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Design, Evaluation and GCM-Performance of a New Parameterization for Microphysics of Clouds with Relaxed Arakawa-Schubert Scheme (McRas)

A prognostic cloud scheme named McRAS (Microphysics of clouds with Relaxed Arakawa-Schubert Scheme) was developed with the aim of improving cloud-microphysics, and cloud-radiation interactions in GCMs. McRAS distinguishes convective, stratiform, and boundary-layer clouds. The convective clouds merge into stratiform clouds on an hourly time-scale, while the boundary-layer clouds do so instantly. The cloud condensate transforms into precipitation following the auto-conversion relations of Sundqvist that contain a parametric adaptation for the Bergeron-Findeisen process of ice crystal growth and collection of cloud condensate by precipitation. All clouds convect, advect, and diffuse both horizontally and vertically with a fully active cloud-microphysics throughout its life-cycle, while the optical properties of clouds are derived from the statistical distribution of hydrometeors and idealized cloud geometry. An evaluation of McRAS in a single column model (SCM) with the GATE Phase III data has shown that McRAS can simulate the observed temperature, humidity, and precipitation without discernible systematic errors. An evaluation with the ARM-CART SCM data in a cloud model intercomparison exercise shows reasonable but not an outstanding accurate simulation. Such a discrepancy is common to almost all models and is related, in part, to the input data quality. McRAS was implemented in the GEOS II GCM. A 50 month integration that was initialized with the ECMWF analysis of observations for January 1, 1987 and forced with the observed sea-surface temperatures and sea-ice distribution and vegetation properties (biomes, and soils), with prognostic soil moisture, snow-cover, and hydrology showed a very realistic simulation of cloud process, incloud water and ice, and cloud-radiative forcing (CRF). The simulated ITCZ showed a realistic time-mean structure and seasonal cycle, while the simulated CRF showed sensitivity to vertical distribution of cloud water which can be easily altered by the choice of time constant and incloud critical cloud water amount regulators for auto-conversion. The CRF and its feedbacks also have a profound effect on the ITCZ. Even though somewhat weaker than observed, the McRAS-GCM simulation produces robust 30-60 day oscillations in the 200 hPa velocity potential. Two ensembles of 4-summer (July, August, September) simulations, one each for 1987 and 1988 show that the McRAS-GCM simulates realistic and statistically significant precipitation differences over India, Central America, and tropical Africa. Several seasonal simulations were performed with McRAS-GEOS II GCM for the summer (June-July- August) and winter (December-January-February) periods to determine how the simulated clouds and CRFs would be affected by: i) advection of clouds; ii) cloud top entrainment instability, iii) cloud water inhomogeneity correction, and (iv) cloud production and dissipation in different cloud-processes. The results show that each of these processes contributes to the simulated cloud-fraction and CRF.

Sud, Y. C.↗

Bayesian Estimation of Precipitation from Satellite Passive Microwave Observations Using Combined Radar-Radiometer Retrievals

Precipitation estimation from satellite passive microwave radiometer observations is a problem that does not have a unique solution that is insensitive to errors in the input data. Traditionally, to make this problem well posed, a priori information derived from physical models or independent, high-quality observations is incorporated into the solution. In the present study, a database of precipitation profiles and associated brightness temperatures is constructed to serve as a priori information in a passive microwave radiometer algorithm. The precipitation profiles are derived from a Tropical Rainfall Measuring Mission (TRMM) combined radar radiometer algorithm, and the brightness temperatures are TRMM Microwave Imager (TMI) observed. Because the observed brightness temperatures are consistent with those derived from a radiative transfer model embedded in the combined algorithm, the precipitation brightness temperature database is considered to be physically consistent. The database examined here is derived from the analysis of a month-long record of TRMM data that yields more than a million profiles of precipitation and associated brightness temperatures. These profiles are clustered into a tractable number of classes based on the local sea surface temperature, a radiometer-based estimate of the echo-top height (the height beyond which the reflectivity drops below 17 dBZ), and brightness temperature principal components. For each class, the mean precipitation profile, brightness temperature principal components, and probability of occurrence are determined. The precipitation brightness temperature database supports a radiometer-only algorithm that incorporates a Bayesian estimation methodology. In the Bayesian framework, precipitation estimates are weighted averages of the mean precipitation values corresponding to the classes in the database, with the weights being determined according to the similarity between the observed brightness temperature principal components and the brightness temperature principal components of the classes. Because the classes are stratified by the sea surface temperature and the echo-top-height estimator, the number of classes that are considered for retrieval is significantly smaller than the total number of classes, making the algorithm computationally efficient. The radiometer-only algorithm is applied to TMI observations, and precipitation estimates are compared with combined TRMM precipitation radar (PR) TMI reference estimates. The TMI-only algorithm, supported by the empirically derived database, produces estimates that are more consistent with the reference values than the precipitation estimates from the version-6 TRMM facility TMI algorithm. Cloud-resolving model simulations are used to assign a latent heating profile to each precipitation profile in the empirically derived database, making it possible to estimate latent heating using the radiometer-only algorithm. Although the evaluation of latent heating estimates in this study is preliminary, because realistic conditional probability distribution functions are attached to latent heating structures in the algorithm s database, a generally positive impact on latent heating estimation from passive microwave observations is expected.

