundwater, in the 15 main rivers under future climate change scenarios. We find that the water generated upstream will increase for all the rivers in the future. However, there would be either too little or too much water for different seasons in the future. The peak volume of water will increase in magnitude and the peak time will shift to earlier in the season (in the month of May instead of current June or July) for most rivers in the western part of Asia. This change in the timing of water will have severe impacts on the livelihoods of mountain communities as well as populations downstream where food production, energy production as well as biodiversity depend on the amount and timing of mountain water supply. Key Points: Contrasting seasonal responses are observed for High Mountain Asia's (HMA) rivers, dictated by their hydrological regimesThe onset of early snow and glacier melt in the spring season affects the magnitude and peak water availabilityA relatively consistent decadal climate change responses across HMA, despite a large variability in hydrological regimes [ABSTRACT FROM AUTHOR]

Skillful forecasts of the Indian summer monsoon rainfall (ISMR) at long lead times (4–5 months in advance) pose great challenges due to strong internal variability of the monsoon system and nonstationarity of climatic drivers. Here, we use an advanced causal discovery algorithm coupled with a response-guided detection step to detect low-frequency, remote processes that provide sources of predictability for the ISMR. The algorithm identifies causal precursors without any a priori assumptions, apart from the selected variables and lead times. Using these causal precursors, a statistical hindcast model is formulated to predict seasonal ISMR that yields valuable skill with correlation coefficient (CC) ~0.8 at a 4-month lead time. The causal precursors identified are generally in agreement with statistical predictors conventionally used by the India Meteorological Department (IMD); however, our methodology provides precursors that are automatically updated, providing emerging new patterns. Analyzing ENSO-positive and ENSO-negative years separately helps to identify the different mechanisms at play during different years and may help to understand the strong nonstationarity of ISMR precursors over time. We construct operational forecasts for both shorter (2-month) and longer (4-month) lead times and show significant skill over the 1981–2004 period (CC ~0.4) for both lead times, comparable with that of IMD predictions (CC ~0.3). Our method is objective and automatized and can be trained for specific regions and time scales that are of interest to stakeholders, providing the potential to improve seasonal ISMR forecasts. [ABSTRACT FROM AUTHOR]

Disaster risk reduction efforts traditionally focus on long-term preventative measures or post-disaster response. Outside of these, there are many short-term actions, such as evacuation, that can be implemented in the period of time between a warning and a potential disaster to reduce the risk of impacts. However, this precious window of opportunity is regularly overlooked in the case of climate and weather forecasts, which can indicate heightened risk of disaster but are rarely used to initiate preventative action. Barriers range from the protracted debate over the best strategy for intervention to the inherent uncomfortableness on the part of donors to invest in a situation that will likely arise but is not certain. In general, it is unclear what levels of forecast probability and magnitude are "worth" reacting to. Here, we propose a novel forecast-based financing system to automatically trigger action based on climate forecasts or observations. The system matches threshold forecast probabilities with appropriate actions, disburses required funding when threshold forecasts are issued, and develops standard operating procedures that contain the mandate to act when these threshold forecasts are issued. We detail the methods that can be used to establish such a system, and provide illustrations from several pilot cases. Ultimately, such a system can be scaled up in disaster-prone areas worldwide to improve effectiveness at reducing the risk of disaster. [ABSTRACT FROM AUTHOR]

