Sub-Saharan Africa is today facing a big challenge regarding food deficiency and water scarcity due to climate change. One of these countries is Rwanda, a small landlocked country in the middle of Africa. Rwanda strongly depend on agriculture, both in the aspect of reducing poverty and hunger but also because their economy security depend on it. Because of increasingly fluctuating rainfalls their agriculture becomes more dependent on irrigation and the availability to water resources. To investigate how the climate change will affect the amount of water resources in the coming decades, this study is focusing on the watershed and marshland of Muvumba P8 in Nyagatare, Rwanda. A hydrological model was created, in a software called Soil and Water Assessment Tool (SWAT), with soil, land use and slope maps for the watershed. Calibrating the model was done with help of Climate Forecast System Reanalysis (CFSR) data and run for nine different climate model datasets. An uncertainty had to be taken into account regarding both the measured local data and the downloaded data. To be able to compare the amount of water resources and the irrigation requirements for the rice crop the farmers were growing on the marshland, the crop water requirements for rice was estimated with FAO’s program called CROPWAT. The irrigation system on the marshland allows a double cropping of rice every year and consist of a system depending on elevation differences to create natural fall. There was three reservoirs along the marshland but to limit the project, only the first reservoir was taken into account. This was complemented with existing data and field survey. Six out of nine climate models showed a decrease in median discharge over the coming 30 years compared to the CFSR historical median discharge. This means that less water in general will reach the outlet of the watershed in the years to come. At the same time all climate models indicate an increase in irrigation requirements for the rice crops. The seasons are probably going to change, a longer and drier season between June and August and a rainier season between September and November are projected.

With the election of President Trump, climate deniers feel emboldened and moved from the fringes to the centre of global policy making. We study how an agnostic approach to policy, based on Pascal's wager and allowing for subjective prior probability beliefs about whether climate deniers are right, prices carbon. Using the DICE integrated assessment model, we find that assigning a 10% chance of climate deniers being correct lowers the global price on carbon in 2020 only marginally: from $21 to $19 per ton of carbon dioxide if policymakers apply "Nordhaus discounting" and from $91 to $84 per ton of carbon dioxide if they apply "Stern discounting". Agnostics' reflection of remaining scientific uncertainty leaves climate policy essentially unchanged. The robustness of an ambitious climate policy also follows from using the max-min or the min-max regret principle. Letting the coefficient of relative ambiguity aversion vary from zero, corresponding to expected utility analysis, to infinity, corresponding to the max-min principle, we show how policy makers deal with fundamental climate model uncertainty if they are prepared to assign prior probabilities to different views of the world being correct. Allowing for an ethical discount rate and a higher market discount rate and for a wide range of sensitivity exercises including damage uncertainty, we show that pricing carbon is the robust response under rising climate scepticism. / Series: Ecological Economic Papers

Submitted by Maria Beatriz Vieira (mbeatriz.vieira@gmail.com) on 2017-05-08T16:23:16Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) dissertacao_rodrigo_da_silva_pereira.pdf: 1723922 bytes, checksum: 18533319b08c17041a8e5681e41087ff (MD5) / Approved for entry into archive by Aline Batista (alinehb.ufpel@gmail.com) on 2017-05-09T10:54:02Z (GMT) No. of bitstreams: 2 dissertacao_rodrigo_da_silva_pereira.pdf: 1723922 bytes, checksum: 18533319b08c17041a8e5681e41087ff (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2017-05-09T10:54:02Z (GMT). No. of bitstreams: 2 dissertacao_rodrigo_da_silva_pereira.pdf: 1723922 bytes, checksum: 18533319b08c17041a8e5681e41087ff (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2015-02-27 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Esta dissertação tem como propósito geral a análise do clima presente e o comportamento futuro dos eventos extremos de precipitação local de curta duração com potencial para causar alagamento nas principais cidades do Rio Grande do Sul abrangendo diferentes regiões do Estado: Porto Alegre, Caxias do Sul, Santa Maria e Pelotas. Baseado no histórico de alagamentos de cada cidade e nos dados diários de precipitação obtidos das estações meteorológicas do INMET (Instituto Nacional de Meteorologia) obteve-se o limiar que identificou a taxa de precipitação