Grecu, Mircea↗

Evaluating Twenty-Year Trends in Earth’s Energy Flows from Observations and Reanalyses

Satellite, reanalysis, and ocean in situ data are analyzed to evaluate regional, hemispheric and global mean trends in Earth’s energy fluxes during the first twenty years of the 21st century. Regional trends in net top-of-atmosphere (TOA) radiation from the Clouds and the Earth’s Radiant Energy System (CERES), ECMWF Reanalysis 5 (ERA5), and a model similar to ERA5 with prescribed sea surface temperature (SST) and sea ice differ markedly, particularly over the Eastern Pacific Ocean, where CERES observes large positive trends. Hemispheric and global mean net TOA flux trends for the two reanalyses are smaller than CERES, and their climatological means are half those of CERES in the southern hemisphere (SH) and more than nine times larger in the northern hemisphere (NH). The regional trend pattern of the divergence of total atmospheric energy transport (TEDIV) over ocean determined using ERA5 analyzed fields is similar to that inferred from the difference between TOA and surface fluxes from ERA5 short-term forecasts. There is also agreement in the trend pattern over ocean for surface fluxes inferred as a residual between CERES net TOA flux and ERA5 analysis TEDIV and surface fluxes obtained directly from ERA5 forecasts. Robust trends are observed over the Gulf Stream associated with enhanced surface-to-atmosphere transfer of heat. Within the ocean, larger trends in ocean heating rate are found in the NH than the SH after 2005, but the magnitude of the trend varies greatly among datasets.

Norman G Loeb↗

Method of measuring sea surface water temperature with a satellite including wideband passive synthetic-aperture multichannel receiver

A wideband passive synthetic-aperture multichannel receiver with an antenna is mounted on a satellite which travels in an orbit above the Earth passing over large bodies of water, e.g., the Atlantic Ocean. The antenna is scanned to receive signals over a wide frequency band from each incremental surface area (pixel) of the water which are related to the pixel's sea temperature. The received signals are fed to several channels which are tuned to separate selected frequencies. Their outputs are fed to a processor with a memory for storage. As the antenna points to pixels within a calibration area around a buoy of known coordinates, signals are likewise received and stored. Exactly measured sea temperature is received from the buoy. After passing over several calibration areas, a forward stepwise regression analysis is performed to produce an expression which selects the significant from the insignificant channels and assigns weights (coefficients) to them. The expression is used to determine the sea temperature at each pixel based on the signals received therefrom. Wind temperature, pressure, and wind speed at each pixel can also be calculated.

