scholarly journals A hydrogeologic framework for characterizing summer streamflow sensitivity to climate warming in the Pacific Northwest, USA

2014 ◽  
Vol 18 (9) ◽  
pp. 3693-3710 ◽  
Author(s):  
M. Safeeq ◽  
G. E. Grant ◽  
S. L. Lewis ◽  
M. G. Kramer ◽  
B. Staab
Keyword(s):  
Pacific Northwest ◽  
General Circulation ◽  
Large Scale ◽  
Regional Scale ◽  
Climate Scenario ◽  
General Circulation Models ◽  
Hydrologic Models ◽  
Empirical Measures ◽  
The Pacific ◽  
Hydrogeologic Framework

Abstract. Summer streamflows in the Pacific Northwest are largely derived from melting snow and groundwater discharge. As the climate warms, diminishing snowpack and earlier snowmelt will cause reductions in summer streamflow. Most regional-scale assessments of climate change impacts on streamflow use downscaled temperature and precipitation projections from general circulation models (GCMs) coupled with large-scale hydrologic models. Here we develop and apply an analytical hydrogeologic framework for characterizing summer streamflow sensitivity to a change in the timing and magnitude of recharge in a spatially explicit fashion. In particular, we incorporate the role of deep groundwater, which large-scale hydrologic models generally fail to capture, into streamflow sensitivity assessments. We validate our analytical streamflow sensitivities against two empirical measures of sensitivity derived using historical observations of temperature, precipitation, and streamflow from 217 watersheds. In general, empirically and analytically derived streamflow sensitivity values correspond. Although the selected watersheds cover a range of hydrologic regimes (e.g., rain-dominated, mixture of rain and snow, and snow-dominated), sensitivity validation was primarily driven by the snow-dominated watersheds, which are subjected to a wider range of change in recharge timing and magnitude as a result of increased temperature. Overall, two patterns emerge from this analysis: first, areas with high streamflow sensitivity also have higher summer streamflows as compared to low-sensitivity areas. Second, the level of sensitivity and spatial extent of highly sensitive areas diminishes over time as the summer progresses. Results of this analysis point to a robust, practical, and scalable approach that can help assess risk at the landscape scale, complement the downscaling approach, be applied to any climate scenario of interest, and provide a framework to assist land and water managers in adapting to an uncertain and potentially challenging future.

scholarly journals A geohydrologic framework for characterizing summer streamflow sensitivity to climate warming in the Pacific Northwest, USA

2014 ◽  
Vol 11 (3) ◽  
pp. 3315-3357 ◽  
Author(s):  
M. Safeeq ◽  
G. E. Grant ◽  
S. L. Lewis ◽  
M. G. Kramer ◽  
B. Staab
Keyword(s):  
Pacific Northwest ◽  
General Circulation ◽  
Climate Scenario ◽  
General Circulation Models ◽  
Analytical Framework ◽  
Deep Aquifers ◽  
Temperature And Precipitation ◽  
The Pacific ◽  
Streamflow Response ◽  
Low Sensitivity

Abstract. Summer streamflows in the Pacific Northwest are largely derived from melting snow and groundwater discharge. As the climate warms, diminishing snowpack and earlier snowmelt will cause reductions in summer streamflow. Most assessments of the impacts of a changing climate to streamflow make use of downscaled temperature and precipitation projections from General Circulation Models (GCMs). Projected climate simulations from these GCMs are often too coarse for planning purposes, as they do not capture smaller scale topographic controls and other important watershed processes. This uncertainty is further amplified when downscaled climate predictions are coupled to macroscale hydrologic models that fail to capture streamflow contributions from deep groundwater. Deep aquifers play an important role in mediating streamflow response to climate change, and groundwater needs to be explicitly incorporated into sensitivity assessments. Here we develop and apply an analytical framework for characterizing summer streamflow sensitivity to a change in the timing and magnitude of recharge in a spatially-explicit fashion. Two patterns emerge from this analysis: first, areas with high streamflow sensitivity also have higher summer streamflows as compared to low sensitivity areas. Second, the level of sensitivity and spatial extent of highly sensitive areas diminishes over time as the summer progresses. Results of this analysis point to a robust, practical, and scalable approach that can help assess risk at the landscape scale, complement the downscaling approach, be applied to any climate scenario of interest, and provide a framework to assist land and water managers adapt to an uncertain and potentially challenging future.

