High Precipitation Events Research Articles

Statistical Postprocessing of High-Resolution Regional Climate Model Output

Abstract Statistical postprocessing techniques have become essential tools for downscaling large-scale information to the point scale, and also for providing a better probabilistic characterization of hydrometeorological variables in simulation and forecasting applications at both short and long time scales. In this paper, the authors assess the utility of statistical postprocessing methods for generating probabilistic estimates of daily precipitation totals, using deterministic high-resolution outputs obtained with the Weather Research and Forecasting (WRF) Model. After a preliminary assessment of WRF simulations over a historical period, the performance of three postprocessing techniques is compared: multinomial logistic regression (MnLR), quantile regression (QR), and Bayesian model averaging (BMA)—all of which use WRF outputs as potential predictors. Results demonstrate that the WRF Model has skill in reproducing observed precipitation events, especially during fall/winter. Furthermore, it is shown that the spatial distribution of skill obtained from statistical postprocessing is closely linked with the quality of WRF precipitation outputs. A detailed comparison of statistical precipitation postprocessing approaches reveals that, although the poorest performance was obtained using MnLR, there is not an overall best technique. While QR should be preferred if skill (i.e., small probability forecast errors) and reliability (i.e., match between forecast probabilities and observed frequencies) are target properties, BMA is recommended in cases when discrimination (i.e., prediction of occurrence versus nonoccurrence) and statistical consistency (i.e., equiprobability of the observations within their ensemble distributions) are desired. Based on the results obtained here, the authors believe that future research should explore frameworks reconciling hierarchical Bayesian models with the use of the extreme value theory for high precipitation events.

Dynamical contribution of mean potential vorticity pseudo-observations derived from MetOp/GOME2 ozone data into short-range weather forecast during high precipitation events

Satellites are uniquely capable of providing uniform data coverage globally. Motivated by such capability, this study builds on a previously described methodology that generates numerical weather prediction initial conditions from satellite total column ozone data. The methodology is based on two principal steps. Firstly, the studied linear regression between vertical (100hPa-500hPa) Mean Potential Vorticity (MPV) and MetOp/GOME2 total ozone data (O3) generates MPV pseudo-observations. Secondly, the 3D variational (3D-Var) assimilation method is designed to take into account MPV pseudo-observations in addition to conventional observations.After a successful assimilation of MPV pseudo-observations using a 3D-Var approach within the Moroccan version of the ALADIN limited-area model, the present study aims to assess the dynamical behavior of the short-range forecast at upper levels during heavy precipitation events (HPEs). It is found that MPV assimilation offers the possibility to internally monitor the model upper-level dynamics in addition to the use of Water Vapor Satellite images.

Recharge estimation and soil moisture dynamics in a Mediterranean, semi-arid karst region

Abstract. Knowledge of soil moisture dynamics in the unsaturated soil zone provides valuable information on the temporal and spatial variability of groundwater recharge. This is especially true for the Mediterranean region, where a substantial fraction of long-term groundwater recharge is expected to occur during high magnitude precipitation events of above-average wet winters. To elucidate process understanding of infiltration processes during these extreme events, a monitoring network of precipitation gauges, meteorological stations, and soil moisture plots was installed in an area with a steep climatic gradient in the Jordan Valley region. In three soil moisture plots, Hydrus-1D was used to simulate water movement in the unsaturated soil zone with soil hydraulic parameters estimated by the Shuffled Complex Evolution Metropolis algorithm. To generalize our results, we modified soil depth and rainfall input to simulate the effect of the pronounced climatic gradient and soil depth variability on percolation fluxes and applied the calibrated model to a time series with 62 years of meteorological data. Soil moisture measurements showed a pronounced seasonality and suggested rapid infiltration during heavy rainstorms. Hydrus-1D successfully simulated short and long-term soil moisture patterns, with the majority of simulated deep percolation occurring during a few intensive rainfall events. Temperature drops in a nearby groundwater well were observed synchronously with simulated percolation pulses, indicating rapid groundwater recharge mechanisms. The 62-year model run yielded annual percolation fluxes of up to 66% of precipitation depths during wet years and of 0% during dry years. Furthermore, a dependence of recharge on the temporal rainfall distribution could be shown. Strong correlations between depth of recharge and soil depth were also observed.

