Tom Pruitt

Fine-resolution climate projections enhance regional climate change impact studies

A new data set enhances the abilities of researchers and decision-makers to assess possible future climates, explore societal impacts, and approach policy responses from a risk-based perspective. The data set, which consists of a library of 112 fine-resolution climate projections, based on 16 climate models and three greenhouse gas emissions scenarios, is now publicly available. Monthly climate projections from 1950 to 2099 were downscaled to a spatial resolution of ⅛° (about 140 square kilometers per grid cell) covering the conterminous United States and portions of Canada and Mexico. For the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, climate modeling groups produced hundreds of simulations of past and future climates. The colocation of these simulations in a single archive (at the Program for Climate Model Diagnosis and Intercomparison at Lawrence Livermore National Laboratory (LLNL), established to facilitate assessment of general circulation models, or GCMs) and the conversion of all results to a common data format have made probabilistic, multi-model projections and impact assessments practical. A remaining issue is that the spatial scale of climate model output is typically too coarse for regional impact studies. Multiple downscaling approaches exist for deriving regional climate from coarse-resolution model output; these approaches are typically applied on an ad hoc basis to a particular region.

An intercomparison of statistical downscaling methods used for water resource assessments in the United States

Information relevant for most hydrologic applications cannot be obtained directly from the native-scale outputs of climate models. As a result the climate model output must be downscaled, often using statistical methods. The plethora of statistical downscaling methods requires end-users to make a selection. This work is intended to provide end-users with aid in making an informed selection. We assess four commonly used statistical downscaling methods: daily and monthly disaggregated-to-daily Bias Corrected Spatial Disaggregation (BCSDd, BCSDm), Asynchronous Regression (AR), and Bias Corrected Constructed Analog (BCCA) as applied to a continental-scale domain and a regional domain (BCCAr). These methods are applied to the NCEP/NCAR Reanalysis, as a surrogate for a climate model, to downscale precipitation to a 12 km gridded observation data set. Skill is evaluated by comparing precipitation at daily, monthly, and annual temporal resolutions at individual grid cells and at aggregated scales. BCSDd and the BCCA methods overestimate wet day fraction, and underestimate extreme events. The AR method reproduces extreme events and wet day fraction well at the grid-cell scale, but over (under) estimates extreme events (wet day fraction) at aggregated scales. BCSDm reproduces extreme events and wet day fractions well at all space and time scales, but is limited to rescaling current weather patterns. In addition, we analyze the choice of calibration data set by looking at both a 12 km and a 6 km observational data set; the 6 km observed data set has more wet days and smaller extreme events than the 12 km product, the opposite of expected scaling.

How Does the Choice of Distributed Meteorological Data Affect Hydrologic Model Calibration and Streamflow Simulations

AbstractSpatially distributed historical meteorological forcings (temperature and precipitation) are commonly incorporated into modeling efforts for long-term natural resources planning. For water management decisions, it is critical to understand the uncertainty associated with the different choices made in hydrologic impact assessments (choice of hydrologic model, choice of forcing dataset, calibration strategy, etc.). This paper evaluates differences among four commonly used historical meteorological datasets and their impacts on streamflow simulations produced using the Variable Infiltration Capacity (VIC) model. The four meteorological datasets examined here have substantial differences, particularly in minimum and maximum temperatures in high-elevation regions such as the Rocky Mountains. The temperature differences among meteorological forcing datasets are generally larger than the differences between calibration and validation periods. Of the four meteorological forcing datasets considered, there ...

