Climate variables

Time of Emergence results are currently available for the climate variables listed in Table 1. Some of these may be for general purposes; others may be proxies for a critical ecological or regulatory threshold, design standards, management or operating criteria associated with drought, energy, fish, flood, human health, infrastructure, streamflow and water quality. These variables were selected in collaboration with regional stakeholders and derived from existing regional climate change projections.

Table 1. Variables analyzed for Time of Emergence and source of relevant input datasets [method of calculation]
Climate variable Variable ID Input dataset
Temperature-related variables    
Temperature, each calendar month [monthly average of daily average temperature] T_month BCSD5, BCSD3, ECHAM5-WRF
Number of days with daily maximum temperature above 65°F (18.3°C), each calendar month (Mar-Nov) #Tmax>65degF_month BCSD5, BCSD3, ECHAM5-WRF
Number of days with daily average temperature below 25°F (–3.9°C), winter (Dec-Feb) #Tavg<25degF_DecFeb BCSD5, BCSD3, ECHAM5-WRF
Number of days with daily average temperature above 68°F (20°C), spring (Mar-May) and fall (Sep-Nov) #Tavg>68degF_months BCSD5, BCSD3, ECHAM5-WRF
Number of days with daily maximum temperature above 90°F (32.2°C), annual  #Tavg>90degF BCSD5, BCSD3, ECHAM5-WRF
Number of days with daily maximum temperature at or above 80°F (26.7°C), spring-summer (21 April-21 August)  #Tmax≥80degF_Apr-Aug BCSD5, BCSD3, ECHAM5-WRF
Number of daytime heat waves (3 consecutive days with daily maximum temperature above historical 99th percentile), annual #3dTmax>99th BCSD5, BCSD3, ECHAM5-WRF
Number of nighttime heat waves (3 consecutive days with daily minimum temperature above historical 99th percentile), annual #3dTmin>99th BCSD5, BCSD3, ECHAM5-WRF
Precipitation-related variables    
Precipitation, each calendar month [monthly average of daily average precipitation] P_month BCSD5, BCSD3, ECHAM5-WRF
Precipitation, fall (Oct-Dec), winter (Jan-Mar), spring (Apr-Jun), and summer (Jul-Sep) [seasonal average of daily precipitation] P_months BCSD5, BCSD3, ECHAM5-WRF
Number of days with 24-hour precipitation exceeding historical 90th percentile, October-March Pwet>90th_OctMar BCSD5, BCSD3, ECHAM5-WRF
Number of days with 24-hour precipitation exceeding historical 95th percentile, October-March Pwet>95th_OctMar BCSD5, BCSD3, ECHAM5-WRF
Number of days with 24-hour precipitation exceeding historical 99th percentile, October-March Pwet>99th_OctMar BCSD5, BCSD3, ECHAM5-WRF
Number of days with 24-hour precipitation exceeding 2 inches (50.8 mm), annual #24hP>2" BCSD5, BCSD3, ECHAM5-WRF
Maximum 48-hour precipitation accumulation, annual 48hPmax BCSD5, BCSD3, ECHAM5-WRF
Maximum 24-hour precipitation accumulation, annual 24hPmax BCSD5, BCSD3, ECHAM5-WRF
Number of days with 24-hour precipitation equal to 3 inches (76.2 mm) or more, annual  #24hP≥3" BCSD5, BCSD3, ECHAM5-WRF
Number of wet sequences (18-day cumulative precipitation exceeding 3.5 inches (88.9 mm)), October-March  #18dPwet>3.5"_OctMar BCSD5, BCSD3, ECHAM5-WRF
Hydrologic variables    
Runoff, annual [annual average of daily runoff] Qcombined BCSD3, ECHAM5-WRF 
Runoff, each calendar month [monthly average of daily runoff] Qcombined_month BCSD3, ECHAM5-WRF 
Dryness ratio (fraction of input precipitation lost to evapotranspiration), each calendar month [fraction of input precipitation lost to evapotranspiration] Dryness_month BCSD3, ECHAM5-WRF 
Potential evapotranspiration (PET), each calendar month [calculated by VIC using Penman-Monteith equation where there is assigned natural vegetation and no water limit] PET_month BCSD3, ECHAM5-WRF 
Actual evapotranspiration (AET), each calendar month [calculated by VIC using calculated sum of evaporation and plant transpiration equation] AET_month BCSD3, ECHAM5-WRF 
Soil moisture, each calendar month  Soil_month BCSD3, ECHAM5-WRF 
Snow water equivalent (SWE), each calendar month SWE_month BCSD3, ECHAM5-WRF 
Coefficient of variation of runoff, annual [annual runoff standard deviation divided by annual mean] RunoffCV BCSD3, ECHAM5-WRF 
Highest spring runoff date  SpringRunoff BCSD3, ECHAM5-WRF 
Streamflow-related variables    
Streamflow, each calendar month Stream_month BCSD5, BCSD3
Streamflow center of timing [number of days from 1st of October at which 50% of the year's flow volume for that water year has passed] Centroid BCSD5, BCSD3
Maximum daily streamflow per year Qmax BCSD5, BCSD3
Maximum daily streamflow, each calendar month Qmax_month BCSD5, BCSD3
Minimum daily streamflow, each calendar month Qmin_month BCSD5, BCSD3
Number of flood flows per year [number of days per year where flow is more than historical (1950-1999) 90th percentile (high) flow] #Qflood BCSD5, BCSD3
Number of 7-day low flows per year [number of days per year where the consecutive average 7-day flow is less than historical (1950-1999) 10th percentile (low) flow] #Q7low BCSD5, BCSD3
Number of low flows per year [number of days per year where flow is less than historical (1950-1999) 10th percentile (low) flow] #Qlow BCSD5, BCSD3
Lowest mean streamflow for 30 consecutive days per year 30dLow BCSD5, BCSD3

