Orographic Precipitation Model Research Articles

Simulation of a former ice field with Parallel Ice Sheet Model – Snežnik study case

Abstract. In this paper, we present a reconstruction of climate conditions during the Last Glacial Maximum on a karst plateau Snežnik, which lies in Dinaric Mountains (southern Slovenia) and bears evidence of glaciation. The reconstruction merges geomorphological ice limits, classified as either clear or unclear, and a computer modelling approach based on the Parallel Ice Sheet Model (PISM). Based on extensive numerical experiments where we studied the agreements between simulated and geomorphological ice extent, we propose using a combination of a high-resolution precipitation model that accounts for orographic precipitation combined with a simple elevation-based temperature model. The geomorphological ice extent can be simulated with climate to be around 6 °C colder than the modern day and with a lower-than-modern-day amount of precipitation, which matches other state-of-the art climate reconstructions for the era. The results indicate that an orographic precipitation model is essential for the accurate simulation of the study area, with moist southern winds from the nearby Adriatic Sea having a predominant effect on the precipitation patterns. Finally, this study shows that transforming climate conditions towards wetter and warmer or drier and colder does not significantly change the conditions for glacier formation.

Coupled Surface Process and Orographic Precipitation Model for the Landscape Evolution of the Himalayas

Coupled Surface Process and Orographic Precipitation Model for the Landscape Evolution of the Himalayas

Oerlemans Minimal Model as a Possible Instrument for Describing Mountain Glaciation in Earth System Models

The main approaches to mountain glacier simulation were reviewed, and Oerlemans minimal model was chosen as a parameterization core of mountain glaciation in the Earth System models. The proposed model is based on a one-dimensional equation of glacier mass balance. The mass balance components are calculated with the use of a specially developed model of orographic precipitation, an algorithm for correction of incoming solar radiation onto an inclined ice surface, and schemes of calculation of turbulent heat-moisture exchange based on the Monin–Obukhov theory. The model was implemented for the Djankuat glacier (the Central Caucasus), for which a long measurement series is available. The model gives a good reproduction of the dynamics of glacier length over the period 1985–2020 based on measured mass balance values: –13 m/year, which is in practically perfect agreement with the field data. This means that the Oerlemans model can be used in Earth system models. The results of simulation based on the calculated mass balance showed a significant positive trend in ablation at a slight change in accumulation, which is also in agreement with the reality. However, in this case, the values of the annual thawing depth and the glacier contraction are twice as large and those observed in reality. The further development of the model (the inclusion of a snow cover block, the incorporation of debris mantle and mountain–valley circulation) will eliminate these shortcomings.

Extreme Rainfall over Complex Terrain: An Application of the Linear Model of Orographic Precipitation to a Case Study in the Italian Pre-Alps

Intense meteorological events are the primary cause of geohazard phenomena in mountain areas. In this paper, we present a study of the intense rainfall event that occurred in the provinces of Lecco and Sondrio from 11 to 12 June 2019. The aim of our work is to understand the effect of local topography on the spatial distribution of rainfall and to attempt the reconstruction of a realistic rainfall field relative to that extreme event. This task represents a challenge in the context of complex orography. Classical rain-gauge interpolation techniques, such as Kriging, may be too approximate, while meteorological models can be complex and often unable to accurately predict rainfall extremes. For these reasons, we tested the linear upslope model (LUM) designed for estimating rainfall records in orographic precipitation. This model explicitly addresses the dependence of rainfall intensification caused by the terrain elevation. In our case study, the available radio sounding data identified the convective nature of the event with a sustained and moist southern flow directed northward across the Pre-Alps, resulting in an orographic uplift. The simulation was conducted along a smoothed elevation profile of the local orography. The result was a reliable reconstruction of the rainfall field, validated with the ground-based rain gauge data. The error analysis revealed a good performance of the LUM with a realistic description of the interaction between the airflow and local orography. The areas subjected to rainfall extremes were correctly identified, confirming the determinant role of complex terrain in precipitation intensification.