The feedback between soil moisture and precipitation has long been a topic of interest due to its potential for improving weather and seasonal forecasts. The generally proposed mechanism assumes a control of soil moisture on precipitation via the partitioning of the surface turbulent heat fluxes, as assessed via the evaporative fraction (EF), i.e., the ratio of latent heat to the sum of latent and sensible heat, in particular under convective conditions. Our study investigates the poorly understood link between EF and precipitation by relating the before-noon EF to the frequency of afternoon precipitation over the contiguous US, through statistical analyses of multiple EF and precipitation data sets. We analyze remote-sensing data products (Global Land Evaporation: the Amsterdam Methodology (GLEAM) for EF, and radar precipitation from the NEXt generation weather RADar system (NEXRAD)), FLUXNET station data, and the North American Regional Reanalysis (NARR). Data sets agree on a region of positive relationship between EF and precipitation occurrence in the southwestern US. However, a region of strong positive relationship over the eastern US in NARR cannot be confirmed with observation-derived estimates (GLEAM, NEXRAD and FLUXNET). The GLEAM– NEXRAD data set combination indicates a region of positive EF–precipitation relationship in the central US. These disagreements emphasize large uncertainties in the EF data. Further analyses highlight that much of these EF–precipitation relationships could be explained by precipitation persistence alone, and it is unclear whether EF has an additional role in triggering afternoon precipitation. This also highlights the difficulties in isolating a land impact on precipitation. Regional analyses point to contrasting mechanisms over different regions. Over the eastern US, our analyses suggest that the EF–precipitation relationship in NARR is either atmospherically controlled (from precipitation persistence and potential evaporation) or driven by vegetation interception rather than soil moisture. Although this aligns well with the high forest cover and the wet regime of that region, the role of interception evaporation is likely overestimated because of low nighttime evaporation in NARR. Over the central and southwestern US, the EF–precipitation relationship is additionally linked to soil moisture variations, owing to the soil-moisture-limited climate regime. [ABSTRACT FROM AUTHOR]

Current techniques to disentangle the evaporative fluxes from the continental surface into a contribution evaporated from soils and canopy, or transpired by plants, are under debate. Many isotope-based studies show that transpiration contributes generally more than 70 % to the total evaporation, while other isotope-independent techniques lead to considerably smaller transpiration fractions. This paper provides a perspective on isotope-based versus non-isotope-based partitioning studies. Some partitioning results from isotope-based methods, hydrometric measurements, and modeling are presented for comparison. Moreover, the methodological aspects of the partitioning analysis are considered, including their limitations, and explanations of possible discrepancies between the methods are discussed. We suggest sources of systematic error that may lead to biases in the results, e.g., instruments inaccuracy, assumptions used in analyses, and calibration parameters. A number of comparison studies using isotope-based methods and hydrometric measurements in the same plants and climatic conditions are consistent within the errors; however, models tend to produce lower transpiration fractions. The relatively low transpiration fraction in current state-of-the-art land-surface models calls for a reassessment of the skill of the underlying model parameterizations. The scarcity of global evaporation data makes calibration and validation of global isotope-independent and isotope-based results difficult. However, isotope-enabled land-surface and global climate modeling studies allow for the evaluation of the parameterization of land-surface models by comparing the computed water isotopologue signals in the atmosphere with the available remote sensing and flux-based data sets. Future studies that allow for this evaluation could provide a better understanding of the hydrological cycle in vegetated regions. [ABSTRACT FROM AUTHOR]

Multiple states of woody cover under similar climate conditions are found in both conceptual models and observations. Due to the limitation of the observed woody cover data set, it is unclear whether the observed bimodality is caused by the presence of multiple stable states or is due to dynamic growth processes of vegetation. In this study, we combine a woody cover data set with an above ground biomass data set to investigate the simultaneous occurrences of savanna and forest states under different precipitation forcing. To interpret the results we use a recently developed vegetation dynamics model (the Balanced Optimality Structure Vegetation Model), in which the effect of fires is included. Our results show that bimodality also exists in above ground biomass and retrieved vegetation structure. In addition, the observed savanna distribution can be understood as derived from a stable state and a slightly drifting (transient) state, the latter having the potential to shift to the forest state. Finally, the results indicate that vegetation structure (horizontal vs. vertical leaf extent) is a crucial component for the existence of bimodality. [ABSTRACT FROM AUTHOR]

