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Tropical cyclones (TCs) can cause severe wind and rain hazards. Unusual TC tracks and their extreme precipitation forecasts have become two difficult problems faced by conventional models of primitive equations. The case study in this paper finds that the numerical computation of the climatological component in conventional models restricts the prediction of unusual TC tracks. The climatological component should be a forcing quantity, not a predictor in the numerical integration of all models. Anomaly-based variable models can overcome the bottleneck of forecast time length or the one-week forecasting barrier, which is limited to less than one week for conventional models. The challenge in extreme precipitation forecasting is how to physically get the vertical velocity. The anomalous moisture stress modulus (AMSM), as an indicator of heavy rainfall presented in this paper, considers the two conditions associated with vertical velocity and anomalous specific humidity in the lower troposphere. Vertical velocity is produced by the orthogonal collision of horizontal anomalous airflows. [ABSTRACT FROM AUTHOR]

In the current work we present six hindcast Weather Research and Forecasting (WRF) simulations for the EURO-CORDEX domain with different configurations in microphysics, convection and radiation for the time period 1990-2008. All regional model simulations are forced by the ERA-Interim reanalysis and have the same spatial resolution (0.44°). These simulations are evaluated for surface temperature, precipitation, short- and longwave downward radiation at the surface and total cloud cover. The analysis of the WRF ensemble indicates systematic biases in both temperature and precipitation linked to different physical mechanisms for the summer and winter season. Overestimation of total cloud cover and underestimation of downward shortwave radiation at the surface, mostly when using Grell-Devenyi convection and the CAM radiation scheme, intensifies the negative summer temperature bias in northern Europe (max -2.5 °C). Conversely, a strong positive downward shortwave summer bias in central (40-60 %) and southern Europe mitigates the systematic cold bias in WRF over these regions, signifying a typical case of error compensation. Maximum winter cold bias is over north-eastern Europe (-2.8 °C); this location is indicative of land-atmosphere rather than cloud-radiation interactions. Precipitation is systematically overestimated in summer by all model configurations, especially the higher quantiles, which are associated with summertime deep cumulus convection. The Kain-Fritsch convection scheme produces the larger summertime precipitation biases over the Mediterranean. Winter precipitation is reproduced with lower biases by all model configurations (15-30 %). The results of this study indicate the importance of evaluating not only the basic climatic parameters of interest for climate change applications (temperature-precipitation), but also other components of the energy and water cycle, in order to identify the sources of systematic biases, possible compensatory or masking mechanisms and suggest methodologies for model improvement. [ABSTRACT FROM AUTHOR]

Accurate representations of mean climate conditions, especially in areas of complex terrain, are an important part of environmental monitoring systems. As high-resolution satellite monitoring information accumulates with the passage of time, it can be increasingly useful in efforts to better characterize the earth's mean climatology. Current state-of-the-science products rely on complex and sometimes unreliable relationships between elevation and station-based precipitation records, which can result in poor performance in food and water insecure regions with sparse observation networks. These vulnerable areas (like Ethiopia, Afghanistan, or Haiti) are often the critical regions for humanitarian drought monitoring. Here, we show that long period of record geo-synchronous and polar-orbiting satellite observations provide a unique new resource for producing high resolution (0.05°) global precipitation climatologies that perform reasonably well in data sparse regions. Traditionally, global climatologies have been produced by combining station observations and physiographic predictors like latitude, longitude, elevation, and slope. While such approaches can work well, especially in areas with reasonably dense observation networks, the fundamental relationship between physiographic variables and the target climate variables can often be indirect and spatially complex. Infrared and microwave satellite observations, on the other hand, directly monitor the earth's energy emissions. These emissions often correspond physically with the location and intensity of precipitation. We show that these relationships provide a good basis for building global climatologies. We also introduce a new geospatial modeling approach based on moving window regressions and inverse distance weighting interpolation. This approach combines satellite fields, gridded physiographic indicators, and in situ climate normals. The resulting global 0.05° monthly precipitation climatology, the Climate Hazards Group's Precipitation Climatology version 1 (CHPclim v.1.0, http://dx.doi.org/10.15780/G2159X), is shown to compare favorably with similar global climatology products, especially in areas with complex terrain and low station densities. [ABSTRACT FROM AUTHOR]

The article presents a study which provides reference publication on the description of the land-surface precipitation data products of the Global Precipitation Climatology Centre (GPCC) with applications such as centennial trend analysis. The study employs interpolation of gauge data, gridding method, and Kriging interpolation. It says that sample applications provide potential users of GPCC data products information regarding the constraints and capabilities of the gridded data sets.

We present a methodology to correct precipitation fluxes from the ECMWF atmospheric reanalysis (ERA-Interim) for oceanographic applications. The correction is performed by means of a spatially varying monthly climatological coefficient, computed within the period 1989-2008 by comparison between ERA-Interim and a satellite-based passive microwave precipitation product. ERA-Interim exhibits a systematic over-estimation of precipitation within the inter-tropical convergence zones (up to 3mmd-1) and underestimation at mid- and high- latitudes (up to -4mmd-1). The correction has been validated within eddy-permitting resolution global ocean hindcasts (1989-2009), demon strating the ability of our strategy in attenuating the 20-yr mean global EMP negative imbalance by 16 %, reducing the near-surface salinity fresh bias in the Tropics up to 1 psu and improving the representation of the sea level interannual variability, with an SSH error decrease of 8%. The ocean circulation is also proved to benefit from the correction, especially in correspondence of the Antarctic Circumpolar Current, where the error in the near-surface current speed decreases by a 9%. Finally, we show that the correction leads to volume and freshwater transports that better agree with independent estimates. [ABSTRACT FROM AUTHOR]

Gridded precipitation (PRP) data have been largely used in diagnostic studies on the climate variability in several time scales, as well as to validate model results. The three most used gauge-based PRP datasets are from the Global Precipitation Climatology Centre (GPCC), University of Delaware (UDEL), and Climate Research Unit (CRU). This paper evaluates the performance of these datasets in reproducing spatiotemporal PRP climatological features over the entire South America (SA) for the 1901–2015 period, aiming to identify the differences and similarities among the datasets as well as time intervals and areas with potential uncertainties involved with these datasets. Comparisons of the PRP annual means and variances between the 1901–2015 period and the non-overlapping 30-year subperiods of 1901–1930, 1931–1960, 1961–1990, and the 25-year subperiod of 1991–2015 for each dataset show varying means of the annual PRP over SA depending on the subperiod and dataset. Consistent patterns among datasets are found in most of southeastern SA and southeastern Brazil, where they evolved gradually from less to more rainy conditions from 1901–1930 to the 1991–2015 subperiod. All three datasets present limitations and uncertainties in regions with poor coverage of gauge stations, where the differences among datasets are more pronounced. In particular, the GPCC presents reduced PRP variability in an extensive area west of 50° W and north of 20° S during the 1901–1930 subperiod. In monthly time scale, PRP time series in two areas show differences among the datasets for periods before 1941, which are likely due to spurious or missing data: central Bolivia (CBO), and central Brazil (CBR). The GPCC has less monthly variability before 1940 than the other two datasets in these two areas, and UDEL presents reduced monthly variability before 1940 and spurious monthly values from May to September of the years from 1929 to 1941 in CBO. Thus, studies with these three datasets might lead to different results depending on the study domain and period of analysis, in particular for those including years before 1941. The results here might be relevant for future diagnostic and modelling studies on climate variability from interannual to multidecadal time scales. [ABSTRACT FROM AUTHOR]