Recent Climatic Mass Balance of the Schiaparelli Glacier at the Monte Sarmiento Massif and Reconstruction of Little Ice Age Climate by Simulating Steady-State Glacier Conditions

The Cordillera Darwin Icefield loses mass at a similar rate as the Northern and Southern Patagonian Icefields, showing contrasting individual glacier responses, particularly between the north-facing and south-facing glaciers, which are subject to changing climate conditions. Detailed investigations of climatic mass balance processes on recent glacier behavior are not available for glaciers of the Cordillera Darwin Icefield and surrounding icefields. We therefore applied the coupled snow and ice energy and mass balance model in Python (COSIPY) to assess recent surface energy and mass balance variability for the Schiaparelli Glacier at the Monte Sarmiento Massif. We further used COSIPY to simulate steady-state glacier conditions during the Little Ice Age using information of moraine systems and glacier areal extent. The model is driven by downscaled 6-hourly atmospheric data and high resolution precipitation fields, obtained by using an analytical orographic precipitation model. Precipitation and air temperature offsets to present-day climate were considered to reconstruct climatic conditions during the Little Ice Age. A glacier-wide mean annual climatic mass balance of −1.8 ± 0.36 m w.e. a − 1 was simulated between between April 2000 and March 2017. An air temperature decrease between −0.9 ° C and −1.7 ° C in combination with a precipitation offset of up to +60% to recent climate conditions is necessary to simulate steady-state conditions for Schiaparelli Glacier in 1870.

Multi‐scale evaluation of a linear model of orographic precipitation over Sierra de Guadarrama (Iberian Central System)

A linear model of orographic precipitation is validated at Sierra de Guadarrama (Iberian Central System) using ERA‐Interim as input and a historical set of precipitation data. It is the first time that a linear precipitation model is tested in a semi‐arid region like this. The historical precipitation data come from three high‐quality observatories located at the south, north and top of the mountain range. Different timescales ranging from daily, monthly and annual precipitation are analysed. Phenomena not generally taken into account in linear models like a sub‐saturated air condition and topographic mesoscale flow blocking are included in the modelling. Model results show a good agreement with observations at annual and monthly scales. The model reproduces well the high inter‐annual variability and the annual cycle, including the pronounced summer drought. Bigger differences between observed and modelled precipitations are found for some winter months and for May. Winter overestimation is attributed to measurement undersampling during snowy conditions. The underestimation in May is likely related to thermally driven convective precipitation, which is not modelled. Results also show how orographic precipitation is an important contributor to total precipitation in this area. The high‐resolution precipitation fields obtained can be used in the future for precipitation assessment and other hydrological applications. Modelled time series can also be very helpful for completing and validating the precipitation observations for the winter months.

Glacier Mass Changes of Lake-Terminating Grey and Tyndall Glaciers at the Southern Patagonia Icefield Derived From Geodetic Observations and Energy and Mass Balance Modeling

In this study we demonstrate how energy and mass fluxes vary in space and time for Grey and Tyndall glaciers at the Southern Patagonia Icefield (SPI). Despite the overall glacier retreat of most Patagonian glaciers, a recent increase in mass loss has been observed, but individual glaciers respond differently in terms of spatial and temporal changes. In this context, the detailed investigation of the effect of mass balance processes on recent glacier response to climate forcing still needs refinement. We therefore quantify surface energy-fluxes and climatic mass balance of the two neighboring glaciers, Grey and Tyndall. The COupled Snow and Ice energy and MAss balance model COSIMA is applied to assess recent surface energy and climatic mass balance variability with a high temporal and spatial resolution for a 16-year period between April 2000 to March 2016. The model is driven by downscaled 6-hourly atmospheric data derived from ERA-Interim reanalysis and MODIS/Terra Snow Cover and validated against ablation measurements made in single years. High resolution precipitation fields are determined by using an analytical orographic precipitation model. Frontal ablation is estimated as residual of climatic mass balance and geodetic mass balance derived from TanDEM-X/SRTM between 2000 and 2014. We simulate a positive glacier-wide mean annual climatic mass balance of +1.02$\pm$0.52\,m\,w.e. a$^{-1}$ for Grey Glacier and of +0.68$\pm$0.54\,m\,w.e. a$^{-1}$ for Tyndall Glacier between 2000 and 2014. Climatic mass balance results show a high year to year variability. Comparing climatic mass balance results with previous studies underlines the high uncertainty in climatic mass balance modeling with respect to accumulation on the SPI. Due to the lack of observations accumulation estimates differ from previous studies based on the methodological approaches. Mean annual ice loss by frontal ablation is estimated to be 2.07$\pm$0.70\,m\,w.e.\,a$^{-1}$ for Grey Glacier and 3.26$\pm$0.82\,m\,w.e.\,a$^{-1}$ for Tyndall Glacier between 2000 and 2014. Ice loss by surface ablation exceeds ice loss by frontal ablation for both glaciers. The overall mass balance of Grey and Tyndall glaciers are clearly negative with -1.05$\pm$0.18\,m\,w.e.\,a$^{-1}$ and -2.58$\pm$0.28\,m\,w.e.\,a$^{-1}$ respectively.