scholarly journals Comparing Large-Scale Hydrological Model Predictions with Observed Streamflow in the Pacific Northwest: Effects of Climate and Groundwater*

2014 ◽  
Vol 15 (6) ◽  
pp. 2501-2521 ◽  
Author(s):  
Mohammad Safeeq ◽  
Guillaume S. Mauger ◽  
Gordon E. Grant ◽  
Ivan Arismendi ◽  
Alan F. Hamlet ◽  
...  
Keyword(s):  
Pacific Northwest ◽  
Large Scale ◽  
Model Performance ◽  
Rank Correlation ◽  
Hydrologic Models ◽  
Infiltration Capacity ◽  
Vic Model ◽  
Temperature And Precipitation ◽  
Model Parameterization ◽  
The Pacific

Abstract Assessing uncertainties in hydrologic models can improve accuracy in predicting future streamflow. Here, simulated streamflows using the Variable Infiltration Capacity (VIC) model at coarse (°) and fine (°) spatial resolutions were evaluated against observed streamflows from 217 watersheds. In particular, the adequacy of VIC simulations in groundwater- versus runoff-dominated watersheds using a range of flow metrics relevant for water supply and aquatic habitat was examined. These flow metrics were 1) total annual streamflow; 2) total fall, winter, spring, and summer season streamflows; and 3) 5th, 25th, 50th, 75th, and 95th flow percentiles. The effect of climate on model performance was also evaluated by comparing the observed and simulated streamflow sensitivities to temperature and precipitation. Model performance was evaluated using four quantitative statistics: nonparametric rank correlation ρ, normalized Nash–Sutcliffe efficiency NNSE, root-mean-square error RMSE, and percent bias PBIAS. The VIC model captured the sensitivity of streamflow for temperature better than for precipitation and was in poor agreement with the corresponding temperature and precipitation sensitivities derived from observed streamflow. The model was able to capture the hydrologic behavior of the study watersheds with reasonable accuracy. Both total streamflow and flow percentiles, however, are subject to strong systematic model bias. For example, summer streamflows were underpredicted (PBIAS = −13%) in groundwater-dominated watersheds and overpredicted (PBIAS = 48%) in runoff-dominated watersheds. Similarly, the 5th flow percentile was underpredicted (PBIAS = −51%) in groundwater-dominated watersheds and overpredicted (PBIAS = 19%) in runoff-dominated watersheds. These results provide a foundation for improving model parameterization and calibration in ungauged basins.

scholarly journals A global satellite view of aerosol cloud interactions

2004 ◽  
Vol 4 (5) ◽  
pp. 6823-6836 ◽  
Author(s):  
C. Luo
Keyword(s):  
North Africa ◽  
North Atlantic ◽  
Radiative Forcing ◽  
General Circulation ◽  
Large Scale ◽  
Regional Scale ◽  
Cloud Amount ◽  
General Circulation Models ◽  
Aerosol Cloud ◽  
Aerosol Cloud Interactions

Abstract. Long-term and large-scale correlations between Advanced Very High-Resolution Radiometer (AVHRR) aerosol optical depth and International Satellite Cloud Climatology Project (ISCCP) monthly cloud amount data show significant regional scale relationships between cloud amount and aerosols, consistent with aerosol-cloud interactions. Positive correlations between aerosols and cloud amount are associated with North American and Asian aerosols in the North Atlantic and Pacific storm tracks, and mineral aerosols in the tropical North Atlantic. Negative correlations are seen near biomass burning regions of North Africa and Indonesia, as well as south of the main mineral aerosol source of North Africa. These results suggest that there are relationships between aerosols and clouds in the observations that can be used by general circulation models to verify the correct forcing mechanisms for both direct and indirect radiative forcing by clouds.

scholarly journals Impact of 2000–2050 climate change on fine particulate matter (PM<sub>2.5</sub>) air quality inferred from a multi-model analysis of meteorological modes