Stacey, J. M.↗

High Lapse Rates in AIRS Retrieved Temperatures in Cold Air Outbreaks

The Atmospheric Infrared Sounder (AIRS) experiment, on NASA's Aqua spacecraft, uses a combination of infrared and microwave observations to retrieve cloud and surface properties, plus temperature and water vapor profiles comparable to radiosondes throughout the troposphere, for cloud cover up to 70%. The high spectral resolution of AIRS provides sensitivity to important information about the near-surface atmosphere and underlying surface. A preliminary analysis of AIRS temperature retrievals taken during January 2003 reveals extensive areas of superadiabatic lapse rates in the lowest kilometer of the atmosphere. These areas are found predominantly east of North America over the Gulf Stream, and, off East Asia over the Kuroshio Current. Accompanying the high lapse rates are low air temperatures, large sea-air temperature differences, and low relative humidities. Imagery from a Visible / Near Infrared instrument on the AIRS experiment shows accompanying clouds. These lines of evidence all point to shallow convection in the bottom layer of a cold air mass overlying warm water, with overturning driven by heat flow from ocean to atmosphere. An examination of operational radiosondes at six coastal stations in Japan shows AIRS to be oversensitive to lower tropospheric lapse rates due to systematically warm near-surface air temperatures. The bias in near-surface air temperature is seen to be independent of sea surface temperature, however. AIRS is therefore sensitive to air-sea temperature difference, but with a warm atmospheric bias. A regression fit to radiosondes is used to correct AIRS near-surface retrieved temperatures, and thereby obtain an estimate of the true atmosphere-ocean thermal contrast in five subtropical regions across the north Pacific. Moving eastward, we show a systematic shift in this air-sea temperature differences toward more isothermal conditions. These results, while preliminary, have implications for our understanding of heat flow from ocean to atmosphere. We anticipate future improvements in the AIRS retrieval algorithm will lead to improved understanding of the exchange of sensible and latent heat from ocean to atmosphere, and more realistic near-surface lapse rates.

cold air outbreak↗

Improved Simulation of East Asian Summer Monsoon in the High-resolution CESM1 and Its Causes

Based on the high- and low-resolution Community Earth System Model, version 1 (CESM1), and corresponding simulations from phase 6 of the Coupled Model Intercomparison Project (CMIP6), we compare the interannual variability of the East Asian summer monsoon (EASM). The EASM interannual variability is characterized by the anomalous western North Pacific anticyclone (WNPAC) circulation and the dipole rainfall pattern with a negative southern lobe over the western North Pacific and a positive northern lobe along the Meiyu–Baiu region, which is better reproduced by the high-resolution models. Here, the reason for the improvement in the high-resolution models has been attributed to the better simulation of the warm temperature advection from the wind anomalies on the climatological temperature gradient. Positive sea surface temperature (SST) anomalies over the tropical Indian Ocean are the key to the improved wind anomalies featuring a WNPAC in the high-resolution models. The warm SST anomalies over the tropical Indian Ocean strengthen the WNPAC by triggering a Kelvin-wave response to the enhanced heat release induced by the increased precipitation. Based on the mixed-layer heat budget analysis, the warm SST anomalies over the western Indian Ocean in the high-resolution CESM1 are tied to the anomalous easterly wind along the equator, which reduces surface evaporation and upwelling. Therefore, the better simulations of air-sea feedback and the oceanic mesoscale eddy over the western Indian Ocean are the key for the improved simulation of the EASM interannual variations in the high-resolution CESM1.

54 ENVIRONMENTAL SCIENCES↗

An increase in marine heatwaves without significant changes in surface ocean temperature variability

Marine heatwaves (MHWs)—extremely warm, persistent sea surface temperature (SST) anomalies causing substantial ecological and economic consequences—have increased worldwide in recent decades. Concurrent increases in global temperatures suggest that climate change impacted MHW occurrences, beyond random changes arising from natural internal variability. Moreover, the long-term SST warming trend was not constant but instead had more rapid warming in recent decades. Here we show that this nonlinear trend can—on its own—appear to increase SST variance and hence MHW frequency. Using a Linear Inverse Model to separate climate change contributions to SST means and internal variability, both in observations and CMIP6 historical simulations, we find that most MHW increases resulted from regional mean climate trends that alone increased the probability of SSTs exceeding a MHW threshold. Our results suggest the need to carefully attribute global warming-induced changes in climate extremes, which may not always reflect underlying changes in variability.

