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NASA NTRS1994

Observation of melt onset on multiyear Arctic sea ice using the ERS 1 synthetic aperture radar

We present nearly coincident observations of backscattering from the Earth Remote-Sensing Satellite (ERS) 1 synthetic aperture radar (SAR) and of near-surface temperature from six drifting buoys in the Beaufort Sea, showing that the onset of melting in snow on multiyear sea ice is clearly detectable in the SAR data. Melt onset is marked by a clean, steep decrease in the backscattering cross section of multiyear ice at 5.3 GHz and VV polarization. We investigate the scattering physics responsible for the signature change and find that the cross section decrease is due solely to the appearance of liquid water in the snow cover overlying the ice. A thin layer of moist snow is sufficient to cause the observed decrease. We present a prototype algorithm to estimate the date of melt onset using the ERS 1 SAR and apply the algorithm first to the SAR data for which we have corresponding buoy temperatures. The melt onset dates estimated by the SAR algorithm agree with those obtained independently from the temperature data to within 4 days or less, with the exception of one case in which temperatures oscillated about 0 C for several weeks. Lastly, we apply the algorithm to the entire ERS 1 SAR data record acquired by the Alaska SAR Facility for the Beaufort Sea north of 73 deg N during the spring of 1992, to produce a map of the dates of melt onset over an area roughly 1000 km on a side. The progression of melt onset is primarily poleward but shows a weak meridional dependence at latitudes of approximately 76 deg-77 deg N. Melting begins in the southern part of the study region on June 13 and by June 20 has progressed to the northermost part of the region.

Winebrenner, D. P.↗

NASA NTRS1995

Sea surface winds-A critical input to oceanic models, but are they accurately measured?

Wind, driving oceans, and the links between them to the atmosphere compose a critical parameter for the world circulation model as well as for the evaluation of climate changes. Traditionally, wind velocities have been reported by ships of oppurtunity and recorded on a network of buoys; they have also recently been generated by numerical weather prediction models and mapped with spaceborne remote sensors. Wind speeds from buoy measurements, ship observations, and model computations are compared, using the globally available altimeter returns that they have in common. Large, systematic deviations are found among the results obtained with these techniques, cautioning against use of these wind speeds.

Wu, Jin↗

NASA NTRS1994

Comparison of TOPEX/POSEIDON sigma(sub 0) and significant wave height distributions to Geosat

Monthly Ku band sigma(sub 0) and significant wave height (SWH) histograms from the NASA altimeter on the TOPEX/POSEIDON satellite are preseneted for January through June 1993 for three latitude bands between +/- 60 degrees. The data are compared to distributions from the Geosat mission for the same months in 1987-1989. Generally, the distributions agree quite well, although there are some seasonal/hemispherical differences. The sigma(sub 0) comparison reveals an overall bias between the two altimeters with the TOPEX sigma(sub 0) higher by about 0.7 dB, which is consistent with algorithm improvements for TOPEX. The SWH distributions show strong hemispherical/seasonal changes. The seasonal/hemispherical differences between TOPEX and Geosat are consistent for SWH and sigma(sub 0). The joint distribution of sigma(sub 0) and SWH is extremely stable friom month to month. The typical SWH is independent of sigma(sub 0) for sigma(sub 0) greater than 11.3 dB. The minimum SWH grows exponentially with wind speed. This joint distribution may be useful for understanding electromagnetic bias in altimeter measurements. Finally, altimeter data are compared to buoy values from 21 overflights of the NASA verification site near Pt. Conception, California. Wave heights agree well with an root mean square (RMS) difference of only 0.2 m. Altimeter sigma(sub 0) values are compared to buoy wind speeds. The results are consistent with the -0.7 dB sigma(sub 0) offset from the histogram comparisons.

