Investigating the Impact of Land-PBL Coupling on the Water and Energy Cycle in NASA Model and Observation Products

Transcription

1 Investigating the Impact of Land-PBL Coupling on the Water and Energy Cycle in NASA Model and Observation Products PI: Joseph A. Santanello, Jr. Hydrological Sciences Laboratory NASA-GSFC, Greenbelt, MD Co-Is: Toshi Matsui 3,1, Christa D. Peters-Lidard NASA-GSFC, Greenbelt, MD Collaborators: Joel Susskind 1, Eric Fetzer 2, Sujay Kumar 4,1 1 NASA-GSFC, Greenbelt, MD 2 Jet Propulsion Laboratory, Caltech, Pasadena, CA 3 University of Maryland, College Park, MD 4 Science Applications International Corporation, McLean, VA

2 Investigating the Impact of Land-PBL Coupling on the Water and Energy Cycle in NASA Model and Observation Products! Extend'the'development'and'evaluation'of'local%land( atmosphere%coupling'( LoCo )'diagnostics'for'news'and' community'model'and'observation'products.' Determine'if'AIRS%retrievals%can'be'used'to'evaluate,' PBL'coupling'and'its'inDluence'on'the'water'and'energy' cycle.'

3 Objective I Evaluate the accuracy, variability, and limitations of local land-pbl coupling ( LoCo ) in an array of NASA and community model and observation products using a suite of LoCo diagnostics. LoCo Diagnostics: Mixing Diagrams, EF vs. PBLH, LCL Deficit Products: LIS-WRF, MERRA, NARR, CFSR Location: SGP (ARM-LoCo Testbed) Cases: Daily, composites, monthly, seasonal (JJA), extremes (dry/wet)

4 Objective I - Updates LIS-WRF Testbed -Products: LIS-WRF w/3 LSMs and 3 PBLs -Diagnostics: MDs, LCL, EF/PBLH -Period: dry/wet extremes over SGP Paper Published: Santanello, J. A., C. D. Peters-Lidard, A. Kennedy, S. V. Kumar, 2013: Diagnosing the Nature of Land Atmosphere Coupling: A Case Study of Dry/Wet Extremes in the U.S. Southern Great Plains. J. Hydrometeor, 14, LoCo-RA Study -Products: MERRA, NARR, and CFSR -Diagnostics: MDs, LCL, EF/PBLH -Period: JJA over SGP -Observations: ARMBE and MERGESONDE Paper Submitted: Santanello, J. A., J. Roundy, and P. Dirmeyer: Quantifying the Land-Atmosphere Coupling Behavior in Modern Reanalysis Products over the U.S. Southern Great Plains. J. Climate, (June 2014).

5 LoCo Diagnostics 1) Mixing Diagrams (Santanello et al. 2009) Requirements: Daytime evolution of T and q, surface fluxes (mean), PBL height (mean) Diagnosis: Diurnal coupling between land-pbl water and energy balance, entrainment fluxes of heat and moisture 2) Evaporative Fraction vs. PBL Height (Santanello et al. 2009, 2011a) Requirements: Daytime mean land surface evaporative fraction (EF) and PBL height Diagnosis: Impact of EF on PBL growth (and vice-versa), sensitivity of land-pbl system to different models, inputs, or configurations 3) PBL Budgets of Heat and Moisture (Santanello et al. 2009, 2011a) Requirements: Same as mixing diagrams Diagnosis: Complete budget of land-pbl fluxes, contribution of land fluxes to atmospheric water and energy cycle 4) Thermodynamic Overlays (Santanello et al. 2011a) Requirements: Same as mixing diagrams Diagnosis: Diurnal evolution of equivalent potential temperature (theta-e), PBL saturation (q*), relative humidity (RH), and lifting condensation level (LCL) deficit 5) LCL Deficit (Santanello et al. 2011a) Requirements: Mixing diagrams (1) and thermodynamic overlays (4) Diagnosis: Temporal and spatial analysis (PBL height - LCL height) of potential for clouds/precipitation, sensitivity of moist processes to changes in land-pbl components LoCo Process Chain ΔSM ΔEFsm ΔPBL ΔENT ΔEFatm ΔP/Clouds (1) (a) (b) (c) (d)

