Showing papers in "International Journal of Climatology in 2018"

Will drought events become more frequent and severe in Europe

Abstract: As a result of climate change in recent past and unsustainable land management, drought became one of the most impacting disasters and, with the projected global warming, it is expected to progressively cause more damages by the end of the 21st century. This study investigates changes in drought occurrence, frequency, and severity in Europe in the next decades. A combined indicator based on the predominance of the drought signal over normal/wet conditions has been used. The indicator, which combines the standardized precipitation index (SPI, which accounts for anomalous low rainfall), the standardized precipitation evapotranspiration index (SPEI, which accounts for high temperatures and scarce precipitations), and the reconnaissance drought indicator (RDI, similar to SPEI but more affected by extreme events), has been computed at 3- and 12-month accumulation scales to characterize trends in seasonal and annual events from 1981 to 2100. Climate data from 11 bias-adjusted high-resolution (0.11°) simulations from the EURO-CORDEX (coordinated regional climate downscaling experiment) have been used in the analyses. For each simulation, the frequency and severity of drought and extreme drought events for 1981–2010, 2041–2070, and 2071–2100 have been analysed. Under the moderate emission scenario (RCP4.5), droughts are projected to become increasingly more frequent and severe in the Mediterranean area, western Europe, and Northern Scandinavia, whereas the whole European continent, with the exception of Iceland, will be affected by more frequent and severe extreme droughts under the most severe emission scenario (RCP8.5), especially after 2070. Seasonally, drought frequency is projected to increase everywhere in Europe for both scenarios in spring and summer, especially over southern Europe, and less intensely in autumn; on the contrary, winter shows a decrease in drought frequency over northern Europe.

Frequency, duration and severity of drought in the Semiarid Northeast Brazil region.

Abstract: Drought is the natural disaster that impacts the greatest number of people and produces the most significant economic losses. This work presents a quantitative assessment of drought events occurred in the Semiarid region of Northeast Brazil during 1981–2016. The purpose of this study is to provide an overview of drought intensity for the last 36 years, analysing their severity, frequency and duration, considering hydro-meteorological and agricultural aspects. To evaluate these two aspects, the 12-month standardized precipitation index and the vegetation health index were considered to investigate drought characteristics. The definition of drought event for both these indices was performed regarding start and end month. In this context, drought duration is considered equal to the number of months of event, drought frequency is the number of events per time period and the drought severity is the absolute value of integral area below zero. Results show that the most severe and prolonged drought occurred in 2011–2016. In a clear contrast to previous droughts in past decades, during these last 5-years period drought were more frequent, severe and affected a larger area with significant impacts for population, as well as economical activities.

Precipitation over the Tibetan Plateau during recent decades: a review based on observations and simulations

Abstract: The Tibetan Plateau (TP) has a significant influence on local, regional, and even global weather and climate systems. Precipitation on the TP plays a critical role in the energy and water cycle and terrestrial ecosystem. This study reviewed recent research progress in precipitation changes in recent decades and explored their mechanisms involved based on observations (meteorological station data and satellite remote sensing data) and simulations [global climate models (GCMs) and downscaling modelling]. Our review suggested that the TP precipitation decreases progressively from southeast to northwest, mainly occurs in summer (June–August), accounting for ∼60–70% of annual total, and marginally occurs in winter (December–February), accounting for less than 10%. Diurnal variation of precipitation and convective activity are obvious on the TP. The TP has experienced an overall surface air wetting trend since the 1960s, but with apparent regional and seasonal differences. Projected precipitation on the TP from GCMs and statistical downscaling methods (SDMs) generally increases, while from dynamic downscaling methods (DDMs) slightly increases or even decreases as greenhouse gas emissions continue in the future. Influencing factors such as the TP' and Asian land heating, large-scale atmospheric circulations, climate warming, aerosols, and land surface conditions all exert prominent but complicated effects on precipitation changes on the TP. More efforts should be made to improve the reliabilities and accuracies of precipitation observational data sets, GCMs, and downscaling modelling. Finally, directions for future research are discussed based on the various means covering high-quality precipitation observations and more skilful simulations, which are synthetically used to investigate the TP precipitation and its driving mechanisms. It is expected that this review and its results will be beneficial for hydrological and precipitation studies over the TP.