Callahan, Philip S.↗

NASA NTRS1996

Marine Optical Characterizations

The team's major emphasis during this reporting period has been focused on the completion of the operational versions of the Marine Optical Buoys (MOBY's). Other work areas consisted of designing and testing bio-optical instrumentation, evaluating several of the SeaWiFS bio-optical protocols, processing data collected during field experiments, and reprocessing several of the Marine Optical Characteristics Experiment (MOCE) 2 and 3 bio-optical data sets. The team conducted one trip to the operations site in Honolulu, Hawaii, making necessary preparations for future field experiments. Part of the team also traveled to Moss Landing Marine Laboratories, Salinas, CA, and to American Holographic Co. Fitchburg MA, to assist with the fabrication of the next generation Marine Optical Buoys. Technical memoranda are being written to address the remote sensing reflectance, and instrument self-shading protocols. During the Ocean Color 96 meeting discussions with the Spanish on acquiring research vessel support during the MODIS validation period were conducted. A proposal will be generated towards this purpose for an experiment to be conducted off the North African coast during the summer of 1999.

Clark, Dennis K.↗

NASA NTRS1998

Mechanisms Regulating Deep Moist Convection and Sea-Surface Temperatures of the Tropics

Despite numerous previous studies, two relationships between deep convection and the sea-surface temperature (SST) of the tropics remain unclear. The first is the cause for the sudden emergence of deep convection at about 28 deg SST, and the second is its proximity to the highest observed SST of about 30 C. Our analysis provides a rational explanation for both by utilizing the Improved Meteorological (IMET) buoy data together with radar rainfall retrievals and atmospheric soundings provided by the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA-COARE). The explanation relies on the basic principles of moist convection as enunciated in the Arakawa-Schubert cumulus parameterization. Our analysis shows that an SST range of 28-29 C is necessary for "charging" the atmospheric boundary layer with sufficient moist static energy that can enable the towering convection to reach up to the 200 hPa level. In the IMET buoy data, the changes in surface energy fluxes associated with different rainfall amounts show that the deep convection not only reduces the solar flux into the ocean with a thick cloud cover, but it also generates downdrafts which bring significantly cooler and drier air into the boundary-layer thereby augmenting oceanic cooling by increased sensible and latent heat fluxes. In this way, the ocean seasaws between a net energy absorber for non-raining and a net energy supplier for deep-convective raining conditions. These processes produce a thermostat-like control of the SST. The data also shows that convection over the warm pool is modulated by dynamical influences of large-scale circulation embodying tropical easterly waves (with a 5-day period) and MJOs (with 40-day period); however, the quasi-permanent feature of the vertical profile of moist static energy, which is primarily maintained by the large-scale circulation and thermodynamical forcings, is vital for both the 28 C SST for deep convection and its upper limit at about 30 C.

Sud, Y. C.↗

NASA NTRS1996

Responses of the Tropical Pacific to Wind Forcing as Observed by Spaceborne Sensors and Simulated by an Ocean General Circulation Model

In this study, satellite observations, in situ measurements, and model simulations are combined to assess the oceanic response to surface wind forcing in the equatorial Pacific. The surface wind fields derived from observations by the spaceborne special sensor microwave imager (SSM/I) and from the operational products of the European Centre for Medium-Range Weather Forecasts (ECMWF) are compared. When SSM/I winds are used to force a primitive-equation ocean general circulation model (OGCM), they produce 3 C more surface cooling than ECMWF winds for the eastern equatorial Pacific during the cool phase of an El Nino-Southern Oscillation event. The stronger cooling by SSM/I winds is in good agreement with measurements at the moored buoys and observations by the advanced very high resolution radiometer, indicating that SSM/I winds are superior to ECMWF winds in forcing the tropical ocean. In comparison with measurements from buoys, tide gauges, and the Geosat altimeter, the OGCM simulates the temporal variations of temperature, steric, and sea level changes with reasonable realism when forced with the satellite winds. There are discrepancies between model simulations and observations that are common to both wind forcing fields, one of which is the simulation of zonal currents; they could be attributed to model deficiencies. By examining model simulations under two winds, vertical heat advection and uplifting of the thermocline are found to be the dominant factors in the anomalous cooling of the ocean mixed layer.