2012 ◽  
Vol 12 (23) ◽  
pp. 11329-11337 ◽  
Author(s):  
A. P. K. Tai ◽  
L. J. Mickley ◽  
D. J. Jacob
Keyword(s):  
Climate Change ◽  
Particulate Matter ◽  
Air Quality ◽  
Pacific Northwest ◽  
General Circulation ◽  
Fine Particulate Matter ◽  
Weighted Average ◽  
General Circulation Models ◽  
Fine Particulate ◽  
The Pacific

Abstract. Studies of the effect of climate change on fine particulate matter (PM2.5 air quality using general circulation models (GCMs) show inconsistent results including in the sign of the effect. This reflects uncertainty in the GCM simulations of the regional meteorological variables affecting PM2.5. Here we use the CMIP3 archive of data from fifteen different IPCC AR4 GCMs to obtain improved statistics of 21st-century trends in the meteorological modes driving PM2.5 variability over the contiguous US. We analyze 1999–2010 observations to identify the dominant meteorological modes driving interannual PM2.5 variability and their synoptic periods T. We find robust correlations (r > 0.5) of annual mean PM2.5 with T, especially in the eastern US where the dominant modes represent frontal passages. The GCMs all have significant skill in reproducing present-day statistics for T and we show that this reflects their ability to simulate atmospheric baroclinicity. We then use the local PM2.5-to-period sensitivity (dPM2.5/dT) from the 1999–2010 observations to project PM2.5 changes from the 2000–2050 changes in T simulated by the 15 GCMs following the SRES A1B greenhouse warming scenario. By weighted-average statistics of GCM results we project a likely 2000–2050 increase of ~ 0.1 μg m−3 in annual mean PM2.5 in the eastern US arising from less frequent frontal ventilation, and a likely decrease albeit with greater inter-GCM variability in the Pacific Northwest due to more frequent maritime inflows. Potentially larger regional effects of 2000–2050 climate change on PM2.5 may arise from changes in temperature, biogenic emissions, wildfires, and vegetation, but are still unlikely to affect annual PM2.5 by more than 0.5 μg m−3.

scholarly journals Analog Downscaling of Seasonal Rainfall Forecasts in the Murray Darling Basin

2013 ◽  
Vol 141 (3) ◽  
pp. 1099-1117 ◽  
Author(s):  
Andrew Charles ◽  
Bertrand Timbal ◽  
Elodie Fernandez ◽  
Harry Hendon
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Seasonal Prediction ◽  
General Circulation Models ◽  
Meridional Wind ◽  
Seasonal Forecasts ◽  
Local Climate ◽  
Continental Scale ◽  
Predictive Skill ◽  
Murray Darling Basin

Abstract Seasonal predictions based on coupled atmosphere–ocean general circulation models (GCMs) provide useful predictions of large-scale circulation but lack the conditioning on topography required for locally relevant prediction. In this study a statistical downscaling model based on meteorological analogs was applied to continental-scale GCM-based seasonal forecasts and high quality historical site observations to generate a set of downscaled precipitation hindcasts at 160 sites in the South Murray Darling Basin region of Australia. Large-scale fields from the Predictive Ocean–Atmosphere Model for Australia (POAMA) 1.5b GCM-based seasonal prediction system are used for analog selection. Correlation analysis indicates modest levels of predictability in the target region for the selected predictor fields. A single best-match analog was found using model sea level pressure, meridional wind, and rainfall fields, with the procedure applied to 3-month-long reforecasts, initialized on the first day of each month from 1980 to 2006, for each model day of 10 ensemble members. Assessment of the total accumulated rainfall and number of rainy days in the 3-month reforecasts shows that the downscaling procedure corrects the local climate variability with no mean effect on predictive skill, resulting in a smaller magnitude error. The amount of total rainfall and number of rain days in the downscaled output is significantly improved over the direct GCM output as measured by the difference in median and tercile thresholds between station observations and downscaled rainfall. Confidence in the downscaled output is enhanced by strong consistency between the large-scale mean of the downscaled and direct GCM precipitation.

scholarly journals The MJO in a Coarse-Resolution GCM with a Stochastic Multicloud Parameterization

2015 ◽  
Vol 72 (1) ◽  
pp. 55-74 ◽  
Author(s):  
Qiang Deng ◽  
Boualem Khouider ◽  
Andrew J. Majda
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Deterministic Model ◽  
Weather Prediction ◽  
General Circulation Models ◽  
Radar Data ◽  
Equation Model ◽  
Death Process ◽  
Relevant Parameter ◽  
Convective Systems