The feedback between soil moisture and precipitation has long been a topic of interest due to its potential for improving weather and seasonal forecasts. The generally proposed mechanism assumes a control of soil moisture on precipitation via the partitioning of the surface turbulent heat fluxes, as assessed via the Evaporative Fraction, EF, i.e. the ratio of latent heat to the sum of latent and sensible heat, in particular under convective conditions. Our study investigates the poorly understood link between EF and precipitation by investigating the impact of before-noon EF on the frequency of afternoon precipitation over the contiguous US, using a statistical analysis of the relationship between multiple datasets of EF and precipitation. We analyze remote sensing data products (EF from GLEAM, Global Land Evaporation: the Amsterdam Methodology, based on satellite observations; and radar precipitation from NEXRAD, the NEXt generation weather RADar system), FLUXNET station data, and the North American Regional Reanalysis (NARR). While most datasets agree on the existence of regions of positive relationship between between EF and precipitation in the Eastern and Southwestern US, observation-based estimates (GLEAM, NEXRAD and to some extent FLUXNET) also indicate a strong relationship in the Central US which is not found in NARR. Investigating these differences, we find that much of these relationships can be explained by precipitation persistence alone, with ambiguous results on the additional role of EF in causing afternoon precipitation. Regional analyses reveal contrasting mechanisms over different regions. Over the Eastern US, our analyses suggest that the apparent EF-precipitation coupling takes place on a short day-to-day time scale and is either atmospherically controlled (from precipitation persistence and potential evaporation) or driven by vegetation interception and subsequent re-evaporation (rather than soil moisture and related plant transpiration/bare soil evaporation), in line with the high forest cover and the wet regime of that region. Over the Central and Southwestern US, the impact of EF on convection triggering is additionally linked to soil moisture variations, owing to the soil moisture--limited climate regime. [ABSTRACT FROM AUTHOR]

ABSTRACT The main windiness index in the Netherlands (Windex-CBS) has been subject to a decreasing trend since the systematic recording started in 1988. This seriously complicates the estimation of future long-term wind supply. Therefore, it is necessary to know the main causes of the reported decline. For this purpose, Windex-CBS, derived from actual wind turbine yields, is compared with two alternative windiness indices. The first index is based on wind speed observations Wland and the second on geostrophic wind speed Gland. Similar indices are formulated for offshore wind supply in the North Sea, Woff and Goff. High mutual correlations between the indices indicate that they do efficiently account for natural variability. Yet, the trends of the different indices do substantially differ from each other. The decrease of Windex-CBS is twice as large as (200%) the decrease of Wland. The trend of the difference between both indices is highly significant. This suggests that the Windex-CBS is contaminated by operational or methodological factors. Wland does not suffer from such factors and is therefore the preferred measure of wind supply. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

A myriad of interactions exist between vegetation and local climate for arid and semiarid regions. Vegetation function, structure and individual behavior have large impacts on carbon-water-energy balances, which consequently influence local climate variability that, in turn, feeds back to the vegetation. In this study, a conceptual vegetation structure scheme is formulated and tested in a new carbon-water-energy coupled model to explore the importance of vegetation structure and vegetation adaptation to water stress on equilibrium biomass states. Surface energy, water and carbon fluxes are simulated for a range of vegetation structures across a precipitation gradient in West Africa and optimal vegetation structures that maximizes biomass for each precipitation regime are determined. Two different strategies of vegetation adaptation to water stress are included. Under dry conditions vegetation tries to maximize the Water Use Efficiency and Leaf Area Index as it tries to maximize carbon gain. However, an important negative feedback mechanism is found as the vegetation also tries to mini15 mize its cover to optimize the surrounding bare ground area from which water can be extracted, thereby forming patches of vertical vegetation. Under larger precipitation, a positive feedback mechanism is found in which vegetation tries to maximize its cover as it then can reduce water loss from bare soil while having maximum carbon gain due to a large Leaf Area Index. The competition between vegetation and bare soil determines a transition between a "survival" state to a "growing" state. [ABSTRACT FROM AUTHOR]

Probability estimates of the future change of extreme precipitation events are usually based on a limited number of available global climate model (GCM) or regional climate model (RCM) simulations. Since floods are related to heavy precipitation events, this restricts the assessment of flood risks. In this study a relatively simple method has been developed to get a better description of the range of changes in extreme precipitation events. Five bias-corrected RCM simulations of the 1961-2100 climate for a single greenhouse gas emission scenario (A1B SRES) were available for the Rhine basin. To increase the size of this five-member RCM ensemble, 13 additional GCM simulations were analysed. The climate responses of the GCMs are used to modify an observed (1961-1995) precipitation time series with an advanced delta change approach. Changes in the temporal means and variability are taken into account. It is found that the range of future change of extreme precipitation across the five-member RCM ensemble is similar to results from the 13-member GCM ensemble. For the RCM ensemble, the time series modification procedure also results in a similar climate response compared to the signal deduced from the direct model simulations. The changes from the individual RCM simulations, however, systematically differ from those of the driving GCMs, especially for long return periods. [ABSTRACT FROM AUTHOR]

The article presents a study on the effect of land use induced land cover change (LULCC) on temperature and rainfall extremes. It states that four climate models within the land use and climate, identification of robust impacts (LUCID) project protocol were used. It concludes that there is a similarity between the changes in temperature extremes and mean temperature caused by LULCC.