Projections of climate change in the Mediterranean Basin by using downscaled global climate model outputs

AbstractThe Mediterranean Basin is one of the regions that shall be affected most by the impacts of the future climate changes on hydrology and water resources. In this study, projected future changes in mean air temperature and precipitation climatology and inter‐annual variability over the Mediterranean region were studied. For performing this aim, the future changes in annual and seasonal averages for the future period of 2070–2100 with respect to the period from 1970 to 2000 were investigated. Global climate model outputs of the World Climate Research Program's Coupled Model Intercomparison Project Phase 3 multi‐model dataset were used in this work. Intergovernmental Panel on Climate Change SRES A2, A1B and B1 emission scenarios' outputs were used in future climate model projections. Future surface mean air temperatures of the larger Mediterranean basin increase mostly in summer and least in winter, and precipitation amounts decrease in all seasons at almost all parts of the basin. Future climate signals for air temperature and total precipitation values are much larger than the inter‐model standard deviation. Inter‐annual temperature variability increases evidently in summer season and decreases in the northern part of the domain in the winter season, while precipitation variability increases in almost all parts of domain. Probability distribution functions are found to be shifted and flattened for future period compared to the reference period. This indicates that the occurrence of frequency and intensity of high temperatures and heavy precipitation events will likely increase in the future period.

Monthly Maximum Accumulated Precipitation Forecasting Using Local Precipitation Data and Global Climate Modes

Successive days of precipitation are known to cause flooding in monsoon-susceptible countries. Forecasting of daily precipitation facilitates the prediction of the occurrences of rainfall and number of wet days. Using the maximum five-day accumulated precipitation (MX5d), we can predict the magnitude of precipitation in a specific period as it may indicate the extreme precipitation. In this study, a method to forecast monthly extreme precipitation using artificial neural networks (ANNs) is assessed using past MX5d data and global climate indices such as Southern Oscillation Index (SOI), Madden Julian Oscillation (MJO), and Dipole Mode Index (DMI) in Kuantan and Kota Bharu, Malaysia. The use of combined inputs (MX5d with SOI, MJO, and DMI) is proposed to investigate the concurrent effect of lagged values of local precipitation data and global climate indices on seasonal extreme precipitation. Four cases of data are sampled representing two major seasonal variations in Malaysia. The analysis of extreme precipitation trends is important for the prediction of high precipitation events. ANNs are widely applied in the hydrology field because of their nonlinear ability in predicting nonstationary and seasonal data. In this paper, we have compared ANNs with seasonal autoregressive integrated moving average (ARIMA) and regression analysis using out-of-sample test data. The results for Kuantan indicate that seasonal ARIMA is the best method to forecast extreme precipitation when MX5d lags are used as input. For Kota Bharu, ANN exhibits better generalization ability than ARIMA and regression analysis when dual inputs (lagged MX5d and lagged global climate indices) are utilized in the model.

Attribution analysis of high precipitation events in summer in England and Wales over the last decade

The crucial question in the public debate of extreme events is increasingly whether and to what extent the event has been caused by anthropogenic warming. In this study we investigate this question using extreme summer precipitation events in England and Wales as an example for probabilistic event attribution using very large ensembles of regional climate model (RCM) simulations within the weather@home.net project. This allows us to analyse the statistics of high precipitation events in England and Wales, a region with a high quality precipitation observational dataset. Validating the model simulations against observations shows a credible shape of the distribution of 5-day precipitation, and thus confidence in the results. While the risk of extreme July precipitation events has at least doubled due to anthropogenic climate change in the modelling framework, no significant changes can be detected for the other two summer months. This study thus highlights the challenges of probabilistic event attribution of complex weather events and identifies the need to further decompose atmospheric features responsible for an event to occur for quantitative attribution analysis.