Liu, W. Timothy↗

NASA NTRS2000

Satellite-Derived Dynamics of Southern Ocean Sea Ice

Antarctic ERS-2, RADARSAT Synthetic Aperture Radar and ERS-1/2 Scatterometer images were analyzed with SMMI radiometer image time-series data to investigate seasonal variability in satellite-tracked sea-ice dynamics in the Southern Ocean during 1992. Supporting field data were acquired during 'in-situ' experiments including the winter 1992 Ice Station Weddell and Winter Weddell Gyre studies. A variety of surface measurements were made during these experiments including Argos-buoy deployment and GPS drift measurements. These are used in conjunction with International Program for Antarctic Buoys drift trajectories for ice-motion tracking validation. Comparisons between gridded Special Sensor Microwave Imager (SSMI) ice-motion vectors and European Center for Medium Range Weather Forecasts/National Centers for Environmental Prediction (ECMWF/NCEP) analyses indicate that large-scale drift is forced predominantly by the long-term mean, large-scale synoptic pressure field. Only sub-daily SAR sea-ice tracking can capture high-frequency fluctuations, driven by polar lows or tidal forcing. In these cases, sea-ice drift can respond rapidly to changes in forcing on semi-diurnal time scales depending on the location with respect to the coastline. Seasonality of ice drift, particularly in the Weddell and Ross Seas, is linked to ice extent and compactness, and internal ice stresses transmitted through the pack ice from the coast. Three-monthly seasonal climatologies are presented of austral winter of ice drift in the Southern Ocean. The large Weddell and Ross Sea gyres are clearly resolved along with key seasonal and spatial attributes of their cyclonic circulation. Regional time series of ice dynamics parameters are used to illustrate correlations with meteorological forcing. Persistent divergence such as that occurring in the Ronne-Filchner polynya system results in large fractions of new ice. Similarly, convergence zones produce large fractions of deformed ice and characterize the dynamics of regions where perennial ice is observed. High shear strains also help delineate the axis of the Antarctic divergence in many places in the ice cover. In these regions, the separation between the coastal 'east wind drift'and ACC-dominated drift regimes is characterized by zonally extended regions of intense shear.

Drinkwater, Mark R.↗

NASA NTRS2003

Satellite Detection of Precipitation over the North Pacific

Intense extratropical winter cyclones often impact the West Coast of North America with strong winds and heavy precipitation. Several times during a winter season, short-term forecasts (24 - 48 hours) of these storms are seriously deficient with central pressure errors in the 10's of hPa and surface low position errors in the 100's of km. For example, 48-hr sea level pressure errors (forecast - observation) at buoy 46005 off the Oregon coast for the 2001 - 2002 winter season is plotted. In addition, two times the standard deviation (determined from pressure errors from the last four winter seasons) are also shown. It is evident from this figure that large forecast errors (i.e. greater than 10 hPa) occurred about 10 times this past winter at buoy 46005 with three events where the errors were 20 hPa. Beside large forecast errors of sea level pressure, numerical forecasts of precipitation for land falling cyclones can also be flawed. This is due in large part to the lack of accurate precipitation information over the ocean. Therefore, remote sensing techniques are the only viable option for obtaining accurate information on the distribution and intensity of precipitation over the North Pacific. Due to the radiative characteristics of precipitation sized hydrometeors at microwave frequencies, microwave sensors are able to detect precipitation over oceanic regions. Past studies have demonstrated the utility of passive microwave rainrate data for locating intense rainfall in rapidly deepening cyclones, in detecting developing polar mesocyclones and in determining frontal bands. There are currently many sources of microwave rainrate data: the Special Sensor Microwave Imager (SSM/I) (currently flying on three platforms), the Advanced Microwave Sounding Unit (AMSU-B) (currently flying on NOAA-15, NOAA-16, and NOAA-17), and the Tropical Rainfall Measuring Mission Microwave Imager (TMI). Data will soon be available from the Advanced Microwave Radiometer-EOS (AMSR-E) on the Aqua platform. In this paper, we present a new technique for mapping rainrate distributions over the North Pacific utilizing rainrate estimates from several microwave sensors and upper-tropospheric winds derived from geosynchronous satellite IR data. The goal of this work is to develop a way to obtain high temporal and spatial rainfall information over the North Pacific. This information will be used to support the verification of model derived precipitation distributions and to support the analysis of in situ measurements of rainfall during the Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE) field campaigns.