que representa um evento com potencial para causar alagamento na cidade, sendo os eventos divididos em caso de atenção (percentil 25) ou de alerta (percentil 75) nas 48h precedentes à ocorrência do alagamento. Os resultados revelaram um crescimento sutil dos casos, tanto atenção quanto alerta, nos últimos 53 anos. A cidade de Porto Alegre foi a que apresentou os menores limiares para condição de alagamento, o que era esperado devido sua maior urbanização. Ao avaliar o comportamento sazonal dos casos constatou-se que no clima presente (1961-2013), o trimestre julho-agosto-setembro foi a época do ano mais propícia a casos de alagamentos. Posteriormente, os casos foram correlacionados com três índices climáticos que medem as anomalias de TSM (Temperatura da Superfície do Mar) do Atlântico Sul e do Pacífico, no intuito de avaliar se suas ocorrências estão associadas a fenômenos climáticos de grande escala. As correlações encontradas variaram de fracas a moderadas, mas com alto nível de confiança estatística para o IME (Índice Multivariado do ENOS). O uso de modelagem climática regional (modelo ETA-HadCM3) denotou que num cenário futuro (A1B de acordo com o Painel Intergovernamental sobre Mudanças Climáticas) para o período de 2021-2070 haverá no geral, um pequeno acréscimo no número de casos de atenção para todas as cidades, quando comparado aos valores observados no clima presente (1961-2013). Em Pelotas, haverá uma mudança na climatologia dos eventos com deslocamento da estação com maior número de casos do trimestre JAS (clima presente) para o OND (cenário futuro). / This work has as general purpose the analysis of present climate and future behavior of short duration extreme local rainfall events with potential for causing flooding in major cities in Rio Grande do Sul State covering different regions: Porto Alegre, Caxias do Sul, Santa Maria and Pelotas. Based on history of floods of each city and on the rainfall data obtained from meteorological stations of INMET (National Institute of Meteorology), the thresholds that have identified which precipitation rate is an event with the potential to cause flooding in the city were obtained, being such events divided in case of attention (25th percentile) or case of alert (75th percentile) in 48 hours before the occurrence of flooding. The results showed a subtle increase of cases, both as alert and attention in the last 53 years. The city of Porto Alegre was presented the least thresholds for flooding condition, which was expected due to its increased urbanization. In assessing the seasonal behavior of the cases it was found that in this climate, the July-August-September was the time of year most facilitates cases of flooding. Later, cases were correlated with three climate indices that measure the SST (Sea Surface Temperature) anomalies in order to assess whether their occurrences are associate to large-scale climatic phenomena. It was found weak to moderate correlations, but with a high level of statistical confidence for the EMI (ENSO Multivariate Index). The use of regional climate model (ETA-HadCM3) denotes that in a future scenario (A1B following International Panel on Climate Change) for the period 2021-2070 will be in general an increase number of cases of attention for all cities, when compared to those observed in the present climate (1961-2013). In Pelotas there will be a climatological change due to a displacement of the season with more cases: from JAS quarter (present) to OND quarter (future scenario).

Ensemble simulations of smoke aerosol radiative effects with a regional climate model in the Amazon has been conducted to investigate the radiative effects of aerosols on clouds, rainfall, and circulation from dry to wet season. The results of the ensemble simulations suggest that the radiative effect of the smoke aerosols can reduce daytime surface radiative and sensible fluxes, the depth and instability of the planetary boundary layer (PBL), consequently the clouds in the lower troposphere in early afternoon in the smoke center, where the aerosols optical depth, AOD, exceeds 0.3. The aerosol radiative forcing also appears to weaken moisture transport into the smoke center and increase moisture transport and cloudiness in the region upwind to the smoke center, namely, the northern Amazon. Anomalous wind convergence over the equatorial western Amazon occurs to compensate the anomalous wind divergence in the southern Amazon, leading to an increase of both clouds and rainfall in that region. The increased atmospheric thermodynamic stability in Southern Amazonia also appears to block synoptic cyclonic activities propagated from extratropical South America, leading to an increased synoptic cyclonic activities and rainfall in southern Brazil, Paraguay and northern Argentina. Evidently, the dynamic response of the monsoon circulation plays a major role in determining the pattern of rainfall change induced by the radiative effect of the aerosols.