Contrasting patterns of the extreme drought episodes of 2005, 2010 and 2015 in the Amazon Basin

Abstract: Future climate scenarios point to an increase in the frequency of extreme droughts events, even in humid biomes. Throughout the 21st century, large areas of the Amazon basin experienced the most severe droughts ever recorded with special emphasis on the 2005 and 2010 events due to their severity and extent. Currently, there is an increased demand to understand the geographic extent and seasonal variability of climate variables during drought events, especially with respect to the social and environmental impacts. In this study, we aim to compare the observed climate conditions during the drought episodes of 2005, 2010 and 2015. We perform a detailed assessment of the measured precipitation, land-surface temperature (LST) and solar radiation anomalies. We provide evidence that the anomalous precipitation deficit during 2015 exceeded the amplitude and spatial extent of the previous events, affecting more than 80% of Amazon basin, particularly the eastern portion. The pronounced lack of rainfall availability during late spring and early summer, coincident with radiation and temperature surpluses during these years are significant and notable. Changed meteorological spatial patterns were observed, with precipitation and radiation being the most prominent parameters in 2005, whereas precipitation and LST were most relevant in 2010. Understanding the behaviour and interactions of pertinent meteorological variables, as well as identifying similar or divergent patterns over the region during distinct extreme events, is essential for the improvement of our knowledge of Amazon forest vulnerability to climate fluctuation changes.

Impacts of different ENSO flavors and tropical Pacific convection variability (ITCZ, SPCZ) on austral summer rainfall in South America, with a focus on Peru

Abstract: El Nino in the eastern and central Pacific has different impacts on the rainfall of South America, and the atmospheric pathways through the South Pacific Convergence Zone (SPCZ) and Inter-Tropical Convergence Zone (ITCZ) are poorly understood. To address this, we performed linear regression analysis of E (eastern Pacific) and C (central Pacific) indices of sea surface temperature (SST), as well as precipitation indices for the SPCZ and ITCZ, with gridded precipitation and reanalysis data sets during the austral summer (December–February) for the 1980–2016 period. Positive C induces dry anomalies along the tropical Andes and northern South America (NSA), while wet anomalies prevail over southeastern South America (SESA). Moreover, it produces wet conditions in the northwestern Peruvian Amazon. In contrast, positive E enhances wet conditions along the coasts of Ecuador and northern Peru associated with the southward displacement of the eastern Pacific ITCZ and induces dry conditions in Altiplano, Amazon basin, and northeastern Brazil (NEB). Both El Nino Southern Oscillation (ENSO) indices are associated with weakened upper-level easterly flow over Peru, but it is more restricted to the central and southern Peruvian Andes with positive E. Both SPCZ indices, the zonal position of the SPCZ and its latitudinal displacement, suppress rainfall along western Peruvian Andes when are positive, but the latter also inhibits rainfall over the Bolivian Altiplano. They are also linked to upper-level westerly wind anomalies overall of Peru, but these anomalies do not extend as far south in the first. The southward displacement of the eastern Pacific ITCZ also induces wet anomalies in SESA while dry anomalies prevail over NEB, the western Amazon basin, and Bolivia. Oppositely, the southward displacement of the central Pacific ITCZ induces dry anomalies in NEB and along the northern coast of Peru; while wet anomalies occur mainly in eastern Brazil, Paraguay, and Bolivia through an enhancement of the low level jet.

Temperature-extreme precipitation scaling: a two-way causality?

