The mean structure and diurnal cycle of southeast (SE) Atlantic boundary layer clouds are described with satellite observations and multiscale modeling framework (MMF) simulations during austral ...spring (September–November). Hourly resolution cloud fraction (CF) and cloud-top height (HT
) are retrieved fromMeteosat-9radiances using modified Clouds and the Earth’s Radiant Energy System (CERES) Moderate Resolution Imaging Spectroradiometer (MODIS) algorithms, whereas liquid water path (LWP) is from the University of Wisconsin microwave satellite climatology. The MMF simulations use a 2D cloud-resolving model (CRM) that contains an advanced third-order turbulence closure to explicitly simulate cloud physical processes in every grid column of a general circulation model. The model accurately reproduces themarine stratocumulus spatial extent and cloud cover. The mean cloud cover spatial variability in the model is primarily explained by the boundary layer decoupling strength, whereas a boundary layer shoaling accounts for a coastal decrease in CF. Moreover, the core of the stratocumulus cloud deck is concomitant with the location of the strongest temperature inversion. Although the model reproduces the observed westward boundary layer deepening and the spatial variability of LWP, it overestimates LWP by 50%. Diurnal cycles ofHT
, CF, and LWP from satellites and the model have the same phase, with maxima during the early morning and minima near 1500 local solar time, which suggests that the diurnal cycle is driven primarily by solar heating. Comparisons with the SE Pacific cloud deck indicate that the observed amplitude of the diurnal cycle is modest over the SE Atlantic, with a shallower boundary layer as well. The model qualitatively reproduces these interregime differences.
Analysis of the cloud components in numerical weather prediction models using advanced data assimilation techniques has been a prime topic in recent years. In this research, the variational data ...assimilation (DA) system for the Weather Research and Forecasting (WRF) Model (WRFDA) is further developed to assimilate satellite cloud products that will produce the cloud liquid water and ice water analysis. Observation operators for the cloud liquid water path and cloud ice water path are developed and incorporated into the WRFDA system. The updated system is tested by assimilating cloud liquid water path and cloud ice water path observations from Global Geostationary Gridded Cloud Products at NASA. To assess the impact of cloud liquid/ice water path data assimilation on short-term regional numerical weather prediction (NWP), 3-hourly cycling data assimilation and forecast experiments with and without the use of the cloud liquid/ice water paths are conducted. It is shown that assimilating cloud liquid/ice water paths increases the accuracy of temperature, humidity, and wind analyses at model levels between 300 and 150 hPa after 5 cycles (15 h). It is also shown that assimilating cloud liquid/ice water paths significantly reduces forecast errors in temperature and wind at model levels between 300 and 150 hPa. The precipitation forecast skills are improved as well. One reason that leads to the improved analysis and forecast is that the 3-hourly rapid update cycle carries over the impact of cloud information from the previous cycles spun up by the WRF Model.
Atmospheric models rely on high-accuracy, high-resolution initial radiometric and surface conditions for better short-term meteorological forecasts, as well as improved evaluation of global climate ...models. Remote sensing of the Earth’s energy budget, particularly with instruments flown on geostationary satellites, allows for near-real-time evaluation of cloud and surface radiation properties. The persistence and coverage of geostationary remote sensing instruments grant the frequent retrieval of near-instantaneous quasi-global skin temperature. Among other cloud and clear-sky retrieval parameters, NASA Langley provides a non-polar, high-resolution land and ocean skin temperature dataset for atmospheric modelers by applying an inverted correlated k-distribution method to clear-pixel values of top-of-atmosphere infrared temperature. The present paper shows that this method yields clear-sky skin temperature values that are, for the most part, within 2 K of measurements from ground-site instruments, like the Southern Great Plains Atmospheric Radiation Measurement (ARM) Infrared Thermometer and the National Climatic Data Center Apogee Precision Infrared Thermocouple Sensor. The level of accuracy relative to the ARM site is comparable to that of the Moderate-resolution Imaging Spectroradiometer (MODIS) with the benefit of an increased number of daily measurements without added bias or increased error. Additionally, matched comparisons of the high-resolution skin temperature product with MODIS land surface temperature reveal a level of accuracy well within 1 K for both day and night. This confidence will help in characterizing the diurnal and seasonal biases and root-mean-square differences between the retrievals and modeled values from the NASA Goddard Earth Observing System Version 5 (GEOS-5) in preparation for assimilation of the retrievals into GEOS-5. Modelers should find the immediate availability and broad coverage of these skin temperature observations valuable, which can lead to improved forecasting and more advanced global climate models.
