Development of Consistent Long-term Global Land Parameter Data Record based on AMSR-E, AMSR2 and MWRI observations Jinyang Du, Lucas A. Jones, and John.

Slides:

Advertisements

Similar presentations

Development of Bias-Corrected Precipitation Database and Climatology for the Arctic Regions Daqing Yang, Principal Investigator Douglas L. Kane, Co-Investigator.

Advertisements

Extension and application of an AMSR global land parameter data record for ecosystem studies Jinyang Du, John S. Kimball, Lucas A. Jones, Youngwook Kim,

Ecoregion level climate constraints on vegetation NPP (Nemani et al., Science 2003) VOD SOS offset by ecoregion relative to NDVI Greenup date. VOD SOS.

Landscape Temperature and Frozen/Thawed Condition over Alaska with Infrared and Passive Microwave Remote Sensing Determination of Thermal Controls on Land-Atmosphere.

Maintaining and Improving the AMSR-E and WindSat Ocean Products Frank J. Wentz Remote Sensing Systems, Santa Rosa CA AMSR TIM Agenda 4-5 September 2013.

3. Climate Change 3.1 Observations 3.2 Theory of Climate Change 3.3 Climate Change Prediction 3.4 The IPCC Process.

The first three rows in equation control the estimates of soil moisture from the regression equation assuring that the estimated soil moisture content.

Xin Kong, Lizzie Noyes, Gary Corlett, John Remedios, Simon Good and David Llewellyn-Jones Earth Observation Science, Space Research Centre, University.

Measuring Soil Water Contents at Different Scales – FZ Jülich – 17 th November 2005 Global estimation of the 1-m soil water content using microwave measurements.

Outline Background, climatology & variability Role of snow in the global climate system Indicators of climate change Future projections & implications.

CSIRO LAND and WATER Estimation of Spatial Actual Evapotranspiration to Close Water Balance in Irrigation Systems 1- Key Research Issues 2- Evapotranspiration.

Satellite Microwave Detection of Phenological Start of Season for North America using AMSR-E Matthew O. Jones 1,2, John S. Kimball 1,2, Lucas A. Jones.

Regional Climate Modeling in the Source Region of Yellow River with complex topography using the RegCM3: Model validation Pinhong Hui, Jianping Tang School.

Experiments with the microwave emissivity model concerning the brightness temperature observation error & SSM/I evaluation Henning Wilker, MIUB Matthias.

3. Climate Change 3.1 Observations 3.2 Theory of Climate Change 3.3 Climate Change Prediction 3.4 The IPCC Process.

Improving the AMSR-E snow depth product: recent developments Richard Kelly University of Waterloo, Canada.

Snow Cover: Current Capabilities, Gaps and Issues (Canadian Perspective) Anne Walker Climate Research Branch, Meteorological Service of Canada IGOS-Cryosphere.

The role of vegetation-climate interaction on Africa under climate change - literature review seminar Minchao Wu Supervisor: Markku Rummukainen, Guy Schurgers.

ISCCP at 30, April 2013 Concurrent Study of a) 22 – year reanalysis and extension of global water vapor over both land and ocean (NVAP–M) and b) the matching.

Summary of Research on Climate Change Feedbacks in the Arctic Erica Betts April 01, 2008.

Princeton University Development of Improved Forward Models for Retrievals of Snow Properties Eric. F. Wood, Princeton University Dennis. P. Lettenmaier,

Retrieving Snowpack Properties From Land Surface Microwave Emissivities Based on Artificial Neural Network Techniques Narges Shahroudi William Rossow NOAA-CREST.

Development and evaluation of Passive Microwave SWE retrieval equations for mountainous area Naoki Mizukami.

APPLICATIONS OF THE INTEGRAL EQUATION MODEL IN MICROWAVE REMOTE SENSING OF LAND SURFACE PARAMETERS In Honor of Prof. Adrian K. Fung Kun-Shan Chen National.

Coupling of the Common Land Model (CLM) to RegCM in a Simulation over East Asia Allison Steiner, Bill Chameides, Bob Dickinson Georgia Institute of Technology.

William Crosson, Ashutosh Limaye, Charles Laymon National Space Science and Technology Center Huntsville, Alabama, USA Soil Moisture Retrievals Using C-

Reducing Canada's vulnerability to climate change - ESS J28 Earth Science for National Action on Climate Change Canada Water Accounts AET estimates for.

Spatial and temporal patterns of CH 4 and N 2 O fluxes from North America as estimated by process-based ecosystem model Hanqin Tian, Xiaofeng Xu and other.