54 ENVIRONMENTAL SCIENCES↗

FUTURE LEVELS OF AEROSOLS & RADIATIVE FORCING OVER THE ARCTIC

The Arctic Monitoring and Assessment Programme (AMAP) is currently assessing the impacts of Short-Lived Climate Forcers (SLCF) on Arctic climate and air quality. In support of the assessment, we used the NASA Goddard Institute of Space Sciences (GISS) Earth System Model (modelE2.1), with prescribed sea surface temperature and sea-ice fraction, to simulate SLCF concentrations globally between 1995 and 2015. Two simulations were conducted, using the One-Moment Aerosol (OMA) and the Multiconfiguration Aerosol TRacker of mIXing state (MATRIX) aerosol modules. OMA is a mass-based scheme in which aerosols are assumed to remain externally mixed and have a prescribed and constant size distribution, while MATRIX is an aerosol microphysics scheme based on the quadrature method of moments, which is able to explicitly simulate the mixing state of aerosols. Anthropogenic emissions from the ECLIPSE v6b emissions database were used, along with emissions from aircrafts and open biomass burning from the Coupled Model Intercomparison Project Phase 6 (CMIP6), while the natural emissions of sea salt, DMS, isoprene and dust are calculated interactively. The simulated monthly surface concentrations of sulfate (SO4), black carbon (BC), organic carbon (OA), and ozone (O3) are compared with observations from a set of Arctic stations, extracted from the EBAS and IMPROVE databases, as well as a few additional locations. Simulated aerosol optical depths (AOD) are also compared with Advanced Very-High Resolution Radiometer (AVHRR). The study will present the evaluation of the modelE2.1 in simulating SLCF levels over the Arctic using different aerosol schemes, along with observed and simulated trends of SLCFs over the Arctic between 1995 and 2015.

Aersosols↗

Northern Hemisphere 700 mb heights and Pacific Ocean temperatures for winter months

Mean monthly 700 mb height data are analyzed in relation to Pacific Ocean sea-surface temperatures (SST). Instead of treating the winter season as a unit, the data are analyzed separately for December, January and February; some results for November are also included. The associated pattern of the atmospheric circulation is most pronounced in January and February, especially over the Pacific. This indicates that time intervals of one month, and even shorter ones, are long enough to reveal the atmospheric relation to the sea-surface temperature. Moreover, an average of 700 mb data over the Pacific for January and February, would probably show a greater correlation with SST than the 'winter' average which commonly includes December. The differences between December and February observations are discussed with the aid of the theoretical model of Hoskins and Karoly (1981).

Fritz, S.↗

Global decline in ocean memory over the 21st century

Ocean memory, the persistence of ocean conditions, is a major source of predictability in the climate system beyond weather time scales. We show that ocean memory, as measured by the year-to-year persistence of sea surface temperature anomalies, is projected to steadily decline in the coming decades over much of the globe. This global decline in ocean memory is predominantly driven by shoaling of the upper-ocean mixed layer depth in response to global surface warming, while thermodynamic and dynamic feedbacks can contribute substantially regionally. As the mixed layer depth shoals, stochastic forcing becomes more effective in driving sea surface temperature anomalies, increasing high-frequency noise at the expense of persistent signals. Reduced ocean memory results in shorter lead times of skillful persistence-based predictions of sea surface thermal conditions, which may present previously unknown challenges for predicting climate extremes and managing marine biological resources under climate change.

54 ENVIRONMENTAL SCIENCES↗

Mechanisms of tropical Pacific decadal variability

Naturally occurring tropical Pacific variations at timescales of 7–70 years — tropical Pacific decadal variability (TPDV) — describe basin-scale sea surface temperature (SST), sea-level pressure and heat content anomalies. Several mechanisms are proposed to explain TPDV, which can originate through oceanic processes, atmospheric processes or as an El Niño/Southern Oscillation (ENSO) residual. In this Review, we synthesize knowledge of these mechanisms, their characteristics and contribution to TPDV. Oceanic processes include off-equatorial Rossby waves, which mediate oceanic adjustment and contribute to variations in equatorial thermocline depth and SST; variations in the strength of the shallow upper-ocean overturning circulation, which exhibit a large anti-correlation with equatorial Pacific SST at interannual and decadal timescales; and the propagation of salinity-compensated temperature (spiciness) anomalies from the subtropics to the equatorial thermocline. Atmospheric processes include midlatitude internal variability leading to tropical and subtropical wind anomalies, which result in equatorial SST anomalies and feedbacks that enhance persistence; and atmospheric teleconnections from Atlantic and Indian Ocean SST variability, which induce winds conducive to decadal anomalies of the opposite sign in the Pacific. Although uncertain, the tropical adjustment through Rossby wave activity is likely a dominant mechanism. Finally, a deeper understanding of the origin and spectral characteristics of TPDV-related winds is a key priority.

