Wet Spells Research Articles

Vulnerability of Ecological Condition to the Sequencing of Wet and Dry Spells Prior to and during the Murray-Darling Basin Millennium Drought

AbstractDroughts are a significant stressor for water supply systems and freshwater ecosystems. Studies on drought risks and impacts have focused on the frequency, duration, and severity of drought...

Trends in Precipitation and Temperatures in Eastern Slovakia (1962–2014)

In this paper, the results of trend analysis applied to precipitation and temperature monthly data for the period from 1962 to 2014 is presented for the hydrological year (from November to October) in sixteen climatic stations in Eastern Slovakia. The topography of this part of the country is very diverse and it affects the climate. The Mann-Kendall non-parametric test coupled with Sen’s slope was applied to identify the significant long-term climatic trends, as well as the magnitude of those trends. According to the present study, all climatic stations in Eastern Slovakia show a positive trend in temperature during the year and almost all of them show a significant positive annual trend in temperature. Seasonal and monthly trend analyses produced the same results. Trends in temperature are always positive during winter and spring. Trends in precipitation are also mostly positive during winter and spring, although some negative trends were also found during these seasons. The spatial distribution of precipitation and temperature trends was modelled in ArcGIS using geostatistical analysis. Abrupt positive trend shifts in annual precipitation and temperature time series were also investigated. An abrupt shift in precipitation at the highest climatic station, Lomnický peak, began around 1985 (+). Abrupt shifts in temperature began around 1970 (+) at the presented climatic stations. The extremity of the climate is confirmed by an analysis of the trends in wet and dry spells. Trends showed increasing tendencies in medium- and long-term wet spells.

Changes in climate extremes over West and Central Africa at 1.5 °C and 2 °C global warming

In this study, we investigate changes in temperature and precipitation extremes over West and Central Africa (hereafter, WAF domain) as a function of global mean temperature with a focus on the implications of global warming of 1.5 °C and 2 °C according the Paris Agreement. We applied a scaling approach to capture changes in climate extremes with increase in global mean temperature in several subregions within the WAF domain: Western Sahel, Central Sahel, Eastern Sahel, Guinea Coast and Central Africa including Congo Basin.While there are several uncertainties and large ensemble spread in the projections of temperature and precipitation indices, most models show high-impact changes in climate extremes at subregional scale. At these smaller scales, temperature increases within the WAF domain are projected to be higher than the global mean temperature increase (at 1.5 °C and at 2 °C) and heat waves are expected to be more frequent and of longer duration. The most intense warming is observed over the drier regions of the Sahel, in the central Sahel and particularly in the eastern Sahel, where the precipitation and the soil moisture anomalies have the highest probability of projected increase at a global warming of 1.5 °C. Over the wetter regions of the Guinea Coast and Central Africa, models project a weak change in total precipitation and a decrease of the length of wet spells, while these two regions have the highest increase of heavy rainfall in the WAF domain at a global warming of 1.5 °C. Western Sahel is projected by 80% of the models to experience the strongest drying with a significant increase in the length of dry spells and a decrease in the standardized precipitation evapotranspiration index. This study suggests that the ‘dry gets drier, wet gets wetter’ paradigm is not valid within the WAF domain.

Projected climate over the Greater Horn of Africa under 1.5 °C and 2 °C global warming

We analyze the potential effect of global warming levels (GWLs) of 1.5 °C and 2 °C above pre-industrial levels (1861−1890) on mean temperature and precipitation as well as intra-seasonal precipitation extremes over the Greater Horn of Africa. We used a large, 25-member regional climate model ensemble from the Coordinated Regional Downscaling Experiment and show that, compared to the control period of 1971−2000, annual mean near-surface temperature is projected to increase by more than 1 °C and 1.5 °C over most parts of the Greater Horn of Africa, under GWLs of 1.5 °C and 2 °C respectively. The highest temperature increases are projected in the northern region, covering most parts of Sudan and northern parts of Ethiopia, and the lowest temperature increases are projected over the coastal belt of Tanzania. However, the projected mean surface temperature difference between 2 °C and 1. 5 °C GWLs is higher than 0.5 °C over nearly all land points, reaching 0.8 °C over Sudan and northern Ethiopia. This implies that the Greater Horn of Africa will warm faster than the global mean.While projected changes in precipitation are mostly uncertain across the Greater Horn of Africa, there is a substantial decrease over the central and northern parts of Ethiopia. Additionally, the length of dry and wet spells is projected to increase and decrease respectively. The combined effect of a reduction in rainfall and the changes in the wet and dry spells will likely impact negatively on the livelihoods of people within the coastal cities, lake regions, highlands as well as arid and semi-arid lands of Kenya, Tanzania, Somalia, Ethiopia and Sudan. The probable impacts of these changes on key sectors such as agriculture, water, energy and health sectors, will likely call for formulation of actionable policies geared towards adaptation and mitigation of the impacts of 1.5 °C and 2 °C warming.

