Ensemble prediction for nowcasting with a convection-permitting model—I: description of the system and the impact of radar-derived surface precipitation rates

A key strategy to improve the skill of quantitative predictions of precipitation, as well as hazardous weather such as severe thunderstorms and flash floods is to exploit the use of observations of convective activity (e.g. from radar). In this paper, a convection-permitting ensemble prediction system (EPS) aimed at addressing the problems of forecasting localized weather events with relatively short predictability time scale and based on a 1.5 km grid-length version of the Met Office Unified Model is presented. Particular attention is given to the impact of using predicted observations of radar-derived precipitation intensity in the ensemble transform Kalman filter (ETKF) used within the EPS. Our initial results based on the use of a 24-member ensemble of forecasts for two summer case studies show that the convective-scale EPS produces fairly reliable forecasts of temperature, horizontal winds and relative humidity at 1 h lead time, as evident from the inspection of rank histograms. On the other hand, the rank histograms seem also to show that the EPS generates too much spread for forecasts of (i) surface pressure and (ii) surface precipitation intensity. These may indicate that for (i) the value of surface pressure observation error standard deviation used to generate surface pressure rank histograms is too large and for (ii) may be the result of non-Gaussian precipitation observation errors. However, further investigations are needed to better understand these findings. Finally, the inclusion of predicted observations of precipitation from radar in the 24-member EPS considered in this paper does not seem to improve the 1-h lead time forecast skill.

Multi-satellite observed responses of precipitation and its extremes to interannual climate variability

The consistency of precipitation variability estimated from the multiple satellite-based observing systems is assessed. There is generally good agreement between TRMM TMI, SSM/I, GPCP and AMSRE datasets for the inter-annual variability of precipitation since 1997 but the HOAPS dataset appears to overestimate the magnitude of variability. Over the tropical ocean the TRMM 3B42 dataset produces unrealistic variabilitys. Based upon deseasonalised GPCP data for the period 1998-2008, the sensitivity of global mean precipitation (P) to surface temperature (T) changes (dP/dT) is about 6%/K, although a smaller sensitivity of 3.6%/K is found using monthly GPCP data over the longer period 1989-2008. Over the tropical oceans dP/dT ranges from 10-30%/K depending upon time-period and dataset while over tropical land dP/dT is -8 to -11%/K for the 1998-2008 period. Analyzing the response of the tropical ocean precipitation intensity distribution to changes in T we find the wetter area P shows a strong positive response to T of around 20%/K. The response over the drier tropical regimes is less coherent and varies with datasets, but responses over the tropical land show significant negative relationships over an interannual time-scale. The spatial and temporal resolutions of the datasets strongly influence the precipitation responses over the tropical oceans and help explain some of the discrepancy between different datasets. Consistency between datasets is found to increase on averaging from daily to 5-day time-scales and considering a 1o (or coarser) spatial resolution. Defining the wet and dry tropical ocean regime by the 60th percentile of P intensity, the 5-day average, 1o TMI data exhibits a coherent drying of the dry regime at the rate of -20%/K and the wet regime becomes wetter at a similar rate with warming.

Daily precipitation statistics in regional climate models: evaluation and intercomparison for the European Alps

An evaluation is undertaken of the statistics of daily precipitation as simulated by five regional climate models using comprehensive observations in the region of the European Alps. Four limited area models and one variable-resolution global model are considered, all with a grid spacing of 50 km. The 15-year integrations were forced from reanalyses and observed sea surface temperature and sea ice (global model from sea surface only). The observational reference is based on 6400 rain gauge records (10–50 stations per grid box). Evaluation statistics encompass mean precipitation, wet-day frequency, precipitation intensity, and quantiles of the frequency distribution. For mean precipitation, the models reproduce the characteristics of the annual cycle and the spatial distribution. The domain mean bias varies between −23% and +3% in winter and between −27% and −5% in summer. Larger errors are found for other statistics. In summer, all models underestimate precipitation intensity (by 16–42%) and there is a too low frequency of heavy events. This bias reflects too dry summer mean conditions in three of the models, while it is partly compensated by too many low-intensity events in the other two models. Similar intermodel differences are found for other European subregions. Interestingly, the model errors are very similar between the two models with the same dynamical core (but different parameterizations) and they differ considerably between the two models with similar parameterizations (but different dynamics). Despite considerable biases, the models reproduce prominent mesoscale features of heavy precipitation, which is a promising result for their use in climate change downscaling over complex topography.