Abstract: Extreme precipitation events are widely thought to intensify in a warmer atmosphere through the Clausius-Clapeyron equation. The temperature-extreme precipitation scaling was proposed to analyze the temperature dependency of short-duration extreme precipitation and since then, the concept has been widely used in climatology. Bao et al. (2017) (Nature Climate Change, DOI:10.1038/NCLIMATE3201) suggest that the apparent scaling reflects not only how surface air properties affect extreme precipitation, but how synoptic conditions and localised cooling due to the storm itself affect the scaling – implying two-way causality. We address here critical issues of this paper and provide evidence that dew point temperature drives extreme precipitation, with the direction of causality reversed only for the storm’s peak intensity. This physical inference may serve as a basis to better quantify scaling rates and to help establish the relationship between extreme precipitation and environmental conditions in the current climate, and thereby provide insights into future changes to precipitation extremes due to climate change. 11

1961–1990 high-resolution monthly precipitation climatologies for Italy

Abstract: High-resolution monthly precipitation climatologies for Italy are presented. They are based on 1961–1990 precipitation normals obtained from a quality-controlled dataset of 6134 stations covering the Italian territory and part of the Northern neighbouring regions. The climatologies are computed by means of two interpolation methods modelling the precipitation-elevation relationship at a local level, more precisely a local weighted linear regression (LWLR) and a local regression kriging (RK) are performed. For both methods, local optimisations are also applied in order to improve model performance. Model results are compared with those provided by two other widely used interpolation methods which do not consider elevation in modelling precipitation distribution: ordinary kriging and inverse distance weighting. Even though all the four models produce quite reasonable results, LWLR and RK show the best agreement with the observed station normals and leave-one-out-estimated mean absolute errors ranging from 5.1 mm (July) to 11 mm (November) for both models. Their better performances are even clearer when specific clusters of stations (e.g. high-elevation sites) are considered. Even though LWLR and RK provide very similar results both at station and at grid point level, they show some peculiar features. In particular, LWLR is found to have a better extrapolation ability at high-elevation sites when data density is high enough, while RK is more robust in performing extrapolation over areas with complex orography and scarce data coverage, where LWLR may provide unrealistic precipitation values. However, by means of prediction intervals, LWLR provides a more straightforward approach to quantify the model uncertainty at any point of the study domain, which helps to identify the areas mainly affected by model instability. LWLR and RK high-resolution climatologies exhibit a very heterogeneous and seasonal-dependent precipitation distribution throughout the domain and allow to identify the main climatic zones of Italy.

Analysis of variability and trends of precipitation extremes in Singapore during 1980–2013

Abstract: Changes in precipitation extremes in the tropical urban context is complex, where the precipitation activities are influenced by the combined effects of El Nino–Southern Oscillation (ENSO), global warming and local effects. This study presents a comprehensive framework to investigate the variability and trends in precipitation extremes in a tropical urban city-state, Singapore, based on a set of extreme indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI). The long-term trends in the precipitation extremes over the period from 1980 until 2013 are examined using an iterative-based Mann–Kendall trend test. Besides, the relative importance of precipitation frequency and intensity in inter-annual variability of wet-day precipitation totals is investigated. Finally, the correlations between precipitation extremes and three potential large-scale and local factors, i.e. ENSO, global mean temperature and local temperature are analysed based on linear regression method. Results reveal that annual wet-day precipitation totals, as well as average wet-day precipitation intensity, have increased significantly, accompanied by a significant increase in the frequency and intensity of precipitation extremes in Singapore. The inter-annual variability of wet-day precipitation totals is mainly dominated by precipitation intensity. Significant correlations are found between precipitation extremes and all the three factors, and the signature of local effects is more evident than global warming. These findings have implications for adaption planning and disaster risk reduction in Singapore in the context of global warming.

Using multi-model ensembles of CMIP5 global climate models to reproduce observed monthly rainfall and temperature with machine learning methods in Australia.