We introduce and document the first version of the Centre National de Recherches Météorologiques Earth system model (CNRM-ESM1). This model is based on the physical core of the CNRM-CM5 model and employs the Interactions between Soil, Biosphere and Atmosphere (ISBA) module and the Pelagic Interaction Scheme for Carbon and Ecosystem Studies (PISCES) as terrestrial and oceanic components of the global carbon cycle. We describe a preindustrial and 20th century climate simulation following the CMIP5 protocol. We detail how the various carbon reservoirs were initialized and analyze the behavior of the carbon cycle and its prominent physical drivers. CNRM-ESM1 reproduces satisfactorily several aspects of the modern carbon cycle. On land, the model reasonably captures the carbon cycling through vegetation and soil, resulting in a net terrestrial carbon sink of 2.2 PgCy-1. In the ocean, the large-scale distribution of hydrodynamical and biogeochemical tracers agrees well with a modern climatology from the World Ocean Atlas. The combination of biological and physical processes induces a net CO2 uptake of 1.7 PgCy-1 that falls within the range of recent estimates. Our analysis shows that the atmospheric climate of CNRM-ESM1 compares well with that of CNRM-CM5. Biases in precipitation and shortwave radiation over the Tropics generate errors in gross primary productivity and ecosystem respiration. Compared to CNRM-CM5, the revised ocean-sea ice coupling has modified the sea-ice cover and ocean ventilation, unrealistically strengthening the flow of North Atlantic deep water (26.1±2 Sv). It results in an accumulation of anthropogenic carbon in the deep ocean. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) plays a key role in the water cycle of High Asia and its downstream regions. The respective influence of the Indian and East Asian summer monsoon on TP precipitation and the regional water resources, together with the detection of moisture transport pathways and source regions are subject of recent research. In this study we present a twelve-year high-resolution climatology of the atmospheric water transport (AWT) on and towards the TP, using a new dataset, the High Asia Reanalysis (HAR), which better represents the complex topography of the TP and surrounding high mountain ranges than coarse resolution datasets. We focus on spatio temporal patterns, vertical distribution and transport through the TP boundaries. The results show that the mid-latitude westerlies have a higher share in summertime AWT on the TP than assumed so far. Water vapour (WV) transport constitute the main part, whereby transports of water as cloud particles (CP) play also a role in winter in the Karakoram and western Himalayan regions. High mountain valleys in the Himalayas facilitate AWT from the south whereas the high mountain regions inhibit the AWT to a large extend and limit the influence of the Indian summer monsoon. No transport from the East Asian monsoon to the TP could be detected. Our results show that 40% of the atmospheric moisture needed for precipitation comes from outside the TP, while the remaining 60% are provided by local moisture recycling. How far precipitation variability can be explained by variable moisture supply has to be studied in future research by analysing the atmospheric dynamic and moisture recycling more in detail. [ABSTRACT FROM AUTHOR]

The article presents a study that demonstrates the usefulness of the Norwegian Climate Center's Earth System Model (NorESM1-M) in the coupled model intercomparison project phase 5 (CMIP5). It outlines the role of the model in providing complementary results to the evaluation of possible man made climate change. It also demonstrates the effectiveness of the model in accurately depicting the changes in the atmospheric water cycle in precipitation events.

The combination of precipitation formation and fallout affects atmospheric flows through the release of latent heat and through the removal of mass from the atmosphere, but because the mass of water vapor is only a small fraction of the total mass of Earth's atmosphere, precipitation mass sinks are often neglected in theory and models. However, a small number of modeling studies suggest that water mass sources and sinks can intensify heavily precipitating weather systems. These studies point to a need to more systematically verify the impact of neglecting precipitation mass sinks, particularly for warmer and moister climates in which precipitation rates can be much higher. In this paper, we add precipitation mass sources and sinks to an idealized general circulation model and examine their effects on steady-state midlatitude storm track statistics. The model has several idealizations, including that all condensates immediately fall out of the atmosphere, and is run across a wide range of climates, including very warm climates. We find that modifying the model to include mass sources and sinks has no detectable effect on midlatitude variability or extremes, even in climates much warmer and moister than the modern. However, we find that a 10-fold exaggeration of mass sources and sinks is sufficient to produce more intense midlatitude weather extremes and increase surface pressure variance. This result is consistent with theoretical potential vorticity analysis, which suggests that the dynamical effects of mass sources and sinks are much smaller than the dynamical effects of accompanying latent heating unless mass sinks are artificially amplified by at least a factor of 10. Finally, we use simulations of "tropical cyclone worlds" to attempt to reconcile our results with earlier work showing stronger deepening in a simulation of a tropical cyclone case study when precipitation mass sinks were included. We demonstrate that abruptly "turning on" mass sources and sinks can lead to stronger transient deepening in some individual storms (consistent with results of past work) but weaker transient deepening in other storms, without modifying the steady-state statistics of storms in equilibrium with the large-scale environment (consistent with our other results). Our results provide a firmer foundation for using general circulation models that neglect moist mass sources and sinks in climate simulations, even in climates much warmer than today, while leaving open the possibility that their inclusion might lead to short-term improvements in forecast skill. [ABSTRACT FROM AUTHOR]

The seasonal variability of surface layer salinity (SLS), evaporation (E), precipitation (P ) and E -P over the global ocean is examined using in situ salinity data and the National Center for Environmental Prediction's Climate System Forecast Reanalysis. Sea- 5 sonal amplitudes and phases are calculated using harmonic analysis and presented in all areas of the open ocean between 60° S and 60° N. Areas with large amplitude SLS seasonal variations include: the intertropical convergence zone in the Atlantic, Pacific and Indian Oceans; western marginal seas of the Pacific; and the Arabian Sea. The median value in areas that have statistically significant seasonal cycles of SLS 10 is 0.19. Between about 60° S and 60° N, 37% of the ocean surface has a significant seasonal cycle of SLS and 75% a seasonal cycle of E -P . Phases of SLS have a bimodal distribution, with most areas of the ocean peaking in SLS in either March/April or September/October. The same calculation is done with surface freshwater flux using a mixed-layer depth 15 climatology. With the exception of an area near the western boundaries of the North Atlantic and North Pacific, seasonal variability is dominated by precipitation. Surface freshwater fluxes also have a bimodal distribution, with peaks in January and July, 1-2 months before the peaks of SLS. The amplitudes and phases of SLS and surface fluxes compare well in a qualitative 20 sense, suggesting that much of the variability in SLS is due to E -P forcing. However, the amplitudes of SLS are somewhat larger than would be expected and the peak of SLS comes typically about one month earlier than expected. The differences of the amplitudes of the two quantities is largest in such areas as the Amazon River plume, the Arabian Sea, the ITCZ and the eastern equatorial Pacific and Atlantic, indicating 25 that other processes such as ocean mixing and lateral transport must be important, especially in the tropics. [ABSTRACT FROM AUTHOR]

The article discusses a research about the use of tree rings in providing information about the amount of snow or rainfall. It references a study by Kerstin Treydte and colleagues published within the issue. They concluded that the latter part of the twentieth century was by far the wettest period, suggesting that humans may play a role in the climate of the world.