Aquaplanet Experiments Using CAM’s Variable-Resolution Dynamical Core

Abstract A variable-resolution option has been added within the spectral element (SE) dynamical core of the U.S. Department of Energy (DOE)–NCAR Community Atmosphere Model (CAM). CAM-SE allows for static refinement via conforming quadrilateral meshes on the cubed sphere. This paper investigates the effect of mesh refinement in a climate model by running variable-resolution (var-res) simulations on an aquaplanet. The variable-resolution grid is a 2° (~222 km) grid with a refined patch of 0.25° (~28 km) resolution centered at the equator. Climatology statistics from these simulations are compared to globally uniform runs of 2° and 0.25°. A significant resolution dependence exists when using the CAM version 4 (CAM4) subgrid physical parameterization package across scales. Global cloud fraction decreases and equatorial precipitation increases with finer horizontal resolution, resulting in drastically different climates between the uniform grid runs and a physics-induced grid imprinting in the var-res simulation. Using CAM version 5 (CAM5) physics significantly improves cloud scaling at different grid resolutions. Additional precipitation at the equator in the high-resolution mesh results in collocated zonally anomalous divergence in both var-res simulations, although this feature is much weaker in CAM5 than CAM4. The equilibrium solution at each grid spacing within the var-res simulations captures the majority of the resolution signal of the corresponding globally uniform grids. The var-res simulation exhibits good performance with respect to wave propagation, including equatorial regions where waves pass through grid transitions. In addition, the increased frequency of high-precipitation events in the refined 0.25° area within the var-res simulations matches that observed in the global 0.25° simulations.

Evaluation of ERA‐Interim reanalysis precipitation products using England and Wales observations

Precipitation forecast data from the ERA‐Interim reanalysis (33 years) are evaluated using the daily England and Wales Precipitation (EWP) observations obtained from a rain‐gauge network. Observed and reanalysis daily precipitation data are both described well by Weibull distributions with indistinguishable shapes but different scale parameters, such that the reanalysis underestimates the observations by an average of 22%. The correlation between the observed and ERA‐Interim time series of regional daily precipitation is 0.91. ERA‐Interim also captures the statistics of extreme precipitation including a slightly lower likelihood of the heaviest precipitation events (> 15 mm day−1 for the regional average) than indicated by the Weibull fit. ERA‐Interim is also closer to EWP for the high precipitation events. Since these carry weight in longer accumulations, a smaller underestimation of 19% is found for monthly mean precipitation. The partition between convective and stratiform precipitation in the ERA‐Interim forecast is also examined. In summer both components contribute equally to the total precipitation amount, while in winter the stratiform precipitation is approximately double the convective. These results are expected to be relevant to other regions with low orography on the coast of a continent at the downstream end of midlatitude stormtracks.

The Evaluation of Soil Water Storage in A Small Catchment in 2009 And 2010

Abstract The soil water storage in a soil profile was calculated from the measured values of volumetric soil water content by the Profile Probe PR2/6 (Delta-T Device Ltd.) in the Bocegaj catchment in the depth up to 1m. The monitored season in the year 2009 followed after a dry season, and in the year 2010, rainfalls were above the average values. The soil water storage was higher than the mean value of field capacity during the season with high precipitation events. With a decreased amount of rainfalls, rising air temperature and crops growing, the soil water storage was in recession. In the vertical direction, the volumetric soil moisture as well as soil water storage in every soil profile have their characteristic progresses.