Abstract: NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, New South Wales, Australia School of Computing and Mathematics, Charles Sturt University, Wagga Wagga, New South Wales, Australia Climate Change Research Centre and ARC Centre of Excellence for Climate Extremes, University of New South Wales, Sydney, New South Wales, Australia NSW Office of Environment and Heritage, Department of Planning and Environment, Sydney, New South Wales, Australia NSW Department of Primary Industries, Orange Agricultural Institute, Orange, New South Wales, Australia Faculty of Science, School of Life Sciences, University of Technology Sydney, Sydney, New South Wales, Australia Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, University of Chinese Academy of Sciences, Beijing, China State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling, China

Projected changes in mean rainfall and temperature over East Africa based on CMIP5 models

Abstract: This study presents potential future variations of mean rainfall and temperature over East Africa (EA) based on five models that participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and representative concentration pathways (RCPs): 4.5 and 8.5. In this study, climate simulations of two timeframes, a baseline period (1961–1990) and projection period (2071–2100), are compared. The models reproduce EA's bimodal rainfall pattern but overestimate and underestimate seasonal rainfall of October–December (OND) and March–May (MAM), respectively. Rainfall is projected to increase under the two scenarios. Larger increases in rainfall will occur during the OND season than during the MAM season and in RCP8.5 than in RCP4.5. During the last half of the 21st century, EA is likely to warm by 1.7–2.8 and 2.2–5.4 °C under the RCP4.5 and RCP8.5 scenarios, respectively, relative to the baseline period. Scenario uncertainty is projected to exceed model uncertainty from the middle to the end of the 21st century. The central parts of Kenya and the Lake Victoria Basin will witness the highest increases in seasonal rainfall. The probability density functions (PDFs) of future seasonal rainfall show a positive shift and a statistically insignificant increase in variance relative to the baseline. Thus, EA is likely to experience an increase in extreme rainfall events. Understanding the future climate variability in EA is important for planning purposes but these results are based on relatively course resolution models prone to bias and therefore should be used with caution. There is a need for further research on climate projections over EA, including determining the causes of the poor performance of global models in reproducing rainfall climatology and trends over the region.

Spatiotemporal variation of snow cover over the Tibetan Plateau based on MODIS snow product, 2001–2014

Abstract: In this paper, we investigate the spatiotemporal characteristics and trends of snow cover fraction (SCF) in the Tibetan Plateau (TP) and seven upstream river basins (Yellow, Yangtze, Mekong, Salween, Brahmaputra, Indus and Yarkant) by employing the Moderate Resolution Imaging Spectroradiometer (MODIS) data for 2001–2014. The possible linkage between the SCF, and temperature and precipitation changes over the TP and individual basins is also investigated. Results suggest that the distribution of snow cover over the TP exhibit a large spatiotemporal heterogeneity with high SCFs mainly concentrating on the southern and western edges which is strongly linked to the moist air supplies. The distribution of snow cover is highly dependent on the elevations, with a higher SCF and a later onset of snow melt at the higher elevation zones than at the lowers. There is an elevation threshold existing for separating two distinct snow cover regimes, which are 4000 m for the western basins and 5000 m for the southeastern basins. The snow cover over the TP has slightly decreased by about 1.1% during 2001–2014, with dramatic reductions mostly lying in the heavy snowy regions and some light increases occurring in the areas with annual mean SCFs mostly less than 10%. The reduction rates of snow cover increase with the rising of altitudes for the TP average, and the basins of Indus, Yarkant, Salween and Brahmaputra. At the same time, the Yellow and Yangtze basins exhibit larger increasing rates of snow cover at the higher elevations zones. The SCF variations are linked to the temperature and precipitation changes. Precipitation tends to be the major factor impacting the snow cover changes in the TP during 2001–2014.

The role of regional circulation features in regulating El Niño climate impacts over southern Africa: A comparison of the 2015/2016 drought with previous events

Abstract: Extremely dry conditions were experienced across most of southern Africa during the austral summer (October-March) of 2015/16, associated with one of the strongest observed El Nino events in the Pacific. Dry conditions peaked in the early austral summer months (October-December) producing the most intense drought in the 116 year historical record, as measured by the intensity of the Standardized Precipitation Index across all spatial scales up to the sub-continental. We estimate the return period of this extreme early summer drought to be greater than 200 years. The interior and eastern parts of South Africa were particularly hard-hit with station data showing rainfall totals being at their lowest since at least 1950. The early summer dry conditions make the 2015/16 event atypical compared to past El Nino events of similar magnitude. We find that key regional circulation patterns, influenced by planetary scale processes, play an important role in modulating the spatial and temporal evolution of the summer rainfall during these El Nino events. Specifically, (i) the Angola Low and the South Indian Ocean High, two dominant low level circulation features that drive moisture convergence to support convective precipitation in the region, were anomalously weakened in early austral summer of 2015/16 resulting in less moisture being transported over the continent, and (ii) the mid-level Botswana High was stronger than in previous El Nino years further producing unfavourable conditions for rainfall through stronger subsidence in the mid- to upper levels over southern Africa.