Cloud top heights retrieved from Geostationary Operational Environmental Satellite (GOES) data are evaluated using comparisons to 5 years of surface‐based cloud radar and lidar data taken at the ...Atmospheric Radiation Measurement (ARM) program's site near Lamont, Oklahoma. Separate daytime and nighttime algorithms developed at NASA Langley Research Center (LaRC) applied to GOES imager data and an operational CO2‐slicing technique applied to GOES sounder data are tested. Comparisons between the daytime, nighttime and CO2‐slicing cloud top heights and the surface retrievals yield mean differences of −0.84 ± 1.48 km, −0.56 ± 1.31 km, and −1.30 ± 2.30 km, respectively, for all clouds. The errors generally increase with increasing cloud altitude and decreasing optical thickness. These results, which highlight some of the challenges associated with passive satellite cloud height retrievals, are being used to guide development of a blended LaRC/CO2‐slicing cloud top height product with accuracies suitable for assimilation into weather forecast models.
This research represents the second part of a two-part series describing the development of a prototype ensemble data assimilation system for the Warn-on-Forecast (WoF) project known as the NSSL ...Experimental WoF System for ensembles (NEWS-e). Part I describes the NEWS-e design and results from radar reflectivity and radial velocity data assimilation for six severe weather events occurring during 2013 and 2014. Part II describes the impact of assimilating satellite liquid and ice water path (LWP and IWP, respectively) retrievals from the GOES Imager along with the radar observations. Assimilating LWP and IWP observations may improve thermodynamic conditions at the surface over the storm-scale domain through better analysis of cloud coverage in the model compared to radar-only experiments. These improvements sometimes corresponded to an improved analysis of supercell storms leading to better forecasts of low-level vorticity. This positive impact was most evident for events where convection is not ongoing at the beginning of the radar and satellite data assimilation period. For more complex cases containing significant amounts of ongoing convection, only assimilating clear-sky satellite retrievals in place of clear-air reflectivity resulted in spurious regions of light precipitation compared to the radar-only experiments. The analyzed tornadic storms in these experiments are sometimes too weak and quickly diminished in intensity in the forecasts. The lessons learned as part of these experiments should lead to improved iterations of the NEWS-e system, building on the modestly successful results described here.
Abstract
The increasing maturity of the Warn-on-Forecast System (WoFS) coupled with the now operational
GOES-16
satellite allows for the first time a comprehensive analysis of the relative impacts of ...assimilating
GOES-16
all-sky 6.2-, 6.9-, and 7.3-
μ
m channel radiances compared to other radar and satellite observations. The WoFS relies on cloud property retrievals such as cloud water path, which have been proven to increase forecast skill compared to only assimilating radar data and other conventional observations. The impacts of assimilating clear-sky radiances have also been explored and shown to provide useful information on midtropospheric moisture content in the near-storm environment. Assimilation of all-sky radiances adds a layer of complexity and is tested to determine its effectiveness across four events occurring in the spring and summer of 2019. Qualitative and object-based verification of severe weather and the near-storm environment are used to assess the impact of assimilating all-sky radiances compared to the current model configuration. We focus our study through the entire WoFS analysis and forecasting cycle (1900–0600 UTC, daily) so that the impacts throughout the evolution of convection from initiation to large upscale growth can be assessed. Overall, assimilating satellite data improves forecasts relative to radar-only assimilation experiments. The retrieval method with clear-sky radiances performs best overall, but assimilating all-sky radiances does have very positive impacts in certain conditions. In particular, all-sky radiance assimilation improved convective initiation forecast of severe storms in several instances. This work represents an initial attempt at assimilating all-sky radiances into the WoFS and additional research is ongoing to further improve forecast skill.
Widespread persistent contrails over the western Great Lakes during 9 October 2000 were examined using commercial flight data, coincident meteorological data, and satellite remote sensing data from ...several platforms. The data were analyzed to determine the atmospheric conditions under which the contrails formed and to measure several physical properties of the contrails, including areal coverage, spreading rates, fall speeds, and optical properties. Most of the contrails were located between 10.6 and 11.8 km in atmospheric conditions consistent with a modified form of the Appleman contrail formation theory. However, the Rapid Update Cycle-2 analyses have a dry bias in the upper-tropospheric relative humidity with respect to ice (RHI), as indicated by persistent contrail generation during the outbreak where RHI > or = 85%. The model analyses show that synoptic-scale vertical velocities affect the formation of persistent contrails. Areal coverage by linear contrails peaked at 30 000 km^sup 2^, but the maximum contrail-generated cirrus coverage was over twice as large. Contrail spreading rates averaged around 2.7 km h^sup -1^, and the contrails were visible in the 4-km Geostationary Operational Environmental Satellite (GOES) imagery approximately 1 h after formation. Contrail fall speed estimates were between 0.00 and 0.045 m s^sup -1^ based on observed contrail advection rates. Optical depth measurements ranged from 0.1 to 0.6, with consistent differences between remote sensing methods. Contrail formation density was roughly correlated with air traffic density after the effects of competing cloud coverage, humidity, and vertical velocity were considered. Improved tropospheric humidity measurements are needed for realistic simulations of contrail and cirrus development. PUBLICATION ABSTRACT
