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Browsing by Author "Vonder Haar, Thomas H., advisor"

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    Assimilation of geostationary, infrared satellite data to improve forecasting of mid-level, mixed-phase clouds
    (Colorado State University. Libraries, 2009) Seaman, Curtis J., author; Vonder Haar, Thomas H., advisor
    Mid-level, mixed-phase clouds (altocumulus and altostratus) are difficult to forecast due to the fact that they are generally thin and form in areas of weak vertical velocity where operational models typically have poor vertical resolution and poor moisture initialization. This study presents experiments designed to test the utility of assimilating infrared window and water vapor channels from the Geostationary Operational Environmental Satellite (GOES) instruments, Imager and Sounder, into a mesoscale cloud-resolving model to improve model forecasts of mid-level clouds. The Regional Atmospheric Modeling Data Assimilation System (RAMDAS) is a four-dimensional variational (4-DVAR) assimilation system used to test the viability of assimilating cloudy scene radiances into a cloud-free initial model state for one case of a long-lived, isolated altocumulus cloud over the Great Plains of the United States. Observations from one observation time are assimilated and significant innovations are achieved. Three experiments are performed: (1) assimilation of the 6.7 μm (water vapor) and 10.7 μm (window) channels from GOES Imager, (2) assimilation of the 7.02μm (water vapor) and 12.02 μm (window) channels from GOES Sounder, and (3) assimilation of the 6.7 μm channel from GOES Imager and the 7.02 μm channel from GOES Sounder. It is shown that the GOES Sounder channels provide more useful information than the GOES Imager channels due to increased sensitivity to the mid-troposphere. The decorrelation lengths and variance used in the background error covariance are varied and the impact on the results of the experiments is discussed. The effect of constraining the surface temperatures during assimilation of the window channels is also discussed. It is found that, in a cloud-free initial model state, the adjoint sensitivities are calculated on the assumption that there is no cloud, even with cloud in the satellite observations. This has a significant impact on the success of other 4-DVAR satellite data assimilation experiments.
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    Cloudiness, the planetary radiation budget, and climate
    (Colorado State University. Libraries, 1978) Ellis, James S. (James Stephen), author; Vonder Haar, Thomas H., advisor; Cox, Stephen K., committee member
    Satellite planetary radiation budget measurements from the Nimbus 3 satellite for four semi-monthly periods along with a 29 month composite of measurements from six satellites are applied in a quantitative study to evaluate the effect of cloudiness on the planetary radiation budget. Annual and seasonal results are expressed as zonal, hemispherical and global mean values. The results show that for the planet as a whole the effect of "present day" clouds in reducing the absorbed shortwave flux is larger than their effect in reducing the long wave emitted flux. The difference between the two effects is significantly larger over oceans than over land. Similarly, the sensitivity to changes in cloud amount is greater in the shortwave absorbed flux than in the longwave flux emitted to space. It was also shown that the presence of clouds act to reduce the amplitude of the annual variation of the global planetary net radiation budget. One may hypothesize from the results of this study and the works of others that a uniform increase in global cloud amount (in the absence of changes in cloud top height, cloud albedo, other atmospheric constituents, and vertical temperature lapse rates) will decrease the global mean surface temperature until radiative equilibrium is restored.