Secular trends in daily precipitation characteristics: greenhouse gas simulation with a coupled AOGCM

Secular trends of daily precipitation characteristics are considered in the transient climate change experiment with a coupled atmosphere-ocean general circulation model ECHAM4/OPYC3 for 1900-2099. The climate forcing is due to increasing concentrations of the greenhouse gases in the atmosphere. Mean daily precipitation, precipitation intensity, probability of wet days and parameters of the gamma distribution are analyzed. Particular attention is paid to the changes of heavy precipitation, Analysis of the annual mean precipitation trends for 1900-1999 revealed general agreement with observations with significant positive trends in mean precipitation over continental areas. In the 2000-2099 period precipitation trend patterns followed the tendency obtained for 1900-1999 but with significantly increased magnitudes. Unlike the annual mean precipitation trends for which negative values were found for some continental areas, the mean precipitation intensity and scale parameter of the fitted gamma distribution increased over all land territories . Negative trends in the number of wet days were found over most of the land areas except high latitudes in the Northern Hemisphere. The shape parameter of the gamma distribution in general revealed a slight negative trend in the areas of the precipitation increase. Investigation of daily precipitation revealed an unproportional increase of heavy precipitation events for the land areas including local maxima in Europe and the eastern United States.

Extratropical cyclones and the projected decline of winter Mediterranean precipitation in the CMIP5 models

The Mediterranean region has been identified as a climate change "hot-spot" due to a projected reduction in precipitation and fresh water availability which has potentially large socio-economic impacts. To increase confidence in these projections, it is important to physically understand how this precipitation reduction occurs. This study quantifies the impact on winter Mediterranean precipitation due to changes in extratropical cyclones in 17 CMIP5 climate models. In each model, the extratropical cyclones are objectively tracked and a simple approach is applied to identify the precipitation associated to each cyclone. This allows us to decompose the Mediterranean precipitation reduction into a contribution due to changes in the number of cyclones and a contribution due to changes in the amount of precipitation generated by each cyclone. The results show that the projected Mediterranean precipitation reduction in winter is strongly related to a decrease in the number of Mediterranean cyclones. However, the contribution from changes in the amount of precipitation generated by each cyclone are also locally important: in the East Mediterranean they amplify the precipitation trend due to the reduction in the number of cyclones, while in the North Mediterranean they compensate for it. Some of the processes that determine the opposing cyclone precipitation intensity responses in the North and East Mediterranean regions are investigated by exploring the CMIP5 inter-model spread.

Can climate models represent the precipitation associated with extratropical cyclones?

Extratropical cyclones produce the majority of precipitation in many regions of the extratropics. This study evaluates the ability of a climate model, HiGEM, to reproduce the precipitation associated with extratropical cyclones. The model is evaluated using the ERA-Interim reanalysis and GPCP dataset. The analysis employs a cyclone centred compositing technique, evaluates composites across a range of geographical areas and cyclone intensities and also investigates the ability of the model to reproduce the climatological distribution of cyclone associated precipitation across the Northern Hemisphere. Using this phenomena centred approach provides an ability to identify the processes which are responsible for climatological biases in the model. Composite precipitation intensities are found to be comparable when all cyclones across the Northern Hemisphere are included. When the cyclones are filtered by region or intensity, differences are found, in particular, HiGEM produces too much precipitation in its most intense cyclones relative to ERA-Interim and GPCP. Biases in the climatological distribution of cyclone associated precipitation are also found, with biases around the storm track regions associated with both the number of cyclones in HiGEM and also their average precipitation intensity. These results have implications for the reliability of future projections of extratropical precipitation from the model.