A 17-year Record of Meteorological Observations Across the Gran Campo Nevado Ice Cap in Southern Patagonia, Chile, Related to Synoptic Weather Types and Climate Modes

The network of long-term meteorological observations in Southernmost Patagonia is still sparse but crucial to improve our understanding of climatic variability, in particular in the more elevated and partially glaciated Southernmost Andes. Here we present a unique 17-year meteorological record (2000-2016) of four automatic weather stations across the Gran Campo Nevado Ice Cap (53$^{\circ}$S) in the Southernmost Andes (Chile) and the conventional weather station Jorge Schythe of the Instituto de la Patagonia in Punta Arenas for comparison. We revisit the relationship between in-situ observations and large-scale climate models as well as mesoscale weather patterns. For this purpose, a 37-year record of ERA Interim Reanalysis data has been used to compute a weather type classification based on a hierarchical correlation-based leader algorithm. The orographic perturbation on the predominantly westerly airflow determines the hydroclimatic response across the mountain range, leading to significant west-east gradients of precipitation, air temperature and humidity. Annual precipitation sums heavily drop within only tens of kilometers from \textasciitilde 7500 mm\,a$^{-1}$ to less than 800 mm\,a$^{-1}$. The occurrence of high precipitation events of up to 620 mm in 5 days and wet spells of up to 61 consecutive days underscore the year-around wet conditions in the Southernmost Andes. Given the strong link between large-scale circulation and orographically controlled precipitation, the synoptic-scale weather conditions largely determine the precipitation and temperature variability on all time scales. Major synoptic weather types with distinct low-pressure cells in the Weddell Sea or Bellingshausen Sea, causing a prevailing southwesterly, northwesterly or westerly airflow, determine the weather conditions in Southernmost Patagonia during 68$\%$ of the year. At Gran Campo Nevado, more than 80$\%$ of extreme precipitation events occur during the persistence of these weather types. The evolution of the El Ni\~{n}o Southern Oscillation and Antarctic Oscillation impose intra- and inter-annual precipitation and temperature variations. Positive Antarctic Oscillation phases on average are linked to an intensified westerly airflow and warmer conditions in Southernmost Patagonia. Circulation patterns with high-pressure influence leading to colder and dryer conditions in Southernmost Patagonia are more frequent during negative Antarctic Oscillation phases.

Coupling Poisson rectangular pulse and multiplicative microcanonical random cascade models to generate sub-daily precipitation timeseries

To simulate the impacts of within-storm rainfall variabilities on fast hydrological processes, long precipitation time series with high temporal resolution are required. Due to limited availability of observed data such time series are typically obtained from stochastic models. However, most existing rainfall models are limited in their ability to conserve rainfall event statistics which are relevant for hydrological processes. Poisson rectangular pulse models are widely applied to generate long time series of alternating precipitation events durations and mean intensities as well as interstorm period durations. Multiplicative microcanonical random cascade (MRC) models are used to disaggregate precipitation time series from coarse to fine temporal resolution.To overcome the inconsistencies between the temporal structure of the Poisson rectangular pulse model and the MRC model, we developed a new coupling approach by introducing two modifications to the MRC model. These modifications comprise (a) a modified cascade model (“constrained cascade”) which preserves the event durations generated by the Poisson rectangular model by constraining the first and last interval of a precipitation event to contain precipitation and (b) continuous sigmoid functions of the multiplicative weights to consider the scale-dependency in the disaggregation of precipitation events of different durations.The constrained cascade model was evaluated in its ability to disaggregate observed precipitation events in comparison to existing MRC models. For that, we used a 20-year record of hourly precipitation at six stations across Germany. The constrained cascade model showed a pronounced better agreement with the observed data in terms of both the temporal pattern of the precipitation time series (e.g. the dry and wet spell durations and autocorrelations) and event characteristics (e.g. intra-event intermittency and intensity fluctuation within events). The constrained cascade model also slightly outperformed the other MRC models with respect to the intensity-frequency relationship.To assess the performance of the coupled Poisson rectangular pulse and constrained cascade model, precipitation events were stochastically generated by the Poisson rectangular pulse model and then disaggregated by the constrained cascade model. We found that the coupled model performs satisfactorily in terms of the temporal pattern of the precipitation time series, event characteristics and the intensity-frequency relationship.