Modeling Winter Precipitation Over the Juneau Icefield, Alaska, Using a Linear Model of Orographic Precipitation

Assessing and modeling precipitation in mountainous areas remains a major challenge in glacier mass balance modeling. Observations are typically scarce and reanalysis data and similar climate produ ...

The Use of an Orographic Precipitation Model to Assess the Precipitation Spatial Distribution in Lake Kinneret Watershed

A high-resolution 3-D orographic precipitation model (OPM) forced by Climate Forecast System (CFS) reanalysis fields was developed for the Lake Kinneret watershed (Israel-Syria-Lebanon territories). The OPM was tuned to represent the interaction between the advected and stratiform rainfall, and the local orographic enhancement. The OPM evaluation was focused on the densely instrumented lower part of the watershed. To evaluate the ungauged upper-elevation, bias-adjusted precipitation estimates from the Global-Hydro-Estimator were used. The OPM simulates higher rainfall amounts in the upper-elevation watershed compared to currently used rainfall estimates from an elevation dependent regression. The larger differences are during rain events with southwesterly wind flow and high moisture flux. These conditions, according to the OPM, are conducive to enhanced orographic lifting in the Hermon Mountain. A sensitivity analysis indicated that the higher wind speeds for southwesterly–northwesterly trajectories generate significant orographic lifting and increase the precipitation differences between the lower and upper elevations.

Bayesian prediction of monthly precipitation on a fine grid using covariates based on a regional meteorological model

In this article a Bayesian hierarchical model (BHM) for observed monthly precipitation is proposed. This BHM incorporates covariates based on an output on a fine grid from a regional meteorological model. At the data level of the BHM, the observed monthly precipitation is transformed using the Box–Cox transformation, and each month is modeled separately. To capture spatial correlation at the data level, a Gaussian field with Matérn correlation function is used. It is assumed that the data are subject to measurement error. The location and log‐scale parameters at the latent level are also modeled with Gaussian fields with Matérn correlation functions. An output from a regional meteorological model on a fine grid is used to construct spatial covariates for the latent parameters of the BHM for each month of the year. These covariates are then projected onto each of the observed sites for each month and incorporated into the BHM. Markov chain Monte Carlo simulation is used for posterior inference and Bayesian kriging is used to predict the latent parameters on the grid. This BHM was applied to observed data on monthly precipitation, which come from forty sites across Iceland from the years 1958 to 2006. The data were corrected for wind, wetting, and evaporation loss. An output from a linear model of orographic precipitation defined on a 1 km by 1 km grid over Iceland was used to construct the covariates for the BHM. Copyright © 2015 John Wiley & Sons, Ltd.

Topographic Evolution and Climate Aridification during Continental Collision: Insights from Computer Simulations.

How do the feedbacks between tectonics, sediment transport and climate work to shape the topographic evolution of the Earth? This question has been widely addressed via numerical models constrained with thermochronological and geomorphological data at scales ranging from local to orogenic. Here we present a novel numerical model that aims at reproducing the interaction between these processes at the continental scale. For this purpose, we combine in a single computer program: 1) a thin-sheet viscous model of continental deformation; 2) a stream-power surface-transport approach; 3) flexural isostasy allowing for the formation of large sedimentary foreland basins; and 4) an orographic precipitation model that reproduces basic climatic effects such as continentality and rain shadow. We quantify the feedbacks between these processes in a synthetic scenario inspired by the India-Asia collision and the growth of the Tibetan Plateau. We identify a feedback between erosion and crustal thickening leading locally to a <50% increase in deformation rates in places where orographic precipitation is concentrated. This climatically-enhanced deformation takes place preferentially at the upwind flank of the growing plateau, specially at the corners of the indenter (syntaxes). We hypothesize that this may provide clues for better understanding the mechanisms underlying the intriguing tectonic aneurisms documented in the Himalayas. At the continental scale, however, the overall distribution of topographic basins and ranges seems insensitive to climatic factors, despite these do have important, sometimes counterintuitive effects on the amount of sediments trapped within the continent. The dry climatic conditions that naturally develop in the interior of the continent, for example, trigger large intra-continental sediment trapping at basins similar to the Tarim Basin because they determine its endorheic/exorheic drainage. These complex climatic-drainage-tectonic interactions make the development of steady-state topography at the continental scale unlikely.