6 Mixing Diagrams All RAs tend to be drier than observations -CFSR driest, lowest LHF, largest PBL, largest entrainment; MERRA vice-versa -Diurnal range of T2 and Q2 and overall T2 is represented well in RAs

7 Evaporative Fraction vs. PBL Height!MERRA!OBS!NARR!CFSR -PBL height vs. EF relationship indicates sensitivity of PBL to surface moisture state -CFSR/NARR much deeper PBLs and larger sensitivity to evaporation

8 LCL Deficit (PBL height LCL)!MERRA!OBS!NARR!CFSR -NARR has tendency to reach the LCL in afternoon; CFSR furthest away -NARR is in sweet spot of having enough moisture vs. large enough PBL growth -Indicative of dry vs. wet extremes

9 Diurnal Cycle of Precipitation!MERRA!OBS!NARR!CFSR -MERRA consistent midday peak in precipitation -Obs tend to show more bimodal distribution (am/pm)

10 Summary Statistics -CFSR performs worst overall, driven by dry bias -Post-2007 improvement in CFSR driven by incorporation of IASI and improved AIRS observations.

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12 Coupling Drought Index (CDI; Roundy et al.) -LoCo results explain processes responsible for differences and biases in drought indices

13 Objective I NEWS Integration Extremes WG -Investigating the causes of the flash drought of 2012 over CGP -LoCo insight and analysis produced for manuscript -July minus June relationships and trends over the RA record -Show the potential land preconditioning and PBL feedbacks present in 2012 (vs. 2011). Paper in Prep: Wang, S. et al., 2014: Could the 2012 drought have been anticipated?

14 LandBAtmosphere%Coupling%(LoCo)%Diagnos.cs%and%the%Drought%of%2012%!It#is#hypothesized#that#the# flashness #of#the#2012# drought#was#result#of#the#absence#of#large=scale# influences#such#as#sst#anomalies#which#allowed#for# L=A#interacCons#play#a#larger#role#in#iniCaCng#and# enhancing#the#drought.###!by#comparing#loco#metrics#in#cfsr,#narr,#and# MERRA#from#1979=2012#at#ARM=SGP,#it#can#be#seen# that#a#posicve#july#minus#june#anomaly#in#pbl#height# exists#in#2012#that#is#significantly#larger#than#that#of# 2011#and#one#of#the#largest#in#the#period#of#record.##!EF#(not#shown)#shows#only#a#slight#negaCve#value#of# July#minus#June#in#2012,#indicaCng#that#the#land# surface#was#precondiconed#to#be#dry#in#june#before# the#impacts#were#felt#in#the#pbl#in#july.### %June%and%July%mean%values%of%PBL%Height%(m)%from%each%RA% product%over%the%1979b2012%period%at%sgp%!the#onset#of#the#drought#was#then#supported#by# significantly#increased#pbl#height#in#july,#and# entrainment#and#residual#layer#(posicve)#feedbacks# that#further#dried#the#soil#and#supported#the#rapid# deepening#of#the#drought.## Santanello,%J.%A.,#J.#Roundy,#and#P.#Dirmeyer:##QuanCfying#the#Land= Atmosphere#Coupling#Behavior#in#Modern#Reanalysis#Products#over# the#u.s.#southern#great#plains.##j.!climate,#(submijed%june%2014).# June%minus%July%anomalies%in%day.me%mean%PBL%Height%

15 July minus June PBL height and Evaporative Fraction

16 Objective I - Updates LoCo Community Developments -GEWEX-GLASS core theme of L-A Coupling -LoCo WG continues to grow & sponsor initiatives on L-A coupling "LoCo-SGP Testbed -Community survey conducted on data needs for LoCo -Collaboration with DOE to create a new ARM-Best Estimate (ARMBE-Land product) at SGP for LoCo studies -First time buy-in from DOE ARM/ASR programs

