# Presentation: 216801

## The Emergence of Land-Surface Modeling

**in Modern-Era NWP:**
**The NCEP Experience and Collaborations**

*NWP 50-Year Anniversary Symposium*
*15-17 June 2004*

**NCEP****: *****Where America's Weather and Climate Services Begin***

## Improving Weather and Climate Prediction:

**Becoming a Complete **_**Earth System**_** Endeavor**

- 1 - _**ATMOSPHERE**_**:**	       troposphere, stratosphere
- 	(GARP)	         - initial conditions require
- 			         _atmosphere data assimilation_
- 2 - _**OCEAN**_**:**		deep ocean, seas, coastal ocean, sea ice
-         (TOGA/CLIVAR)       - initial conditions require
- 			          _ocean data assimilation_
- 3 - _**LAND**_**:**		**soil moisture, snowpack, vegetation, runoff**
-         (GEWEX/GAPP)	- initial conditions require
- 			            _land data assimilation_

## Historical Timeline of NCEP LSMs:With respect to NCEP atmospheric models

**1955-1965: Barotropic Model**
- no land surface, no radiation, no diurnal cycle
**1965-1985: Multi-layer PE and LFM models**
- simple surface friction effect on wind velocity
- surface sensible/latent heat fluxes _over ocean only_
- _assume zero sensible/latent heat flux over land_
- no diurnal cycle, no radiation
**1986-1995: global MRF, regional NGM & Eta models**
- first viable land surface models included
- bucket model hydrology and slab model thermodynamics
- first diurnal cycle of land surface energy balance & radiative forcing

## Historical Timeline of NCEP LSMs:With respect to NCEP atmospheric models

**1995-2004: global GFS, regional Eta & WRF models**
- The Oregon State University (OSU) LSM
- The NCEP Noah LSM descendant of the OSU LSM
**Four soil layers**
- Includes liquid and frozen soil moisture (OHD)
- Vertical profiles of soil moisture and soil temperature
**Explicit vegetation canopy with root zone**
- Satellite NDVI-based seasonal cycle of green vegetation fraction (NESDIS)
**Snowpack physics, including water content and density**
- Daily snow cover and snowpack analyses from NESDIS and AFWA
- Dynamic snowmelt and snow sublimation
**Stream network and streamflow simulation**

## Slide 5

## Multi-institution Land-Surface Partners:1990 - present

**Air Force (AFWA and AFRL)**
**NESDIS Land Team (ORA)**
**NWS Office of Hydrological Development (OHD)**
**NOAA Office of Global Programs (OGP):**** **
**GEWEX Programs: GAPP, GCIP, PILPS, ISLSCP**
**NLDAS: N.American Land Data Assimilation System**
**Six university partners plus above partners**
**Many are GAPP/OGP sponsored**
**NASA Hydrological Sciences Branch and GMAO**
**NCAR WRF Land Surface Working Group**
**USWRP sponsored**

## NESDIS Interactive Multi-sensor Snow (IMS) Product: 

**NESDIS Interactive Multi-sensor Snow (IMS) Product: **
**Daily 4-km Snow/Ice Analysis**
**Used along with AFWA Snowdepth Analysis for the daily**
**Initialization of snowpack in NCEP global and regional models**

**28 Feb 2004**

**13 May 2004**

## Partitioning of Incoming Solar Radiation

**Partitioning of Incoming Solar Radiation**

**34% reflected to space**
- -- 25% reflected by clouds
- -- 7% back scatter by air
- -- 2% reflected by earth sfc
**19% absorbed by atmos**
- -- 17% absorbed by air
- -- 2% absorbed by clouds
**47%**** absorbed by earth sfc**

## Land Surface Energy Balance 
(Exp: Monthly mean, mid-day summer, central U.S.)

**(Exp: Monthly mean, mid-day summer, central U.S.)**

**             ****Sd -  ****αSd****  + Ld - ****Lu****  =  ****H****  +  ****LE****  + G**
**	****  ****800    - 150   +   400   ****-  550****	**** =   125   +   300****   +  75**
**Complexity of LSM driven by representation of LE and G**
**   ****Sd   = Downward solar insolation: ****	****	****800 W/m**2**
** ****-αSd = Reflected solar insolation:****	****	****-150**
**   ****Ld  =  Downward longwave radiation:****	****	**** 400 **
**  ****-Lu  =  Upward longwave radiation:****	****	****-550  ****(based on land skin temp)**
**   ****G   = Ground heat flux****	****	****	****	****   75**
**    ****H  = Sensible heat flux:****	****	****	****125**
**   ****LE = L*E = Latent heat flux (evaporation)****	****300**

## Land Surface Water Balance

**(Exp: monthly, summer, central U.S.)**

**dS  =  P –  R –  E**
**dS  = change in soil moisture content:      - 75 mm****	****	**
**P    = precipitation:****	****	****	****	**** 75**
**R    = runoff****	****	****	****	****             25**
**E    = evaporation****	****	****	****	**** 125**
**(P-R) = infiltration**
**Evaporation is a ****function of soil moisture and **_**vegetation**_
**type, rooting depth/density, fractional cover, greenness.**
**All terms in units of mm.**