This thesis examines the utility of mathematical complexity measures for the analysis of stratospheric dynamics. Through theoretical considerations and tests with artificial data sets, e.g., the iteration of the logistic map, suitable parameters are determined for the application of the statistical entropy measures sample entropy (SE) and Rényi entropy (RE) to methane (a long-lived stratospheric tracer) data from simulations of the SOCOL chemistry-climate model. The SE is shown to be useful for quantifying the variability of recurring patterns in a time series and is able to identify tropical patterns similar to those reported by previous studies of the ``tropical pipe'' region. However, the SE is found to be unsuitable for use in polar regions, due to the non-stationarity of the methane data at extra-tropical latitudes. It is concluded that the SE cannot be used to analyse climate complexity on a global scale. The focus is turned to the RE, which is a complexity measure of probability distribution functions (PDFs). Using the second order RE and a normalisation factor, zonal PDFs of ten consecutive days of methane data are created with a Bayesian optimal binning technique. From these, the RE is calculated for every day (moving 10-day window). The results indicate that the RE is a promising tool for identifying stratospheric mixing barriers. In Southern Hemisphere winter and early spring, RE produces patterns similar to those found in other studies of stratospheric mixing. High values of RE are found to be indicative of the strong fluctuations in tracer distributions associated with relatively unmixed air in general, and with gradients in the vicinity of mixing barriers, in particular. Lower values suggest more thoroughly mixed air masses. The analysis is extended to eleven years of model data. Realistic inter-annual variability of some of the RE structures is observed, particularly in the Southern Hemisphere. By calculating a climatological mean of the RE for this period, additional mixing patterns are identified in the Northern Hemisphere. The validity of the RE analysis and its interpretation is underlined by showing that qualitatively similar patterns can be seen when using observational satellite data of a different tracer. Compared to previous techniques, the RE has the advantage that it requires significantly less computational effort, as it can be used to derive dynamical information from model or measurement tracer data without relying on any additional input such as wind fields. The results presented in this thesis strongly suggest that the RE is a useful new metric for analysing stratospheric mixing and its variability from climate model data. Furthermore, it is shown that the RE measure is very robust with respect to data gaps, which makes it ideal for application to observations. Hence, using the RE for comparing observations of tracer distributions with those from model simulations potentially presents a novel approach for analysing mixing in the stratosphere.

Made available in DSpace on 2014-08-20T14:25:52Z (GMT). No. of bitstreams: 1 dissertacao_gilson_carlos_da_silva.pdf: 6390842 bytes, checksum: 4ee553c938a05c41b76eeb4831643835 (MD5) Previous issue date: 2011-08-31 / The time-variation feature of extreme precipitation events (those can result in flooding) on east and north regions of the Santa Catarina State, one of the Brazilian regions most attained by damages owning to heavy rain episodes, is analyzed in this study. For this, it were selected some cities whose history of flooding based on many sources, as the Defesa Civil Estadual was employed to built a threshold to identify the precipitation events that can cause flooding. The observed precipitation data, from 1951 to 2010, from ANA (Agência Nacional de Águas) was used to the analysis of daily rainfall occurred until fifteen days before the flooding and for the counting of this type of event. The methodology employed to detect these events was based on mean thresholds following the rainfall observed on the selected cities. The counting of the occurrences generated the time-variation over such period, indicating positive and also some negative, although not significant tendencies on this region, and a significative linear correlation with global scale climate phenomena in some of the cities. It is also observed the seasonal behavior for the present time and for a future climate scenario, ranging from 2070 to 2100, which aim is to give information to a better planning of the cities, through the regional climate model HadRM3P, from Hadley Centre (UK), simulated and provided by CCST (Centro de Ciências do Sistema Terrestre) do INPE (Instituto Nacional de Pesquisas Espaciais), considering the A2 scenario (more