The article focuses on potential feedback mechanism regarding land use and climate change. It states that potential regional feedbacks were explored in four hot-spots including the Amazon Basin, sub-Saharan Africa (SSA), and Europe. It mentions that in Amazon, drought events can lead to further reduction of rainfall when the recycling processes of water are affected.

This paper presents an extended version of a widely used precipitation data set and evaluates it along with a recently released precipitation data set, using streamflow simulations. First, the existing precipitation data set issued by the Commission for the Hydrology of the Rhine basin (CHR), originally covering the period 1961-1995, was extended until 2008 using a number of additional precipitation data sets. Next, the extended version of the CHR, together with E-OBS Version 4 (ECA&D gridded data set) were evaluated for their performance in the Rhine basin for extreme events. Finally, the two aforementioned precipitation data sets and a meteorological reanalysis data set were used to force a hydrological model, evaluating the influence of different precipitation forcings on the annual mean and extreme discharges compared to observational discharges for the period from 1990 until 2008. The extended version of CHR showed good agreement in terms of mean annual cycle, extreme discharge (both high and low flows), and spatial distribution of correlations with observed discharge. E-OBS performed well with respect to extreme discharge. However, its performance of the mean annual cycle in winter was rather poor and remarkably well in the summer. Also, CHR08 outperformed E-OBS in terms of temporal correlations in most of the analyzed sub-catchment means. The length extension for the CHR and the even longer length of E-OBS permit the assessment of extreme discharge and precipitation values with lower uncertainty for longer return periods. This assessment classifies both of the presented precipitation data sets as possible reference data sets for future studies in hydrological applications. [ABSTRACT FROM AUTHOR]

This paper evaluates a number of recently constructed or extended precipitation data sets used for hydrological applications and climate change studies in the Rhine basin. Firstly, the existing precipitation data set issued by the Commission for the Hydrology of the Rhine basin (CHR), originally covering the period 1961-1995, was extended until 2008 using a number of additional precipitation data sets. The length extension permits the assessment of extreme discharge and precipitation values with lower uncertainty than the original version. Secondly, the E-OBS Version 4 (ECA&D gridded data set) was evaluated for its performance in the Rhine basin for extreme events. The two extended precipitation data sets and a meteorological reanalysis data set were used to force a hydrological model, evaluating the influence of different precipitation forcings on the annual mean and extreme discharges compared to observational discharges for the period from 1990 until 2008. The extended version of CHR showed good agreement in terms of mean annual cycle, extreme discharge (both high and low flows), and spatial distribution of correlations with observed discharge. E-OBS performed well with respect to extreme discharge, but its performance of the mean annual cycle was rather poor in winter and remarkably well in the summer. [ABSTRACT FROM AUTHOR]

The skill of the land surface model HTESSEL is assessed to reproduce evaporation in response to land surface characteristics and atmospheric forcing, both being spatially variable. Evaporation estimates for the 2005 growing season are inferred from satellite observations of the Western part of Hungary and compared to model outcomes. Atmospheric forcings are obtained from a hindcast run with the Regional Climate Model RACMO2. Although HTESSEL slightly underpredicts the seasonal evaporative fraction as compared to satellite estimates, the mean, 10th and 90th percentile of this variable are of the same magnitude as the satellite observations. The initial water as stored in the soil and snow layer does not have a significant effect on the statistical properties of the evaporative fraction. However, the spatial distribution of the initial soil and snow water significantly affects the spatial distribution of the calculated evaporative fraction and the models ability to reproduce evaporation correctly in low precipitation areas in the considered region. HTESSEL performs weaker in dryer areas. In Western Hungary these areas are situated in the Danube valley, which is partly covered by irrigated cropland and which also may be affected by shallow groundwater. Incorporating (lateral) groundwater flow and irrigation, processes that are not included now, may improve HTESSELs ability to predict evaporation correctly. Evaluation of the model skills using other test areas and larger evaluation periods is needed to confirm the results. Based on earlier sensitivity analysis, the effect of a number of modifications to HTESSEL has been assessed. A more physically based reduction function for dry soils has been introduced, the soil depth is made variable and the effect of swallow groundwater included. However, the combined modification does not lead to a significantly improved performance of HTESSEL. [ABSTRACT FROM AUTHOR]