This paper introduces three quantitative indicators to conduct research for characterizing Northeast China cold vortex persistence activity: cold vortex persistence, generalized "cold vortex," and cold vortex precipitation. As discussed in the first part of paper, a hindcast is performed by multiple regressions using Northeast China precipitation from 2012 to 2014 combination with the previous winter 144 air-sea system factors. The results show that the mentioned three cold vortex index series can reflect the spatial and temporal distributions of observational precipitation in 2012–2014 and obtain results. The cold vortex factors are then added to the Forecast System on Dynamical and Analogy Skills (FODAS) to carry out dynamic statistical hindcast of precipitation in Northeast China from 2003 to 2012. Based on the characteristics and significance of each index, precipitation hindcast is carried out for Northeast China in May, June, July, August, May–June, and July–August. It turns out that the Northeast Cold Vortex Index Series, as defined in this paper, can make positive corrections to the FODAS forecast system, and most of the index correction results are higher than the system's own correction value. This study provides quantitative index products and supplies a solid technical foundation and support for monthly precipitation forecast in Northeast China. [ABSTRACT FROM AUTHOR]

This paper presents an investigation of the role of climatic variability on interannual groundwater and streamflow variability in the southeast United States. For this purpose, streamflow and associated groundwater levels are analyzed for 20 basins that are minimally affected by reservoirs and groundwater pumping. Using the spatially averaged monthly precipitation time series obtained from the Precipitation-elevation Regressions on Independent Slopes Model (PRISM), this paper identifies the recharge and discharge periods that influence the groundwater levels during the winter [January, February, March (JFM)] and summer [July, August, September (JAS)] seasons. Recharge-discharge dependency analyses indicate that precipitation during the previous 3 months influences the groundwater level in a given month. Streamflow in any given month depends on the groundwater level during the previous 3 months. Principal component analysis (PCA) on the precipitation, temperature, streamflow, and groundwater data indicates that groundwater levels and streamflow are the two dominant variables influencing the basin hydroclimatology. Furthermore, relating the percentage variance explained from the PCA to baseflow index (BFI) clearly shows that basins with high BFI have higher eigenvalues, indicating that groundwater is a spatial integrator of hydroclimatic processes. Relating the groundwater levels with El Niño/ Southern Oscillation (ENSO) index, NINO3.4, shows that interannual variability in JFM groundwater levels could be partially explained by the ENSO conditions, but the relationship between JAS groundwater levels and JAS NINO3.4 is not statistically significant. Precipitation forecasts from the ECHAM4.5 general circulation model indicate that it is possible to quantify groundwater availability during the winter season on the basis of the forecasted precipitation and ENSO conditions. [ABSTRACT FROM AUTHOR]

The Western Arctic Linkage Experiment (WALE) is aimed at understanding the role of high-latitude terrestrial ecosystems in the response of the Arctic system to global change through collection and comparison of climate datasets and model results. In this paper, a spatiotemporal approach is taken to compare and validate model results from the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) with commonly used analysis and reanalysis datasets for monthly averages of temperature and precipitation in 1992–2000 and for a study area at 55°–65°N, 160°–110°W in northwestern Canada and Alaska. Objectives include a quantitative assessment of similarity between datasets and climate model fields, and identification of geographic areas and seasons that are problematic in modeling, with potential causes that may aid in model improvement. These are achieved by application of algebraic similarity mapping, a simple yet effective method for synoptic analysis of many (here, 45) different spatial datasets, maps, and models. Results indicate a dependence of model–data similarity on seasonality, on climate variable, and on geographic location. In summary, 1) similarity of data and models is better for temperature than for precipitation; and 2) modeling of summer precipitation fields, and to a lesser extent, temperature fields, appears more problematic than that of winter fields. The geographic distribution of areas with best and worst agreement shifts throughout the year, with generally better agreement between maps and models in the northeastern and northern inland areas than in topographically complex and near-coastal areas. The study contributes to an understanding of the geographic complexity of the Arctic system and modeling its diverse climate. [ABSTRACT FROM AUTHOR]

Gridded data products, for example interpolated daily measurements of precipitation from weather stations, are commonly used as a convenient substitute for direct observations because these products provide a spatially and temporally continuous and complete source of data. However, when the goal is to characterize climatological features of extreme precipitation over a spatial domain (e.g., a map of return values) at the native spatial scales of these phenomena, then gridded products may lead to incorrect conclusions because daily precipitation is a fractal field and hence any smoothing technique will dampen local extremes. To address this issue, we create a new "probabilistic" gridded product specifically designed to characterize the climatological properties of extreme precipitation by applying spatial statistical analysis to daily measurements of precipitation from the Global Historical Climatology Network over the contiguous United States. The essence of our method is to first estimate the climatology of extreme precipitation based on station data and then use a data-driven statistical approach to interpolate these estimates to a fine grid. We argue that our method yields an improved characterization of the climatology within a grid cell because the probabilistic behavior of extreme precipitation is much better behaved (i.e., smoother) than daily weather. Furthermore, the spatial smoothing innate to our approach significantly increases the signal-to-noise ratio in the estimated extreme statistics relative to an analysis without smoothing. Finally, by deriving a data-driven approach for translating extreme statistics to a spatially complete grid, the methodology outlined in this paper resolves the issue of how to properly compare station data with output from earth system models. We conclude the paper by comparing our probabilistic gridded product with a standard extreme value analysis of the Livneh gridded daily precipitation product. Our new data product is freely available on the Harvard Dataverse (https://bit.ly/2CXdnuj). [ABSTRACT FROM AUTHOR]

This paper evaluates the simulation performance of the 37 coupled models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) with respect to the East Asian summer monsoon (EASM) and the Indo-Pacific warm pool and North Pacific Ocean dipole (IPOD) and also the interrelationships between them. The results show that the majority of the models are unable to accurately simulate the interannual variability and long-term trends of the EASM, and their simulations of the temporal and spatial variations of the IPOD are also limited. Further analysis showed that the correlation coefficients between the simulated and observed EASM index (EASMI) is proportional to those between the simulated and observed IPOD index (IPODI); that is, if the models have skills to simulate one of them then they will likely generate good simulations of another. Based on the above relationship, this paper proposes a conditional multi-model ensemble method (CMME) that eliminates those models without capability to simulate the IPOD and EASM when calculating the multi-model ensemble (MME). The analysis shows that, compared with the MME, this CMME method can significantly improve the simulations of the spatial and temporal variations of both the IPOD and EASM as well as their interrelationship, suggesting the potential for the CMME approach to be used in place of the MME method. [ABSTRACT FROM AUTHOR]