Assessing the Impact of the Tropopause on Mountain Waves and Orographic Precipitation Using Linear Theory and Numerical Simulations

Abstract The partial reflection of mountain waves at the tropopause has been studied extensively for its contribution to downslope windstorms, but its impact on orographic precipitation has not been addressed. Here linear theory and numerical simulations are used to investigate how the tropopause affects the vertical structure of mountain waves and, in turn, orographic precipitation. Relative to the no-tropopause case, wave-induced ascent above the windward slope of a two-dimensional ridge is found to be enhanced or diminished depending on the ratio of the tropopause height to the vertical wavelength of the mountain waves—defined here as the “nondimensional tropopause height” . In idealized simulations of flow over both two-dimensional and three-dimensional ridges, variations in are found to modulate the precipitation rate by roughly a factor of 2 under typical atmospheric conditions. The sensitivity of precipitation to is related primarily to the depth of windward ascent but also to the location and strength of leeside descent, with significant impacts on the distribution of precipitation across the range (i.e., the rain-shadow effect). Using a modified version of Smith and Barstad’s orographic precipitation model, variations in are found to produce significant rain-shadow variability in the Washington Cascades, perhaps explaining some of the variability in rain-shadow strength observed among Cascade storms.

The Landfall and Inland Penetration of a Flood-Producing Atmospheric River in Arizona. Part II: Sensitivity of Modeled Precipitation to Terrain Height and Atmospheric River Orientation

Abstract This manuscript documents numerical modeling experiments based on a January 2010 atmospheric river (AR) event that caused extreme precipitation in Arizona. The control experiment (CNTL), using the Weather Research and Forecasting (WRF) Model with 3-km grid spacing, agrees well with observations. Sensitivity experiments in which 1) model grid spacing decreases sequentially from 81 to 3 km and 2) upstream terrain is elevated are used to assess the sensitivity of interior precipitation amounts and horizontal water vapor fluxes to model grid resolution and height of Baja California terrain. The drying ratio, a measure of airmass drying after passage across terrain, increases with Baja’s terrain height and decreases with coarsened grid spacing. Subsequently, precipitation across Arizona decreases as the Baja terrain height increases, although it changes little with coarsened grid spacing. Northern Baja’s drying ratio is much larger than that of southern Baja. Thus, ARs with a southerly orientation, with water vapor transports that can pass south of the higher mountains of northern Baja and then cross the Gulf of California, can produce large precipitation amounts in Arizona. Further experiments are performed using a linear model (LM) of orographic precipitation for a central-Arizona-focused subdomain. The actual incidence angle of the AR (211°) is close to the optimum angle for large region-mean precipitation. Changes in region-mean precipitation amounts are small (~6%) owing to AR angle changes; however, much larger changes in basin-mean precipitation of up to 33% occur within the range of physically plausible AR angles tested. Larger LM precipitation sensitivity is seen with the Baja-terrain-modification experiments than with AR-angle modification.

A mixed-phase bulk orographic precipitation model with embedded convection

A novel analytical model for mixed-phase, unblocked and unseeded orographic precipitation with embedded convection is developed and evaluated. The model takes an idealized background flow and terrain geometry and calculates the area-averaged precipitation rate and other microphysical quantities. The results provide insight into key physical processes, including cloud condensation, vapour deposition, evaporation and sublimation, as well as precipitation formation and sedimentation (fallout). To account for embedded convection in nominally stratiform clouds, diagnostics for purely convective and purely stratiform clouds are calculated independently and combined using weighting functions based on relevant dynamical and microphysical time-scales. An in-depth description of the model is presented, as well as a quantitative assessment of its performance against idealized, convection-permitting numerical simulations with a sophisticated microphysics parametrization. The model is found to reproduce the simulation diagnostics accurately over most of the parameter space considered.