Precipitation variability in Sao Paulo State, Brazil

The State of Sao Paulo is the richest in Brazil, responsible for over 30% of the Brazilian gross rate. It has a population of around 30 million and its economy is based on agriculture and industrial products. Any change in climate can have a profound influence on the socio-economics of the State. In order to determine changes in total and extreme rainfall over Sao Paulo State, climate change indices derived from daily precipitation data were calculated using specially designed software. Maps of trends for a subset of 59 rain gauge stations were analysed for the period 1950-1999 and also for a subset of this period, 1990-1999, representing more recent climate. A non-parametric Mann-Kendall test was applied to the time series. Maps of trends for six annual precipitation indices (annual total precipitation (PRCPTOT), very heavy precipitation days (R20mm), events greater than the 95th percentile (R95p), maximum five days precipitation total (RX5day), the length of the largest wet spell (CWD) and the length of the largest dry spell (CDD)) were analysed for the entire period. These exhibited statistically significant trends associated with a wetter climate. A significant increase in PRCPTOT, associated with very heavy precipitation days, were observed at more than 45% of the rain gauge stations. The Mann-Kendall test identified that the positive trend in PRCPTOT is possibly related to the increase in the R95p and R20mm indices. Therefore, the results suggest that there has been a change in precipitation intensity. In contrast, the indices for the more recent shorter time series are significantly different to the longer term indices. The results indicate that intense precipitation is becoming concentrated in a few days and spread over the period when the CDD and R20mm indices show positive trends, while negative ones are seen in the RX5day index. The trends found could be related to many anthropogenic aspects such as biomass burning aerosols and land use.

Data assimilation for precipitation nowcasting using Bayesian inference

This work introduces a new variational Bayes data assimilation method for the stochastic estimation of precipitation dynamics using radar observations for short term probabilistic forecasting (nowcasting). A previously developed spatial rainfall model based on the decomposition of the observed precipitation field using a basis function expansion captures the precipitation intensity from radar images as a set of ‘rain cells’. The prior distributions for the basis function parameters are carefully chosen to have a conjugate structure for the precipitation field model to allow a novel variational Bayes method to be applied to estimate the posterior distributions in closed form, based on solving an optimisation problem, in a spirit similar to 3D VAR analysis, but seeking approximations to the posterior distribution rather than simply the most probable state. A hierarchical Kalman filter is used to estimate the advection field based on the assimilated precipitation fields at two times. The model is applied to tracking precipitation dynamics in a realistic setting, using UK Met Office radar data from both a summer convective event and a winter frontal event. The performance of the model is assessed both traditionally and using probabilistic measures of fit based on ROC curves. The model is shown to provide very good assimilation characteristics, and promising forecast skill. Improvements to the forecasting scheme are discussed

Soil losses from typic cambisols and red latosol as related to three erosive rainfall patterns

Rainfall erosivity is one of the main factors related to water erosion in the tropics. This work focused on relating soil loss from a typic dystrophic Tb Haplic Cambisol (CXbd) and a typic dystrophic Red Latosol (LVdf) to different patterns of natural erosive rainfall. The experimental plots of approximately 26 m² (3 x 8.67 m) consisted of a CXbd area with a 0.15 m m-1 slope and a LVdf area with 0.12 m m-1 slope, both delimited by galvanized plates. Drainpipes were installed at the lower part of these plots to collect runoff, interconnected with a Geib or multislot divisor. To calculate erosivity (EI30), rainfall data, recorded continuously at a weather station in Lavras, were used. The data of erosive rainfall events were measured (10 mm precipitation intervals, accuracy 0.2 mm, 24 h period, 20 min intervals), characterized as rainfall events with more than 10 mm precipitation, maximum intensity > 24 mm h-1 within 15 min, or kinetic energy > 3.6 MJ, which were used in this study to calculate the rainfall erosivity parameter, were classified according to the moment of peak precipitation intensity in advanced, intermediate and delayed patterns. Among the 139 erosive rainfall events with CXbd soil loss, 60 % were attributed to the advanced pattern, with a loss of 415.9 Mg ha-1, and total losses of 776.0 Mg ha-1. As for the LVdf, of the 93 erosive rainfall events with soil loss, 58 % were listed in the advanced pattern, with 37.8 Mg ha-1 soil loss and 50.9 Mg ha-1 of total soil loss. The greatest soil losses were observed in the advanced rain pattern, especially for the CXbd. From the Cambisol, the soil loss per rainfall event was greatest for the advanced pattern, being influenced by the low soil permeability.