17 17 LoCo-SGP Testbed Based on community feedback and through collaboration between LoCo, ARM, and the NASA NEWS program, a new data product called ARM Best Estimate (ARMBE) - Land has been produced for the SGP Central Facility (Lamont, OK). PI: Shaocheng Xie, Lawrence Livermore National Laboratory Data Product Name: ARMBELAND - Critical soil quantities for describing land properties Product Type: ARM Evaluation Products Date Range of Product: 01/01/ /31/2012 Data Directory Location: Currently, the ARMBE-Land contains the following quantities: * Soil temperature measured from CO2FLX, EBBR, and SWATS * Soil moisture content measured from CO2FLX, EBBR and SWATS * Soil heat flux from CO2FLX, EBBR * CO2 flux from CO2FLX * CO2 density from CO2FLX * Friction velocity from CO2FX * Photosynthetic photon flux density (PAR) from CO2FX #Data#availability:# QuanCCes#from#CO2FLX#:#2003=2012# QuanCCes#from#EBBR:#1994=2012# QuanCCes#from#SWATS:#1996=2012# Work has begun on a 2-D gridded (variational analysis) product over the broader ARM SGP network, which will include all the fields relevant for land-atmosphere coupling studies as well as sub-grid scale variability. Delivery of this product is expected by early #

18 Objective I - Updates LoCo Community Developments -GEWEX-GLASS core theme -LoCo WG continues to grow & sponsor initiatives on L-A coupling "Assessment of PBL Observations at SGP -PBL height, profiles, diurnal evolution are critical to LoCo -Previously limited to sparse radiosonde -Many new value-added and merged products being developed

19 PBL Observation Inventory ARMBSGP%Value%Added%Product%(*PBLH)% SGP#sonde#data#(4x#daily)#over#period#of#record#1996=present# 4#method#intercomparison#of#PBLH#detecCon# Hecer#(gradient),#Liu=Liang#(parcel),#Bulk#Richardson#0.5#and#0.25#(stability/shear)# ARMBSGP%PBLH%Product%(*PBLH)% AERI#+#Raman#Lidar#to#construct#temperature#profile#in#lower#troposphere# 2009=2012#hourly#dataset# LiBSawyer%Method%(*PBLH)% Combines#gradient/wavelet#detecCon# To#be#released#soon# ARMBSGP%Merge%Sonde%VAP%(*profs)% Sonde+MWR+Met+ECMWF#data# Beta#tesCng#and#helping#with#reprocessing# AERIoe%Produce%(*profs)% NEW#ARM#highlight,#profiles#based#on#AERI#for#clear#and#cloudy# #focused#on#pbl# hip:// CeilometerBderived%(*PBLH)% 2011=present#at#SGP;#3#methods,#16s#resoluCon# hip:// Airborne%HSRL%PBLH%(NASA%Langley)% Vs.#WRF=Chem#and#Sondes# Transects#over#Calnex# COSMIC% %GPS%Radio%Occulta.on%(*prof/PBLH)% India#Dept.#of#Space# VerCcal#profiles#of#refracCvity#(N)# PBLH#from#wavelet#analysis# Irregular,#global#coverage#depending#on#land/sea#and#laCtude# SGP#2006=12,#+/=#2#degrees#saw#1136#profiles#available#(~1#every#2#days)# ECMWF%(ERABInterim)%Climatology%Product%(*PBLH)% Teixeira#and#von#Englen# 5#gradient#methods# #RH#most#robust# AIRS%(*prof)% NEWS#proposal#(2012=2014)# L2#profiles#limited#in#lower#troposphere# AIRS#radiances#as#a#proxy#for#L=A#condiCons# Gadanki,%India%Site%(*prof)% Met#staCon,#tower,#soil#moisture/temperature,#and#fluxes#(installed#recently)# 3=hourly#Radiosonde#(2006=present)# Monsoon#studies# 19 SGP#products#highlight#the# diversity#and#difficulces#in#pbl# profile#and#height#escmacon.# # MERGESONDE#shows#promise# for#filling#in#temporal#dimension# and#allowing#for#automacon.# # SCll#site=specific#and#subject#to# sonde/profiler#limitacons.# # MoCvaCon#for#satellite=derived# PBL#informaCon#(e.g.#AIRS).#