BCSD5: Bias-Corrected Statistically Downscaled CMIP5 projections.

BCSD3: Bias-Corrected Statistically Downscaled CMIP3 projections.

WRF: Dynamically-downscaled projections from a single CMIP3 global climate model.

See Input Datasets for more information

 

How were these climate variables identified?

Selection criteria included: stakeholder interest, key regional climate vulnerabilities, data availability, and suitability for Time of Emergence analysis.

Specifically, identifying a list of candidate variables for Time of Emergence analysis involved consideration of:

  • The potential impacts caused by climate change (such as droughts, floods, human health, energy supply, water availability, fish survival) that could have implications for stakeholders’ planning, management, operations or regulatory responsibilities.
  • The underlying climate drivers of these climate change impacts.
  • PNW stakeholders’ existing or anticipated vulnerabilities, concerns and priorities as climate changes.

How regional stakeholders are addressing or plan to address the issues or potential impacts related to climate change.

  • Availability of climate change projections – either already available within the relevant existing downscaled climate and hydrology datasets or feasibly derived therefrom using techniques established in the literature

Variable identification proceeded by the combined efforts of:

  • Consultation with regional stakeholders, including federal, state and local government agencies, and tribal entities
  • Review of peer-reviewed publications on projected PNW climate change and climate impacts
  • Review of information prepared by, and for, specific stakeholders: goals and strategies, official and unofficial documents, climate change-related studies, regulatory standards, guidelines and mandates.

 

How were the streamflow locations selected?

Time of Emergence results are currently available for streamflow-related variables at 96 locations (~50 from each of the BCSD5 and BCSD3 datasets; Figure 1). These locations were selected for analysis using the following criteria:

1.     Locations common to both datasets (i.e., within 5 km)

2.     Locations close to (~50 km) the Puget Sound Basin

3.     Locations showing diversity in watershed type, for example, rain dominant vs. snow dominant

 

Figure 1. Streamflow locations for Time of Emergence analysis of streamflow-related variables listed in Table 1. CMIP3 and CMIP5 indicate source datasets described in the text as BCSD3 and BCSD5, respectively.

 

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The Time of Emergence project was conceived and funded by U.S. Army Corps of Engineers Climate Preparedness & Resilience programs & U.S. Environmental Protection Agency-Region 10. Methodologies and stakeholder engagement were developed and implemented by the University of Washington's Climate Impacts Group. The Time of Emergence online tool was developed with support from the Center for Data Science, University of Washington-Tacoma.