1. NCA-LDAS Meeting, Sept 23, 2014 NCA-LDAS: An Integrated Terrestrial Water Analysis System for the National Climate Assessment “Water Indicators” Hiroko Beaudoing Jordan Borak Mike Jasinski Sujay Kumar Bailing Li Yuqiong Liu David Mocko Matthew Rodell Meeting w/Dr. Allison Leidner NASA GSFC Sept 23, 2014

2. NCA-LDAS Meeting, Sept 23, 2014 NCA-LDAS Output Quantities (Noah) Aerodynamic conductance Albedo Canopy conductance Evaporation directly from bare soil Evaporation from snow (sublimation) Evaporation(canopy water evaporation) Evapotranspiration (total) Heat flux (ground) Heat flux (latent) Heat flux (sensible) Heat flux (snow phase-change) Humidity parameter in canopy conductance Leaf area index (0-9) Liquid soil moisture content (layer 1, 0-10 cm, non-frozen) Liquid soil moisture content (layer 2, 10-40 cm, non-frozen) Liquid soil moisture content (layer 3, 40-100 cm, non-frozen) Liquid soil moisture content (layer 4, 100-200 cm, non-frozen) Minimal stomatal resistance Plant canopy surface water Potential evaporation rate Radiation flux (surface incident longwave) Radiation flux (surface incident shortwave) Radiation flux (surface net longwave) Radiation flux (surface net shortwave) Rainfall (unfrozen precipitation) Relative soil moisture availability control factor Root zone soil moisture Runoff Snow cover Snow depth Snow melt Snow water-equivalent (accumulated) Snowfall (frozen precipitation) Soil moisture availability (root zone, 0-100 cm) Soil moisture availability (total column, 0-200 cm) Soil moisture content (layer 1, 0-10 cm) Soil moisture content (layer 2, 10-40 cm) Soil moisture content (layer 3, 40-100 cm) Soil moisture content (layer 4, 100-200 cm) Soil moisture content (top 1 meter, 0-100 cm) Soil moisture content (total column, 0-200 cm) Soil moisture parameter in canopy conductance Soil temperature (layer 1, 0-10 cm) Soil temperature (layer 2, 10-40 cm) Soil temperature (layer 3, 40-100 cm) Soil temperature (layer 4, 100-200 cm) Solar parameter in canopy conductance Subsurface runoff (baseflow) Surface runoff (non-infiltrating) Temperature (average surface skin) Temperature parameter in canopy conductance Transpiration Vegetation Water Balance Equation P = R + Et + I +  S Energy Balance Equation Rnet = Et + H + G +  H

3. NCA-LDAS Meeting, Sept 23, 2014 Evaluation of Indicators 1. Multivariate DA Evaluation Comparison of modeled outputs with in situ data and other reanalysis products: RMSE, Bias Nash Sutcliff, and the Normalized Information Contribution (NIC) metrics 1. Multivariate DA Evaluation Comparison of modeled outputs with in situ data and other reanalysis products: RMSE, Bias Nash Sutcliff, and the Normalized Information Contribution (NIC) metrics 2. Mann-Kendall Significance test Non-parametric comparison of modeled output. Evaluates trend and level of significance. 2. Mann-Kendall Significance test Non-parametric comparison of modeled output. Evaluates trend and level of significance. 3. Comparison of NCA-LDAS with other climate models E.g. Modern Era Retrospective analysis for Research and Applications (MERRA-Land; Reichle et al.,2011), Climate Forecast System Reanalysis (CFSR; Saha et al., 2010), ERA Interim (Dee et al. 2011), North American Regional Reanalysis (NARR; Mesinger et al.,2006), North American Land Data Assimilation System-2 (Xia et al. 2012), and the Global Land Data Assimilation System (Rodell et al. 2004). 3. Comparison of NCA-LDAS with other climate models E.g. Modern Era Retrospective analysis for Research and Applications (MERRA-Land; Reichle et al.,2011), Climate Forecast System Reanalysis (CFSR; Saha et al., 2010), ERA Interim (Dee et al. 2011), North American Regional Reanalysis (NARR; Mesinger et al.,2006), North American Land Data Assimilation System-2 (Xia et al. 2012), and the Global Land Data Assimilation System (Rodell et al. 2004).

4. NCA-LDAS Meeting, Sept 23, 2014 Sample Indicators

5. NCA-LDAS Meeting, Sept 23, 2014 NCA-LDAS surface forcing from NLDAS-2 (Top) all points – (Bottom) Mann-Kendall significance test with 10% confidence interval David Mocko

6. NCA-LDAS Meeting, Sept 23, 2014 Integrated Water Trend Analysis with NCA-LDAS Trends in LSM surface forcings of precipitation and temperature from NLDAS-2 data Above: Example trend analysis from CLSM with assimilation of GRACE terrestrial water storage (TWS) anomalies. (Left) Evaporation (Middle) Total runoff (Right) TWS – all units in mm/year. Trends calculated using Mann-Kendall trend test. Only areas with 10% confidence interval plotted. Noted are higher ET in the Great Plains, and higher runoff in the Northeast regions. The TWS also has a higher trend in the upper Great Plains, and a lower trend in the West region. David Mocko

7. NCA-LDAS Meeting, Sept 23, 2014 Bailing Li Modeled Trends in annual mean groundwater storage and annual precipitation Trend Significant trend Significance tested using Mann-Kendal with 10% confidence interval

8. NCA-LDAS Meeting, Sept 23, 2014 Jan-May Snowmelt/Runoff Ratio Trend (Significant) Notes: -Significance was tested using Mann-Kendal with 10% confidence interval -Data period: 1979-2012 (34 years) -Trends are in the unit of ratio/decade for snowmelt/runoff and mm/decade for precipitation Yuqiong Liu

9. NCA-LDAS Meeting, Sept 23, 2014 Trend in Mean Annual SWE (mm/yr) Noah Multi-Sensor DA, WY1980-2012 (α = 0.10)(α = 0.05)(α = 0.01) Jordan Borak

10. NCA-LDAS Meeting, Sept 23, 2014 Trend in Maximum Annual SWE (mm/yr) Noah Multi-Sensor DA, WY1980-2012 (α = 0.10)(α = 0.05)(α = 0.01) Jordan Borak

11. NCA-LDAS Meeting, Sept 23, 2014 SWE Analysis J. Borak