Perturbations in the initial soil moisture conditions: Impacts on hydrologic simulation in a large river basin

Real time hydrologic forecasting requires near accurate initial condition of soil moisture; however, continuous monitoring of soil moisture is not operational in many regions, such as, in Ganga basin, extended in Nepal, India and Bangladesh. Here, we examine the impacts of perturbation/error in the initial soil moisture conditions on simulated soil moisture and streamflow in Ganga basin and its propagation, during the summer monsoon season (June to September). This provides information regarding the required minimum duration of model simulation for attaining the model stability. We use the Variable Infiltration Capacity model for hydrological simulations after validation. Multiple hydrologic simulations are performed, each of 21 days, initialized on every 5th day of the monsoon season for deficit, surplus and normal monsoon years. Each of these simulations is performed with the initial soil moisture condition obtained from long term runs along with positive and negative perturbations. The time required for the convergence of initial errors is obtained for all the cases. We find a quick convergence for the year with high rainfall as well as for the wet spells within a season. We further find high spatial variations in the time required for convergence; the region with high precipitation such as Lower Ganga basin attains convergence at a faster rate. Furthermore, deeper soil layers need more time for convergence. Our analysis is the first attempt on understanding the sensitivity of hydrological simulations of Ganga basin on initial soil moisture conditions. The results obtained here may be useful in understanding the spin-up requirements for operational hydrologic forecasts.

Runoff sensitivity to climate change in the Nile River Basin

In data scarce basins, such as the Nile River Basin (NRB) in Africa, constraints related to data availability, quality, and access often complicate attempts to estimate runoff sensitivity using conventional methods. In this paper, we show that by integrating the concept of the aridity index (AI) (derived from the Budyko curve) and climate elasticity, we can obtain the first order response of the runoff sensitivity using minimal data input and modeling expertise or experience. The concept of runoff elasticity relies on the fact that the energy available for evapotranspiration plays a major role in determining whether the precipitation received within a drainage basin generates runoff. The approach does not account for human impacts on runoff modification and or diversions. By making use of freely available gauge-corrected satellite data for precipitation, temperature, runoff, and potential evapotranspiration, we derived the sensitivity indicator (β) to determine the runoff response to changes in precipitation and temperature for four climatic zones in the NRB, namely, tropical, subtropical, semiarid and arid zones. The proposed sensitivity indicator can be partitioned into different elasticity components i.e: precipitation (εp), potential evapotranspiration (εETp), temperature (εT) and the total elasticity (εtot). These elasticities allow robust quantification of the runoff response to the potential changes in precipitation and temperature with a high degree of accuracy. Results indicate that the tropical zone is energy-constrained with low sensitivity, (β<1.0), implying that input precipitation exceeds the amounts that can be evaporated given the available energy. The subtropical zone is subdivided into two distinct regions, the lowland (Machar and Sudd marshes), and the highland area (Blue Nile Basin), where each area has a unique sensitivity. The lowland area has high sensitivity, (β>1.0). The subtropical-highland zone moves between energy-limited to water-limited conditions during periods of wet and dry spells with varying sensitivity. The semiarid and arid zones are water limited, with high sensitivity, (β>1.0). The calculated runoff elasticities show that a 10% decrease in precipitation leads to a decrease in runoff of between 19% in the tropical zone and 30% in the arid zones. On the other hand, a 10% precipitation increase leads to a runoff increase of 14% in the tropical zone and 22% in the arid zone. The estimated runoff changes are consistent with the result obtained using other methods. Thus, the elasticity approach combines data parsimony and analytical simplicity to produce results that are practically useful for most purposes while facilitating communication with stakeholders with different levels of scientific knowledge. More research is needed to extend the application of the method to incorporate the effects of human activities, and land use change.