Abstract The representation of the Madden–Julian oscillation (MJO) is still a challenge for numerical weather prediction and general circulation models (GCMs) because of the inadequate treatment of convection and the associated interactions across scales by the underlying cumulus parameterizations. One new promising direction is the use of the stochastic multicloud model (SMCM) that has been designed specifically to capture the missing variability due to unresolved processes of convection and their impact on the large-scale flow. The SMCM specifically models the area fractions of the three cloud types (congestus, deep, and stratiform) that characterize organized convective systems on all scales. The SMCM captures the stochastic behavior of these three cloud types via a judiciously constructed Markov birth–death process using a particle interacting lattice model. The SMCM has been successfully applied for convectively coupled waves in a simplified primitive equation model and validated against radar data of tropical precipitation. In this work, the authors use for the first time the SMCM in a GCM. The authors build on previous work of coupling the High-Order Methods Modeling Environment (HOMME) NCAR GCM to a simple multicloud model. The authors tested the new SMCM-HOMME model in the parameter regime considered previously and found that the stochastic model drastically improves the results of the deterministic model. Clear MJO-like structures with many realistic features from nature are reproduced by SMCM-HOMME in the physically relevant parameter regime including wave trains of MJOs that organize intermittently in time. Also one of the caveats of the deterministic simulation of requiring a doubling of the moisture background is not required anymore.

scholarly journals Cloud and Precipitation Parameterizations in Modeling and Variational Data Assimilation: A Review

2007 ◽  
Vol 64 (11) ◽  
pp. 3766-3784 ◽  
Author(s):  
Philippe Lopez
Keyword(s):  
Data Assimilation ◽  
General Circulation ◽  
Large Scale ◽  
Weather Prediction ◽  
General Circulation Models ◽  
Variational Data Assimilation ◽  
Current Status ◽  
General Question ◽  
Observation Error ◽  
Moist Processes

Abstract This paper first reviews the current status, issues, and limitations of the parameterizations of atmospheric large-scale and convective moist processes that are used in numerical weather prediction and climate general circulation models. Both large-scale (resolved) and convective (subgrid scale) moist processes are dealt with. Then, the general question of the inclusion of diabatic processes in variational data assimilation systems is addressed. The focus is put on linearity and resolution issues, the specification of model and observation error statistics, the formulation of the control vector, and the problems specific to the assimilation of observations directly affected by clouds and precipitation.

scholarly journals Precipitation in the Amazon and its relationship with moisture transport and tropical Pacific and Atlantic SST from the CMIP5 simulation

2015 ◽  
Vol 12 (1) ◽  
pp. 671-704 ◽  
Author(s):  
G. Martins ◽  
C. von Randow ◽  
G. Sampaio ◽  
A. J. Dolman
Keyword(s):  
Moisture Transport ◽  
General Circulation ◽  
Regional Analysis ◽  
Coupled Model ◽  
General Circulation Models ◽  
Moisture Convergence ◽  
Cmip5 Models ◽  
Wet Season ◽  
The Pacific ◽  
Eastern Edge

