NCA-LDAS Meeting, Sept 23, 2014

NCA-LDAS: An Integrated Terrestrial Water Analysis System for the National Climate Assessment

“Water Indicators”

Hiroko BeaudoingJordan BorakMike JasinskiSujay KumarBailing LiYuqiong LiuDavid MockoMatthew Rodell

Meeting w/Dr. Allison LeidnerNASA GSFC

Sept 23, 2014

NCA-LDAS Meeting, Sept 23, 2014

NCA-LDASOutput 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 EquationP = R + Et + I + dS

Energy Balance EquationRnet = Et + H + G + dH

NCA-LDAS Meeting, Sept 23, 2014

Evaluation of Indicators

1. Multivariate DA EvaluationComparison of modeled outputs with in situ data and other reanalysis products:RMSE, Bias Nash Sutcliff, and the Normalized Information Contribution (NIC) metrics2. Mann-Kendall

Significance testNon-parametric comparison of modeled output. Evaluates trend and level of significance.

3. Comparison of NCA-LDAS with other climate modelsE.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).

NCA-LDAS Meeting, Sept 23, 2014

Sample Indicators

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

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

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

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

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

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

NCA-LDAS Meeting, Sept 23, 2014

SWE AnalysisJ. Borak