Clear sky Net Surface Radiative Fluxes over Rugged Terrain from Satellite Measurements Tianxing Wang Guangjian Yan

Modeling Modes of Variability in Carbon Exchange Between High Latitude Ecosystems and the Atmosphere Dave McGuire (UAF), Joy Clein (UAF), and Qianlai.

Importance of Recent Shifts in Soil Thermal Dynamics on Growing Season Length, Productivity, and Carbon Sequestration in Terrestrial High-Latitude Ecosystems.

Recent increases in the growing season length at high northern latitudes Nicole Smith-Downey* James T. Randerson Harvard University UC Irvine Sassan S.

Printed by Introduction: The nature of surface-atmosphere interactions are affected by the land surface conditions. Lakes (open water.

The Relation Between SST, Clouds, Precipitation and Wave Structures Across the Equatorial Pacific Anita D. Rapp and Chris Kummerow 14 July 2008 AMSR Science.

Using MODIS snow cover fraction

WATER VAPOR RETRIEVAL OVER CLOUD COVER AREA ON LAND Dabin Ji, Jiancheng Shi, Shenglei Zhang Institute for Remote Sensing Applications Chinese Academy of.

ISCCP at 30, April 2013 Backup Slides. ISCCP at 30, April 2013 NVAP-M Climate Monthly Average TPW Animation Less data before 1993.

1) Canadian Airborne and Microwave Radiometer and Snow Survey campaigns in Support of International Polar Year. 2) New sea ice algorithm Does not use a.

Variations in Continental Terrestrial Primary Production, Evapotranspiration and Disturbance Faith Ann Heinsch, Maosheng Zhao, Qiaozhen Mu, David Mildrexler,

Land Surface Modeling Studies in Support of AQUA AMSR-E Validation PI: Eric F. Wood, Princeton University Project Goal: To provide modeling support to.

Long-term drought assessment of Northern Central African continent using Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST)

A New Inter-Comparison of Three Global Monthly SSM/I Precipitation Datasets Matt Sapiano, Phil Arkin and Tom Smith Earth Systems Science Interdisciplinary.

AGU2012-GC31A963: Model Estimates of Pan-Arctic Lake and Wetland Methane Emissions X.Chen 1, T.J.Bohn 1, M. Glagolev 2, S.Maksyutov 3, and D. P. Lettenmaier.

A review on different methodologies employed in current SWE products from spaceborne passive microwave observations Nastaran Saberi, Richard Kelly Interdisciplinary.

As components of the GOES-R ABI Air Quality products, a multi-channel algorithm similar to MODIS/VIIRS for NOAA’s next generation geostationary satellite.

Goal: to understand carbon dynamics in montane forest regions by developing new methods for estimating carbon exchange at local to regional scales. Activities:

Evapotranspiration Estimates over Canada based on Observed, GR2 and NARR forcings Korolevich, V., Fernandes, R., Wang, S., Simic, A., Gong, F. Natural.

AN OVERVIEW OF THE CURRENT NASA OPERATIONAL AMSR-E/AMSR2 SNOW SCIENCE TEAM ACTIVITIES M. Tedesco*, J. Jeyaratnam, M. Sartori The Cryospheric Processes.

IGARSS 2011, Jul. 27, Vancouver 1 Monitoring Vegetation Water Content by Using Optical Vegetation Index and Microwave Vegetation Index: Field Experiment.

Use of AMSR-E Land Parameter Modeling and Retrievals for SMAP Algorithm Development Steven Chan Eni Njoku Joint AMSR Science Team Meeting Telluride, Colorado.

Recent Improvements and Ecological Applications of the UMT AMSR Land Parameter Record Jinyang Du, Lucas A. Jones, and John S. Kimball Numerical Terradynamic.

Matt Rodell NASA GSFC Multi-Sensor Snow Data Assimilation Matt Rodell 1, Zhong-Liang Yang 2, Ben Zaitchik 3, Ed Kim 1, and Rolf Reichle 1 1 NASA Goddard.

The Inter-Calibration of AMSR-E with WindSat, F13 SSM/I, and F17 SSM/IS Frank J. Wentz Remote Sensing Systems 1 Presented to the AMSR-E Science Team June.

Validation of Satellite-derived Clear-sky Atmospheric Temperature Inversions in the Arctic Yinghui Liu 1, Jeffrey R. Key 2, Axel Schweiger 3, Jennifer.

A step toward operational use of AMSR-E horizontal polarized radiance in JMA global data assimilation system Masahiro Kazumori Numerical Prediction Division.