Differences in CAPE between wet and dry spells of the monsoon over the southeastern peninsular India

In the present research we explored the variability of convective available potential energy (CAPE) during wet and dry spells over southeast India. Comparison between India Meteorological Department (IMD) observations and reanalysis products (NCEP, ERA-interim, and MERRA) reconfirms that gridded data sets can be utilized to fill the void of observations. Later, GPS radiosonde measurements made at Gadanki (13.5 N, 79.2 E) Andre analysis output are utilized to address key scientific issues related to CAPE over the southeastern peninsular region. They are: (1) How does CAPE vary between different spells of the Indian summer monsoon (i.e., from wet to dry spell)? (2) Does differences in CAPE and in the vertical structure of buoyancy between spells are localized features over Gadanki or observed all over southeastern peninsular region? (3) What physical/dynamical processes are responsible for the differences in CAPE between spells and how do they affect the convection growth in dry spell? Interestingly, CAPE is higher in wet spell than in dry spell, in contrast to the observations made elsewhere over land and warm oceans. Similar feature (high CAPE in wet spell) is observed at all grid points in the southeastern peninsular India. Furthermore, vertical buoyancy profiles show only one peak in the middle–upper troposphere in wet spell, while two peaks are observed in most of the profiles (66%) in dry spell over the entire study region in all the reanalysis products. Plausible mechanisms are discussed for the observed CAPE differences. They are, among others, timing of sounding with reference to rain occurrence, rapid buildup of surface instabilities, moistening of lower troposphere by evaporation of the surface moisture in wet spell, enhanced low-level moisture convergence, evaporation of rain in relatively warm and dry atmosphere, and reduction of positive buoyancy in dry spell. The omnipresence of stable layers and strong and deep shear in the presence of weak updrafts (buoyancy) limits the growth of convective draft cores in dry spell.

Changes in duration of dry and wet spells associated with air temperatures in Russia

This study uses daily precipitation records from 517 Russian stations (1966–2010) to examine the relationships between continuous dry and wet day duration and surface air temperature for all four seasons. The study found that both mean and extreme durations of dry periods increase with air temperature at about 7.0% (0.24 day/°C) and 7.7% (0.86 day/°C) respectively, while those of wet periods decrease at about 1.3% (−0.02 day/°C) and 2.2% (−0.10 day/°C) respectively averaged over the entire study region during summer. An increase in the duration of dry periods with higher air temperature is also found in other seasons at locations with a mean seasonal air temperature of about −5 °C or higher. Opposite relationships of shorter durations of dry periods and longer wet periods associated with higher air temperature are observed over the northern part of the study region in winter. The changes in durations of both dry and wet periods have significant correlations with the changes in total dry and wet days but are about 2.5 times higher for dry periods and 0.5 times lower for wet periods. The study also found that locations with longer durations of dry periods experience faster rates of increase in air temperature, suggesting the likelihood of exacerbating drought severity in drier and/or warmer locations for all seasons.

Variations in droughts and wet spells and their influences in China: 1924–2013

The Wetness Index was calculated using gridded monthly precipitation and potential evapotranspiration in China during 1924–2013. Variations of dry and wet periods in different areas and the impact of meteorological factors were analyzed. The results show the following: (1) Drought areas (W ≤ 0.5) and wet areas (W > 0.65) in China constituted 33–56% and 35–55%, respectively, of the total land area and there were no secular trends during 1924–2013. During this period, the areas of drought and wet were inversely proportional, but had different changes among seven regions. (2) Since 1954, the overall trend in China has changed from wet to dry. Drought areas increased significantly (p < 0.05) during 1954–1983. Drought areas increased (not significantly) during 1984–2013, but the rate of drought/wetness clearly decreased (tendency rates were between − 0.05 and 0.05/30 year, and accounted for 54.79% of China). (3) Dry/wet variation in North, Northeast, Central, and Southwest China played major roles. (4) Except in the North region, drought/wet conditions were affected by surface warming.