Impact of two conceptual precipitation downscaling schemes on mass-balance modeling of Gran Campo Nevado ice cap, Patagonia

AbstractPrecipitation downscaling in mountainous regions with sparse station data is challenging, but needed to link global climate datasets with high-resolution glacier models. In this study, we apply a linear orographic precipitation model (OPM) to generate orographic precipitation fields for mass-balance studies at Gran Campo Nevado (GCN), Southern Patagonia. The OPM is driven by large-scale atmospheric input variables taken from the reanalysis data of the US National Centers for Environmental Prediction and the US National Center for Atmospheric Research. The orographic precipitation fields are compared to precipitation fields assessed by a linear precipitation gradient, widely used in earlier mass-balance studies of GCN and elsewhere. Both downscaling methods are implemented into a degree-day model to analyze the sensitivity of mass-balance modeling to different precipitation inputs. Significant spatio-temporal differences are found, particularly in the summit region. The mass-balance modeling shows high sensitivity to the different precipitation distribution methods, leading to differences in the mass-balance gradients on the east side of GCN.

Climate Change in Western North America caused by CO2 rise: A Coupled Atmosphere-Ocean Model Simulation

This study investigates the interactions between carbon dioxide, global atmospheric circulation and the climate of the cordillera of western North America in the twenty-first century under a relatively conservative Intergovernmental Panel on Climate Changed (IPCC), emission scenario through the use of a global coupled atmosphere-ocean model. Increasing global carbon dioxide concentrations result in rising temperatures and increasing atmospheric water vapour, particularly at higher latitudes where precipitation increases are most pronounced. The greater warming in polar regions induces a poleward shift in the position of the mid-latitude jets and reduces their strength throughout most of the mid-latitudes, reducing the formation of baroclinic eddies. Nevertheless, a simple model of orographic precipitation indicates that if relative humidity changes little in a warmer climate, western North America will experience substantially larger precipitation increases than the global average, despite weakening mean orographic forcing. R ésumé [Traduit par la rédaction] Dans un scénario relativement prudent sur les émissions élaboré par le Groupe d'experts intergouvernemental sur l’évolution du climat (IPCC), nous nous penchons, dans la présente étude, sur les interactions entre le dioxyde de carbone, la circulation atmosphérique mondiale et le climat de la Cordillère de la partie ouest de l'Amérique du Nord au XXIe siècle en recourant à un système de modélisation avec couplage océan-atmosphère. L'augmentation des concentrations de dioxyde de carbone à l’échelle planétaire entraîne une hausse des températures et des quantités de vapeur d'eau dans l'atmosphère, notamment dans les latitudes plus élevées, où les précipitations augmentent le plus. Le réchauffement accru dans les régions polaires se traduit par un déplacement marqué vers les pôles de la position des courants-jets des latitudes moyennes et elle réduit leur force dans la majeure partie des latitudes moyennes, ce qui diminue la formation de tourbillons barocliniques. Cependant, d'après un modèle simple de précipitations orographiques, si l'humidité relative varie peu dans un climat plus chaud, les quantités de précipitations dépasseront largement la moyenne mondiale dans la partie ouest de l'Amérique du Nord, malgré la diminution du forçage orographique moyen.

Relationships between Barrier Jet Heights, Orographic Precipitation Gradients, and Streamflow in the Northern Sierra Nevada

Abstract The rate of precipitation increase with elevation, termed the orographic precipitation gradient (OPG), is critically important for hydrologic forecasting in mountain basins that receive both rain and snow. Here, the following are examined to see how well they are able to predict the OPG and how it changes between storms and years: 1) a linear model of orographic precipitation forced by upstream radiosonde data, 2) monthly Parameter-Elevation Regressions on Independent Slopes Model (PRISM) precipitation data, and 3) seven years of hourly wind profiler data used to identify characteristics of the Sierra barrier jet (SBJ). These are compared against 124 daily resolution (four of which also had quality controlled, hourly resolution) precipitation gauge records in the northern Sierra Nevada. All methods represent the OPG well in the mean and during a year when less than 30% of the precipitation occurred on days with SBJs. However, the linear model and PRISM do not adequately capture annual variations in the OPG during years when more than 70% of the precipitation occurred on days with SBJs. Throughout all of the years, wind profiler data indicating the height of the SBJ provided additional, and necessary, information. The OPG is negatively correlated with the height of the SBJ. The SBJ height is lower, and hence, the OPG greater when the westerly winds are stronger, with more vertical wind shear. These westerly storms result in greater increases of precipitation with elevation, which act to increase snow storage in most storms but also to increase storm runoff during warmer-than-average storms.