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    Evaluating satellite-based cloud persistence and displacement nowcasting techniques over complex terrain
    (Colorado State University. Libraries, 2010) Guillot, Eric Michael, author; Vonder Haar, Thomas H., advisor; Heald, Colette L., committee member; Reising, Steven C., committee member
    Cloud nowcasting (0-6 hour forecasts) is an important area of study for weather forecasting, solar energy estimation, and Department of Defense (DoD) applications. The DoD is developing data assimilation methods to predict cloud movement. However these systems require valuable time to run and are not always accurate. Because many military operations are of a time-sensitive nature, fast-processing cloud nowcasting techniques are required. Satellite imagery has shown that clouds move at varying speeds and in different directions, while some tend not to move at all. We test the hypothesis that clouds forced by complex terrain do not displace with the wind, but instead persist along the barrier on which they were formed. Thus, a combination of persistence and displacement techniques in regions of complex terrain are expected to yield a better forecast than either of them alone. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard both the Terra and Aqua satellites allows for the same region of Earth to be sampled twice by each satellite in a roughly 2-4 hour timeframe. This allows a 2-4 hour cloud nowcast to be created and tested. Using the MODIS Cloud Mask algorithm at 5 km resolution (interpolated to 1 km) and wind data from local weather balloon soundings, a cloud climatology nowcast, a cloud persistence nowcast, a cloud 700mb wind nowcast, a cloud various wind speed nowcast, and a cloud terrain-influenced nowcast were developed from December 2008 through November 2009 over Utah and southwestern Wyoming. Persistence/displacement forecasts were also conducted based on the phase of the cloud, as determined by the MODIS Cloud Phase algorithm. A new forecast skill evaluation scheme was also introduced, designed to equally appreciate correct cloudy areas and correct clear areas. Contrary to our hypothesis, the persistence nowcasting method demonstrated the best skill, especially in the winter months, by as much as 10% critical success index (CSI) over the other methods. The Persistence Method, 700mb Method, and Various Winds Method performed similarly during the summer months (~65% CSI for all three). Use of cloud phase information revealed that ice cloud persistence, while displacing either liquid-water clouds or mixed-phase clouds yielded the highest CSI scores, but the resulting scores were still lower than the Persistence Method. We conclude that cloud analysis at high resolution over complex terrain in Utah, using no model wind or moisture data, cannot improve upon a persistence nowcast over Utah. However, because these basic nowcasting methods can be run and their skill evaluated in less than two minutes, educated decisions can be made nearly instantaneously.
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    Observation of progressive convective interactions from the Rocky Mountain slopes to the Plains
    (Colorado State University. Libraries, 1979) Philipp, Ceri Burns, author; Vonder Haar, Thomas H., advisor; Cotton, William R., committee member; Meiman, James R., committee member
    Geosynchronous satellite data were employed for a climatological study of two summers' data and for a specific case study to observe convective interactions between the eastern slopes of the Colorado Rocky Mountains and the plains of eastern Colorado and western Kansas. The climatological study involved imagery for May-August 1976 and 1977 for a study region defined from eastern Utah to western Kansas that was divided into five areas. Development and movement of convective activity from the mountains to the plains was identified by the satellite imagery analysis for 12% of the 1976 summer days (13 out of 108) and 17% of the 1977 summer days (16 out of 94). When precipitation records for stations in western Kansas were consulted, it was found that these satellite- identified development and movement days made a significant contribution to the monthly and seasonal total precipitation for this area. There were instances when the contribution was greater than 90% (for some months) and greater than 50% (for seasonal total). Further results from the climatological study showed that cumulus clouds were most likely to form in the southwestern and central Colorado mountains between 0700 and 1000 MDT (1300 to 1600 GMT). Mountain regions were generally clearing remnants of old cells during the late afternoon, evening and night hours with development and growth of new cells occurring in the early morning to early afternoon. Plains regions generally were clearing remnants during morning and early afternoon hours with convection developing in late afternoon, evening and night hours. A quantitative case study was performed for 4 August 1977 when 3-minute rapid scan satellite data were available. It was a day when optimum conditions for development and movement from the mountains to the plains existed. Computer programs on the All Digital Video Imaging System for Atmospheric Research (ADVISAR) were used to study changes in cloud size, cloud number, and cloud brightness for two areas in Colorado. The first area was in the northeastern Colorado Rocky Mountains where the primary storm system moved through. The second area was in southern Colorado (near Pueblo) which included both mountains and plains regions and primarily stationary convective activity. From the quantitative study, no definite correlation was found between changes in cloud number and changes in cloud brightness. Differences in both quantities over 3-minute intervals were found to be significant and were sometimes larger than 6 or 9-minute changes. Both areas showed varying patterns of increasing and decreasing cloud number and brightness. The first area with the active moving system tended to have greater mean brightness and more time periods with large clouds than the stationary system area. It also had larger "largest clouds" over the time period studied (1100 - 1624 MDT) than the second area.