Climate Change Resilience and Public Education in Response to Hydrologic Extremes in Singapore

Aims: In February and March 2014, more than 300,000 households were affected by water rationing in Kuala Lumpur, Malaysia and the surrounding State of Selangor. Further south, reservoir levels in Singapore were dropping, prompting the government to raise the water conservation rhetoric, but falling short of implementing water rationing schemes. The region experienced a dry spell that was unprecedented in the last 30 years. Preparedness for storms has been the talk of the town since the 2001, 2006 and 2007 extreme high precipitation events in the southern parts of the peninsula and in Singapore resulted in costly flood damage. While resilience has been a concept used frequently in climate change adaptation, it is derived from ecology, where it refers to the capacity of the system to respond to a disturbance and resist the impact or recover from the damage of the disturbance. This paper examines the case of Singapore as an urban area in responding to a similar extreme hydrologic phenomenon by examining the climate Original Research Article British Journal of Environment & Climate Change, 4(3): 328-354, 2014 329 change resilience of the small city-state, with a view to recommending some considerations in designing climate change adaptation strategies. Place of Study: Singapore and peninsular Malaysia. Methodology: The paper reviews the rainfall extremes statistics covering the last 30 years for Singapore and then takes a hydrologic event-based case study approach to more closely examine the impact of record storms and the drought of March 2014 to discuss aspects of resilience that can serve as lessons for tropical cities in future adaptation to a climate-changing world. Results: Extreme rainfall events have become more frequent in Singapore over the past 30 years, while February, 2014 was the driest February since 1869. February, 2014 also had the lowest recorded daily relative humidity at 74.5%. Tropical cyclones are not expected to hit Singapore because of its location near the equator, yet Typhoon Vamei made history by delivering 210 mm of rain on 27 December, 2001. Between 19 and 20 December, 2007 Singapore received 366 mm of rain and within the same week another storm deposited 140 mm of rain in a 24 hour period. While there were some environmental and health impacts related to the February 2014 drought, including low dissolved oxygen levels in water and a localized fish kill, as well as reports of greater human respiratory problems, Singapore was able to weather the drought by requesting voluntary conservation measures, prudent reservoir management, and increasing the output of NEWater and desalinized water. Recent extreme rainfall events have produced localized flooding, but Singapore has progressively pursued a program of improved drainage, stream naturalization, and implementation of Low Impact Development (LID) technology to reduce flood-prone areas from 3,200 ha in the 1970’s to 36 ha today. Conclusion: We do not suggest that all countries need to have NEWater or desalinated water to solve drought problems. We do suggest that in managing rainfall related hazards, droughts and extremes have been treated rather independently. Based on the case study of extremes presented for Singapore we propose the importance of establishing a three-step preparedness program for extremes that includes Preparation (vulnerability and risk identification, adaptive capacity building, and monitoring), Response (information dissemination and relief action), and Recovery.

Geographically heterogeneous temporal trends of extreme precipitation in Wisconsin, USA during 1950-2006

Large flood events in recent years in the state of Wisconsin, USA raised a question of whether high precipitation events are on the rise. The objective of the research was to examine temporal and spatial patterns of extreme precipitation in Wisconsin during 1950–2006. The daily precipitation data used in the study were created by researchers at the University of Wisconsin-Madison using spatial interpolation of weather stations data across the state to a grid mesh with a spatial resolution of 8 km. For extreme precipitation indices, we calculated 99th, 95th, 90th, 85th, and 80th percentiles of daily total precipitation (>1 mm) in a year and the number of days per year with daily precipitation exceeding 10 mm, 20 mm, and 50 mm. We also conducted the Mann–Kendall test for trend, examined how geographical heterogeneity varied over time, and built quantile regression models for annual summer precipitation. Main findings include the following: the temporal trend of extreme precipitation varied widely across the state; the highest percentile index showed an increasing trend over the largest area, whereas indices of less extreme precipitation tended to generally decrease; extreme precipitation tended to show more dispersed and skewed spatial patterns than annual total precipitation. Overall, indices related to frequency showed more similar spatial and temporal trends to total precipitation than magnitude indices.