Recent SeaWiFS view of the forest fires over Alaska Gene Feldman, NASA GSFC, Laboratory for Hydrospheric Processes, Office for Global Carbon Studies

Determination of cloud immersion and biogeography of cloud forests using satellite data Udaysankar S. Nair 1, Salvi Asefi 3, Ron Welch 3, Robert O. Lawton.

Using Satellite Data and Fully Coupled Regional Hydrologic, Ecological and Atmospheric Models to Study Complex Coastal Environmental Processes Funded by.

Whats new with MODIS NPP and GPP MODIS/VIIRS Science Team Meeting May 20, 2015 Steven W. Running Numerical Terradynamic Simulation Group College of Forestry.

MODIS Atmosphere Products: The Importance of Record Quality and Length in Quantifying Trends and Correlations S. Platnick 1, N. Amarasinghe 1,2, P. Hubanks.

A comparison of AMSR-E and AATSR SST time-series A preliminary investigation into the effects of using cloud-cleared SST data as opposed to all-sky SST.

Arctic RIMS & WALE (Regional, Integrated Hydrological Monitoring System & Western Arctic Linkage Experiment) John Kimball FaithAnn Heinsch Steve Running.

Ocean Sciences The oceans cover 3/4 of the Earth’s surface. They provide the thermal memory for the global climate system, and are a major reservoir of.

Passive Microwave Remote Sensing

5th International Conference on Earth Science & Climate Change

Ecosystem Model Evaluation

GPM Microwave Radiometer Vicarious Cold Calibration

Passive Microwave Systems & Products

NSIDC DAAC UWG Meeting August 9-10 Boulder, CO

Development and Evaluation of a Forward Snow Microwave Emission Model

Presentation transcript:

Development of Consistent Long-term Global Land Parameter Data Record based on AMSR-E, AMSR2 and MWRI observations Jinyang Du, Lucas A. Jones, and John S. Kimball Numerical Terradynamic Simulation Group and Flathead Lake Biological Station, Division of Biological Sciences, The University of Montana AMSR Joint Science Team Meeting September 2014 Huntsville, AL

AMSR Joint Science Team Meeting September 2014, Huntsville, AL OVERVIEW Consistent long-term land parameter records including retrievals of vegetation optical depth, surface temperature & moisture, landscape freeze/thaw dynamics, open water inundation & Atm. water vapor changes are desirable for Ecological studies & applications  In this study, satellite Tb inter-calibrations were carried out between similar sensors including AMSR-E ( ), AMSR2 (from Jun-2012) and FY3B-MWRI (from Dec., 2010);  Further developments and re-calibration of UMT Global Land Parameter algorithms were also made for L1R AMSR2 swath data and then implemented for the reprocessed ( RSS V7) AMSR-E data;  AMSR-E algorithm has been applied to the calibrated Tb datasets to produce long-term land parameter data records from 2002 to MWRI AMSR2 NOW

Algorithm Calibration WMO Stations Temp. AIRS Water Vapor MODIS Land Cover DEM Subset Brightness Temperature and AIRS products for WMO Stations Screening Datasets for RFI, Snow, Precipitation and High DEM variations Adjust Algorithm Parameters based on WMO measurements and AIRS products Calibrated brightness Temperature AMSR-E / AMSR/MWRI Swath Brightness Temperature Gridded brightness Temperature Data Gridding & Tb Inter-Calibration Run Land Parameter Retrieval Algorithms General Data Record Production Procedures

AMSR Joint Science Team Meeting September 2014, Huntsville, AL Towards Consistent Land Surface Parameter Records --Part I Inter-calibration of AMSR-E, AMSR2 and MWRI Observations

AMSR Joint Science Team Meeting September 2014, Huntsville, AL Instruments Configurations AMSR-2AMSR-EMWRI Satellite PlatformGCOM-W1AQUAFY3B Altitude700 km705 km836 km Equator Crossing Time1:30 PM Ascending 1:40 PM Ascending Antenna Size2 m1.6 m0.977 m x m Incident Angle55 53 Spatial Resolution [km x km] Band [GHz] AMSR-2AMSR-EMWRI x 3575 x 43N/A x 35N/A x 2451 x 29 85x x 1427 x 16 50x x 1532 x 1845x x 714 x 830x x 3 6 x 4 15x 9