Three resampling approaches based on method of fragments for daily‐to‐subdaily precipitation disaggregation

ABSTRACTPrecipitation data of finer timescale and higher spatial density are crucial for continuous hydrological modelling and flood risk assessment. Disaggregation methods are often used to transform the coarser‐timescale precipitation data into finer resolutions. The nonparametric approach based on method of fragments (MOF) has received broad attention in precipitation disaggregation literature, given its superiority in reproducing the at‐site statistical attributes. However, a detailed literature review has shown that the MOF‐based resampling approaches are mainly focused in the single‐site precipitation disaggregation context, which may subject to limitations such as the unavailability of at‐site precipitation records and the incapability to preserve the inter‐site correlation structure. To address these issues, we propose three resampling approaches based on MOF. The first approach is a single‐site interval‐based resampling approach which only draws subdaily fragment vectors from at‐site record. The second one extends the first one to a regionalized version where subdaily fragment vectors are drawn from both the at‐site and neighbouring stations. The third one is a multi‐site approach developed to preserve the observed inter‐site correlation. The performances of the three methods are evaluated with applications to daily‐to‐hourly precipitation disaggregation at six rain gauges in Singapore and eight precipitation stations in Wangkuai reservoir catchment in northern China. An elaborate list of performance measures, including standard validation statistics, spatial correlation, inter‐day connectivity, annual extreme analysis, and intra‐day dry and wet spell characteristics are used to assess the performance. The proposed three methods are shown to be effective in reproducing the at‐site attributes, and no significant deterioration of performance is observed when moving from the single‐site method to the regionalized and multi‐site versions. As expected, the multi‐site approach is the only one method that is able to reconstruct the spatial correlation in the disaggregated precipitation field. The approaches can be applied for daily‐to‐subdaily precipitation disaggregation in different regions.

Extreme Rainfall in the Eastern Region of Peninsular Malaysia

Modeling of daily rainfall data, particularly rainfall amount, is important not only for hydrological purposes but also for providing input for models of crop growth, design of urban drainage systems, land management systems and other environmental projects. This study tests the performance of Gamma and Weibull that are incorporated in the weather generator in simulating extreme rainfall and extreme dry/wet spell lengths for the eastern region of Peninsular Malaysia. Next, the monthly rainfall and the extreme rainfall are simulated using the best distribution. A weather generator known as Advanced Weather Generator (AWE-GEN) is chosen to model hourly rainfall time series in the eastern region of Peninsular Malaysia. Previously, Gamma distribution is incorporated in AWE-GEN to represent the rainfall intensity. This study proposes Weibull distribution and the performances between Gamma and Weibull distributions in generating rainfall series are compared based on Root Mean Square (RMSE) value error. Minimum RMSE value indicates the best distribution for eastern region. Results have shown that Gamma is the best distribution in simulating hourly rainfall in the east coast as compared to Weibull despite not being able to capture the peak/extreme values at several stations in the east coast of Peninsular Malaysia. The extreme wet spell length is well simulated although the extreme dry spell is under-estimated at all stations. Rainfall in November is contributing most of the annual rainfall followed by December. This study is relevant and very crucial for a tropical country like Malaysia which will benefit the policy makers in executing the strategic management of flooding in urban areas that is predominantly caused by convective activities.

Development and evaluation of a stochastic daily rainfall model with long-term variability

Abstract. The primary objective of this study is to develop a stochastic rainfall generation model that can match not only the short resolution (daily) variability but also the longer resolution (monthly to multiyear) variability of observed rainfall. This study has developed a Markov chain (MC) model, which uses a two-state MC process with two parameters (wet-to-wet and dry-to-dry transition probabilities) to simulate rainfall occurrence and a gamma distribution with two parameters (mean and standard deviation of wet day rainfall) to simulate wet day rainfall depths. Starting with the traditional MC-gamma model with deterministic parameters, this study has developed and assessed four other variants of the MC-gamma model with different parameterisations. The key finding is that if the parameters of the gamma distribution are randomly sampled each year from fitted distributions rather than fixed parameters with time, the variability of rainfall depths at both short and longer temporal resolutions can be preserved, while the variability of wet periods (i.e. number of wet days and mean length of wet spell) can be preserved by decadally varied MC parameters. This is a straightforward enhancement to the traditional simplest MC model and is both objective and parsimonious.