Characterizing Water Holding Capacity and Runoff during Composting of Greenwaste and Biosolids

ABSTRACT Most composters in the United States use open-windrows. During high intensity precipitation events, uncontained water running off of the surface of the compost piles can potentially contaminate surface waters with nutrients and metals. Water that is absorbed poses no runoff concern but may threaten groundwater quality. To gain insight into these processes, stormwater runoff fractions and water holding capacity of compost piles have been characterized for greenwaste (GW) and biosolids (BS) materials. Laboratory scale experiments were conducted using days 1, 7, and 14 materials representing three different stages of composting. This study also evaluated sloped and flat-top as different pile geometries and surfactant use for promoting infiltration. Results indicate that fresh materials were most hydrophobic and the infiltration rates increased with increased composting times. The water storage capacity of the compost pile increased with the age of the compost pile. Compost water storage capacities could not be reliably estimated as the difference between field capacity and as-received water contents.

Characterization of the groundwater response to rainfall on a hillslope with fractured bedrock by creep deformation and its implication for the generation of deep-seated landslides on Mt. Wanitsuka, Kyushu Island

In this study, the hydrogeological response of a hillslope affected by gravitational deformation was analyzed based on the data obtained for two observation boreholes: a 10-m borehole representing a relatively superficial section of the hillslope dominated by soil and old landslide deposits and a 40-m borehole representing the bedrock aquifer. For this analysis, the precipitation events in the area, groundwater levels of the two boreholes, electrical conductivity and isotopic concentration (oxygen and hydrogen) of the groundwater in the boreholes and rainfall samples were measured. Derived from the rainfall data, the antecedent precipitation index (API) with a 6-h half-life offers a good correlation with the peaks in the groundwater levels in the bedrock aquifer. The characteristics of the groundwater response suggest the existence of a single structure in the bedrock that controls the response of the hillslope. The structure serves as a conduit, which rapidly drives the rainfall water (recharge) into the bedrock. Evidently, this process is unrelated to the superficial section represented by the observations in the 10-m borehole. The structure is associated with an area of high hydraulic conductivity in the bedrock caused by the gravitational deformation in the hillslope. The strong control of this structure in the hillslope's hydrogeological response makes it responsible for the hillslope's stability during high-precipitation events. This information is highly relevant to areas featuring the generation of several deep-seated landslides under heavy-rain conditions.

Top‐down estimate of China's black carbon emissions using surface observations: Sensitivity to observation representativeness and transport model error

This study examines the sensitivity of “top‐down” quantification of Chinese black carbon (BC) emissions to the temporal resolution of surface observations and to the transport model error associated with the grid resolution and wet deposition. At two rural sites (Miyun in North China Plain and Chongming in Yangtze River Delta), the model‐inferred emission bias based on hourly BC observations can differ by up to 41% from that based on monthly mean observations. This difference relates to the intrinsic inability of the grid‐based model in simulating high pollution plumes, which often exert a larger influence on the arithmetic mean of observations at monthly time steps. Adopting the variation of BC to carbon monoxide correlation slope with precipitation as a suitable measure to evaluate the model's wet deposition, we found that wet removal of BC in the model was too weak, due in part to the model's underestimation of large precipitation events. After filtering out the observations during high pollution plumes and large precipitation events for which the transport model error should not be translated into the emission error, the inferred emission bias changed from −11% (without filtering) to −2% (with filtering) at the Miyun site, and from −22% to +1% at the Chongming site. Using surface BC observations from three more rural sites (located in Northeast, Central, and Central South China, respectively) as constraints, our top‐down estimate of total BC emissions over China was 1.80 ± 0.65 Tg/yr in 2006, 0.5% lower than the bottom‐up inventory of Zhang et al. (2009) but with smaller uncertainty.