Hydrologic projections for the western United States

Motivated by a common interest in establishing data access for climate change impacts analysis, the U.S. Department of the Interiors Bureau of Reclamation (referred to hereinafter as Reclamation) has collaborated since 2007 with federal and nonfederal entities to provide monthly gridded precipitation and temperature data from 112 contemporary climate projections (Coupled Model Intercomparison Project Phase 3 (CMIP3)) over the contiguous United States. The grid size resolution of this downscaled data archive (publicly available at http://gdo-dcp.ucllnl.org/downscaled_cmip3_projections/) is 1/8° latitude x 1/8° longitude (approximately 12 x 12 kilometers) and covers the period 1950–2099 [Maurer et al., 2007]. Downscaling is necessary to develop hydroclimate data (e.g., precipitation and temperature) from a coarse- resolution climate model grid to a higher-resolution grid, and the CMIP3 archive was downscaled using the statistical method of bias correction. Although approximately 1000 unique users to date have downloaded the precipitation and temperature information contained within the archive (commonly referred to as the bias corrected spatially downscaled, or BCSD-CMIP3, archive), these temperature and precipitation projections have not been used to consistently generate hydrologic projections over the United States and at fine enough scale to perform hydrologic impacts analysis and support local adaptation assessments. Without available hydrologic projections, planners typically develop and apply their own site-specific and local hydrology models to fill this information gap. However, this makes consistent regional intercomparisons of hydrologic impacts of climate change difficult.

Changes in groundwater recharge under projected climate in the upper Colorado River basin

Understanding groundwater-budget components, particularly groundwater recharge, is important to sustainably manage both groundwater and surface water supplies in the Colorado River basin now and in the future. This study quantifies projected changes in upper Colorado River basin (UCRB) groundwater recharge from recent historical (1950–2015) through future (2016–2099) time periods, using a distributed-parameter groundwater recharge model with downscaled climate data from 97 Coupled Model Intercomparison Project Phase 5 climate projections. Simulated future groundwater recharge in the UCRB is generally expected to be greater than the historical average in most decades. Increases in groundwater recharge in the UCRB are a consequence of projected increases in precipitation, offsetting reductions in recharge that would result from projected increased temperatures.

Understanding the past to interpret the future: comparison of simulated groundwater recharge in the upper Colorado River basin (USA) using observed and general-circulation-model historical climate data