Using 30 years of hourly rain gauge records and reanalysis data, this paper reveals two types of heavy summer rainfall in central North China (CNC): the lasting mountain (LM) rainfall and the mountain-plain (MP) rainfall, and further explains their formation mechanisms. The evolutions of the rainfall are found to be closely connected to upper-tropospheric temperature anomalies. When upper-tropospheric warm (cold) anomalies dominate North China (the Japan Sea) and stretch down to lower layers, positive (negative) geopotential anomalies, which appear above the warm (cold) anomalies governed by hydrostatic equilibrium, extend from upper to lower troposphere. In the lower layers, evident low-level easterly anomalies form to the south (north) of the positive (negative) geopotential center, controlling the downstream of CNC and making convective systems difficult to progress eastward. Correspondingly, the low-level convergence and strong convection maintain in the west, and the rainfall persists over the mountains constituting the LM process. But when upper-tropospheric cold (warm) anomalies dominate the west (east) of 110°E and stretch down to lower layers, CNC is situated between an upstream trough and a downstream ridge. As the trough-ridge system progresses eastward, the low-level moisture tongue and strong convections in front of the trough move from the mountains to the plains, and the rainfall propagates downstream constituting the MP process. Results in this paper indicate that upper-tropospheric temperature has significant influence on the evolution of rainfall, and pay attention to its characteristics could provide helpful information in the analysis and forecasting of rainfall propagation. [ABSTRACT FROM AUTHOR]

In recent years, numerous studies have investigated the relationship of extreme precipitation intensities with temperature derived from a binning method using present‐day weather data. The aim of this approach is that these dependencies, or so‐called apparent scaling rates, provide insights on how precipitation extremes could evolve in the future climate. In a recent paper, Bao et al. showed that there is a large discrepancy between the present‐day apparent scaling rates—showing a negative dependency of daily rainfall extremes on temperature for Darwin—and the climate change response showing a substantial increase in daily rainfall extremes. Their results provide compelling evidence that it may not be straightforward to predict the climate change response from the temperature scaling. We agree with this statement, but disagree with the physical explanation put forward in that study and think that moisture limitations are the most likely cause. Therefore, we advocate the use of dew point temperatures in scaling studies as a much more direct proxy of the absolute humidity of the air in which precipitation extremes develop, which we think is physically more consistent with the underlying mechanism causing the increase in precipitation extremes with global warming. [ABSTRACT FROM AUTHOR]

The characterization of the alpine extreme precipitation is the basis to study the projected changes in frequency and intensity of heavy rainfall and is needed to improve the resilience of communities to high‐impact weather. Climatological features of extreme daily and sub‐daily precipitation are documented here for the Swiss Alps and surrounding regions at a high spatial resolution (1 km2). The basis is 12 years of data from rain gauges and CombiPrecip, a rainfall field produced by locally adjusting the radar precipitation map to the values measured by rain gauges. The agreement between rain gauges and CombiPrecip concerning both the timing and the magnitude of the extreme events is quantified by cross‐validation; overall, it increases with diminishing the severity of the extremes and increasing accumulation time. If the extremes represent on average the 10 most intense rainfall accumulations per year, in general 50–65% of rain gauges extremes are extremes also for CombiPrecip, 40–50% of CombiPrecip extremes are not extremes according to rain gauges, and CombiPrecip extremes are till 7% lower than rain gauges extremes. The maps presented in this paper show that both daily and sub‐daily extremes are more intense along the alpine slopes compared to the crest of the Alps in all seasons, with the Lago Maggiore region showing the largest values. The fraction of yearly rainfall due to extremes is generally smaller in the Alps than in flat terrain. Extreme 1‐hr precipitation is more clustered in time in the inner Alps, but is less frequent, and exhibits a strong diurnal cycle in summer. The paper also shows that sub‐daily and daily extremes occur essentially over the same 24‐hr period. [ABSTRACT FROM AUTHOR]

Climate models suggest that anthropogenic emissions are likely to induce an important drying during summer over most of Europe in the late 21st century. However, the amplitude of the associated decrease in precipitation strongly varies among the different climate models. In order to reduce this spread, it is first necessary to identify its causes and the associated physical mechanisms. Consequently, the focus of this paper is to better estimate the role of large scale circulation (LSC) in precipitation changes over Europe using a multi-model framework and then to characterize the LSC changes using the weather regime paradigm. We show that LSC changes directly lead to a decrease of precipitation over northwestern Europe. This circulation-driven decrease in rainfall is mainly linked to an increase (decrease) of the occurrence of positive (negative) phase of the North Atlantic Oscillation regime. LSC is also responsible for a significant part of the models spread in precipitation changes over these regions. Over southern Europe, the role of LSC changes on multi-model mean precipitation changes is generally weak. We also show that the precipitation anomalies directly induced by LSC modifications seem to be further amplified through local feedbacks. [ABSTRACT FROM AUTHOR]

This paper applies the methods of historical climatology to present a climate reconstruction for the area of the Burgundian Low Countries during the 15th century. The results are based on documentary evidence that has been handled very carefully, especially with regard to the distinction between contemporary and non-contemporary sources. Approximately 3000 written records derived from about 100 different sources were examined and converted into seasonal seven-degree indices for temperature and precipitation. For the Late Middle Ages only a few climate reconstructions exist. There are even fewer reconstructions which include spring and autumn temperature or any precipitation information at all. This paper therefore constitutes a useful contribution to the understanding of climate and weather conditions in the less well researched but highly interesting 15th century. The extremely cold winter temperatures during the 1430s and an extremely cold winter in 1407/1408 are striking. Moreover, no other year in this century was as hot and dry as 1473. At the beginning and the end of the 1480s and at the beginning of the 1490s summers were considerably wetter than average. [ABSTRACT FROM AUTHOR]

Accurate reporting and forecasting of PM2.5 concentration are important for improving public health. In this paper, we propose a partial differential equation (PDE) model, specially, a linear diffusive equation, to describe the spatial-temporal characteristics of PM2.5 in order to make short-term prediction. We analyze the temporal and spatial patterns of a real dataset from China’s National Environmental Monitoring and validate the PDE-based model in terms of predicting the PM2.5 concentration of the next day by the former days’ history data. Our experiment results show that the PDE model is able to characterize and predict the process of PM2.5 transport. For example, for 300 continuous days of 2016, the average prediction accuracy of the PDE model over all city-regions is 93% or 83% based on different accuracy definitions. To our knowledge, this is the first attempt to use PDE-based model to study PM2.5 prediction in both temporal and spatial dimensions. [ABSTRACT FROM AUTHOR]