Smith, Jeremy↗

NASA NTRS2003

Applications of Sea-Ice Motion and Deformation Derived from Satellite Data

QuikSCAT backscatter, AMSR and DMSP SSM/I radiance data have been used to derive sea ice motion for both the Arctic and Antarctic region using the wavelet analysis tracking method. All results from QuikSCAT, AMSR and SSM5 are compatible with buoys and can then be merged by data fusion method to generate composite sea ice motion maps for more complete coverage. Furthermore, based on this merged data set daily sea-ice deformation (shear, and convergence) maps have been produced and show consistent spatial and temporal patterns. Temporal correlation maps between ice deformation and SSM/II ice concentration show interesting results in the Arctic, especially the coast area. In this study, principal component analysis for both the merged ice tracking result from satellite data and pressure field from buoy have also been examined for the relationship between the principal components and eigenvectors from these two data sets. While the result shows that principal components of modes 1 and 2 from two data sets are highly correlated which confirms that wind forcing is a major factor driving the ice drift, it also reveals that other high energy modes are not highly correlated which maybe caused by coastal effects. Principal component analysis of Arctic sea-ice motion during fall/winter period in different years shows the reverse of dominant modes or patterns is related to the Arctic Oscillation.

Liu, Antony K.↗

NASA NTRS2005

Satellite Validation: A Project to Create a Data-Logging System to Monitor Lake Tahoe

Flying aboard the satellite Terra, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is an imaging instrument used to acquire detailed maps of Earth's surface temperature, elevation, emissivity, and reflectance. An automated site consisting of four buoys was established 6 years ago at Lake Tahoe for the validation of ASTERS thermal infrared data. Using Campbell CR23X Dataloggers, a replacement system to be deployed on a buoy was designed and constructed for the measurement of the lake's temperature profile, surrounding air temperature, humidity, wind direction and speed, net radiation, and surface skin temperature. Each Campbell Datalogger has been programmed to control, power, and monitor 14 different temperature sensors, a JPL-built radiometer, and an RM Young 32500 meteorological station. The logger communicates with the radiometer and meteorological station through a Campbell SDM-SIO4 RS232 serial interface, sending polling commands, and receiving filtered data back from the sensors. This data is then cataloged and sent back across a cellular modem network every hour to JPL. Each instrument is wired via a panel constructed with 18 individual plugs that allow for simple installation and expansion. Data sent back from the system are analyzed at JPL, where they are used to calibrate ASTER data.

Roy, Rudy A.↗

NASA NTRS1978

Spinoff For Survival

The Givens Buoy Raft cannot be overturned, its manufacturer claims and others concur. An independent test group conducted a series of demonstrations and found that every type of raft :I except the Givens could be capsized either by one man boarding or several shifting weight within the raft. Termed by the group "a remarkable stability achievement," the Givens Buoy raft offers the first major advance in inflatable survival equipment in many years. It is a spinoff product resulting in part from NASA technology and in part from years of research by Jim Givens, president of Res-Q-Raft, Inc., of Lake Worth, Florida and Seattle, Washington. NASA used inflatable rafts to transfer astronauts returning from space between their ocean-landed spacecraft and a recovery ship. NASA found a problem in the use of conventional flat-bottom inflatables; they tended to overturn when exposed to the downdraft from helicopters of the recovery fleet. So Johnson Space Center developed a new and highly-effective method of raft stabilization for which NASA secured a patent. Working separately, Jim Givens came up with a very similar system. He subsequently patented his own invention and secured an exclusive patent license to use the NASA technology

Source record↗

NASA NTRS2004

Evaluation of High-Resolution Ocean Surface Vector Winds Measured by QuikSCAT Scatterometer in Coastal Regions