Spatiotemporal trends in extreme rainfall and temperature indices over Upper Tapi Basin, India

The flood risk across the globe is intensified due to global warming and subsequent increase in extreme temperature and precipitation. The long-term trends in extreme rainfall (1944–2013) and temperature (1969–2012) indices have been investigated at annual, seasonal, and monthly time scales using nonparametric Mann-Kendall (MK), modified Mann-Kendall (MMK), and Sen’s slope estimator tests. The extreme rainfall and temperature indices, recommended by the Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI), have been analyzed at finer spatial scales for trend detection. The results of trend analyses indicate decreasing trend in annual total rainfall, significant decreasing trend in rainy days, and increasing trend in rainfall intensity over the basin. The seasonal rainfall has been found to decrease for all the seasons except postmonsoon, which could affect the rain-fed agriculture in the basin. The 1- and 5-day annual maximum rainfalls exhibit mixed trends, wherein part of the basin experiences increasing trend, while other parts experience a decreasing trend. The increase in dry spells and concurrent decrease in wet spells are also observed over the basin. The extreme temperature indices revealed increasing trends in hottest and coldest days, while decreasing trends in coldest night are found over most parts of the basin. Further, the diurnal temperature range is also found to increase due to warming tendency in maximum temperature (T max) at a faster rate compared to the minimum temperature (T min). The increase in frequency and magnitude of extreme rainfall in the basin has been attributed to the increasing trend in maximum and minimum temperatures, reducing forest cover, rapid pace of urbanization, increase in human population, and thereby increase in the aerosol content in the atmosphere. The findings of the present study would significantly help in sustainable water resource planning, better decision-making for policy framework, and setting up infrastructure against flood disasters in Upper Tapi Basin, India.

Classification of precipitation regimes in Pakistan using wet and dry spells

ABSTRACTWet (dry) spells can cause extreme climatic conditions, such as floods (droughts) which can adversely influence the natural resources. A spatio‐temporal analysis of observed wet and dry spells is carried out for vulnerable and data sparse region of Pakistan (24°–38°N and 61°–78°E). Observed monthly precipitation data sets from 46 weather station are used for a length of consecutive 32 years (1976−2007). Additionally, after bias adjustment, the Asian Precipitation Highly‐Resolved Observational Data Integration Towards Evaluation (APHRODITE) precipitation data set, abbreviated as APH, is utilized to corroborate the findings. For both data sets, a threshold of 1 mm is used to define a wet spell. Decadal variability of precipitation for observed and APH data sets indicates that there is gradual decrease in wet spell length for arid and humid regimes, as compared to semi‐arid regimes where there is no change in wet spell length. Monthly dry and wet slope difference (SD), on a log–log plot between number of spells and spell length, is used to classify precipitation regimes in Pakistan, for the first time. A weather station is categorized as humid if SD is less than −2.38 in units of number of spells per length of spells. If SD lies between −2.37 and −0.51, then the weather station is classified as semi‐arid and if SD is greater than −0.51, then it is classified as arid. Thus, according to SD classification, 66% of area in Pakistan is arid, whereas 30% (4%) is semi‐arid (humid). Comparison of precipitation regimes based upon observed and APH data sets with other climate classification schemes that involve both precipitation and temperature is presented.

Changes in temporal inequality and persistence of precipitation over China during the period 1961–2013

Abstract The spatial-temporal variability of precipitation is closely related to the occurrence of drought/flood, which thus merits close study. Here we examine the temporal inequality and persistence of precipitation over China from 1961 to 2013, through the use of Gini coefficient, Lorenz asymmetry coefficient and parameters (P00 and P11) of first-order Markov chain. The Mann-Kendall test was also applied to assess the changes in all indices used. The results showed that the temporal inequality of daily precipitation increased, associated with decreased wet days and increased heavy precipitation events, during the past century in most parts of China. The dry spell overall increased while wet spell declined during the period 1961–2013, which implied that the risks of both drought and flood would enhance over China in the future. However, the changes in temporal inequality and persistence of precipitation varied among sub-regions and basins, for example, extreme precipitation decreased in Songhua River basin and Pearl River basin but increased in other basins. The results obtained in this study would be helpful for understanding the spatial-temporal changes of precipitation (and thus drought and flood disasters) and for developing reasonable strategies for water resources management over China under the changing climate.