AMSR Joint Science Team Meeting September 2014, Huntsville, AL Sensor Inter-calibration – Estimating Observation Biases Estimating Sensor Biases using Double Difference Method Example global distributions of estimated ascending orbit biases between uncalibrated AMSR2 and AMSR-E baseline observations for the H-Polarized (a) 23GHz, and (b) 18GHz channels, respectively (areas with correlation coefficient R<0.95 are marked in grey) (a)23 GHz (b)18 GHz Source: Du et al Remote Sensing 6

AMSR Joint Science Team Meeting September 2014, Huntsville, AL H-Polarized 18 GHz Tb comparisons from overlapping MWRI and AMSR ascending orbit observations for the selected Amazon tropical reference area Sensor Inter-Calibration– Linear Calibration Linear Calibration of AMSR2 and MWRI against AMSR-E observations

AMSR Joint Science Team Meeting September 2014, Huntsville, AL Towards Consistent Land Surface Parameter Records --Part II Precipitable Water Vapor (PWV) & Surface Air Temperature Retrieval over Land from AMSR2

AMSR Joint Science Team Meeting September 2014, Huntsville, AL Development of PWV Retrieval Algorithm for AMSR2 Ascending Descending Comparisons between AMSR2 & AIRS PWV retrievals over 200 global WMO sites Source: Du et al TGARS (In-review)

AMSR Joint Science Team Meeting September 2014, Huntsville, AL Comparisons of PWV Seasonal Distribution Patterns from Three Products AMSR2 MODIS NVAP-M AMSR2 MODIS NVAP-M Winter (DJF) Summer (JJA) Source: Du et al TGARS (In-review)

AMSR Joint Science Team Meeting September 2014, Huntsville, AL Updated AMSR2 Surface Air Temperature Retrieval Algorithm Winter (DJF)Summer (JJA) AMSR2 mean daily maximum air temperature over Winter (left) and Summer (Right) RMSE Tmn (Kelvin) RMSE Tmx (Kelvin)

AMSR Joint Science Team Meeting September 2014, Huntsville, AL Towards Consistent Land Surface Parameter Records-- Part III Generating Long-term Land Surface Parameters from with Updated UMT Land Parameter Algorithm

AMSR Joint Science Team Meeting September 2014, Huntsville, AL Evaluation of the Extended Daily Maximum/Minimum Temperature Records based on WMO site measurements AMSR-E (2010) AMSR2 & MWRI (2012) AMSR2(2013)

AMSR Joint Science Team Meeting September 2014, Huntsville, AL Statistical Summary of the Validation Results Retrieved Air Temperature vs WMO measurements TminTmax RMSE (Celcius) R^2RMSE (Celcius) R^2 AMSR-E (year 2010) AMSR2&MWRI (year 2012) AMSR2 (year 2013) Retrieved PWV vs AIRS products AscendingDescending RMSE (mm) R^2RMSE (mm) R^2 AMSR-E (year 2010) AMSR2 &MWRI (year 2012) AMSR2 (year 2013) Surface Air Temperature Validation Results Water Vapor Validation Results

AMSR Joint Science Team Meeting September 2014, Huntsville, AL Recent Ecological Application Studies

AMSR Joint Science Team Meeting September 2014, Huntsville, AL Spring Hydrology Determines Summer Net Carbon Uptake in Northern Ecosystems Major Findings: Wetter springs promote summer net carbon uptake independent of temperature effects; Warming still promotes widespread greening (as observed by NDVI), but with less net carbon uptake in warmer, drier years; Stronger coupling of northern carbon & water cycles with continued climate warming. Surface soil moisture anomaly for June, 2009 from satellite observations ( 1 AMSR-E); positive values denote wetter-than-normal conditions from the mean ( ). A synthesis of atmospheric CO 2 and satellite and regional climate data reveals the major role of spring hydrology in determining summer net carbon uptake (NCU) for northern (≥50°N) ecosystems. Spring wetting inhibits fire emissions and promotes NCU, independent of temperature effects. Summer (JJA) Net Ecosystem CO 2 Exchange (NEE) anomaly for 2009 from CarbonTracker; NEE +/- sign denotes ecosystem carbon gain/loss, where NCU ≈ NEE + fire emissions. Source: Yi et al ERL 9,