54 ENVIRONMENTAL SCIENCES↗

Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM–MPAS variable-resolution model

Abstract. Comprehensive assessment of climate datasets is important for communicating model projections and associated uncertainties to stakeholders. Uncertainties can arise not only from assumptions and biases within the model but also from external factors such as computational constraint and data processing. To understand sources of uncertainties in global variable-resolution (VR) dynamical downscaling, we produced a regional climate dataset using the Model for Prediction Across Scales (MPAS; dynamical core version 4.0) coupled to the Community Atmosphere Model (CAM; version 5.4), which we refer to as CAM–MPAS hereafter. This document provides technical details of the model configuration, simulations, computational requirements, post-processing, and data archive of the experimental CAM–MPAS downscaling data. The CAM–MPAS model is configured with VR meshes featuring higher resolutions over North America as well as quasi-uniform-resolution meshes across the globe. The dataset includes multiple uniform- (240 and 120 km) and variable-resolution (50–200, 25–100, and 12–46 km) simulations for both the present-day (1990–2010) and future (2080–2100) periods, closely following the protocol of the North American Coordinated Regional Climate Downscaling Experiment. A deviation from the protocol is the pseudo-warming experiment for the future period, using the ocean boundary conditions produced by adding the sea surface temperature and sea-ice changes from the low-resolution version of the Max Planck Institute Earth System Model (MPI-ESM-LR) in the Coupled Model Intercomparison Project Phase 5 to the present-day ocean state from a reanalysis product. Some unique aspects of global VR models are evaluated to provide background knowledge to data users and to explore good practices for modelers who use VR models for regional downscaling. In the coarse-resolution domain, strong resolution sensitivity of the hydrological cycles exists over the tropics but does not appear to affect the midlatitude circulations in the Northern Hemisphere, including the downscaling target of North America. The pseudo-warming experiment leads to similar responses of large-scale circulations to the imposed radiative and boundary forcings in the CAM–MPAS and MPI-ESM-LR models, but their climatological states in the historical period differ over various regions, including North America. Such differences are carried to the future period, suggesting the importance of the base state climatology. Within the refined domain, precipitation statistics improve with higher resolutions, and such statistical inference is verified to be negligibly influenced by horizontal remapping during post-processing. Limited (≈50 % slower) throughput of the current code is found on a recent many-core/wide-vector high-performance computing system, which limits the lengths of the 12–46 km simulations and indirectly affects sampling uncertainty. Our experience shows that global and technical aspects of the VR downscaling framework require further investigations to reduce uncertainties for regional climate projection.

58 GEOSCIENCES↗

Predictability of Zonal Means During Boreal Summer

This study examines the predictability of seasonal means during boreal summer. The results are based on ensembles of June-July-August (JJA) simulations (started in mid May) carried out with the NASA Seasonal-to-Interannual Prediction Project (NSIPP-1) atmospheric general circulation model (AGCM) forced with observed sea surface temperatures (SSTS) and sea ice for the years 1980-1999. We find that the predictability of the JJA extra-tropical height field is primarily in the zonal mean component of the response to the SST anomalies. This contrasts with the cold season (January-February-March) when the predictability of seasonal means in the boreal extratropics is primarily in the wave component of the El Nino/Southern Oscillation (ENSO) response. Two patterns dominate the interannual variability of the ensemble mean JJA zonal mean height field. One has maximum variance in the tropical/subtropical upper troposphere, while the other has substantial variance in middle latitudes of both hemispheres. Both are symmetric with respect to the equator. A regression analysis suggests that the tropical/subtropical pattern is associated with SST anomalies in the far eastern tropical Pacific and the Indian Ocean, while the middle latitude pattern is forced by SST anomalies in the tropical Pacific just east of the dateline. The two leading zonal height patterns are reproduced in model runs forced with the two leading JJA SST patterns of variability. A comparison with observations shows a signature of the middle latitude pattern that is consistent with the occurrence of dry and wet summers over the United States. We hypothesize that both patterns, while imposing only weak constraints on extratropical warm season continental-scale climates, may play a role in the predilection for drought or pluvial conditions.