A New HadGEM3-A-Based System for Attribution of Weather- and Climate-Related Extreme Events

Abstract A new system for attribution of weather and climate extreme events has been developed based on the atmospheric component of the latest Hadley Centre model. The model is run with either observational data of sea surface temperature and sea ice or estimates of what their values would be without the effect of anthropogenic climatic forcings. In that way, ensembles of simulations are produced that represent the climate with and without the effect of human influences. A comparison between the ensembles provides estimates of the change in the frequency of extremes due to anthropogenic forcings. To evaluate the new system, reliability diagrams are constructed, which compare the model-derived probability of extreme events with their observed frequency. The ability of the model to reproduce realistic distributions of relevant climatic variables is another key aspect of the system evaluation. Results are then presented from analyses of three recent high-impact events: the 2009/10 cold winter in the United Kingdom, the heat wave in Moscow in July 2010, and floods in Pakistan in July 2010. An evaluation assessment indicates the model can provide reliable results for the U.K. and Moscow events but not for Pakistan. It is found that without anthropogenic forcings winters in the United Kingdom colder than 2009/10 would be 7–10 times (best estimate) more common. Although anthropogenic forcings increase the likelihood of heat waves in Moscow, the 2010 event is found to be very uncommon and associated with a return time of several hundred years. No reliable attribution assessment can be made for high-precipitation events in Pakistan.

A quantitative evaluation of the high resolution HARMONIE model for critical weather phenomena

Abstract. The high resolution non-hydrostatic Harmonie model (Seity et al., 2012) seems capable of delivering high quality precipitation forecasts. The quality with respect to the European radar composite is assessed using the Model Evaluation Tool, as distributed by the NCAR DTC (Developmental Testbed Center, 2012), and compared to that of the reference run of Hirlam (Unden et al., 2002), the current operational NWP model at KNMI. Both neighbourhood and object-based verification methods are compared for a week with several high intensity precipitation events in July 2010. It is found that Hirlam scores very well in most metrics, and that in spite of the higher resolution the added value of the Harmonie model is sometimes hard to quantify. However, higher precipitation intensities are better represented in the Harmonie model with its higher resolution. Object-based methods do not yet yield a sharp distinction between the different models, as it proves difficult to construct a meaningful and distinguishing metric with a solid physical basis for the many settings that can be varied.

Analysis of intense rainfall events on Madeira Island during the 2009/2010 winter

Abstract. This paper constitutes a step towards the understanding of some characteristics associated with high rainfall amounts and flooding on Madeira Island. The high precipitation events that occurred during the winter of 2009/2010 have been considered with three main goals: to analyze the main atmospheric characteristics associated with the events; to expand the understanding of the interaction between the island and the atmospheric circulations, mainly the effects of the island on the generation or intensification of orographic precipitation; and to evaluate the performance of high resolution numerical modeling in simulating and forecasting heavy precipitation events over the island. The MESO-NH model with a horizontal resolution of 1 km is used, as well as rain gauge data, synoptic charts and measurements of precipitable water obtained from the Atmospheric InfraRed Sounder (AIRS). The results confirm the influence of the orographic effects on precipitation over Madeira as well as the tropical–extratropical interaction, since atmospheric rivers were detected in six out of the seven cases analyzed, acting as a low level moisture supplier, which together with the orographic lifting induced the high rainfall amounts. Only in one of the cases the presence of a low pressure system was identified over the archipelago.

Effects of flooding-induced N2O production, consumption and emission dynamics on the annual N2O emission budget in wetland soil