A plausible atmospheric trigger for the 2017 coastal El Niño

Abstract: The far eastern tropical Pacific experienced a rapid, marked warming in early 2017, causing torrential rains along the west coast of South America with a significant societal toll in Peru and Ecuador. This strong coastal El Niño was largely unpredicted, even a few weeks before its onset, and it developed differently from either central or eastern events. Here we provide an overview of the event, its impacts and concomitant atmospheric circulation. It is proposed that a remotely forced, sustained weakening of the free tropospheric westerly flow impinging the subtropical Andes leads to a relaxation of the southeasterly (SE) trades off the coast, which in turn may have warmed the eastern Pacific throughout the weakening of upwelling in a near-coastal band and the lessening of the evaporative cooling farther offshore.

Regional changes of precipitation and temperature over Bangladesh using bias-corrected multi-model ensemble projections considering high-emission pathways

Abstract: A multi-model ensemble provides useful information about the uncertainty of the future changes of climate. High-emission scenarios using representative concentration pathways (RCP8.5) of the Fifth Phase Coupled Model Inter-comparison Project (CMIP5) in the Intergovernmental Panel on Climate Change (IPCC) also aids to capture the possible extremity of the climate change. Using the CMIP5 regional climate modelling predictions, this study analyses the distribution of the temperature and precipitation in Bangladesh in the recent years (1971–2000) and in three future periods (2010–2040, 2041–2070 and 2070–2100) considering RCP8.5 scenarios. Climate changes are expressed in terms of 30-year return values of annual near-surface temperature and 24-h precipitation amounts. At the end of the century, the mean temperature increase over Bangladesh among the 11 RCMs will vary from 5.77 to 3.24 °C. Spatial analysis of the 11 RCMs exhibited that the southwest and the south central parts of Bangladesh will experience a greater temperature rise in the future. Possible changes in rainfall are also exhibited both temporally and spatially. Based on the analysis of all the RCMs, a significant increase of rainfall in the pre- and post-monsoon period is observed. It is also evident that monsoon rainfall will not increase in comparison with pre-monsoon season. Zonal statistics of 64 districts of Bangladesh are also conducted for the 2020s, 2050s and 2080s to find out the most exposed regions in terms of the highest rise in temperature and changes in precipitation.

Assessment of NASA/POWER satellite-based weather system for Brazilian conditions and its impact on sugarcane yield simulation

Abstract: The gridded database provided by National Aeronautics and Space Administration/Prediction of World Wide Energy Resources (NASA/POWER) presents a global coverage of complete weather data at horizontal resolution of 1° latitude–longitude, becoming a potential source for agrometeorological studies. Once Brazil is a country with continental dimensions and the major sugarcane world producer, and its density of ground weather stations suitable for an efficient agricultural planning is sparse, the objectives of this study were to test how robust is the NASA/POWER database through its comparison with the Brazilian ground weather stations network records (INMET) and to quantify the impacts on potential (Yp) and attainable (Yatt) sugarcane yield simulations when setting NASA/POWER as source of input weather data. The comparisons for weather data records and sugarcane yield simulations were carried out from 1997 to 2016. Statistical indices presented a satisfactory performance for average air temperature (R2 = 0.73; d = 0.91), minimum air temperature (R2 = 0.72; d = 0.91), maximum air temperature (R2 = 0.57; d = 0.84), solar radiation (SR) (R2 = 0.71; d = 0.92), sunshine hours (R2 = 0.68; d = 0.90) and reference evapotranspiration, when calculated through Priestley–Taylor (ETo-PT) method (R2 = 0.76; d = 0.93). When the weather variables were aggregated and compared with a 10-day time scale, a strong improvement of statistical indices was obtained. Yp presented root mean square error (RMSE) smaller than 10 t ha−1 while relative mean error (RME) ranged between ±10% for majority of grid cells, with exception for southern Brazil due to low and frost temperatures that satellite cannot capture accurately. Even NASA/POWER offering a relatively coarse grid size database and perhaps some regional data fitting would give better results at higher latitudes and elevation. The results found in this study proved that NASA/POWER products could be used as a source of climatic data for agricultural activities with a reasonable confidence for regional and national spatial scales.

