Arctic Land Surface Arctic Land Surface Hydrology:Hydrology:Moving Towards a SynthesisMoving Towards a Synthesis

Global DatasetsGlobal Datasets

Available DatasetsAvailable Datasets

ERA-40 ReanalysisERA-40 Reanalysis NCEP-NCAR ReanalysisNCEP-NCAR Reanalysis Remote sensing dataRemote sensing data Global Runoff Data Center (GRDC, UNH)Global Runoff Data Center (GRDC, UNH) Global River Discharge Database Global River Discharge Database

(RivDis, UNH)(RivDis, UNH) Adam Adam et al. et al. (2006) Precipitation Dataset(2006) Precipitation Dataset Sheffield Sheffield et al.et al. (2006) 50-yr (2006) 50-yr

Meteorological ForcingsMeteorological Forcings

PGF50PGF501948-2000, 3hr, daily, 1.0deg1948-2000, 3hr, daily, 1.0degP, T, Lw, Sw, q, p, wP, T, Lw, Sw, q, p, w

CRUCRU1901-2000, Monthly, 0.5deg1901-2000, Monthly, 0.5degP, T, Tmin, Tmax, CldP, T, Tmin, Tmax, Cld

GPCPGPCP1997-, Daily, 1.0deg1997-, Daily, 1.0degPP

UWUW1979-2000, Daily, 2.0deg1979-2000, Daily, 2.0degPP

TRMMTRMM2002-, 3hr, 0.25deg2002-, 3hr, 0.25degPP

SRBSRB1985-2000, 3hr, 1.0deg1985-2000, 3hr, 1.0degLw, SwLw, Sw

NCEP/NCAR ReanalysisNCEP/NCAR Reanalysis1948-, 3hr, 6hr, daily, T621948-, 3hr, 6hr, daily, T62P, T, Lw, Sw, q, p, wP, T, Lw, Sw, q, p, w

ReanalysisReanalysisHigh temporal/low High temporal/low spatial resolutionspatial resolution

ObservationsObservationsGenerally low temporal/high Generally low temporal/high

spatial resolutionspatial resolution

Bias-CorrectedBias-CorrectedHigh temporal/high High temporal/high

spatial resolutionspatial resolution

Global Forcing DatasetGlobal Forcing Dataset

Global Forcing Dataset: Correction of Daily Precipitation Statistics

• High latitude anomaly in reanalysis rain days

• Corrected to match observed wetwet, drydry statistics

• By resampling wet and dry days from reanalysis record

• Other variables resampled for the same days for consistency

• Monthly P totals scaled to match observations

Global Forcing Dataset: Interpolation and Elevation Corrections

• disaggregated from 2.0 to 1.0 degree using bilinear interpolation but with adjustments for differences in elevation between the two grids

• air temperature adjusted using the environmental lapse rate (6.5 oC/km)

• adjust q, p, Lw via water vapor state equations and Stefan-Boltzmann law

• assumes that the relative humidity is constant to avoid the possibility of super-saturationDifference in elevation between reanalysis and 1.0deg grid

Global Forcing DatasetGlobal Forcing Dataset: Disaggregation of Precipitation: Disaggregation of Precipitation

• AA = sub-grid area of precipitation = sub-grid area of precipitation• II = daily precipitation amount = daily precipitation amount• Bayes theorem used to derive the sub-grid Bayes theorem used to derive the sub-grid areal coverage of precipitation for a given grid areal coverage of precipitation for a given grid precipitation and season precipitation and season • weighted by neighboring cellsweighted by neighboring cells

)(

)()|()|(

Ip

ApAIpIAp

Disaggregation in SpaceDisaggregation in Space

• disaggregated from daily to 3-hr by disaggregated from daily to 3-hr by resampling from TRMM resampling from TRMM pp(3hr|daily)(3hr|daily)

Disaggregation in TimeDisaggregation in Time

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

1 2 3 4 5 6 7 8

3-hr periodP

rob

abili

ty o

f p

reci

pit

atio

n

2.0 degree2.0 degree 1.0 degree1.0 degree

Global Forcing DatasetGlobal Forcing Dataset: Correction of Radiation: Correction of Radiation

• Sw scaled to match SRBSw scaled to match SRB

• Lw scaled to match SRB using probability Lw scaled to match SRB using probability matching.matching.

• Spurious trend in reanalysis SwSpurious trend in reanalysis Sw

• Form regression between reanalysis Sw Form regression between reanalysis Sw and Cldand Cld

• New Sw time series generated from Cru cldNew Sw time series generated from Cru cld

Correction of Sw TrendsCorrection of Sw Trends

Monthly Bias Correction of Lw and SwMonthly Bias Correction of Lw and Sw

Global Forcing DatasetGlobal Forcing Dataset: P, T Monthly Bias Corrections: P, T Monthly Bias Corrections

PrecipitationPrecipitation

• P scaled to match observed monthly totalsP scaled to match observed monthly totals

• Corrected for gauge undercatchCorrected for gauge undercatch

• Orographic corrections can be addedOrographic corrections can be added

TemperatureTemperature

• T scaled to match observed monthly totalsT scaled to match observed monthly totals

• Tmin, Tmax scaled to match observed DTRTmin, Tmax scaled to match observed DTR

Global Retrospective Hydrology SimulationsGlobal Retrospective Hydrology Simulations

Mean seasonal relative saturation Mean seasonal relative saturation

DJF

JJA

MAM

SON

Global Retrospective Hydrology SimulationsGlobal Retrospective Hydrology Simulations

Mean seasonal evapotranspiration

DJF

JJA

MAM

SON

Global VIC SimulationsGlobal VIC Simulations

Before CalibrationBefore Calibration After CalibrationAfter Calibration

Global Runoff Data Global Runoff Data CenterCenter

Gridded data at 30-min spatial resolutionGridded data at 30-min spatial resolution Monthly climatological mean runoff based on Monthly climatological mean runoff based on

model output and adjusted to match model output and adjusted to match observationsobservations

Global River Discharge Global River Discharge DatabaseDatabase

Data generally from Data generally from 1969-1984 1969-1984

(http://www.rivdis.sr.unh.edu/)(http://www.rivdis.sr.unh.edu/)

Adam Adam et al. (2006)et al. (2006) PrecipitationPrecipitation

Gridded monthly Gridded monthly precipitation, 1979-99precipitation, 1979-99

Half degree resolutionHalf degree resolution Applicable for regions Applicable for regions

with high-quality, long-with high-quality, long-term streamflow data term streamflow data with few anthropogenic with few anthropogenic effects. Basins must effects. Basins must cover area with cover area with orographic effectsorographic effects

(Adam et al., 2006)(Adam et al., 2006)