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David S. Henderson, Christian D. Kummerow, and David A. Marks

Abstract

Ground radar rainfall, necessary for satellite rainfall product (e.g., TRMM and GPM) ground validation (GV) studies, is often retrieved using annual or climatological convective/stratiform Z–R relationships. Using the Kwajalein, Republic of the Marshall Islands (RMI), polarimetric S-band weather radar (KPOL) and gauge network during the 2009 and 2011 wet seasons, the robustness of such rain-rate relationships is assessed through comparisons with rainfall retrieved using relationships that vary as a function of precipitation regime, defined as shallow convection, isolated deep convection, and deep organized convection. It is found that the TRMM-GV 2A53 rainfall product underestimated rain gauges by −8.3% in 2009 and −13.1% in 2011, where biases are attributed to rainfall in organized precipitation regimes. To further examine these biases, 2A53 GV rain rates are compared with polarimetrically tuned rain rates, in which GV biases are found to be minimized when rain relationships are developed for each precipitation regime, where, for example, during the 2009 wet-season biases in isolated deep precipitation regimes were reduced from −16.3% to −4.7%. The regime-based improvements also exist when specific convective and stratiform Z–R relationships are developed as a function of precipitation regime, where negative biases in organized convective events (−8.7%) are reduced to −1.6% when a regime-based Z–R is implemented. Negative GV biases during the wet seasons lead to an underestimation in accumulated rainfall when compared with ground gauges, suggesting that satellite-related bias estimates could be underestimated more than originally described. Such results encourage the use of the large-scale precipitation regime along with their respective locally characterized convective or stratiform classes in precipitation validation endeavors and in development of Z–R rainfall relationships.

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David S. Henderson, Christian D. Kummerow, and Wesley Berg

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Discrepancies between Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Precipitation Radar (PR) oceanic rainfall retrievals are prevalent between El Niño and La Niña conditions with TMI exhibiting systematic shifts in precipitation. To investigate the causality of this relationship, this paper focuses on the evolution of precipitation organization between El Niño and La Niña and their impacts on TRMM precipitation. The results indicate that discrepancies are related to shifts from isolated deep convection during La Niña toward organized precipitation during El Niño with the largest variability occurring in the Pacific basins. During El Niño, organized systems are more frequent, have increased areal coverage of stratiform rainfall, and penetrate deeper into the troposphere compared to La Niña. The increased stratiform raining fraction leads to larger increases in TMI rain rates than PR rain rate retrievals. Reanalysis and water vapor data from the Atmospheric Infrared Sounder (AIRS) indicate that organized systems are aided by midtropospheric moisture increases accompanied by increased convective frequency. During La Niña, tropical rainfall is dominated by isolated deep convection due to drier midtropospheric conditions and strong mid- and upper-level zonal wind shear. To examine tropical rainfall–sea surface temperature relations, regime-based bias corrections derived using ground validation (GV) measurements are applied to the TRMM rain estimates. The robust connection with GV-derived biases and oceanic precipitation leads to a reduction in TMI-PR regional differences and tropics-wide precipitation anomalies. The improved agreement between PR and TMI estimates yields positive responses of precipitation to tropical SSTs of 10% °C−1 and 17% °C−1, respectively, consistent with 15% °C−1 from the Global Precipitation Climatology Project (GPCP).

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David S. Henderson, Jason A. Otkin, and John R. Mecikalski

Abstract

The evolution of model-based cloud-top brightness temperatures (BT) associated with convective initiation (CI) is assessed for three bulk cloud microphysics schemes in the Weather Research and Forecasting Model. Using a composite-based analysis, cloud objects derived from high-resolution (500 m) model simulations are compared to 5-min GOES-16 imagery for a case study day located near the Alabama–Mississippi border. Observed and simulated cloud characteristics for clouds reaching CI are examined by utilizing infrared BTs commonly used in satellite-based CI nowcasting methods. The results demonstrate the ability of object-based verification methods with satellite observations to evaluate the evolution of model cloud characteristics, and the BT comparison provides insight into a known issue of model simulations producing too many convective cells reaching CI. The timing of CI from the different microphysical schemes is dependent on the production of ice in the upper levels of the cloud, which typically occurs near the time of maximum cloud growth. In particular, large differences in precipitation formation drive differences in the amount of cloud water able to reach upper layers of the cloud, which impacts cloud-top glaciation. Larger cloud mixing ratios are found in clouds with sustained growth leading to more cloud water lofted to the upper levels of the cloud and the formation of ice. Clouds unable to sustain growth lack the necessary cloud water needed to form ice and grow into cumulonimbus. Clouds with slower growth rates display similar BT trends as clouds exhibiting growth, which suggests that forecasting CI using geostationary satellites might require additional information beyond those derived at cloud top.