Schubert, Siegfried↗

A Classification of Mediterranean Cyclones Based on Global Analyses

The Mediterranean Sea region is dominated by baroclinic and orographic cyclogenesis. However, previous work has demonstrated the existence of rare but intense subsynoptic-scale cyclones displaying remarkable similarities to tropical cyclones and polar lows, including, but not limited to, an eye-like feature in the satellite imagery. The terms polar low and tropical cyclone have been often used interchangeably when referring to small-scale, convective Mediterranean vortices and no definitive statement has been made so far on their nature, be it sub-tropical or polar. Moreover, most of the classifications of Mediterranean cyclones have neglected the small-scale convective vortices, focusing only on the larger-scale and far more common baroclinic cyclones. A classification of all Mediterranean cyclones based on operational global analyses is proposed The classification is based on normalized horizontal shear, vertical shear, scale, low versus mid-level vorticity, low-level temperature gradients, and sea surface temperatures. In the classification system there is a continuum of possible events, according to the increasing role of barotropic instability and decreasing role of baroclinic instability. One of the main results is that the Mediterranean tropical cyclone-like vortices and the Mediterranean polar lows appear to be different types of events, in spite of the apparent similarity of their satellite imagery. A consistent terminology is adopted, stating that tropical cyclone- like vortices are the less baroclinic of all, followed by polar lows, cold small-scale cyclones and finally baroclinic lee cyclones. This classification is based on all the cyclones which occurred in a four-year period (between 1996 and 1999). Four cyclones, selected among all the ones which developed during this time-frame, are analyzed. Particularly, the classification allows to discriminate between two cyclones (occurred in October 1996 and in March 1999) which both display a very well-defined eye-like feature in the satellite imagery. According to our classification system, the two events are dynamically different and can be categorized as being respectively a tropical cyclone-like vortex and well-developed polar low.

Reale, Oreste↗

The NASA Airborne Earth Science Microwave Imaging Radiometer (AESMIR): A New Sensor for Earth Remote Sensing

The Airborne Earth Science Microwave Imaging Radiometer (AESMIR) is a versatile new airborne imaging radiometer recently developed by NASA. The AESMIR design is unique in that it performs dual-polarized imaging at all standard passive microwave frequency bands (6-89 GHz) using only one sensor headscanner package, providing an efficient solution for Earth remote sensing applications (snow, soil moisture/land parameters, precipitation, ocean winds, sea surface temperature, water vapor, sea ice, etc.). The microwave radiometers themselves will incorporate state-of-the-art receivers, with particular attention given to instrument calibration for the best possible accuracy and sensitivity. The single-package design of AESMIR makes it compatible with high-altitude aircraft platforms such as the NASA ER-2s. The arbitrary 2-axis gimbal can perform conical and cross-track scanning, as well as fixed-beam staring. This compatibility with high-altitude platforms coupled with the flexible scanning configuration, opens up previously unavailable science opportunities for convection/precip/cloud science and co-flying with complementary instruments, as well as providing wider swath coverage for all science applications. By designing AESMIR to be compatible with these high-altitude platforms, we are also compatible with the NASA P-3, the NASA DC-8, C-130s and ground-based deployments. Thus AESMIR can provide low-, mid-, and high- altitude microwave imaging. Parallel filter banks allow AESMIR to simultaneously simulate the exact passbands of multiple satellite radiometers: SSM/I, TMI, AMSR, Windsat, SSMI/S, and the upcoming GPM/GMI and NPOESS/CMIS instruments --a unique capability among aircraft radiometers. An L-band option is also under development, again using the same scanner. With this option, simultaneous imaging from 1.4 to 89 GHz will be feasible. And, all receivers except the sounding channels will be configured for 4-Stokes polarimetric operation using high-speed digital correlators in the near future. The capabilities and unique design features of this new sensor will be described, and example imagery will be presented.

Kim, Edward↗

Scientific Impacts of Wind Direction Errors

An assessment on the scientific impact of random errors in wind direction (less than 45 deg) retrieved from space-based observations under weak wind (less than 7 m/s ) conditions was made. averages, and these weak winds cover most of the tropical, sub-tropical, and coastal oceans. Introduction of these errors in the semi-daily winds causes, on average, 5% changes of the yearly mean Ekman and Sverdrup volume transports computed directly from the winds, respectively. These poleward movements of water are the main mechanisms to redistribute heat from the warmer tropical region to the colder high- latitude regions, and they are the major manifestations of the ocean's function in modifying Earth's climate. Simulation by an ocean general circulation model shows that the wind errors introduce a 5% error in the meridional heat transport at tropical latitudes. The simulation also shows that the erroneous winds cause a pile-up of warm surface water in the eastern tropical Pacific, similar to the conditions during El Nino episode. Similar wind directional errors cause significant change in sea-surface temperature and sea-level patterns in coastal oceans in a coastal model simulation. Previous studies have shown that assimilation of scatterometer winds improves 3-5 day weather forecasts in the Southern Hemisphere. When directional information below 7 m/s was withheld, approximately 40% of the improvement was lost