The purpose of this research was to identify major drought events on the Spanish mainland between 1961 and 2014 by means of two drought indices, and analyze the spatial propagation of drought conditions. The indices applied were the standardized precipitation index (SPI) and the standardized evaporation precipitation index (SPEI). The first was calculated as standardized anomalies of precipitation at various temporal intervals, while the second examined the climatic balance normalized at monthly scale, incorporating the relationship between precipitation and the atmospheric water demand. The daily meteorological data from Spanish Meteorological Archives (AEMet) were used in performing the analyses. Within the framework of the DESEMON project, original data were converted into a high spatial resolution grid (1.1 km2) following exhaustive quality control. Values of both indices were calculated on a weekly scale and different timescales (12, 24 and 36 months). The results show that during the first half of the study period, the SPI usually returned a higher identification of drought areas, while the reverse was true from the 1990s, suggesting that the effect from atmospheric evaporative demand could have increased. The temporal propagation from 12- to 24-month and 36-month timescales analyzed in the paper seems to be a far from straightforward phenomenon that does not follow a simple rule of time lag, because events at different temporal scales can overlap in time and space. Spatially, the propagation of drought events affecting more than 25% of the total land indicates the existence of various spatial gradients of drought propagation, mostly east-west or west-east, but also north-south have been found. No generalized episodes were found with a radial pattern, i.e., from inland to the coast. [ABSTRACT FROM AUTHOR]

I investigate the intraday effects of rain on the demand for indoor leisure. To do so, I use sub-daily museum attendance and weather data to reveal a dynamic response to precipitation that would be obscured using day-level data. I find that the magnitudes and signs of the effects of rainfall vary significantly throughout the day. In some hours, the predicted increase in visitors is nearly three times larger than would be expected from estimates using daily measures. Many individuals appear to actively adjust their plans throughout the day in response to rain, while others’ attendance depends upon prior weather forecasts of rain. Further analysis reveals that visit duration also increases during rainy periods, and visitors are more likely to attend pay-to-enter special exhibits. International visitors make up a greater share of total visitors during periods of observed precipitation. More broadly, this paper establishes the viability and value of working with widely available sub-daily rainfall data to uncover these dynamics. [ABSTRACT FROM AUTHOR]

The Romanian Plain, covering a surface area of about 52 600 sq.km and stretching along the Danube, is one of the largest agricultural regions in the European Union. It presents diverse ecological conditions in four major zonal units, steppe, silvo-steppe, forest zone and its large Danube floodplain. In this context, the assessments of climate change, specifically of those climatic elements like temperature and precipitation which may have an important impact on various economic sectors, represent a necessary scientific support for end-users to envisage sustainable development strategies. This paper presents 1) the evaluation of the regional climatic model RCA4 driven by the ERA-Interim reanalysis and five general climatic models under historical forcing, 2) the adjustment of the bias identified in the simulations compared to the observation data using the Delta Change method, and 3) the projected changes of seasonal mean temperature and precipitation in the Romanian Plain for the mid-term period 2021-2050 under the RCP4.5 scenario compared with the reference period 1971-2000 of ROCADA observations. [ABSTRACT FROM AUTHOR]

Various meteorological studies require probabilistic modeling such as the flood, drought, and wet and dry spell occurrences. The most commonly employed approaches are based on the binomial probability distribution function (pdf), which is valid for homogeneous temporal and spatial probabilities. However, in practice, heterogeneous probabilities are very common, and in this case, the classical binomial pdf cannot be employed. This paper presents a rigorous probabilistic methodology for heterogeneous probabilities by considerations from the random field concept. The general form of the binomial pdf is derived and it is shown that for homogeneous probabilities it yields the classical binomial pdf exactly. The necessary analytical formulations are derived with the assumption that the meteorological occurrences at a set of sites or time periods (day, month, and year) are independent from each other. The probability statements derived in this paper are helpful in predicting the regional and temporal probable potential future meteorological occurrences. The application of the proposed methodology is presented for annual precipitation occurrences at six meteorology stations around Istanbul, Turkey. [ABSTRACT FROM AUTHOR]

In this paper, we attempt to highlight the relevance of cutoff low systems (CoLs) to large-scale heavy precipitation events within the Alpine region which often lead to catastrophic flooding. The main results of this study are (1) a detailed climatology (1971-1999) of CoLs for the European region, (2) contribution of CoLs to extreme precipitation events in the European Alpine region, (3) identification of regions within the European Alps most affected by extreme precipitation caused by CoLs, and (4) identification of regions where presence of CoLs is related to extreme precipitation in the Alpine region. The findings of this paper suggest that CoLs have a significant correlation with extreme precipitation events and strongly influence the climate of the Alpine region. The total contribution of CoLs to large-scale heavy precipitation events ranges between 20 and 95 % and is most pronounced in the northern and eastern parts of the Alps. More than 80 % of the events occur in the summer season. The area around the Alps and West of Spain (over the Atlantic Ocean) is the most affected region. The location of the center of CoLs that affect the Alpine region most occur on the northern and southern sides of the Alpine ridge. [ABSTRACT FROM AUTHOR]

The second West African Monsoon Modeling and Evaluation Project Experiment (WAMME II) is designed to improve understanding of the possible roles and feedbacks of sea surface temperature (SST), land use land cover change (LULCC), and aerosols forcings in the Sahel climate system at seasonal to decadal scales. The project's strategy is to apply prescribed observationally based anomaly forcing, i.e., 'idealized but realistic' forcing, in simulations by climate models. The goal is to assess these forcings' effects in producing/amplifying seasonal and decadal climate variability in the Sahel between the 1950s and the 1980s, which is selected to characterize the great drought period of the last century. This is the first multi-model experiment specifically designed to simultaneously evaluate such relative contributions. The WAMME II models have consistently demonstrated that SST forcing is a major contributor to the twentieth century Sahel drought. Under the influence of the maximum possible SST forcing, the ensemble mean of WAMME II models can produce up to 60 % of the precipitation difference during the period. The present paper also addresses the role of SSTs in triggering and maintaining the Sahel drought. In this regard, the consensus of WAMME II models is that both Indian and Pacific Ocean SSTs greatly contributed to the drought, with the former producing an anomalous displacement of the Intertropical Convergence Zone before the WAM onset, and the latter mainly contributes to the summer WAM drought. The WAMME II models also show that the impact of LULCC forcing on the Sahel climate system is weaker than that of SST forcing, but still of first order magnitude. According to the results, under LULCC forcing the ensemble mean of WAMME II models can produces about 40 % of the precipitation difference between the 1980s and the 1950s. The role of land surface processes in responding to and amplifying the drought is also identified. The results suggest that catastrophic consequences are likely to occur in the regional Sahel climate when SST anomalies in individual ocean basins and in land conditions combine synergistically to favor drought. [ABSTRACT FROM AUTHOR]