pessimist) following IPCC (Intergovernmental Panel on Climate Change). In comparison against present climate, the estimated projection by climatic model shows an increasing of the frequency of these extreme precipitation events in all selected cities, for all seasons mainly in autumn. / Este estudo analisa o aspecto temporal dos eventos extremos de precipitação com potencial para causar inundação na região Leste e Norte do Estado de Santa Catarina, uma das regiões brasileiras que mais sofrem transtornos devido à chuva intensa. Foram selecionadas algumas cidades cujo histórico de inundação construído através de várias fontes, como a Defesa Civil Estadual foi usado para a confecção de um limiar para identificar tais eventos. Foram utilizados dados de precipitação da ANA (Agência Nacional de Águas) no período de 1951 a 2010, para análise da chuva diária ocorrida até quinze dias antes das inundações e para a quantificação dos eventos extremos de precipitação com potencial para provocar inundação. A metodologia empregada para detecção desses eventos foi a de limiares médios, baseada na análise pontual da precipitação nas cidades atingidas. A quantificação do número de eventos gerou a variação temporal no período, em que pode-se analisar as ocorrências de tendência positiva e também alguma negativa, embora não significativa na região, além de correlação linear significativa, em algumas cidades, com fenômenos climáticos de escala global. É examinado também o aspecto climatológico sazonal do presente e de um cenário climático para o final do século (2070-2100), cujo objetivo é fornecer informações para um melhor planejamento das cidades, usando dados do modelo climático regional HadRM3P, do Hadley Centre (UK), simulados e fornecidos pelo Centro de Ciências do Sistema Terrestre do Instituto Nacional de Pesquisas Espaciais (CCST/INPE), considerando o cenário A2 (mais pessimista) do IPCC (Painel Intergovernamental sobre Mudanças Climáticas). Na comparação com o clima presente, a projeção simulada pelo modelo climático indicou aumento da frequência de ocorrência dos eventos em todas as cidades, para todas as estações do ano, principalmente para o outono.

Les effets du changement climatique sur les îles du Pacifique constituent un enjeu majeur pour les populations insulaires. En particulier, les précipitations constituent un des paramètres sensibles car elles conditionnent la ressource en eau. Le but de cette thèse est mettre d'apporter les premiers éléments de réponse relatifs à l'évolution des précipitations au cours du 21ème siècle sur Tahiti. Dans un premier temps, les précipitations à Tahiti ont été caractérisées à partir des mesures issues du réseau d'observation de Météo France. La saison des pluies, de novembre à avril, constitue la saison d'intérêt, car c'est à cette période de l'année que les cumuls de pluie sont les plus élevés. En effet, la zone de convergence du Pacifique sud (SPCZ), siège de la convection profonde, est la principale source de précipitations à Tahiti en été austral (Décembre-Janvier-Février). A l'échelle interannuelle et interdécennale, les phénomènes El Niño Southern Oscillation (ENSO) et Interdecadal Pacific Oscillation (IPO) induisent des migrations nord/sud et est/ouest de cette zone de convergence qui l'éloignent ou l'approchent de Tahiti. L'IPO, implique un déplacement de la SPCZ vers le nord-est en phase positive, ce qui induit des cumuls plus élevés observés à Tahiti. Elle est déplacée vers le sud-ouest en phase négative de l'IPO, d'où une diminution des pluies à Tahiti. L'étude montre qu'en IPO positif, l'occurrence d'événements El Niño intenses est favorisée. Pour ces cas de figure, la SPCZ migre brutalement vers le nord-est et adopte une orientation zonale au-dessous de l'équateur. Cette configuration l'éloigne de Tahiti et perturbe le flux d'alizés de sud-est, il en résulte alors des pluies orographiques très abondantes sur les côtes sud-est de l'île. Suite à cet état des lieux des précipitations observées, une méthodologie originale, en l'absence de toute autre expérience internationale sur la région, a été mise en œuvre pour obtenir un modèle capable de distinguer l'île et capturer au mieux les effets orographiques. Deux descentes d'échelle successives ont été nécessaires pour passer du modèle couplé global CNRM-CM, à 150 km de résolution, au modèle à aire limitée ALADIN-Climat, de résolution 12 km, centré sur Tahiti. Les sorties du modèle régional obtenues ont été confrontées aux observations sur la partie historique. Un lien a été établi entre les précipitations observées et modélisées sur la période passée. Ce lien est construit entre stations d'observations et points de grille du modèle exhibant un comportement similaire relatif aux phases de l'ENSO. Il a