Evaluation of Gridded Precipitation Data Products for Hydrological Applications in Complex Topography

Accurate spatial and temporal representation of precipitation is of utmost importance for hydrological applications. Uncertainties in available data sets increase with spatial resolution due to small-scale processes over complex terrain. As previous studies revealed high regional differences in the performance of gridded precipitation data sets, it is important to assess the related uncertainties at the catchment scale, where these data sets are typically applied, e.g., for hydrological modeling. In this study, the uncertainty of eight gridded precipitation data sets from various sources is investigated over an alpine catchment. A high resolution reference data set is constructed from station data and applied to quantify the contribution of spatial resolution to the overall uncertainty. While the results demonstrate that the data sets reasonably capture inter-annual variability, they show large seasonal differences. These increase for daily indicators assessing dry and wet spells as well as heavy precipitation. Although the higher resolution data sets, independent of their source, show a better agreement, the coarser data sets showed great potential especially in the representation of the overall climatology. To bridge the gaps in data scarce areas and to overcome the issues with observational data sets (e.g., undercatch and station density) it is important to include a variety of data sets and select an ensemble for a robust representation of catchment precipitation. However, the study highlights the importance of a thorough assessment and a careful selection of the data sets, which should be tailored to the desired application.

Rainfall analysis in the northern region of Peninsular Malaysia

Modeling of rainfall is important for assessing the possible impacts of climate change. To achieve accurate projections of rainfall events, availability of sufficient hydrological station data is critical. Precipitation is one of the most important meteorological variables for hydrological modeling. In cases where long series of observed precipitation are not available, they can be stochastically generated by weather generators. Advanced Weather Generator (AWE-GEN) has been proven to generate precipitation data at the temperate climate regions with Gamma distribution being incorporated in the model to represent rainfall intensity. However, in a tropical climate such as Malaysia, some studies disputed the incorporation of Gamma distribution. As such, in this study, Weibull a heavy tail distribution is proposed to be used. The AWE-GEN has well performed in the wetter region such as the eastern of the peninsular. However, rainfall distribution within Peninsular Malaysia is highly variable temporally and spatially. The northern region is drier especially during the southwest monsoon season. This region receives minimal rain during the northeast monsoon due to the presence of the Titiwangsa Range which obstructs the region from getting rain by the north easterly winds. Therefore, the objectives of the study are two-fold. First, this study compares the performance of Gamma and Weibull that are incorporated in the AWE-GEN in simulating rainfall series for the northern region of the peninsular. Second, the monthly rainfall and the extreme rainfall series are simulated using the better distribution. The performances of Gamma and Weibull distributions are compared using the goodness of fit test, Root Mean Square Error (RMSE). Results showed that Gamma is the better distribution in simulating rainfall at rainfall stations located at the outer parts of the northern coast whereas Weibull is the better distribution for stations located in the interior parts of the northern coast. Hourly and daily extreme rainfalls seem to be well captured at all stations. Similarly, wet spell length is well simulated while in contrast, dry spell length is slightly underestimated at all stations. Overall, Gamma and Weibull produce commendable results in simulating extreme rainfall as well as wet spell length throughout the northern region of the peninsular. (c) 2017 The Authors. Published by IASE.

Cascade Rainfall Disaggregation Application in U.S. Central Plains

Long-term observations of daily rainfall are common and routinely available for a variety of hydrologic applications. In contrast, observations of 10 or more years of continuous hourly rainfall are rare. Yet, sub-daily rainfall data are required in rainfall-runoff models. Rainfall disaggregation can generate sub-daily time-series from available long term daily observations. Herein, the performance of Multiplicative Random Cascade (MRC) model at disaggregating daily-to-hourly rainfall was investigated. The MRC model was parameterized and validated with 15 years of continuous observed daily and hourly rainfall data at three weather stations in Oklahoma. Model performance, or degree to which the disaggregated rainfall time series replicated observations, was assessed using 46 variables of hourly rainfall characteristics, such as longest wet spell duration, average number of rainfall hours per year, and largest hourly rainfall. Findings include: a) average-type hourly rainfall characteristics were better replicated than single value characteristics such as longest, maximum, or peak hourly rainfall; b) the large number of sub-trace hourly rainfall values (&lt;0.254 mm h-1) generated by the MRC model were not supported by observations; c) the random component of the MRC model led to a variation under 15% of the average value for most rainfall characteristics with the exceptions of the “longest wet spell duration” and “maximum hourly rainfall”; and d) the MRC model produced fewer persistent rainfall events compared to those in the observed rainfall record. The large number of generated trace rainfall values and difficulties to replicate reliably extreme rainfall characteristics, reduces the number of potential hydrologic applications that could take advantage of the MRC disaggregated hourly rainfall. Nevertheless, in most cases, the disaggregated rainfall generated by the MRC model replicated observed average-type rainfall characteristics well.