Liu, W. Timothy↗

RadSTAR L-Band Imaging Scatterometer: Performance Assessment

RadSTAR is an instrument development program aimed at combining a radiometer and a scatterometer system into a highly compact configuration that uses a single, electronically scanned antenna to provide co-located and simultaneous measurements of emission and backscatter for airborne and spaceborne applications [I]. The program was designed to map soil moisture and ocean salinity, both important components of the water cycle, and to map sea ice density and thickness, an important factor in ocean-atmosphere heat exchange in Polar Regions. The accuracy in estimation of these and a number of other Earth science parameters can be greatly enhanced by providing the co-aligned radar/radiometer microwave measurements. For instance, radiometer estimates of soil moisture from soil emission are affected by emission from vegetation, and from the roughness of the surface. Complementary measurements using the scatterometer can be used to evaluate the vegetation and surface roughness effects. Hence, the combined observations can provide an improved estimate. As with soil moisture, the ocean salinity is a function of the microwave emission from the sea surface temperature (SST) and sea roughness. There, the addition of radar backscatter measurements of sea roughness enables the correction of the emissivity and provide more accurate estimates of ocean salinity. Similar arguments can be made for other important Earth science parameters. This paper discusses the RadSTAR program, the radar system design, calibration, and digital beamforming techniques, and presents preliminary analysis of the data collected during the test flights. The data sets obtained during the flights and during the radar calibration in the anechoic chamber are also employed to asses the performance of the radar. The paper also discusses the Digital Beamforming Synthetic Aperture Radar (DBSAR) processor, a real-time processor recently developed for the LIS instrument which enables beam synthesis, fine resolutions, and large swaths.

Rincon, Rafael↗

Forecasting Lake-Effect Precipitation in the Great Lakes Region Using NASA Enhanced-Satellite Data

Lake-effect precipitation is common in the Great Lakes region, particularly during the late fall and winter. The synoptic processes of lake-effect precipitation are well understood by operational forecasters, but individual forecast events still present a challenge. Locally run, high resolution models can assist the forecaster in identifying the onset and duration of precipitation, but model results are sensitive to initial conditions, particularly the assumed surface temperature of the Great Lakes. The NASA Short-term Prediction Research and Transition (SPoRT) Center has created a Great Lakes Surface Temperature (GLST) composite, which uses infrared estimates of water temperatures obtained from the MODIS instrument aboard the Aqua and Terra satellites, other coarser resolution infrared data when MODIS is not available, and ice cover maps produced by the NOAA Great Lakes Environmental Research Lab (GLERL). This product has been implemented into the Weather Research and Forecast (WRF) model Environmental Modeling System (WRF-EMS), used within forecast offices to run local, high resolution forecasts. The sensitivity of the model forecast to the GLST product was analyzed with a case study of the Lake Effect Storm Echinacea, which produced 10 to 12 inches of snowfall downwind of Lake Erie, and 8 to 18 inches downwind of Lake Ontario from 27-29 January 2010. This research compares a forecast using the default Great Lakes surface temperatures from the Real Time Global sea surface temperature (RTG SST), in the WRF-EMS model to the enhanced NASA SPoRT GLST product to study forecast impacts. Results from this case study show that the SPoRT GLST contained less ice cover over Lake Erie and generally cooler water temperatures over Lakes Erie and Ontario. Latent and sensible heat fluxes over Lake Ontario were decreased in the GLST product. The GLST product decreased the quantitative precipitation forecast (QPF), which can be correlated to the decrease in temperatures and heat fluxes. A slight increase in precipitation coverage was noted over Lake Erie due to a decrease in ice cover. Both the RTG SST and the GLST products predicted the precipitation south of the actual location of precipitation. This single case study is the first part of an examination to determine how MODIS data can be applied to improve model forecasts in the Great Lakes region.

Cipullo, Michelle↗