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Richard D. Rosen, John M. Henderson, and David A. Salstein

Abstract

As part of its mandate to oversee the design of measurement networks for future weather and climate observing needs, the North American Atmospheric Observing System (NAOS) program hypothesized that replacing some of the existing radiosonde stations in the continental United States (CONUS) with another observing system would have little impact on weather forecast accuracy. The consequences of this hypothesis for climate monitoring over North America (NA) are considered here by comparing estimates of multidecadal trends in seasonal mean 500-mb temperature (T) integrated regionally over CONUS or NA, made with and without the 14 upper-air stations initially targeted for replacement. The trend estimates are obtained by subsampling gridded reanalysis fields at points nearest the 78 (126) existing CONUS (NA) radiosonde stations and at these points less the 14 stations. Trends in T for CONUS and NA during each season are also estimated based on the full reanalysis grid, but regardless of the sampling strategy, differences in trends are small and statistically insignificant. A more extreme reduction of the existing radiosonde network is also considered here, namely, one associated with the Global Climate Observing System (GCOS), which includes only 6 (14) stations in CONUS (NA). Again, however, trends for CONUS or NA based on the GCOS sampling strategy are not significantly different from those based on the current network, despite the large difference in station coverage. Estimates of continental-scale trends in 500-mb temperature therefore appear to be robust, whether based on the existing North American radiosonde network or on a range of potential changes thereto. This result depends on the large spatial scale of the underlying tropospheric temperature trend field; other quantities of interest for climate monitoring may be considerably more sensitive to the number and distribution of upper-air stations.

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Craig Miller, John Holmes, David Henderson, John Ginger, and Murray Morrison

Abstract

The Dines pressure tube anemometer was the primary wind speed recording instrument used in Australia until it was replaced by Synchrotac cup anemometers in the 1990s. Simultaneous observations of the gust wind speeds recorded using both types of anemometers during tropical cyclones have, however, raised questions about the equivalency of the gust wind speeds recorded using the two instruments. An experimental study of the response of both versions of the Dines anemometer used in Australia shows that the response of the anemometer is dominated by the motion of the float manometer used to record the wind speed. The amplitude response function shows the presence of two resonant peaks, with the amplitude and frequency of the peaks depending on the instrument version and the mean wind speed. Comparison of the gust wind speeds recorded using Dines and Synchrotac anemometers using random process and linear system theory shows that, on average, the low-speed Dines anemometer records values 2%–5% higher than those recorded using a Synchrotac anemometer under the same conditions, while the high-speed Dines anemometer records values 3%–7% higher, depending on the mean wind speed and turbulence intensity. These differences are exacerbated with the adoption of the WMO-recommended 3-s moving average gust wind speed when reporting the Synchrotac anemometer gust wind speeds, rising to 6%–12% and 11%–19% for low- and high-speed Dines anemometers, respectively. These results are consistent with both field observations and an independent extreme value analysis of simultaneously observed gust wind speeds at seven sites in northern Australia.

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David S. Henderson, Christian D. Kummerow, David A. Marks, and Wesley Berg

Abstract

Over the tropical oceans, large discrepancies in TRMM passive and active microwave rainfall retrievals become apparent during El Niño–Southern Oscillation (ENSO) events. This manuscript describes the application of defined precipitation regimes to aid the validation of instantaneous rain rates from TRMM using the S-band radar located on the Kwajalein Atoll. Through the evaluation of multiple case studies, biases in rain-rate estimates from the TRMM radar (PR) and radiometer (TMI) are best explained when derived as a function of precipitation organization (e.g., isolated vs organized) and precipitation type (convective vs stratiform). When examining biases at a 1° × 1° scale, large underestimates in both TMI and PR rain rates are associated with predominately convective events in deep isolated regimes, where TMI and PR retrievals are underestimated by 37.8% and 23.4%, respectively. Further, a positive bias of 33.4% is observed in TMI rain rates within organized convective systems containing large stratiform regions. These findings were found to be consistent using additional analysis from the DYNAMO field campaign. When validating at the TMI footprint scale, TMI–PR differences are driven by stratiform rainfall variability in organized regimes; TMI overestimates this stratiform precipitation by 92.3%. Discrepancies between TMI and PR during El Niño events are related to a shift toward more organized convective systems and derived TRMM rain-rate bias estimates are able to explain 70% of TMI–PR differences during El Niño periods. An extension of the results to passive microwave retrievals reveals issues in discriminating convective and stratiform rainfall within the TMI field of view (FOV), and significant reductions in bias are found when convective fraction is constrained within the Bayesian retrieval.