Rapid flooding of wetland soil promotes subsurface N2O production in the soil and potential emission to the atmosphere in distinctive emission pulses. Changes in flooding frequency of wetland soil following future climate change will likely affect the timing and magnitude of nitrous oxide (N2O) emissions from the soil to the atmosphere. From October 2009 to October 2010, rapid flooding of a natural Danish wetland was observed twice in response to high precipitation events. A flooding-induced N2O emission pulse (delay ∼16 h; duration ∼12 h; total emission 1.83 mg N2O–N m−2, max. emissions ∼250 μg N2O–N m−2 h−1) was observed when the soil conditions in the top soil had been oxidized for more than 2–3 weeks prior to flooding. This flooding-induced N2O emission pulse constituted ∼2.5% of the annual net N2O emissions of 0.74 kg N2O–N ha−1 yr−1. A net uptake of atmospheric N2O was observed during mid-summer when the WL was at its seasonally lowest counterbalancing ∼6.4% of the total annual net N2O emission budget. Main surface emission periods of N2O were observed when the water level and associated peaks in subsurface N2O concentrations were gradually decreasing to soil depths down to 40 cm below the surface. These surface emission patterns are predominantly linked to variations in plant-mediated gas transport via Phalaris arundinacea and N2O producing/consuming processes in the root zone. Soil flooding experiments using high-resolution N2O microsensors demonstrate very large N2O production and consumption capacities where >500 nmol N2O cm−3 were sequentially produced and consumed in less than 24 h. It is concluded that a higher future frequency of flooding-induced N2O emissions will have a very limited effect on the net annual N2O emission budget as long as NO3− availability in the soil prior to rapid flooding is not dramatically increased.

Verification of precipitation forecasts of MM5 model over Epirus, NW Greece, for various convective parameterization schemes

Abstract. The mesoscale meteorological model MM5 is applied to 22 selected days with intense precipitation in the region of Epirus, NW Greece. At first, it was investigated whether and to what extend an increased horizontal resolution (from 8 to 2 km) improves the quantitative precipitation forecasts. The model skill was examined for the 12-h accumulated precipitation recorded at 14 meteorological stations located in Epirus and by using categorical and descriptive statistics. Then, the precipitation forecast skill for the 2 km grid was studied: (a) without and (b) with the activation of a convective parameterization scheme. From the above study, the necessity of the use of a scheme at the 2 km grid is assessed. Furthermore, three different convective parameterization schemes are compared: (a) Betts-Miller, (b) Grell and (c) Kain-Fritsch-2 in order to reveal the scheme, resulting in the best precipitation forecast skill in Epirus. Kain-Fritsch-2 and Grell give better results with the latter being the best for the high precipitation events.

Stage level, volume and time‐frequency information content of Lake Tana using stochastic and wavelet analysis methods

AbstractLake Tana is the largest fresh water body situated in the north‐western highlands of Ethiopia. In addition to its ecological services, it serves for local transport, electric power generation, fishing, recreational purposes, and source of dry season irrigation water supply. Evidence shows that the lake has dried at least once at about 15,000–17,000 before present owing to a combination of high evaporation and low precipitation events. Past attempts to understand and simulate historical fluctuation of Lake Tana based on simplistic water balance approach of inflow, outflow, and storage have failed to capture well‐known events of drawdown and rise of the lake that have happened in the last 44 years. This study tested different stochastic methods of lake level and volume simulation for supporting Lake Tana operational planning decision support. Three stochastic methods (perturbations approach, Monte Carlo methods, and wavelet analysis) were employed for lake level and volume simulation, and the results were compared with the stage level measurements. Forty‐four years of daily, monthly, and mean annual lake level data have shown a Gaussian variation with goodness of fit at 0.01 significant levels of the Kolmogorov–Smirnov test. The stochastic simulations predicted the lake stage level of the 1972, 1984, and 2002/2003 historical droughts 99% of the time. The information content (frequency) of fluctuation of Lake Tana for various periods was resolved using Wigner's Time‐Frequency Decomposition method. The wavelet analysis agreed with the perturbations and Monte Carlo simulations resolving the time (1970s, 1980s, and 2000s) in which low frequency and high spectral power fluctuation has occurred. The Monte Carlo method has shown its superiority for risk analysis over perturbation and deterministic method whereas wavelet analysis reconstructed historical record of lake stage level at daily and monthly time scales. Copyright © 2012 John Wiley & Sons, Ltd.