The SeaWinds scatterometer onboard QuikSCAT covers approximately 90% of the global ocean under clear and cloudy condition in 24 h, and the standard data product has 25-km spatial resolution. Such spatial resolution is not sufficient to resolve small-scale processes, especially in coastal oceans. Based on range-compressed normalized backscatter and a modified wind retrieval algorithm, a coastal wind dataset at 12.5-km resolution was produced. Even with larger error, the high-resolution winds, in medium to high strength, would still be useful over coastal ocean. Using measurements from moored buoys from the National Buoy Data Center, the high-resolution QuikSCAT wind data are found to have similar accuracy as standard data in the open ocean. The accuracy of both high- and standard-resolution winds, particularly in wind directions, is found to degrade near shore. The increase in error is likely caused by the inadequacy of the geophysical model function/ambiguity removal scheme in addressing coastal conditions and light winds situations. The modified algorithm helps to bring the directional accuracy of the high-resolution winds to the accuracy of the standard-resolution winds in near-shore regions, particularly in the nadir and far zones across the satellite track.

scatterometer↗

NASA NTRS2008

The Telesupervised Adaptive Ocean Sensor Fleet (TAOSF) Architecture: Coordination of Multiple Oceanic Robot Boats

Earth science research must bridge the gap between the atmosphere and the ocean to foster understanding of Earth s climate and ecology. Ocean sensing is typically done with satellites, buoys, and crewed research ships. The limitations of these systems include the fact that satellites are often blocked by cloud cover, and buoys and ships have spatial coverage limitations. This paper describes a multi-robot science exploration software architecture and system called the Telesupervised Adaptive Ocean Sensor Fleet (TAOSF). TAOSF supervises and coordinates a group of robotic boats, the OASIS platforms, to enable in-situ study of phenomena in the ocean/atmosphere interface, as well as on the ocean surface and sub-surface. The OASIS platforms are extended deployment autonomous ocean surface vehicles, whose development is funded separately by the National Oceanic and Atmospheric Administration (NOAA). TAOSF allows a human operator to effectively supervise and coordinate multiple robotic assets using a sliding autonomy control architecture, where the operating mode of the vessels ranges from autonomous control to teleoperated human control. TAOSF increases data-gathering effectiveness and science return while reducing demands on scientists for robotic asset tasking, control, and monitoring. The first field application chosen for TAOSF is the characterization of Harmful Algal Blooms (HABs). We discuss the overall TAOSF architecture, describe field tests conducted under controlled conditions using rhodamine dye as a HAB simulant, present initial results from these tests, and outline the next steps in the development of TAOSF.

sensor web↗

NASA NTRS2010

A Simple Technique for Creating Regional Composites of Sea Surface Temperature from MODIS for Use in Operational Mesoscale NWP

This paper describes a simple technique for creating regional, high-resolution, daytime and nighttime composites of sea surface temperature (SST) for use in operational numerical weather prediction (NWP). The composites are based on observations from NASA s Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua and Terra. The data used typically are available nearly in real time, are applicable anywhere on the globe, and are capable of roughly representing the diurnal cycle in SST. The composites resolution is much higher than that of many other standard SST products used for operational NWP, including the low- and high-resolution Real-Time Global (RTG) analyses. The difference in resolution is key because several studies have shown that highly resolved SSTs are important for driving the air sea interactions that shape patterns of static stability, vertical and horizontal wind shear, and divergence in the planetary boundary layer. The MODIS-based composites are compared to in situ observations from buoys and other platforms operated by the National Data Buoy Center (NDBC) off the coasts of New England, the mid-Atlantic, and Florida. Mean differences, mean absolute differences, and root-mean-square differences between the composites and the NDBC observations are all within tenths of a degree of those calculated between RTG analyses and the NDBC observations. This is true whether or not one accounts for the mean offset between the skin temperatures of the MODIS dataset and the bulk temperatures of the NDBC observations and RTG analyses. Near the coast, the MODIS-based composites tend to agree more with NDBC observations than do the RTG analyses. The opposite is true away from the coast. All of these differences in point-wise comparisons among the SST datasets are small compared to the 61.08C accuracy of the NDBC SST sensors. Because skin-temperature variations from land to water so strongly affect the development and life cycle of the sea breeze, this phenomenon was chosen for demonstrating the use of the MODIS-based composite in an NWP model. A simulated sea breeze in the vicinity of New York City and Long Island shows a small, net, but far from universal improvement when MODIS-based composites are used in place of RTG analyses. The timing of the sea breeze s arrival is more accurate at some stations, and the near-surface temperature, wind, and humidity within the breeze are more realistic.