Linear contrail coverage, optical depth, and longwave radiative forcing are derived from NOAA-15 and NOAA-16 Advanced Very High Resolution Radiometer data taken during daytime over the continental ...United States of America (USA), southern Canada, northern Mexico, and the adjacent oceans. Analyses were performed for all available overpasses during 2001, but for NOAA-15 were primarily limited to the eastern half and the northwestern corner of the domain. Contrail coverage averaged 1.17 % and 0.65 % from the early morning NOAA-15 and midafternoon NOAA-16, respectively, for the areas and month common to both satellites. The NOAA-16 contrail coverage and radiative properties for the limited NOAA-15 domain are, on average, nearly identical to those for the entire domain. The estimated combined maximum coverage for the entire domain was ∼1.05 % during February, while the minimum of 0.57 % occurred during August. Mean optical depths varied by ∼20 % with winter minima and summer maxima. The annual mean optical depth of 0.27 translated to a normalized contrail longwave radiative forcing of 15.5 Wm−;2. The overall daytime longwave radiative forcing for the domain is 0.11 Wm−2. The normalized radiative forcing peaked during summer while the overall forcing was at a maximum during winter because of the greater contrail coverage. A detailed error analysis showed that the linear contrail coverage was overestimated by ∼40 % for both satellites the true coverage is closer to 0.70 and 0.40 % for NOAA-15 and 16, respectively. Errors in the mean NOAA-15 optical depths and radiative forcing were negligible while their NOAA-16 counterparts were overestimated by approximately 13 %. Contrail coverage was dramatically lower than expected from previous studies, but is most likely due to the significant decrease in upper tropospheric humidity observed in numerical weather analysis data. Contrail optical depths are much greater than both theoretical estimates for this part of North America and empirical retrievals over Europe. The cause of the morning-afternoon difference in contrail coverage is not yet known. Further modelling studies and additional satellite analyses are needed to understand this diurnal cycle and to explain the differences between the present and previous results.
The Edition 2 (Ed2) cloud property retrieval algorithm system was upgraded and applied to the MODerate-resolution Imaging Spectroradiometer (MODIS) data for the Clouds and the Earth's Radiant Energy ...System (CERES) Edition 4 (Ed4) products. New calibrations for solar channels and the use of the 1.24-<inline-formula> <tex-math notation="LaTeX">\mu \text{m} </tex-math></inline-formula> channel for cloud optical depth (COD) over snow improve the daytime consistency between Terra and Aqua MODIS retrievals. Use of additional spectral channels and revised logic enhanced the cloud-top phase retrieval accuracy. A new ice crystal reflectance model and a CO 2 -channel algorithm retrieved higher ice clouds, while a new regional lapse rate technique produced more accurate water cloud heights than in Ed2. Ice cloud base heights are more accurate due to a new cloud thickness parameterization. Overall, CODs increased, especially over the polar (PO) regions. The mean particle sizes increased slightly for water clouds, but more so for ice clouds in the PO areas. New experimental parameters introduced in Ed4 are limited in utility, but will be revised for the next CERES edition. As part of the Ed4 retrieval evaluation, the average properties are compared with those from other algorithms and the differences between individual reference data and matched Ed4 retrievals are explored. Part II of this article provides a comprehensive, objective evaluation of selected parameters. More accurate interpretation of the CERES radiation measurements has resulted from the use of the Ed4 cloud properties.
Abstract
Forecasts of high-impact weather conditions using convection-allowing numerical weather prediction models have been found to be highly sensitive to the selection of cloud microphysics scheme ...used within the system. The Warn-on-Forecast (WoF) project has developed a rapid-cycling, convection-allowing, data assimilation and forecasting system known as the NSSL Experimental WoF System for ensembles (NEWS-e), which is designed to utilize advanced cloud microphysics schemes. NEWS-e currently (2017–18) uses the double-moment NSSL variable density scheme (NVD), which has been shown to generate realistic representations of convective precipitation within the system. However, very little verification on nonprecipitating cloud features has been performed with this system. During the 2017 Hazardous Weather Testbed (HWT) experiment, an overestimation of the areal coverage of convectively generated cirrus clouds was observed. Changing the cloud microphysics scheme to Thompson generated more accurate cloud fields. This research undertook the task of improving the cloud analysis generated by NVD while maintaining its skill for other variables such as reflectivity. Adjustments to cloud condensation nuclei (CCN), fall speed, and collection efficiencies were made and tested over a set of six severe weather cases occurring during May 2017. This research uses an object-based verification approach in which objects of cold infrared brightness temperatures, high cloud-top pressures, and cloud water path are generated from model output and compared against GOES-13 observations. Results show that the modified NVD scheme generated much more skillful forecasts of cloud objects than the original formulation without having a negative impact on the skill of simulated composite reflectivity forecasts.
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