The variations of large-scale climatic controls and surface responses through the annual cycle during strong positive (El Niño) and negative (La Niña) phase ENSO events are analyzed to assess the within-year and among-year variations of climate anomalies. Data from the NCEP–NCAR reanalysis project are presented as small-multiple maps to illustrate the spatial and temporal variability in North American climate associated with extreme phases of ENSO. Temperature, mean sea level pressure, 500-mb geopotential heights, and 850-mb specific humidity have composite-anomaly patterns that exhibit the greatest degree of spatial and temporal coherence. In general, the composite-anomaly patterns for El Niño and La Niña events are of opposite sign, with stronger, more spatially coherent anomalies occurring during El Niño events than during La Niña events. However, the strength and coherency of the precipitation anomaly patterns are reduced in the interior intermountain west during both positive and negative phase of ENSO. The variations in precipitation anomalies are compared to the 500-mb omega and 850-mb specific humidity composite-anomaly patterns, which provide information on the controls of precipitation by large-scale vertical motions and moisture availability thus providing information on the specific mechanisms associated with precipitation variability during ENSO events. [ABSTRACT FROM AUTHOR]

The time of emergence (TOE) of climate change is defined as the time when a new climate state emerges from a prior one. TOE assessment is particularly relevant in West Africa, a region highly threatened by climate change and urgently needing trustworthy climate predictions. In this paper, the TOE of precipitation change in West Africa is assessed for the first time, by analyzing 6 precipitation metrics (cumulated precipitation, number of wet and very wet days, onset and length of the rainy season) computed from the output of 29 state-of-the-art climate models. In West Sahel, climate conditions characterized by reduced occurrence of wet days are likely to emerge before 2036, leading to the possible emergence of a dryer climate in 2028–2052. In East Sahel, a wetter precipitation regime characterized by increased occurrence of very wet days is likely to emerge before 2054. Results do not provide a clear indication about a possible climate shift in the onset and length of the rainy season. Although uncertainty in climate model future projections still limits the robust determination of TOE locally, this study provides reliable time constraints to the expected climate shift in West Africa at the sub-regional scale, supporting adaptation measures to the future change in the precipitation regime. [ABSTRACT FROM AUTHOR]

An improved understanding of changes in flood hazard and the underlying driving mechanisms is critical for predicting future changes for better adaptation strategies. While recent increases in flooding across the world have been partly attributed to a range of atmospheric or landscape drivers, one often-forgotten driver of changes in flood properties is the variability of river conveyance capacity. This paper proposes a new framework for connecting flood changes to longitudinal variability in river conveyance, precipitation climatology, flows and sediment connectivity. We present a first step, based on a regional analysis, towards a longer-term research effort that is required to decipher the circular causality between floods and rivers. The results show how this system of interacting units in the atmospheric, hydrologic and geomorphological realm function as a nonlinear filter that fundamentally alters the frequency of flood events. To revise and refine our estimation of future flood risk, this work highlights that multidriver attribution studies are needed, that include boundary conditions such as underlying climate, water and sediment connectivity, and explicit estimations of river conveyance properties. [ABSTRACT FROM AUTHOR]

This paper investigates the performance of 10 Regional Climate Models (RCMs) hindcasts from the Coordinated Regional Climate Downscaling Experiments (CORDEX) over Central Africa, covering the period 1998–2008 and performed over a common model grid spacing 0.44° (∼50 km). Multiple observational data sets are used to evaluate model performances over four targeted subregions. Throughout the work, a measure of observational uncertainty is made and we discuss whether or not the models are found within or outside the range of observational uncertainty. Results indicate that RCMs generally capture rainfall and temperature basic features, though important biases exist and vary for models and seasons. Dry (wet) biases are common features over the Congo basin (northern and southern part of the domain). In terms of precipitation and temperature in both seasonal and annual scale, most RCMs along with their ensemble mean generally fall in the range of observational uncertainty. Furthermore, most RCMs show a good spread of grid points where the added value of RCMs is found although the added value in temperature is not as great as with precipitation. UC‐WRF is among models adding less value on ERAINT and this could explain why whatever the time scale of variability, UC‐WRF outputs are generally out from the observational uncertainty. The multimodel ensemble mean is generally found within observational range when most models are there as well. This highlights the fact that the ensemble mean, built from the equal treatment of RCMs, does not generally outperform individual RCMs realization as it is reported in several previous studies. Key Points: Most RCMs along with their ensemble mean generally fall in the range of observational uncertaintyThe ensemble mean of models is generally found within the observational range when most models are there as wellThe ensemble mean of models does not generally outperform individual RCMs realization as it is reported in several previous studies [ABSTRACT FROM AUTHOR]

Information on the variability of precipitation in time and space is critical for many water resource projects. However, precipitation records at the location of interest are often either limited or unavailable due to an inadequate network of rainfall measurements. To address this need, regionalization methods have been employed to characterize spatial patterns of precipitation and to transfer precipitation information from one location to another where records are scarce. Hence, the overall objective of the present paper is to propose a stochastic weather model for generating daily precipitation at ungauged locations. The proposed approach consists of two components: (a) a regionalization approach for identifying homogeneous groups of observed daily precipitation series, and (b) a stochastic model for constructing daily precipitation events at ungauged locations within homogeneous groups. This statistical approach identifies groups of precipitation stations with similar statistical characteristics based on the combination of two multivariate statistical techniques: principal component analysis (PCA) and ordinal factor analysis (OFA). While the application of PCA in climatological regionalization studies based on precipitation amount is common, the application of OFA to include precipitation occurrence in the identification of regions is unusual. The feasibility of the approach is assessed using daily precipitation data from a network of precipitation stations in the Catskill Mountain region of New York State, United States. [ABSTRACT FROM AUTHOR]

This paper highlights detailed projected changes in rainfall over Thailand for the early (2011–2040), middle (2041–2070) and late (2071–2099) periods of the 21st century under the representative concentration pathways (RCP) 4.5 and RCP 8.5 using the high‐resolution multi‐model simulations of the Coordinated Regional Climate Downscaling Experiment (CORDEX) Southeast Asia. The ensemble mean is calculated based on seven members consisting of six general circulation models (GCMs) and three regional climate models (RCMs). Generally, the ensemble mean precipitation agrees reasonably well with observations, best represented by the Global Precipitation Climatology Center (GPCC) data, over Thailand during the historical period (1976–2005). However, inter‐model variations can be large among ensemble members especially during dry months (December to March) for northern‐central‐eastern parts, and throughout the year for the southern parts of Thailand. Similarly for future projection periods, inter‐model variations in the sign and magnitude of changes exist. The ensemble means of projected changes in rainfall for both RCPs during dry months show distinct contrast between the northern‐central‐eastern parts and the southern parts of Thailand with generally wetter and drier conditions, respectively. The magnitude of change can be as high as 15% of the historical period, which varies depending on the sub‐region, season, projection period, and RCP scenario. In contrast, generally drier conditions are projected during the wet season (June to September) throughout the country for both RCPs where the rainfall reduction can be as high as 10% in some areas. However, the magnitude of projected rainfall changes of some individual models can be much larger than the ensemble means, exceeding 40% in some cases. These projected changes are related to the changes in regional circulations associated with the winter and summer monsoons, which are projected to weaken. The drier (wetter) condition is associated with the enhanced subsidence (rising motion). [ABSTRACT FROM AUTHOR]