In evaluating potential impacts of climate change on water resources, water managers seek to understand how future conditions may differ from the recent past. Studies of climate impacts on groundwater recharge often compare simulated recharge from future and historical time periods on an average monthly or overall average annual basis, or compare average recharge from future decades to that from a single recent decade. Baseline historical recharge estimates, which are compared with future conditions, are often from simulations using observed historical climate data. Comparison of average monthly results, average annual results, or even averaging over selected historical decades, may mask the true variability in historical results and lead to misinterpretation of future conditions. Comparison of future recharge results simulated using general circulation model (GCM) climate data to recharge results simulated using actual historical climate data may also result in an incomplete understanding of the likelihood of future changes. In this study, groundwater recharge is estimated in the upper Colorado River basin, USA, using a distributed-parameter soil-water balance groundwater recharge model for the period 1951–2010. Recharge simulations are performed using precipitation, maximum temperature, and minimum temperature data from observed climate data and from 97 CMIP5 (Coupled Model Intercomparison Project, phase 5) projections. Results indicate that average monthly and average annual simulated recharge are similar using observed and GCM climate data. However, 10-year moving-average recharge results show substantial differences between observed and simulated climate data, particularly during period 1970–2000, with much greater variability seen for results using observed climate data.RésuméEn évaluant les impacts potentiels du changement climatique sur les ressources en eau, les gestionnaires de l’eau cherchent à comprendre comment les conditions futures peuvent être différentes de celles d’un passé récent. Les études des impacts du climat sur la recharge des eaux souterraines comparent souvent la recharge simulée de périodes futures et de temps historique sur une moyenne mensuelle ou sur une base moyenne annuelle, ou comparent la recharge moyenne pour des décennies à venir à celle d’une décennie récente. Les estimations de la recharge historique de référence, qui sont comparées avec les conditions futures, sont souvent de simulations utilisant des données climatiques historiques observées. La comparaison des résultats moyens mensuels, des résultats moyens annuels, ou également faisant la moyenne sur des décennies historiques sélectionnées, pourrait masquer la véritable variabilité des résultats historiques et conduire à une interprétation erronée des conditions futures. La comparaison des résultats simulés de la recharge future en utilisant les données climatiques d’un modèle de circulation globale (GCM) aux résultats simulés de la recharge en utilisant les données climatiques historiques actuelles pourraient également conduire à une compréhension incomplète de la probabilité des changements futurs. Dans cette étude, la recharge des eaux souterraines est estimée dans le bassin supérieur de la rivière Colorado, aux Etats-Unis d’Amérique, en utilisant un modèle distribué des paramètres du sol et du bilan hydrique pour calculer la recharge des eaux souterraines pour la période 1951–2010. Les simulations de recharge sont réalisées en utilisant les données de précipitation, de température maximum, et de température minimum, à partir des données climatiques observées et des projections climatiques 97 CMIP5 (Projet d’Intercomparaison de Modèle Couplé, phase 5). Les résultats montrent que les recharges moyennes mensuelles et annuelles simulées sont similaires en utilisant les données climatiques observées ou simulées GCM. Toutefois, les résultats de la recharge moyenne glissante sur 10 ans montrent des différences significatives entre les données climatiques observées et simulées, en particulier durant la période 1970–2000, avec une variabilité beaucoup plus importante constatée pour les résultats utilisant les données climatiques observées.ResumenEn la evaluación de los posibles impactos del cambio climático sobre los recursos hídricos, los gestores del agua tratan de comprender cómo las futuras condiciones pueden diferir de las del pasado reciente. Los estudios de los impactos del clima sobre la recarga de agua subterránea a menudo comparan recargas simuladas a partir de períodos de tiempo futuros e históricos sobre una base promedios mensuales o anuales globales, o comparan la recarga media de las próximas décadas a que a partir de una sola década reciente. Las estimaciones de recarga histórica a partir de una línea de base, que se comparan con las condiciones futuras, son a menudo a partir de simulaciones utilizando datos climáticos históricos observados. La comparación de los resultados de promedio mensuales, los resultados de promedios anuales, o incluso un promedio histórico de más décadas seleccionadas, pueden enmascarar la verdadera variabilidad en los resultados históricos y dar lugar a una interpretación errónea de las condiciones futuras. La comparación de los futuros resultados de recarga simulados utilizando los datos climáticos del modelo de circulación general (GCM) con los resultados simulados utilizando datos climáticos históricos reales también puede dar lugar a una comprensión incompleta de la probabilidad de los cambios futuros. En este estudio se estima la recarga del agua subterránea en la cuenca alta del río Colorado, EEUU, utilizando un modelo de balance de agua del suelo de parámetro distribuido de recarga del agua subterránea para el período 1951–2010. Las simulaciones de la recarga se llevan a cabo utilizando los datos de precipitación, temperatura máxima y mínima a partir de datos climáticos observados y de proyecciones del 97 CMIP5 (Coupled Model Intercomparison Project, phase 5). Los resultados indican que la recarga promedio mensual y anual simulada son similares utilizando datos climáticos observados y el GCM. Sin embargo, utilizando los promedios móviles de 10 años los resultados de la recarga muestran diferencias sustanciales entre los datos climáticos observados y simulados, sobre todo durante período 1970–2000, apreciándose una mucho mayor variabilidad para los resultados a partir de los datos climáticos observados.摘要在评估气候变化对水资源的潜在影响中,水管理者寻求了解未来状况与近期有何不同。研究气候对地下水补给的影响常常在平均每月基础上或者每年基础上比较未来和历史时期的模拟补给量,或者比较未来几十年到最近10年的平均补给量。基线历史补给估算值与未来状况进行了比较,这个估算值常常通过采用观测的历史气候资料进行模拟而获取。平均月度结果、平均年度结果、或者甚至过去所选择的历史上数十年的平均数比较可能会掩盖历史结果的真实变化性,并且导致错误解译未来的状况。采用综合循环模型(GCM)气候资料模拟的未来补给结果与采用实际历史气候资料模拟的补给结果比较也可能会导致不能完全了解未来变化的可能性。在本项研究中,采用分布参数土壤-水平衡地下水补给模型对1951年到2010年间美国上科罗拉多河流域的地下水补给量进行了估算。利用观测的气候资料中以及97 CMIP5(耦合模型相互比较项目,第五阶段)预测结果中的降水、最高温度和最低温度资料进行了补给模拟实验。结果显示,采用观测的和综合循环模型气候资料所模拟的平均月度和平均年度补给量类似。然而,10年移动平均补给结果显示,观测的和气候资料模拟的气候资料有很大差别,特别是在1970–2000期间,采用观测的气候资料获取的结果有更大的变化性。ResumoNa avaliação de potenciais impactos da mudança climática nos recursos hídricos, a gestão de recursos hídricos busca entender como as condições futuras podem diferir do passado recente. Estudos sobre o impacto climático na recarga das águas subterrâneas geralmente comparam a recarga simulada de períodos futuros e históricos com base em uma média mensal ou média anual, ou camparam a recarga média de décadas futuras com aquela de uma única década recente. Estimativas da recarga histórica de referência, que são comparadas com condições futuras, são geralmente de simulação usando dados climáticos históricos observados. A comparação de resultados de médias mensais, resultados de médias anuais ou ainda calculando a média sobre décadas históricas selecionadas, podem mascarar a real variabilidade nos resultados históricos e levar a interpretação equivocada das condições futuras. A comparação resultados simulados da recarga futura usando dados climáticos de modelo de circulação geral (MCG) com resultados simulados da recarga usando dados climáticos históricos atuais também podem resultar em um entendimento incompleto das chances de futuras mudanças. Nesse estudo, a recarga das águas subterrâneas é estimada na bacia superior do Rio Colorado, EUA, usando o modelo de recarga das águas subterrâneas de balanço solo-água com parâmetros distribuídos para o período 1951–2000. Simulações da recarga foram feitas usando dados de precipitação, temperatura máxima e temperatura mínima a partir de dados climáticos observados e das projeções 97 CMIP5 (Coupled Model Intercomparison Project, phase 5). Os resultados indicam que a recarga média simulada mensalmente e anualmente são similares usando dados climáticos observados e do MCG. Entretanto, os resultados da recarga com uma média móvel de 10 anos mostraram diferenças substanciais entre os dados climáticos observados e simulados, particularmente durante o período 1970–2000, com variabilidade visível muito maior para os resultados usando dados climáticos observados.