AMSR Joint Science Team Meeting September 2014, Huntsville, AL Surface Water Inundation in the boreal-Arctic: Potential Impacts on Regional Methane Emissions Key Findings: Strong temporal variability in boreal-Arctic Fw, with sensitivity to regional temp. & precip. patterns; Longer-term ( ) drying across boreal ecosystems, with substantial Fw wetting in Arctic tundra & continuous permafrost landscapes (Above); Accounting for dynamic changes in high-latitude wetland extent (e.g. Fw inputs) can significantly reduce regional CH 4 emission estimates. Sponsors: NASA Earth Science program Above: AMSR-E Fw retrievals indicate that ~5% (8.4 x 10 5 km 2 ) of northern tundra & peatland landscapes are inundated during non-frozen summer months. 1 ERL Video Abstract: A satellite data-driven model study of surface temperature and AMSR-E daily fractional open water (Fw) inundation controls on high-latitude wetland CH 4 emissions reveals a strong regulating influence by contrasting regional wetting and drying patterns. Source: Watts et al ERL 9,

AMSR Joint Science Team Meeting September 2014, Huntsville, AL Recent Publications Journal papers: Du, J.; Kimball, J.S.; Shi, J.; Jones, L.A.; Wu, S.; Sun, R.; Yang, H. Inter- Calibration of Satellite Passive Microwave Land Observations from AMSR-E and AMSR2 Using Overlapping FY3B-MWRI Sensor Measurements. Remote Sens. 2014, 6, Du, J., J.S. Kimball, and L.A. Jones, Satellite microwave retrieval of total precipitable water vapor and surface air temperature over land from AMSR2. TGARS (In-review). Jang, K., S. Kang, J.S. Kimball, et al Retrievals of all-weather daily air temperature using MODIS and AMSR-E data. Remote sensing, 6, 9, Watts, J.D., J.S. Kimball, A. Bartsch, and K.C. McDonald, Surface water inundation in the boreal-Arctic: potential impacts on regional methane emissions. ERL, 9, Yi, Y., J.S. Kimball, and R.H. Reichle, Spring hydrology determines summer net carbon uptake in northern ecosystems. ERL 9,

AMSR Joint Science Team Meeting September 2014, Huntsville, AL Summary Detectable biases found between AMSR-E, AMSR2 and MWRI 1 observations. Inter- calibrations based on swath T b data records significantly decreased sensor biases and improved T b correlations. UMT Global Land Parameter algorithms successfully adapted to AMSR2, with favorable accuracy in surface air temperature and water vapor retrievals. The updated algorithms applied to calibrated AMSR2, MWRI & AMSR-E (V7) Tb data. Based on AMSR-E and calibrated AMSR2/MWRI T b observations and recent algorithm updates, long-term UMT land surface parameter records have been produced. In general, similar retrieval accuracy has been found for the AMSR-E and post AMSR-E periods, except that MWRI water vapor retrieval is slightly lower than the other sensor products. Continuing calibration & extension of UMT record planned in support of several global ecosystem studies. 1 AMSR-E V7 reprocessed T b record provided by Remote Sensing Systems; AMSR2 L1R data are from JAXA; MWRI data are from China National Satellite Meteorological Centre

Thank You! Funding for this study provided from NASA Terra and Aqua Science, and MEaSUREs programs. NTSG Project Team: John Kimball, Jinyang Du, Lucas Jones, Youngwook Kim, Joe Glassy, Matt Jones, Jennifer Watts, Yonghong Yi Project Data Archives (Updates coming soon!):

AMSR Joint Science Team Meeting September 2014, Huntsville, AL Backup Slides

AMSR Joint Science Team Meeting September 2014, Huntsville, AL Algorithm Flowchart Temperature Algorithm Tb 6.9 or 10.7 V & H pol.Tb 18.7, 23.8 V & H pol. 60-day running smoother Estimate slope parameter: Estimate emissivity Invert for VOD (assume dry baseline soil conditions) Invert for SM

Selection of the WMO stations & GPS sites for PWV & Air Temperature Retrieval Study PWV/Temperature Algorithm Development: WMO Training Sites (black Square) and Validation Sites (black triangle) over the MODIS IGBP global land cover map; PWV Algorithm Validation: SuomiNet North American GPS stations (white circles with black outlines)

AMSR Joint Science Team Meeting September 2014, Huntsville, AL AMSR2 PWV Validation using GPS retrievals Ascending Descending AMSR2 PWV vs GPS PWV Histogram of the absolute AMSR2 PWV estimation errors for the ascending (left) and descending (right) orbit retrievals relative to independent PWV observations from 350 SuomiNet North American GPS sites

AMSR Joint Science Team Meeting September 2014, Huntsville, AL Extended Land Parameter Records – Global Vegetation Optical Thickness Distributions X-band Vegetation Optical Thickness (May 30, 2010,2011,2013 / May 31,2012) AMSR-E (2010) AMSR-E (2011) MWRI(2012) AMSR2 (2013)