Assessment of climate change trends over the Loess Plateau in China from 1901 to 2100

Abstract: The Loess Plateau (LP) in China is sensitive to climate change because of its fragile ecological environment and geographic features. This study presents a detailed assessment of the climate change trends over the LP from 1901 to 2100 based on the 1-km spatial resolution climate data generated through delta downscaling. The following results are drawn: (1) Delta downscaling performs well in detecting the monthly precipitation and temperature over the LP based on the mean absolute error between downscaled data and independent surface observations. Among the 28 general circulation models, the GFDL-ESM2M and NorESM1-M models show the best performance in reproducing the monthly precipitation and temperature in the future period, respectively. (2) The annual precipitation over the entire LP shows no significant trends in the historical and future periods. By contrast, the annual temperature shows a significantly increasing trend with 0.097 °C/10 year in the historical period (1901–2014) and with 0.113, 0.24, 0.355, and 0.558 °C/10 year in the future period (2015–2100) under the RCP2.6, RCP4.5, RCP6.0, and RCP8.5 scenarios, respectively. (3) The significantly increasing trends in precipitation and temperature at each grid of the LP present various spatial distributions in terms of their magnitude. The significant trend magnitude calculated by the downscaled data has a larger range and a higher percentage of area – and is even observed at a small area – compared with that calculated by the raw data. (4) The spatial results calculated by the downscaled data provide more detailed information about the locations and percentages of area, both of which are valuable in assessing the change trends in precipitation and temperature. These spatio-temporal results present the climate change trends over the LP in detail and provide valuable insights for developing flexible adaptation and mitigation strategies to address the climate change challenges in this region.

Greenland Blocking Index daily series 1851-2015: analysis of changes in extremes and links with North Atlantic and UK climate variability and change

Abstract: We present a homogenised Greenland Blocking Index (GBI) daily record from 1851-2015, therefore significantly extending our previously published monthly/seasonal GBI analysis. This new time series is analysed for evidence of changes in extreme events, and we investigate the underlying thermodynamic and dynamic precursors. We compare occurrences and changes in extreme events between our GBI record and a recently published, temporally similar daily North Atlantic Oscillation (NAO) series, and use this comparison to test dynamic meteorology hypotheses relating negative NAO to Greenland Blocking. We also compare daily GBI changes and extreme events with long-running indices of England and Wales temperature and precipitation, to assess potential downstream effects of Greenland blocking on UK extreme weather events and climate change. In this extended analysis we show that there have been sustained periods of positive GBI during 1870-1900 and from the late 1990s to present. A clustering of extreme high GBI events since 2000 is not consistently reflected by a similar grouping of extreme low NAO events. Case studies of North Atlantic atmospheric circulation changes linked with extreme high and low daily GBI episodes are used to shed light on potential linkages between Greenland blocking and jet-stream changes. Particularly noteworthy is a clustering of extreme high GBI events during mid-October in four out of five years during 2002-2006, which we investigate from both cryospheric and dynamic meteorology perspectives. Supporting evidence suggests that these autumn extreme GBI episodes may have been influenced by regional sea-ice anomalies off west Greenland but were probably largely forced by increases in Rossby-wave train activity originating from the tropical Pacific. However, more generally our results indicate that high GBI winter anomalies are co-located with sea-ice anomalies, 49 while there seems to be minimal influence of sea-ice anomalies on the recent significant increase in summer GBI.