## Simple “one-layer” slab LSMs of 1985-1995 era at NCEP

- Bucket Model for hydrology
**Surface Evaporation:       LE =  B * EP**
-      B = Surface Wetness coefficient (fraction)
-    EP = potential evaporation:
-              function of atmospheric conditions
-              (humidity, wind speed, temperature)
- Slab Model (“force-restore”) for ground heat flux

## The Surface Wetness Field in the NGM Model(Range: ~ 0.04 – 0.20 )

- (values plotted are actual * 100)

## Land Surface Evaporation Treatmentin modern-era land models 

- WHEREIN:
- E = total evapotranspiration from combined soil/vegetation
- Edir = _direct_ evaporation from _top soil layer_
- Ec = evaporation from canopy-intercepted precipitation or dew
- Et = _transpiration_ through plant canopy via _root uptake_, and
-        _constrained by the canopy resistance to evaporation_

## Noah Land Model Prognostic Equations

**Soil Moisture**:

-  “Richard’s Equation” for soil water movement
-  D, K functions (soil texture)
-  **F********  represents sources (infiltration) and sinks **_**(evaporation)**_
-  Soil Temperature

-   C, Kt functions (soil texture, soil moisture)
-  Soil temperature information used to compute ground heat flux

## Vegetation Greenness

**Vegetation Greenness**
**April Climatology**

**Vegetation Greenness**
**July Climatology**

- Developed and provided
- by NESDIS/ORA
- -- New NESDIS realtime
-    weekly update now
-    being tested by NCEP

## Slide 16

## Ground Heat Flux Evaluation in Eta Model using FIFE Field Exp: 

- Ground Heat Flux Evaluation in Eta Model using FIFE Field Exp:
- Slab/Bucket LSM versus Noah LSM
- (Betts et al., 1997, MWR)

## Validation of surface fluxes of four LSMs vs 15 ARM flux stations.

**Validation of surface fluxes of four LSMs vs 15 ARM flux stations.**
**Monthly mean Rnet, LE, H and G for Jan 98 to Sep 99**

## Improving the Mesoscale NWP Forecastsvia Land-Surface Influences

- _NWP prediction improvement goals_
-    - 2 meter air temperature and humidity
-    - 10 meter wind vector
-    - PBL T and Td profiles
-    - convective stability indices
-    - integrated moisture flux convergence
-    - precipitation and cloud cover

## July 2003 Monthly Mean Diurnal Cycle of 2-m Air Temperature:

**July 2003 Monthly Mean Diurnal Cycle of 2-m Air Temperature:**
- Obs vs NCEP Models (3) for Midwest U.S.: Eta, GFS/AVN, NGM

**NGM**

**Obs**

**ETA**

**AVN**

## NCEP Eta model forecast during July 1998:

- Texas/Oklahoma drought, *24-hour forecast valid 00Z 27 July 1998*

- In late July
- 1998, after nearly two
- months of self-cycling
- the land states in the
- EDAS, the Eta model
- successfully captured
- the extremely dry soil
- moisture (upper left)
- and warm soil temps
- (upper right) over the
- Texas/Oklahoma
- region, yielding
- forecasts of high 2-m
- air temps (lower
- left) and deep, dry,
- hot boundary layers
- that verified well
- against raobs  (e.g.,
- at Norman, OK –
- lower right).

***air temperature (2-meter)***

***Norman, OK sonde***
***(obs=solid, model=dashed)***

***soil moisture availability (1-m)***

***soil temperature (5-cm)***

## The Eta Data Assimilation System: EDASA Coupled Land Data Assimilation System with hourly assimilation of observed precipitation

- In the forecast period between the analysis steps of the 12h pre-forecast data assimilation period, at each time step and at each point where observed precipitation is available, we compare *P**mod* to *P**obs*, then modify the model’s temperature, moisture, cloud and rain field to be more consistent with observed precipitation.

**The Eta Data Assimilation System: EDAS****A Coupled Land Data Assimilation System with ****hourly assimilation of observed precipitation**

- Pre-forecast data assimilation period

- Free forecast period

## IMPACT OF HOURLY PRECIPITATION ASSIMILATION IN ETA MODEL

- Gage precip (06Z, 15 July 1998); EDAS total precip of 1-15 July 1998 for (c) control run without precip
- assim, and (d) test run with hourly Stage IV precip assim; EDAS soil moisture availability (% saturation)
- of top 1-m soil column valid at 12Z 15 July 1998 (e) without precip assim, and (f) with precip assim.

***IMPACT OF HOURLY PRECIPITATION ASSIMILATION IN ETA MODEL***

## 25-Year EDAS-based Regional Reanalysis:

**Example of July 1988 vs. 1993**

## SAMPLE LAND-SURFACE OUTPUT FROM RR

**DROUGHT**
**1988**
**July**
- 15 July, 21Z

**FLOOD**
**1993**
**July**
- 15 July, 21Z

- soil moisture (percent of saturation) in top 1-meter

## SAMPLE LAND-SURFACE OUTPUT FROM RR

- DROUGHT
- YEAR (1988):
- 15 July, 21Z

- FLOOD
- YEAR (1993):
- 15 July, 21Z

- Boundary layer depth [m]

## Conclusions

**Land surface modeling has advanced intensely at NCEP from mid 1980’s to present**
**Above advancements have benefited greatly from multi-institution and multi-disciplinary partnerships**
**These land surface advancements have improved the skill/accuracy of NWP predictions**