été supposé encore pertinent au 21ième siècle pour déduire les précipitations futures les plus réalistes à Tahiti, à partir des précipitations simulées par le modèle à 12 km, suivant deux scénarios du GIEC (RCP4.5 et RCP8.5). La structure spatiale du réchauffement climatique de type El niño conforte la pertinence du lien établi. Les résultats obtenus concernent les côtes sud de Tahiti. Les précipitations vont augmenter progressivement tout au long du 21ème siècle, en réponse au réchauffement global. A Papara, il est tombé en moyenne sur la période 1961-2011 pendant l'été austral 695 mm de pluie. Il tombera en moyenne sur la période 2070-2100, 825 mm selon le scénario RCP4.5, 814 mm selon le scénario RCP8.5, soit une augmentation d'un peu moins de 20 %. Ajoutés à cet accroissement à long terme, les événements El Niño induiront un excédent de précipitations. Mais cet effet sera réduit en fin de période dans le RCP8.5. A l'inverse, les événements La Niña s'accompagneront toujours d'un déficit de précipitations mais sans arriver à contrecarrer l’accroissement à long terme. / The effects of climate change on Pacific islands is a major concern for the local populations. The rainfall parameter, specifically, appears as one of the sensitive parameters, as it determines water resources. The goal of this thesis is to bring a first insight into the 21st century evolution of precipitation in Tahiti.The first step was to characterize rainfall in Tahiti using data records from the observation network of Meteo France. The “rainfall season”, lasting from November to April, is the season of interest, as rainfall amounts are the highest at this time of the year. Indeed, the South Pacific Convergence Zone (SPCZ), host of deep convection, remains the principal source of rainfall in Tahiti in austral summer (December-January-February). On interannual and interdecadal timescales, the El niño Southern Oscillation (ENSO) and the Interdecadal Pacific Oscillation (IPO) imply north/south and east/west migrations of the SPCZ, drawing it away, or closer to Tahiti. The positive phase of the IPO involves a north-eastward displacement of the SPCZ, which causes higher rainfall amounts in Tahiti. The SPCZ is displaced towards the south- west during negative IPO phase, leading to a decrease of rainfall in Tahiti. The study reveals that the IPO positive phase favor the occurrence of intense El niño events. In those cases, the SPCZ is critically displaced to the north-east and lies zonally just south of the equator. Accordingly, the SPCZ is drawn away from Tahiti and alters the south-east flow of trade winds. As a result, substantial orographic precipitation affect the south-east coasts of Tahiti.Following the assessment of observed precipitation for the period 1961-2011, an original method has been set up to obtain a model able to resolve the island and capture the orographic effects at best. Two successive downscaling steps have been necessary to get the limited area model ALADIN-Climat over Tahiti (at the resolution of 12 km), starting from the global coupled model CNRM-CM with a resolution of 150 km. The regional model outputs have been compared to the observed records over the historical period. A linkage between observed and modeled precipitation has been defined. This linkage has been built between meteorological stations and model grid cells exhibiting similar behaviour regarding the phases of ENSO. It has been assumed that this linkage is still relevant in the 21st century. In this way, future precipitation in Tahiti, as realistic as possible, are deduced from modeled precipitation (at 12 km of resolution), following two IPCC scenarios (RCP4.5 and RCP8.5). The El niño-like spatial structure of global warming further confirms the relevance of the linkage built previously. The results obtained concern the southern coasts of Tahiti. Rainfall would gradually increase along the 21st century, as a consequence of global warming. In Papara, the austral summer mean rainfall height is 695 mm over the period 1961-2011. The mean value, for the period 2070-2100, would be 825 mm for the scenario RCP4.5 and 814 mm for the scenario RCP8.5, let say an increase of a little less than 20%. Superimposed to this long-range raise, El niño events would induce an excess of rainfall. This effect would be reduced at the end of the 21st century in RCP8.5. Conversely, La niña events would always involve a decline of rainfall, but would not succeed in counteracting the long-range increase.

Validation of the Regional Climate Model HIRHAM with measurements, especially from radiosondes and GPS-signal-retrieval. Analysis of synoptical structures in Antarctica and comparison of the precipitation in different phases of the Antarctic Oscillation.