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Keith P. Shine, David A. Robinson, Ann Henderson-Sellers, and George Kukla

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Recent work has emphasized the potential importance of atmospheric aerosols in the Arctic. This paper presents results indicating the large-scale presence of arctic aerosols during late spring. Their screening effect may be sufficient to alter significantly the shortwave radiation budget. The ratios of brightness over sea and snow covered ice surfaces are shown to be considerably lower, using DMSP shortwave imagery, than those calculated for clear skies using a radiative transfer scheme. Our analysis shows that aerosols are the most likely cause of the discrepancy. With additional calibration the method offers the potential for remote sensing of the aerosol distribution and concentration over the Arctic.

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Yun Hang, Tristan S. L’Ecuyer, David S. Henderson, Alexander V. Matus, and Zhien Wang

Abstract

The role of clouds in modulating vertically integrated atmospheric heating is investigated using CloudSat’s multisensor radiative flux dataset. On the global mean, clouds are found to induce a net atmospheric heating of 0.07 ± 0.08 K day−1 that derives largely from 0.06 ± 0.07 K day−1 of enhanced shortwave absorption and a small, 0.01 ± 0.04 K day−1 reduction of longwave cooling. However, this small global average longwave effect results from the near cancellation of much larger regional warming by multilayered cloud systems in the tropics and cooling from stratocumulus clouds in subtropical oceans. Clouds are observed to warm the tropical atmosphere by 0.23 K day−1 and cool the polar atmosphere by −0.13 K day−1 enhancing required zonal heat redistribution by the meridional overturning circulation. Zonal asymmetries in the occurrence of multilayered clouds that are more frequent in the Northern Hemisphere and stratocumulus that occur more frequently over the southern oceans also leads to 3 times as much cloud heating in the Northern Hemisphere (0.1 K day−1) than the Southern Hemisphere (0.04 K day−1). These findings suggest that clouds very likely make the strongest contribution to the annual mean atmospheric energy imbalance between the hemispheres (2.0 ± 3.5 PW).

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Daria Kluver, Tom Mote, Daniel Leathers, Gina R. Henderson, Weihan Chan, and David A. Robinson

Abstract

This study details the creation of a gridded snowfall dataset for North America, with focus on the quality of the interpolated product. Daily snowfall amounts from National Weather Service Cooperative Observer Program stations and Meteorological Service of Canada surface stations are interpolated to 1° by 1° grids from 1900 to 2009 and examined for data record length and quality. The interpolation is validated spatially and temporally through the use of stratified sampling and k-fold cross-validation analyses. Interpolation errors average around 0.5 cm and range from less than 0.01 to greater than 2.5 cm. For most locations, this is within the measurement sensitivity. Grid cells with large variations in elevation experience higher errors and should be used with caution. A new gridded snowfall climatology is presented based on in situ observations that capture seasonal and interannual variability in monthly snowfall over most of the North American land area from 1949 to 2009. The Community Collaborative Rain, Hail and Snow Network is used as an independent set of point data that is compared to the gridded product. Errors are mainly in the form of the gridded data underestimating snowfall compared to the point data. The spatial extent, temporal length, and resolution of the dataset are unprecedented with regard to observational snowfall products and will present new opportunities for examining snowfall across North America.

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David S. Henderson, Tristan L’Ecuyer, Graeme Stephens, Phil Partain, and Miho Sekiguchi

Abstract

The launch of CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) in 2006 provided the first opportunity to incorporate information about the vertical distribution of cloud and aerosols directly into global estimates of atmospheric radiative heating. Vertical profiles of radar and lidar backscatter from CloudSat’s Cloud Profiling Radar (CPR) and the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard CALIPSO naturally complement Moderate Resolution Imaging Spectroradiometer (MODIS) radiance measurements, providing a nearly complete depiction of the cloud and aerosol properties that are essential for deriving high-vertical-resolution profiles of longwave (LW) and shortwave (SW) radiative fluxes and heating rates throughout the atmosphere. This study describes a new approach for combining vertical cloud and aerosol information from CloudSat and CALIPSO with MODIS data to assess impacts of clouds and aerosols on top-of-atmosphere (TOA) and surface radiative fluxes. The resulting multisensor cloud–aerosol product is used to document seasonal and annual mean distributions of cloud and aerosol forcing globally from June 2006 through April 2011. Direct comparisons with Clouds and the Earth’s Radiant Energy System (CERES) TOA fluxes exhibit a close correlation, with improved errors relative to CloudSat-only products. Sensitivity studies suggest that remaining uncertainties in SW fluxes are dominated by uncertainties in CloudSat liquid water content estimates and that the largest sources of LW flux uncertainty are prescribed surface temperature and lower-tropospheric humidity. Globally and annually averaged net TOA cloud radiative effect is found to be −18.1 W m−2. The global, annual mean aerosol direct radiative effect is found to be −1.6 ± 0.5 W m−2 (−2.5 ± 0.8 W m−2 if only clear skies over the ocean are considered), which, surprisingly, is more consistent with past modeling studies than with observational estimates that were based on passive sensors.

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