Elevation-dependent effects of climate change on vegetation greenness in the high mountains of southwest China during 1982–2013

Abstract: Effects of climate change on vegetation greenness have attracted considerable attention in the context of global change; however, the dependence of such climatic effects on elevation remains poorly understood. In this study, we examine the relationship between vegetation greenness change and climate change and, in particular, characterize how this relationship changes with elevation in the high mountains of southwest China by using the remotely sensed normalized difference vegetation index (NDVI), and observed temperature and precipitation data sets for the period of 1982–2013. The results show that vegetation exhibited a greening trend (slope: 0.0008 year−1, p 0.05). The vegetation greening and climate warming trends were stronger in the higher elevation plateaus than in the lower elevation mountains. Statistical analysis showed that temperature was the main driving factor on vegetation greening, and the driving effect was elevation-dependent. A substantially more significant correlation between climate warming and vegetation greening was found in the higher elevation plateaus, which reveals a higher temperature sensitivity of these plateaus. In addition, a significant correlation between inter-annual standard deviations of NDVI and precipitation during 1982–2013 was tracked over the entire study area.

Spatio‐temporal variability of daily precipitation concentration in Spain based on a high‐resolution gridded data set

Abstract: An analysis of the spatial and temporal variability of daily precipitation concentration (CI) in Spain was made based on a high‐resolution (5 × 5 km) daily gridded precipitation data set for the 1950–2012 period. For each grid point in the Iberian Peninsula (IP) and Balearic and Canary Islands, the average annual CI was computed, as well as its coefficient of variation and the 5th and 95th percentiles. Annual values were also computed, and the time series of the index were used to assess temporal trends over the whole period. The spatial distribution of the CI showed a strong relationship with the orographic barriers near the coastlines. The Canary Islands showed the highest values of CI, along with the eastern Mediterranean facade of the IP. The highest inter‐annual variations of the CI occurred in the southern IP and in the southern Canary Islands. The trends of CI were, overall, positive and significant, which indicates an increase of daily precipitation concentration over the study period and an increasing environmental risks scenario where erosivity, torrentiality, and floods may become more frequent.

Assessing reliability of precipitation data over the Mekong River Basin: A comparison of ground-based, satellite, and reanalysis datasets

Abstract: Accurate precipitation data are the basis for hydro-climatological studies. As a highly populated river basin, with the biggest inland fishery in Southeast Asia, freshwater dynamics is extremely important for the Mekong River Basin (MB). This study focuses on evaluating the reliability of existing gridded precipitation datasets both from satellite and reanalysis, with a ground observations-based gridded precipitation dataset as the reference. Two satellite products (Tropical Rainfall Measuring Mission [TRMM] and the Precipitation Estimation from Remote Sensing Information using an Artificial Neural NetworkClimate Data Record [PERSIANN-CDR]), as well as three reanalysis products (Modern-Era Retrospective analysis for Research and Applications [MERRA2], the European Centre for Medium-Range Weather Forecasts interim reanalysis [ERA-Interim], and the Climate Forecast System Reanalysis [CFSR]) were compared with the Asian PrecipitationHighly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) over the MB. The APHRODITE was chosen as the reference for the comparison because it was developed based on ground observations and has also been selected as reference data in previous studies. Results show that most of the assessed datasets are able to capture the major climatological characteristics of precipitation in the MB for the 10-year study period (1998-2007). Generally, both satellite data (TRMM and PERSIANN-CDR) show higher reliability than reanalysis products at both spatial and temporal scales across the MB, with the TRMM outperforming when compared to the PERSIANN-CDR. For the reanalysis products, MERRA2 is more reliable in terms of temporal variability, but with some underestimation of precipitation. The other two reanalysis products CFSR and ERA-Interim are relatively unreliable due to large overestimations. CFSR is better positioned to capture the spatial variability of precipitation, while ERA-Interim shows inconsistent spatial patterns but more realistically resembles the daily precipitation probability. These findings have practical implications for future hydro-climatological studies.