Knievel, Jason C.↗

NASA NTRS2014

Landsat-8 Thermal Infrared Sensor (TIRS) Vicarious Radiometric Calibration

Launched in February 2013, the Landsat-8 carries on-board the Thermal Infrared Sensor (TIRS), a two-band thermal pushbroom imager, to maintain the thermal imaging capability of the Landsat program. The TIRS bands are centered at roughly 10.9 and 12 micrometers (Bands 10 and 11 respectively). They have 100 m spatial resolution and image coincidently with the Operational Land Imager (OLI), also on-board Landsat-8. The TIRS instrument has an internal calibration system consisting of a variable temperature blackbody and a special viewport with which it can see deep space; a two point calibration can be performed twice an orbit. Immediately after launch, a rigorous vicarious calibration program was started to validate the absolute calibration of the system. The two vicarious calibration teams, NASA/Jet Propulsion Laboratory (JPL) and the Rochester Institute of Technology (RIT), both make use of buoys deployed on large water bodies as the primary monitoring technique. RIT took advantage of cross-calibration opportunity soon after launch when Landsat-8 and Landsat-7 were imaging the same targets within a few minutes of each other to perform a validation of the absolute calibration. Terra MODIS is also being used for regular monitoring of the TIRS absolute calibration. The buoy initial results showed a large error in both bands, 0.29 and 0.51 W/sq m·sr·micrometers or -2.1 K and -4.4 K at 300 K in Band 10 and 11 respectively, where TIRS data was too hot. A calibration update was recommended for both bands to correct for a bias error and was implemented on 3 February 2014 in the USGS/EROS processing system, but the residual variability is still larger than desired for both bands (0.12 and 0.2 W/sq m·sr·micrometers or 0.87 and 1.67 K at 300 K). Additional work has uncovered the source of the calibration error: out-of-field stray light. While analysis continues to characterize the stray light contribution, the vicarious calibration work proceeds. The additional data have not changed the statistical assessment but indicate that the correction (particularly in band 11) is probably only valid for a subset of data. While the stray light effect is small enough in Band 10 to make the data useful across a wide array of applications, the effect in Band 11 is larger and the vicarious results suggest that Band 11 data should not be used where absolute calibration is required.

TIIRS↗

NASA NTRS2011

Analysis of Ultra High Resolution Sea Surface Temperature Level 4 Datasets

Sea surface temperature (SST) studies are often focused on improving accuracy, or understanding and quantifying uncertainties in the measurement, as SST is a leading indicator of climate change and represents the longest time series of any ocean variable observed from space. Over the past several decades SST has been studied with the use of satellite data. This allows a larger area to be studied with much more frequent measurements being taken than direct measurements collected aboard ship or buoys. The Group for High Resolution Sea Surface Temperature (GHRSST) is an international project that distributes satellite derived sea surface temperatures (SST) data from multiple platforms and sensors. The goal of the project is to distribute these SSTs for operational uses such as ocean model assimilation and decision support applications, as well as support fundamental SST research and climate studies. Examples of near real time applications include hurricane and fisheries studies and numerical weather forecasting. The JPL group has produced a new 1 km daily global Level 4 SST product, the Multiscale Ultrahigh Resolution (MUR), that blends SST data from 3 distinct NASA radiometers: the Moderate Resolution Imaging Spectroradiometer (MODIS), the Advanced Very High Resolution Radiometer (AVHRR), and the Advanced Microwave Scanning Radiometer ? Earth Observing System(AMSRE). This new product requires further validation and accuracy assessment, especially in coastal regions.We examined the accuracy of the new MUR SST product by comparing the high resolution version and a lower resolution version that has been smoothed to 19 km (but still gridded to 1 km). Both versions were compared to the same data set of in situ buoy temperature measurements with a focus on study regions of the oceans surrounding North and Central America as well as two smaller regions around the Gulf Stream and California coast. Ocean fronts exhibit high temperature gradients (Roden, 1976), and thus satellite data of SST can be used in the detection of these fronts. In this case, accuracy is less of a concern because the primary focus is on the spatial derivative of SST. We calculated the gradients for both versions of the MUR data set and did statistical comparisons focusing on the same regions.