Estimating Design-Flood Discharges for Streams in Iowa Using Drainage-Basin and Channel-Geometry Characteristics, HR-322, 1993

Drainage-basin and channel-geometry multiple-regression equations are presented for estimating design-flood discharges having recurrence intervals of 2, 5, 10, 25, 50, and 100 years at stream sites on rural, unregulated streams in Iowa. Design-flood discharge estimates determined by Pearson Type-III analyses using data collected through the 1990 water year are reported for the 188 streamflow-gaging stations used in either the drainage-basin or channel-geometry regression analyses. Ordinary least-squares multiple-regression techniques were used to identify selected drainage-basin and channel-geometry regions. Weighted least-squares multiple-regression techniques, which account for differences in the variance of flows at different gaging stations and for variable lengths in station records, were used to estimate the regression parameters. Statewide drainage-basin equations were developed from analyses of 164 streamflow-gaging stations. Drainage-basin characteristics were quantified using a geographic-information-system (GIS) procedure to process topographic maps and digital cartographic data. The significant characteristics identified for the drainage-basin equations included contributing drainage area, relative relief, drainage frequency, and 2-year, 24-hour precipitation intensity. The average standard errors of prediction for the drainage-basin equations ranged from 38.6% to 50.2%. The GIS procedure expanded the capability to quantitatively relate drainage-basin characteristics to the magnitude and frequency of floods for stream sites in Iowa and provides a flood-estimation method that is independent of hydrologic regionalization. Statewide and regional channel-geometry regression equations were developed from analyses of 157 streamflow-gaging stations. Channel-geometry characteristics were measured on site and on topographic maps. Statewide and regional channel-geometry regression equations that are dependent on whether a stream has been channelized were developed on the basis of bankfull and active-channel characteristics. The significant channel-geometry characteristics identified for the statewide and regional regression equations included bankfull width and bankfull depth for natural channels unaffected by channelization, and active-channel width for stabilized channels affected by channelization. The average standard errors of prediction ranged from 41.0% to 68.4% for the statewide channel-geometry equations and from 30.3% to 70.0% for the regional channel-geometry equations. Procedures provided for applying the drainage-basin and channel-geometry regression equations depend on whether the design-flood discharge estimate is for a site on an ungaged stream, an ungaged site on a gaged stream, or a gaged site. When both a drainage-basin and a channel-geometry regression-equation estimate are available for a stream site, a procedure is presented for determining a weighted average of the two flood estimates.

Anàlisi d'observacions de superfície en relació al diagnòstic de tipus de precipitació observat amb radar

Màster en Meteorologia

The Aqua-Planet Experiment (APE): CONTROL SST Simulation

Climate simulations by 16 atmospheric general circulation models (AGCMs) are compared on an aqua-planet, a water-covered Earth with prescribed sea surface temperature varying only in latitude. The idealised configuration is designed to expose differences in the circulation simulated by different models. Basic features of the aqua-planet climate are characterised by comparison with Earth. The models display a wide range of behaviour. The balanced component of the tropospheric mean flow, and mid-latitude eddy covariances subject to budget constraints, vary relatively little among the models. In contrast, differences in damping in the dynamical core strongly influence transient eddy amplitudes. Historical uncertainty in modelled lower stratospheric temperatures persists in APE. Aspects of the circulation generated more directly by interactions between the resolved fluid dynamics and parameterized moist processes vary greatly. The tropical Hadley circulation forms either a single or double inter-tropical convergence zone (ITCZ) at the equator, with large variations in mean precipitation. The equatorial wave spectrum shows a wide range of precipitation intensity and propagation characteristics. Kelvin mode-like eastward propagation with remarkably constant phase speed dominates in most models. Westward propagation, less dispersive than the equatorial Rossby modes, dominates in a few models or occurs within an eastward propagating envelope in others. The mean structure of the ITCZ is related to precipitation variability, consistent with previous studies. The aqua-planet global energy balance is unknown but the models produce a surprisingly large range of top of atmosphere global net flux, dominated by differences in shortwave reflection by clouds. A number of newly developed models, not optimised for Earth climate, contribute to this. Possible reasons for differences in the optimised models are discussed. The aqua-planet configuration is intended as one component of an experimental hierarchy used to evaluate AGCMs. This comparison does suggest that the range of model behaviour could be better understood and reduced in conjunction with Earth climate simulations. Controlled experimentation is required to explore individual model behaviour and investigate convergence of the aqua-planet climate with increasing resolution.