The Sensitivity of Mountain Snowpack Accumulation to Climate Warming

Abstract Controls on the sensitivity of mountain snowpack accumulation to climate warming (λS) are investigated. This is accomplished using two idealized, physically based models of mountain snowfall to simulate snowpack accumulation for the Cascade Mountains under current and warmed climates. Both models are forced from sounding observations. The first model uses the linear theory (LT) model of orographic precipitation to predict precipitation as a function of the incoming flow characteristics and uses the sounding temperatures to estimate the elevation of the rain–snow boundary, called the melting level (ML). The second “ML model” uses only the ML from the sounding and assumptions of uniform and constant precipitation. Both models simulate increases in precipitation intensity and elevated storm MLs under climate warming. The LT model predicts a 14.8%–18.1% loss of Cascade snowfall per degree of warming, depending on the vertical structure of the warming. The loss of snowfall is significantly greater, 19.4%–22.6%, if precipitation increases are neglected. Comparing the two models shows that the predominant control on λS is the relationship between the distribution of storm MLs and the distribution of topographic area with elevation. Although increases in precipitation due to warming may act to moderate λS, the loss of snow accumulation area profoundly limits the ability of precipitation increases to maintain the snowpack under substantial climate warming (beyond 1°–2°C). Circulation changes may act to moderate or exacerbate the loss of mountain snowpack under climate change via impacts on orographic precipitation enhancement.

Enhancing radar estimates of precipitation over complex terrain using information derived from an orographic precipitation model

Summary The objective of this paper is to present a radar-based quantitative precipitation estimation algorithm and assess its quality over the complex terrain of western Iceland. The proposed scheme deals with the treatment of beam blockage, anomalous propagation, vertical profile of reflectivity and includes a radar adjustment technique compensating for range, orographic effects and variations in the Z – R relationship. The quality of the estimated precipitation is remarkably enhanced after post-processing and in reasonably good agreement with what is known about the spatial distribution of precipitation in the studied area from both rain gauge observations and a gridded dataset derived from an orographic precipitation model. The results suggest that this methodology offers a credible solution to obtain an estimate of the distribution of precipitation in mountainous terrain and appears to be of practical value to meteorologists and hydrologists.

Distribution of snow accumulation on the Svartisen ice cap, Norway, assessed by a model of orographic precipitation

AbstractWe apply a linear model of orographic precipitation (LT model) to estimate snow accumulation on the western Svartisen ice cap (220 km2) in northern Norway. This model combines 3D airflow dynamics with simple parameterizations of cloud physics. The model is forced by large‐scale atmospheric input variables taken from the ECMWF Re‐analysis (ERA‐40) of the European Center for Medium Range Weather Forecast (ECMWF), and the model parameters are kept constant for the entire simulation period, after optimization. The domain covers a 120 × 125 km area surrounding the ice cap. The model is run using a 1‐km resolution digital elevation model, and 6‐h time steps over the period from 1958 to 2002. Precipitation data from surrounding meteorological stations and winter glacier mass balance measurements on several glaciers within the region are used to evaluate the model results. Precipitation obtained from the LT model agrees well with observations from precipitation gauges and there is also fair agreement between model results and specific winter mass balance observations on the ice cap if these are corrected for winter rain. The LT model reproduces well the spatial pattern of winter accumulation across the ice cap as well as the area‐averaged winter mass balances of several other glaciers in the region. This indicates that it is a useful tool in providing high‐resolution, deterministic estimates of precipitation in complex terrain as required for distributed hydrological and/or glacier mass balance modelling of unmeasured areas. Copyright © 2008 John Wiley &amp; Sons, Ltd.