Analyses of infrequent (quasi‐decadal) large groundwater recharge events in the northern Great Basin: Their importance for groundwater availability, use, and management

There has been a considerable amount of research linking climatic variability to hydrologic responses in the western United States. Although much effort has been spent to assess and predict changes in surface-water resources, little has been done to understand how climatic events and changes affect groundwater resources. This study focuses on characterizing and quantifying the effects of large, multi-year, quasi-decadal groundwater recharge events in the northern Utah portion of the Great Basin for the period 1960 to 2013. Annual groundwater level data were analyzed with climatic data to characterize climatic conditions and frequency of these large recharge events. Using observed water-level changes and multivariate analysis, five large groundwater recharge events were identified with a frequency of about 11 to 13 years. These events were generally characterized as having above-average annual precipitation and snow water equivalent and below-average seasonal temperatures, especially during the spring (April through June). Existing groundwater flow models for several basins within the study area were used to quantify changes in groundwater storage from these events. Simulated groundwater storage increases per basin from a single recharge event ranged from about 115 Mm3 to 205 Mm3. Extrapolating these amounts over the entire northern Great Basin indicates that a single large quasi-decadal recharge event could result in billions of cubic meters of groundwater storage. Understanding the role of these large quasi-decadal recharge events in replenishing aquifers and sustaining water supplies is crucial for long-term groundwater management. This article is protected by copyright. All rights reserved.