The ECMWF land surface hydrology has been revised in the last 3 years in its soil and snow hydrological components, leading to improvements in weather and seasonal predictions. It has been shown that efforts devoted to the improvement of land surface processes can lead to a more accurate representation of the global water cycle on monthly timescales. In this paper, we analyse the impact of land hydrology revisions at daily timescales on both atmospheric near-surface quantities and river discharges by coupling the ECMWF land surface model (HTESSEL) to a river routing scheme total runoff integration pathways (TRIP2). This application defines a hydro-meteorological verification for land surface models and it shows the usefulness of river discharge observations for quantitative evaluation of the global water cycle at daily timescales. The relative contributions of the soil and snow hydrology revisions on atmospheric state, in particular for temperature, and the predicted river discharge are evaluated showing a significant incremental performance with the land surface updates. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper describes the evaluation of the KNMI Cloud Physical Properties -- Precipitation Properties (CPP-PP) algorithm over West Africa. The algorithm combines condensed water path (CWP), cloud phase (CPH), cloud particle effective radius (re), and cloud-top temperature (CTT) retrievals from visible, near-infrared and thermal infrared observations of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the Meteosat Second Generation (MSG) satellites to estimate rain occurrence frequency and rain rate. For the 2005 and 2006 monsoon seasons, it is investigated whether the CPP-PP algorithm is capable of retrieving rain occurrence frequency and rain rate over West Africa with sufficient accuracy, using Tropical Monsoon Measurement Mission Precipitation Radar (TRMM-PR) as reference. As a second goal, it is assessed whether SEVIRI is capable of monitoring the seasonal and daytime evolution of rainfall during the West African monsoon (WAM), using Climate Prediction Center Morphing Technique (CMORPH) rainfall observations. The SEVIRI-detected rainfall area agrees well with TRMM-PR, with the areal extent of rainfall by SEVIRI being ∼10% larger than from TRMM-PR. The mean retrieved rain rate from CPP-PP is about 8% higher than from TRMM-PR. Examination of the TRMM-PR and CPP-PP cumulative frequency distributions revealed that differences between CPP-PP and TRMM-PR are generally within +/-10%. Relative to the AMMA rain gauge observations, CPP-PP shows very good agreement up to 5 mm h-1. However, at higher rain rates (5-16 mm h-1) CPP-PP overestimates compared to the rain gauges. With respect to the second goal of this paper, it was shown that both the accumulated precipitation and the seasonal progression of rainfall throughout the WAM is in good agreement with CMORPH, although CPP-PP retrieves higher amounts in the coastal region of West Africa. Using latitudinal Hovmüller diagrams, a fair correspondence between CPP-PP and CMORPH was found, which is reflected by high correlation coefficients (∼0.7) for both rain rate and rain occurrence frequency. The daytime cycle of rainfall from CPP-PP shows distinctly different patterns for three different regions in West Africa throughout the WAM, with a decrease in dynamical range of rainfall near the Inter Tropical Convergence Zone (ITCZ). The dynamical range as retrieved from CPP-PP is larger than that from CMORPH. It is suggested that this results from both the better spatio-temporal resolution of SEVIRI, as well as from thermal infrared radiances being partly used by CMORPH, which likely smoothes the daytime precipitation signal, especially in case of cold anvils from convective systems. The promising results show that the CPP-PP algorithm, taking advantage of the high spatio-temporal resolution of SEVIRI, is of added value for monitoring daytime precipitation patterns in tropical areas. [ABSTRACT FROM AUTHOR]