Abstract. Studies on numerical modeling in Amazonia show that the models fail to capture important aspects of climate variability in this region and it is important to understand the reasons that cause this drawback. Here, we study how the general circulation models of the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulate the inter-relations between regional precipitation, moisture convergence and Sea Surface Temperature (SST) in the adjacent oceans, to assess how flaws in the representation of these processes can translate into biases in simulated rainfall in Amazonia. Using observational data (GPCP, CMAP, ERSST.v3, ERAI and evapotranspiration) and 21 numerical simulations from CMIP5 during the present climate (1979–2005) in June, July and August (JJA) and December, January and February (DJF), respectively, to represent dry and wet season characteristics, we evaluate how the models simulate precipitation, moisture transport and convergence, and pressure velocity (omega) in different regions of Amazonia. Thus, it is possible to identify areas of Amazonia that are more or less influenced by adjacent ocean SSTs. Our results showed that most of the CMIP5 models have poor skill in adequately representing the observed data. The regional analysis of the variables used showed that the underestimation in the dry season (JJA) was twice in relation to rainy season as quantified by the Standard Error of the Mean (SEM). It was found that Atlantic and Pacific SSTs modulate the northern sector of Amazonia during JJA, while in DJF Pacific SST only influences the eastern sector of the region. The analysis of moisture transport in JJA showed that moisture preferentially enters Amazonia via its eastern edge. In DJF this occurs both via its northern and eastern edge. The moisture balance is always positive, which indicates that Amazonia is a source of moisture to the atmosphere. Additionally, our results showed that during DJF the simulations in northeast sector of Amazonia have a strong bias in precipitation and an underestimation of moisture convergence due to the higher influence of biases in the Pacific SST. During JJA, a strong precipitation bias was observed in the southwest sector associated, also with a negative bias of moisture convergence, but with weaker influence of SSTs of adjacent oceans. The poor representation of precipitation-producing systems in Amazonia by the models and the difficulty of adequately representing the variability of SSTs in the Pacific and Atlantic oceans may be responsible for these underestimates in Amazonia.

scholarly journals Causes of the Record-Breaking Pacific Northwest Heatwave, Late June 2021

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1434
Author(s):  
James E. Overland
Keyword(s):  
Pacific Northwest ◽  
Large Scale ◽  
Polar Vortex ◽  
The Arctic ◽  
Large Temperature ◽  
Extreme Heat Event ◽  
The Pacific ◽  
Heat Event ◽  
Large Scale Atmospheric Circulation ◽  
The Bering Sea

The extreme heat event that hit the Pacific Northwest (Oregon, Washington, southern British Columbia) at the end of June 2021 was 3 °C greater than the previous Seattle record of 39 °C; larger extremes of 49 °C were observed further inland that were 6 °C above previous record. There were hundreds of deaths over the region and loss of marine life and forests. At the large scale prior to the event, the polar vortex was split over the Arctic. A polar vortex instability center formed over the Bering Sea and then extended southward along the west coast of North America. The associated tropospheric trough (low geopotential heights) established a multi-day synoptic scale Omega Block (west-east oriented low/high/low geopotential heights) centered over the Pacific Northwest. Warming was sustained in the region due to subsidence/adiabatic heating and solar radiation, which were the main reasons for such large temperature extremes. The seasonal transition at the end of spring suggests the possibility of a southern excursion of a polar vortex/jet stream pair. Both the Pacific Northwest event in 2021 and the Siberian heatwave climax in June 2020 may be examples of crossing a critical state in large-scale atmospheric circulation variability.

scholarly journals Origins of Wilson’s Warblers migrating through southwest Canada: Adding value to banding data by using stable isotopes and genetic markers

2018 ◽  
Vol 5 (1) ◽  
pp. 17-28 ◽  
Author(s):  
Kevin J. Kardynal ◽  
Douglas M. Collister ◽  
Keith A. Hobson
Keyword(s):  
Pacific Northwest ◽  
Large Scale ◽  
Rocky Mountain ◽  
Population Changes ◽  
Stopover Site ◽  
Future Studies ◽  
The Pacific ◽  
Catchment Areas ◽  
Other Information ◽  
Northwestern North America

Abstract Stopovers used by birds during migration concentrate individuals from broad geographic areas potentially providing important information on catchment areas of birds moving through these sites. We combined stable isotope (δ2H), genetic fingerprinting and band recovery data to delineate the molt origins of Wilson’s Warblers (Cardellina pusilla) migrating through a stopover site in southwestern Canada in the fall. We assessed changes in δ2Hf indicating latitudinal origins with ordinal date to show this species likely underwent leapfrog migration through this site. Using the combined approach to determine origins, Wilson’s Warblers migrating through southwestern Alberta in 2015 were mostly from the western boreal population (n = 155, 96%) with some individuals from the Pacific Northwest (n = 1, 0.6%), Rocky Mountain (n = 2, 1.2%) and eastern boreal (n = 3, 1.8%) populations. Our results suggest that individuals migrating through our study site come from a broad catchment area potentially from a large part of northwestern North America. Future studies should link population changes at banding stations with other information to determine associations with large-scale landscape-level drivers (e.g. climate, land use).

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