The accuracy of hydrological assessments in mountain regions is often hindered by the low density of gauges coupled with complex spatial variations in climate. Increasingly, spatial datasets (i.e. satellite and other products) and new computational tools are merged with ground observations to address this problem. This paper presents a comparison of approaches of different complexities to spatially interpolate monthly precipitation and daily temperature time series in the upper Aconcagua catchment in central Chile. A generalised linear mixed model (GLMM) whose parameters are estimated through approximate Bayesian inference is compared with simpler alternatives: inverse distance weighting (IDW), lapse rates (LRs), and two methods that analyse the residuals between observations and WorldClim (WC) data or Climate Hazards Group Infrared Precipitation with Station data (CHIRPS). The assessment is based on a leave-one-out cross validation (LOOCV), with the root-mean-squared error (RMSE) being the primary performance criterion for both climate variables, while the probability of detection (POD) and false-alarm ratio (FAR) are also used for precipitation. Results show that for spatial interpolation of temperature and precipitation, the approaches based on the WorldClim or CHIRPS residuals may be recommended as being more accurate, easy to apply and relatively robust to tested reductions in the number of estimation gauges. The GLMM has comparable performance when all gauges were included and is better for estimating occurrence of precipitation but is more sensitive to the reduction in the number of gauges used for estimation, which is a constraint in sparsely monitored catchments. [ABSTRACT FROM AUTHOR]

The present paper examines the observed variability of maximum depth of snow cover in Poland and its projections for near (2021-2050) and far (2071-2100) future. The study makes use of a set of 43 time series of observation records from stations in Poland, from 1951 to 2013. For the future, two downscaling experiments were conducted with the aim of producing reliable high-resolution climate projections of precipitation and temperature for Poland. The results of these projections were used as the input data to the seNorge snow model in order to transform bias-adjusted daily temperature and precipitation into daily snow conditions. Observed behavior of time series of snow is complex and not easy to interpret. The changes (if any) are dominated by strong inter-winter and intra-winter variability, rendering trend detection difficult. Projected seasonal snow cover depth (for winter as well as spring and autumn) as simulated by the snow model for the near and far future show decreases. The rate of decreasing maximum snow depth is expected to at least double by 2071-2100. [ABSTRACT FROM AUTHOR]

Hydrogen and oxygen stable isotopes are natural tracers and have played an important role in the investigation of hydrological processes. In this paper, year-round precipitation samples were collected and measured in Chengdu, a subtropical monsoon climate region, to compare the stable isotope characteristics in precipitation and their influencing factors between dry and wet seasons. The results showed that the seasonal variation of δD and δ18O in precipitation was significant, and the isotopic values in precipitation in dry season were more enriched than those in wet season. The slope and intercept of local meteoric water line (LMWL) in Chengdu were lower than those in the southeast monsoon region of China but higher than those in north China, indicating the combined influence of ocean-source and inland water vapor. The slope of LMWL in dry season was obviously lower than that in wet season, revealing more intense sub-cloud secondary evaporation. The effect of temperature and precipitation was not significant in both seasons. Meteorological variables had greater influence on precipitation isotopes in wet season. D-excess had greater fluctuation during the dry season, reflecting more complex water vapor sources, which resulted in the influence of meteorological factors being masked. [ABSTRACT FROM AUTHOR]

This paper constructs annual homogenised precipitation series for 13 locations in Scotland (1861–1991) from non-standard sources. Whilst the British Rainfall series represents the backbone of most UK rainfall records before the middle of the twentieth century, this paper returns to the original records to examine spatial and temporal variations in Scottish precipitation. The records were subjected to trend analysis and principal components analysis (PCA), and then related to atmospheric circulation parameters to understand the synoptic- scale mechanisms involved. Upward (downward) trends in precipitation were noted in western (eastern) Scotland over the period 1870–1991. Precipitation variability in western (eastern) Scotland is best explained by fluctuations in the westerly circulation (pressure), with the west- east precipitation gradient closing in those years with below average pressure, and a greater frequency of northerly and/or easterly winds. Precipitation trends cannot be explained by changes in atmospheric circulation patterns, suggesting that other factors must be involved. [ABSTRACT FROM AUTHOR]

Summary This paper promotes a GIS-based method that allows the visualization, the identification and the qualitative assessment of relationships existing among a limitless number of climatological variables. We use a variety of precipitation variables from fourteen Romanian weather stations to demonstrate the techniques and discuss its benefits and limitations. [ABSTRACT FROM AUTHOR]

The principal objectives of this paper are to develop and validate an optimum interpolation method for the spatial analysis of monthly precipitation in Turkey. A two-dimensional optimum interpolation objective analysis scheme has been developed for the spatial analysis of precipitation. The model is developed for generating statistically optimum interpolation based on the irregular distribution of meteorological stations. One question that affects the optimum interpolation method and, indeed, all such techniques, is how many observations should be allowed to influence a given grid point? The method developed in this paper addresses this question. For the implementation of the method, 52 stations are considered for Turkey, with 30 years of monthly data at each point. It is observed that each monthly average spatial correlation function shows a monotonically decreasing pattern based on 15 km interval averages. The method provides high estimation accuracy in dense station locations such as in northwestern Turkey. Precipitation contour maps obtained by the optimum interpolation method indicate two spatial trends over Turkey which have not been identified in any previous study. [ABSTRACT FROM AUTHOR]

The present study aims to present the atmospheric precipitation regime for the western part of Romania, mainly the area located in the Mureş and Banat plains. Relying on the amounts of water gauged at the weather stations and substations located in the fork plain lying between the White Criş and the Danube valleys and which were intermittently operational during the period from 1950 to 2020, a study regarding the areal distribution and time variation of the main parameters of rainfall has been made. A display is made of the main characteristic features of the annual mass curve, the rainfall periodicity and randomness, the maximum rainfall in 24, 48 and 72 hours and the snow cover. The data reduction and validation were done by keeping a close eye on the specific weather phenomena and by analysing the synoptic situation for the most important weather events. The characteristic parameters of the pluviometric regime in the Mures and Banat Plains, which were analysed in this paper, can constitute basic materials for the design of hydro-ameliorative systems, for the construction of irrigation systems or to combat excess moisture, all of which are an important component of the development agriculture in the western part of Romania. [ABSTRACT FROM AUTHOR]

This paper analyzes climatological characteristics and temporal variation of the start and end dates of the rainy season over East Asia using a daily precipitation dataset for the time period 1951-2009. The rainy season is defined by a 5-day rainfall standard, and the regional average time series is constructed by applying the weighted-average method. Results show that the rainy season starts later, ends earlier and lasts shorter from southeast to northwest. In spring, the rainy belt slowly moves northward from 30 to 33°N in China and from 33 to 36°N on the Korean Peninsula and Japanese Islands. From 1951 to 2009, the rainy season generally began earlier in China but later in Korea and Japan, and it ended earlier at latitudes north of 35°N and later south of 35°N. The region-averaged start and end dates of the rainy season in the study region insignificantly advanced, and the duration of the rainy season insignificantly increased from 1951 to 2009. The rainy season duration slightly decreased in the Russian Far East and in northern and western China, and significantly decreased on the Korean Peninsula and the southern Hokkaido Islands, though it obviously increased in the Yangtze--Huaihe River Basins. [ABSTRACT FROM AUTHOR]