A multimodel assessment of future projections of North Atlantic and European extratropical cyclones in the CMIP5 climate models

The response of North Atlantic and European extratropical cyclones to climate change is investigated in the climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). In contrast to previous multimodel studies, a feature-tracking algorithm is here applied to separately quantify the re- sponses in the number, the wind intensity, and the precipitation intensity of extratropical cyclones. Moreover, a statistical framework is employed to formally assess the uncertainties in the multimodel projections. Under the midrange representative concentration pathway (RCP4.5) emission scenario, the December–February (DJF) response is characterized by a tripolar pattern over Europe, with an increase in the number of cyclones in central Europe and a decreased number in the Norwegian and Mediterranean Seas. The June–August (JJA) response is characterized by a reduction in the number of North Atlantic cyclones along the southern flank of the storm track. The total number of cyclones decreases in both DJF (24%) and JJA (22%). Classifying cyclones according to their intensity indicates a slight basinwide reduction in the number of cy- clones associated with strong winds, but an increase in those associated with strong precipitation. However, in DJF, a slight increase in the number and intensity of cyclones associated with strong wind speeds is found over the United Kingdom and central Europe. The results are confirmed under the high-emission RCP8.5 scenario, where the signals tend to be larger. The sources of uncertainty in these projections are discussed.

Análise de superfície de tendência aplicada à chuva, medida por radar meteorológico, nas regiões de Assis e Piracicaba, SP

This paper presents the results from lineal trend surface analysis technique application. The purpose was to detect positive and negative anomalies in the rain measure distribution obtained by the meteorological radar Doppler, band S, located in Bauru, during the period of 21 of October/2004 to 29 of April/2005 in the areas of Assis and Piracicaba. Using three Z-R radar relations for rain quantification was chosen the specific equation Z = 32R1,65, as the best one. The results showed that the applied methodology was able to indicate the space distribution of the rain accumulated, identifying and locating the regions where there was rainy excess and rainy lack during each analyzed period. Such results indicate areas with larger pluvial impact and consequently more favorable for environmental damages.

Hydrologic and Water Quality Assessment of Miller Run: A Study of Bucknell University’s Impact

Human development causes degradation of stream ecosystems due to impacts on channel morphology, hydrology, and water quality. Urbanization, the second leading cause of stream impairment, increases the amount of impervious surface cover, thus reducing infiltration and increasing surface runoff of precipitation, which ultimately affects stream hydrologic process and aquatic biodiversity. The main objective of this study was to assess the overall health of Miller Run, a small tributary of the Bull Run and Susquehanna River watersheds, through an integrative hydrologic and water quality approach in order to determine the degree of Bucknell University’s impact on the stream. Hydrologic conditions, including stage and discharge, and water quality conditions, including total suspended solids, ion, nutrient, and dissolved metal concentrations, specific conductivity, pH, and temperature, were measured and evaluated at two sampling sites (upstream and downstream of Bucknell’s main campus) during various rain events from September 2007 to March 2008. The primary focus of the stream analysis was based on one main rain event on 26 February 2008. The results provided evidence that Miller Run is impacted by Bucknell’s campus. From a hydrologic perspective, the stream’s hydrograph showed the exact opposite pattern of what would be expected from a ‘normal’ stream. Miller run had a flashier downstream hydrograph and a broader upstream hydrograph, which was more than likely due to the increased amount of impervious surface cover throughout the downstream half of the watershed. From a water quality perspective, sediment loads increased at a faster rate and were significantly higher downstream compared to upstream. These elevated sediment concentrations were probably the combined result of sediment runoff from upstream and downstream construction sites that were being developed over the course of the study. Sodium, chloride, and potassium concentrations, in addition to specific conductivity, also significantly increased downstream of Bucknell’s campus due to the runoff of road salts. Calcium and magnesium concentrations did not appear to be impacted by urbanization, although they did demonstrate a significant dilution effect downstream. The downstream site was not directly affected by elevated nitrate concentrations; however, soluble reactive phosphorus concentrations tended to increase downstream and ammonium concentrations significantly peaked partway through the rain event downstream. These patterns suggest that Miller Run may be impacted by nutrient runoff from the golf course, athletic fields, and/or fertilizers applications on the main campus. Dissolved manganese and iron concentrations also appeared to slightly increase downstream, demonstrating the affect of urban runoff from roads and parking lots. pH and temperature both decreased farther downstream, but neither showed a significant impact of urbanization. More studies are necessary to determine how Miller Run responds to changes in season, climate, precipitation intensity, and land-use. This study represents the base-line analysis of Miller Run’s current hydrologic and water quality conditions; based on these initial findings, Bucknell should strongly consider modifications to improve storm water management practices and to reduce the campus’s overall impact on the stream in order to enhance and preserve the integrity of its natural water resources.