20 Objective II Compare radiance and profile retrievals from AIRS against those from model and observation products as generated from a satellite data simulator (G-SDSU). Soundings: Vertical profiles of T,q in PBL (AIRS vs. sonde vs. model) Radiances: AIRS retrieved vs. G-SDSU simulated (models and obs) AIRS Science Team Collaboration: AIRS Stand-Alone Radiative Transfer Algorithm (SARTA) and Tb spectra analysis (L. Strow, J. Susskind)

21 AIRS Profile Retrievals vs. ARM-SGP Central Facility Day - 14 June 2003 Day - 27 July 2003 AIRS-d 1130 UTC 2330 UTC AIRS-d 1130 UTC 2330 UTC Night - 14 June 2003 Night July July AIRS-n 1130 UTC 2330 UTC AIRS-n 1130 UTC 2330 UTC

22 Vertical Temperature Profiles over SGP Dry Year (2007)

23 Sensitivity of AIRS spectrum to Land-PBL conditions 50 7-Jul Jun 3-Jun h w H s γ Storage 7 July June June Wavenumber*(1/cm) 2ch-window 5ch-γ 5ch-H s 5ch-h 5c-w 5ch-Δθ 2m * Preliminary work has established correlations with as few as 5 AIRS channels and Land-PBL quantities of interest. w H s h Δθ 2m γ WN WN WN WN WN

24 Radiance*(Tb)*Spectra*from*AIRS*and*Models* Brightness*Temp*(K)* 340# 320# 300# 280# 260# 240# LIS6WRF;*6*Sept* LIS6WRF;*25*Jan* LIS6WRF;*27*July* AIRS*CCR;*27*July* 220# 200# 650# 1150# 1650# Frequency*(cm61)* 2150# 2650#

25 Forward#Model## SARTA#in#G=SDSU# Simulated#AIRS#L1B#Tb# Spectra# (1)# Observed#AIRS#L1B# Tb#spectra## Obs#T=q#Profiles# and#ts## (sonde#data)# Model#T=q#Profiles# and#ts## (WRF,#MERRA,#etc.)# (2)# GSFC#AIRS# Algorithm# Retrieved#AIRS#L2# T=q#Profile#and#Ts# Proposed%Goals:# 1. Intercompare#L1B#Tb#spectra# 2. Intercompare#L2#profiles# a. Model#(WRF,#RAs)# b. Observed#(radiosonde)# c. AIRS#radiances# # Focus#on#L=A#quanCCes#and# processes#of#interest,#in#parccular# PBL#and#surface#turbulent#SH/LH# fluxes.## Examine#sensiCvity#of#land= surface#emissivity#and#diurnal# cycle.#

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28 Objective II - Updates AIRS PBL Profile Retrievals -AIRS V3, V5, and V6 analysis shows significant limitations in the PBL -Sensitivity of AIRS L2 profiles over land in lower troposphere (e.g. for PBL height detection) is weak and inconsistent AIRS Radiance Spectra -Intercompare Tb spectra from AIRS vs. WRF vs. RA products vs. radiosonde -Use G-SDSU to generate Tb from vertical profiles of T, q from models and observations -Supports need for AIRS RTM (SARTA) incorporation into G-SDSU for more direct comparison (resolution and specifications)

29 LISBWRF%output%over%SGP% %Dry%Year%(2006)%

30 LISBWRF%output%over%SGP% %Wet%Year%(2007)%

31 Global%Infrared%Land%Surface%Emissivity:% =UW=Madison#Baseline#Fit#Emissivity#Database#(MODIS=based)# =Incorporated#into#SARTA/G=SDSU#

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33 Future Work Evaluate the ability of hyperspectral sounders (e.g. AIRS or IASI) to be used as an observational benchmark against models. Tb and profile intercomparison for dry/wet regimes and locations/ regions outside SGP (e.g. AMMA, Cabauw). Statistical linkages of Land-PBL variables to specific regions of the AIRS spectrum. Identify potential areas of improvement for AIRS profile retrievals (and AIRS Science Team) through the lower troposphere.