sea surface temperature SST)↗

NASA NTRS2016

Global Ocean Evaporation Increases Since 1960 in Climate Reanalyses: How Accurate Are They?

AGCMs w/ Specified SSTs (AMIPs) GEOS-5, ERA-20CM Ensembles Incorporate best historical estimates of SST, sea ice, radiative forcing Atmospheric "weather noise" is inconsistent with specified SST. Instantaneous Sfc fluxes can be wrong sign (e.g. Indian Ocean Monsoon, high latitude oceans). Averaging over ensemble members helps isolate SST-forced signal. Reduced Observational Reanalyses: NOAA 20CR V2C, ERA-20C, JRA-55C Incorporate observed Sfc Press (20CR), Marine Winds (ERA-20C) and rawinsondes (JRA-55C) to recover much of true synoptic or weather w/o shock of new sat obs. Comprehensive Reanalyses (MERRA-2) Full suite of observational constraints- both conventional and remote sensing. But... substantial uncertainties owing to evolving satellite observing system. Multi-source Statistically Blended OAFlux, LargeYeager Blend reanalysis, satellite, and ocean buoy information. While climatological biases are removed, non-physical trends or variations in components remain. Satellite Retrievals GSSTF3, SeaFlux, HOAPS3... Global coverage. Retrieved near sfc wind speed, & humidity used with SST to drive accurate bulk aerodynamic flux estimates. Satellite inter-calibration, spacecraft pointing variations crucial. Short record ( late 1987-present). In situ Measurements ICOADS, IVAD, Res Cruises VOS and buoys offer direct measurements. Sparse data coverage (esp south of 30S. Changes in measurement techniques (e.g. shipboard anemometer height).

Climate↗

NASA NTRS2018

Reconstruction of Snow on Arctic Sea Ice

Snow on Arctic sea ice is a poorly observed variable that plays an important role in the Arctic climate system and impacts the remote sensing systems that monitor Arctic sea ice. We present and validate a reconstruction of Arctic snow depth based on observed sea ice motion and snowfall derived from reanalysis data. Overall, the reconstruction is in good agreement with direct measurements of snow depth from Operation IceBridge, slightly underestimating mean IceBridge snow depth. At the local scale (10 km), the reconstruction is more skilled than a weighted climatology over first year ice, but underestimates deeper snow over multiyear ice. Reconstructions of single buoy snow depths are unskilled, but the reconstruction shows skill in simulating the mean snow depth across all buoys. Spring snow depths show a lowtohigh crossArctic gradient and tend to be greatest in the Atlantic sector of the eastern Arctic. The relationship between ice type (multiyear or firstyear ice) and snow depth previously documented in the western Arctic is not evident in the eastern Arctic. Using ice type to weight snow depths for satellite ice thickness retrievals may not be justifiable in the eastern Arctic. Reconstructed snow depth across the Arctic shows significant interannual variability, suggesting that use of a fixed snow depth climatology may lead to biases in retrieved ice thickness and its variability. However, interannual variability in panArctic mean snow depth is comparable or smaller than the uncertainty in both the reconstruction and IceBridge, highlighting the need for high accuracy snow depth products and reconstructions.

sea ice↗