In this thesis, using the principles of confirmatory factor analysis (CFA) and the cause-effect concept associated with structural equation modelling (SEM), a new flexible statistical framework for evaluation of climate model simulations against observational data is suggested. The design of the framework also makes it possible to investigate the magnitude of the influence of different forcings on the temperature as well as to investigate a general causal latent structure of temperature data. In terms of the questions of interest, the framework suggested here can be viewed as a natural extension of the statistical approach of 'optimal fingerprinting', employed in many Detection and Attribution (D&amp;A) studies. Its flexibility means that it can be applied under different circumstances concerning such aspects as the availability of simulated data, the number of forcings in question, the climate-relevant properties of these forcings, and the properties of the climate model under study, in particular, those concerning the reconstructions of forcings and their implementation. It should also be added that although the framework involves the near-surface temperature as a climate variable of interest and focuses on the time period covering approximately the last millennium prior to the industrialisation period, the statistical models, included in the framework, can in principle be generalised to any period in the geological past as soon as simulations and proxy data on any continuous climate variable are available.  Within the confines of this thesis, performance of some CFA- and SEM-models is evaluated in pseudo-proxy experiments, in which the true unobservable temperature series is replaced by temperature data from a selected climate model simulation. The results indicated that depending on the climate model and the region under consideration, the underlying latent structure of temperature data can be of varying complexity, thereby rendering our statistical framework, serving as a basis for a wide range of CFA- and SEM-models, a powerful and flexible tool. Thanks to these properties, its application ultimately may contribute to an increased confidence in the conclusions about the ability of the climate model in question to simulate observed climate changes. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 2: Manuscript. Paper 3: Manuscript. Paper 3: Manuscript.</p>

Arctic sea ice has undergone a dramatic transformation in recent decades, including a substantial reduction in sea ice extent in summer months. Such changes, combined with relatively recent advancements in seasonal (1-12 months) to decadal forecasting, have prompted a rapidly-growing body of research on forecasting Arctic sea ice on seasonal timescales. These forecasts are anticipated to benefit a vast array of end-users whose activities are dependent on Arctic sea ice conditions. The research goal of this thesis is to address fundamental challenges pertaining to seasonal forecasts of Arcitc sea ice, with a particular focus placed on improving operational sea ice forecasts in the Canadian Seasonal to Interannual Prediction System (CanSIPS). Seasonal forecasts are strongly dependent on the accuracy of observations used as initial condition inputs. A key challenge initializing Arctic sea ice is the sparse availability of Arctic sea ice thickness (SIT) observations. I present on the development of three statistical models that can be used for estimating Arctic SIT in real time for sea ice forecast initialization. The three statistical models are shown to vary in their ability to capture the recent thinning of sea ice, as well as their ability to capture interannual variations in SIT anomalies; however, each of the models is shown to dramatically improve the representation of SIT compared to the climatological SIT estimates used to initialize CanSIPS. I conduct a thorough assessment of sea ice hindcast skill using the Canadian Climate Model, version 3 (one of two models used in CanSIPS), in which the dependence of hindcast skill on SIT initialization is investigated. From this assessment, it can be concluded that all three statistical models are able to estimate SIT sufficiently to improve hindcast skill relative to the climatological initialization. However, the accuracy with which the initialization fields represent both the thinning of the ice pack over time and interannual variability impacts predictive skill for pan-Arctic sea ice area (SIA) and regional sea ice concentration (SIC), with the most robust improvements obtained with two statistical models that adequately represent both processes. The final goal of this thesis is to improve the quantification of uncertainty in seasonal forecasts of regional Arctic sea ice coverage. Information regarding forecast uncertainty is crucial for end-users who want to quantify the risk associated with trusting a particular forecast. I develop statistical post-processing methodology for improving probabilistic forecasts of Arctic SIC. The first of these improvements is intended to reduce sampling uncertainty by fitting ensemble SIC forecasts to a parametric probability distribution, namely the zero- and one- inflated beta (BEINF) distribution. It is shown that overall, probabilistic forecast skill is improved using the parametric distribution relative to a simpler count-based approach; however, model biases can degrade this skill improvement. The second of these improvements is the introduction of a novel calibration method, called trend-adjusted quantile mapping (TAQM), that explicitly accounts for SIC trends and is specifically designed for the BEINF distribution. It is shown that applying TAQM greatly reduces model errors, and results in probabilistic forecast skill that generally surpasses that of a climatological reference forecast, and to some degree that of a trend-adjusted climatological reference forecast, particularly at shorter lead times. / Graduate