Precipitation displays a remarkable variability in space and time. An important yet poorly documented aspect of this variability is intermittency. In this paper, a new way of quantifying intermittency based on the burstiness B and memory M of interamount times is proposed. The method is applied to a unique dataset of 325 high-resolution rain gauges in the United States and Europe. Results show that the M- B diagram provides useful insight into local precipitation patterns and can be used to study intermittency over a wide range of temporal scales. It is found that precipitation tends to be more intermittent in warm and dry climates with the largest observed values in the southwest of the United States (i.e., California, Nevada, Arizona, and Texas). Low-to-moderate values are reported for the northeastern United States, the United Kingdom, the Netherlands, and Germany. In the second half of the paper, the new metrics are applied to daily rainfall data for 1954-2013 to investigate regional trends in intermittency due to climate variability and global warming. No evidence is found of a global shift in intermittency but a weak trend toward burstier precipitation patterns and longer dry spells in the south of Europe (i.e., Portugal, Spain, and Italy) and an opposite trend toward steadier and more correlated precipitation patterns in Norway, Sweden, and Finland is observed. [ABSTRACT FROM AUTHOR]

Climate change harms the households of coastal areas in Bangladesh because of the geographical position and changes in the climatic elements that are primarily at play. This study looks at the pattern of two prominent climatic elements: temperature and precipitation over thirty years, from 1992 to 2021, focusing on how those factors have changed. The findings revealed an upward increase in all elements, i.e., the maximum temperature, the lowest temperature, and the amount of precipitation. Using the Livelihood Vulnerability Index, this research looked at how vulnerable households are to the effects of climate change in the southwestern coastal area, namely in Amadi Union and Koyra Upazila in the Khulna district of Bangladesh. The original data came from a survey of 276 households and secondary data on rainfall and temperature for the period beginning in 1992 and continuing through 2021. The research conducted a comparative analysis to determine the household's vulnerability to climate change. The empirical research found that families in the Amadi union were moderately exposed to the effects of climate change and the weather variability regarding their strategies for making a living, their social networks, the food they have, and their level of health. By considering the socio-demographic elements, social networks, livelihoods, natural disasters, and climate variability, households of the Amadi union were equally vulnerable regarding their adaptation potential and exposure. These findings have implications for the governments, donor agencies, and other relevant agencies in Amadi Union, Koyra Upazila, and Khulna, initiating and implementing initiatives to adapt to climate change and increase household resilience. [ABSTRACT FROM AUTHOR]

Translating changes in land surface conditions and climate into changes in precipitation, runoff and flood frequencies over a range of catchment scales is a pressing challenge for hydrologic design and flood risk management today. In this paper, we describe a novel approach for modeling areal runoff frequency from heavy-to-extreme precipitation in large urban areas using a simple but general stochastic model for runoff at point scale and bi- and univariate parametric probability distributions for positive point precipitation and areal runoff, respectively. We apply the approach to the Dallas–Fort Worth area using a 22-year historical multisensor precipitation dataset from the National Weather Service to characterize how the different factors that specify the second-order statistics of precipitation, imperviousness and soil water holding capacity at point scale may shape areal runoff frequency, and to assess how changes in precipitation climatology and land surface conditions may change areal runoff frequency as a function of catchment scale and magnitude of precipitation. The results indicate that areal runoff frequency is impacted most significantly by changes in climatological mean and coefficient of variation of positive point precipitation, water holding capacity of soil, imperviousness, and spatial correlation scale of positive point precipitation given the probability of occurrence of heavy-to-extreme precipitation, and that a very small number of low-order statistics of point precipitation may describe areal runoff frequency given the conditional probability distribution models for point precipitation and areal runoff. The approach presented hence offers a parsimonious physically-based alternative to purely numerical approaches based on integrated modeling, or empirical approaches based solely on statistical modeling toward predictive modeling of areal precipitation and runoff frequencies under changing hydroclimatological conditions. [ABSTRACT FROM AUTHOR]

Long‐term trends in equatorial African rainfall have proven difficult to determine because of a dearth in ground‐measured rainfall data. Multiple, satellite‐based products now provide daily rainfall estimates from 1983 to the present at relatively fine spatial resolutions, but in order to assess trends in rainfall, they must be validated alongside ground‐based measurements. The purpose of this paper is twofold: (a) to assess the accuracy of four rainfall products covering the past several decades in western Uganda; and (b) to ascertain recent, multi‐decadal trends in annual rainfall for the region. The four products are African Rainfall Climatology Version 2 (ARC2), Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN‐CDR), and TAMSAT African Rainfall Climatology And Timeseries (TARCAT). The bias and accuracy of 10‐day, monthly, and seasonal rainfall totals of the four products were assessed using approximately 10 years of data from 10 rain gauges. The homogeneity of the products over multiple time periods was assessed using change‐point analysis. The accuracy of the four products increased with an increase in temporal scale, and CHIRPS was the only product that could be considered sufficiently accurate at estimating seasonal rainfall totals throughout most of the region. TARCAT tended to underestimate totals, and ARC2 and PERSIANN were in general the least accurate products. Only annual rainfall estimates from CHIRPS and TARCAT were significantly correlated with ground‐measured rainfall totals. TARCAT was the most homogeneous product, while ARC2, CHIRPS, and PERSIANN had significant negative change points that caused a drying bias over the 1983–2016 period. After adjusting the satellite‐based rainfall estimates based on the timing and magnitude of the change points, annual rainfall totals derived from all four products indicated that western Uganda experienced significantly increasing rainfall from 1983 to 2016. [ABSTRACT FROM AUTHOR]

Extreme precipitation associated with extratropical cyclones can lead to flooding if cyclones track over land. However, the dynamical mechanisms by which moist air is transported into cyclones is poorly understood. In this paper we analyze airflows within a climatology of cyclones in order to understand how cyclones redistribute moisture stored in the atmosphere. This analysis shows that within a cyclone's warm sector the cyclone-relative airflow is rearwards relative to the cyclone propagation direction. This low-level airflow (termed the feeder airstream) slows down when it reaches the cold front, resulting in moisture flux convergence and the formation of a band of high moisture content. One branch of the feeder airstream turns toward the cyclone center, supplying moisture to the base of the warm conveyor belt where it ascends and precipitation forms. The other branch turns away from the cyclone center exporting moisture from the cyclone. As the cyclone travels, this export results in a filament of high moisture content marking the track of the cyclone (often used to identify atmospheric rivers). We find that both cyclone precipitation and water vapor transport increase when moisture in the feeder airstream increases, thus explaining the link between atmospheric rivers and the precipitation associated with warm conveyor belt ascent. Atmospheric moisture budgets calculated as cyclones pass over fixed domains relative to the cyclone tracks show that continuous evaporation of moisture in the precyclone environment moistens the feeder airstream. Evaporation behind the cold front acts to moisten the atmosphere in the wake of the cyclone passage, potentially preconditioning the environment for subsequent cyclone development. [ABSTRACT FROM AUTHOR]