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    Quasi-global and regional water vapor and rainfall rate climatologies for a 35 month period
    (Colorado State University. Libraries, 2010) Howell, Kelly Michelle, author; Vonder Haar, Thomas H., advisor; Kidder, Stanley Q., advisor; Kummerow, Christian Detlef, committee member; Ramírez, Jorge A., committee member
    Atmospheric water vapor and rainfall are crucial elements in the global water cycle. The spatial and temporal variations of total precipitable water (TPW) and rainfall rate (RR) between 60° N and 60° S are investigated. In addition, nine oceanic locations in different climate regions are further studied in order to clarify regional differences in a more detailed manner. The Blended Total Precipitable Water (bTPW) product from the Cooperative Institute for Research in the Atmosphere (CIRA) provides the water vapor observations and the Climate Prediction Center morphing method (CMORPH) product is used for the rainfall rate. These six-hourly datasets were analyzed at 0.25°×0.25° resolution during the period between February 2006 and December 2008. The variations present in these quasi-global TPW and RR climatologies are found to be similar to the variations presented in previous studies. For instance, oceanic TPW maximizes around 7° N at 45 mm, the most land-falling rain occurs around 2° S, and the most oceanic rainfall occurs around 7° N. However, both datasets over the 35 month period indicate an occurrence of the double Intertropical Convergence Zone during the boreal spring that is not evident in the previous TPW studies presented. Over the study period, the quasi-global CMORPH mean daily RR is 2.63 mm day-1 and the quasi-global bTPW mean oceanic TPW is 24.94 mm. Regionally, the rainfall rate distributions were found to approximate exponential decay, with typically drier regions corresponding with faster decay rates. This pattern is also evident on a global scale. While one might expect an increased TPW to correspond with an increased RR, it was found that rainfall is possible at nearly any TPW value. On a global scale, higher TPW values are associated with higher probabilities of rainfall, although global patterns of moisture convergence and vertical motion are key factors in the production of this rainfall. The RR algorithms used to form the CMORPH product are less sensitive to stratiform light rain, which means that rainfall is likely underestimated in areas receiving mostly this type of rain, such as the subtropical eastern Pacific Ocean. The results demonstrate that the bTPW and CMORPH products produce observations consistent with past climatologies and that TPW on its own is not an accurate indicator of rainfall; other dynamical and thermodynamical effects must be considered.
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    Three regional climatologies of marine stratocumulus characteristics using the A-train satellite data
    (Colorado State University. Libraries, 2010) Ram, Jessica A., author; Vonder Haar, Thomas H., advisor; Miller, Steven D., advisor; Krueger, David A., committee member; Schubert, Wayne H., committee member
    Low-level marine stratocumulus clouds are known to play a large role in the Earth's radiation budget. They also present challenges to forecasts using numerical models. While many studies have attempted to model or explain the complicated microphysical aspects of these clouds, it is important to understand the broader macrophysical relationships between the precipitation and radiative properties of marine stratocumulus. In this thesis, data for these clouds over three subtropical regions has been gathered for the time period spanning from June 15, 2006 to February 15, 2009. The data come from NASA' s A-train satellites, CloudSat, CALIPSO, and Aqua, and some of this data is even compared to buoy observations off of the Pacific South American coast. With marine boundary layer clouds defined by cloud top heights below 2 km in the combined CloudSat-CALIPSO dataset, spatial and temporal averages are calculated for cloud and precipitation frequency as the various combinations of cloud detection are examined as well. Typical values for longwave and shortwave fluxes and cloud optical depth are also obtained for one of the regions off of the South American coast, some of which are compared to in-situ buoy data. Lidar data from CALIPSO is key to detecting a majority of marine stratocumulus while the radar detects about 35% of marine stratocumulus. On average 12% of the marine stratocumulus are precipitating and this accounts for about 1/3 of the radar-detected clouds. Radar detection of marine stratocumulus and precipitation also increased for the nighttime passes. This research also shows the spatial and temporal seasonal and annual averages for cloud and precipitation amounts in each region. We found the South American region to be the cloudiest location with the most frequently precipitating marine stratocumulus. Marine stratocumulus clouds tend to increase the surface downwelling longwave flux by about 100 W m-2 with respect to clear sky while decreasing the downwelling shortwave flux by about 900 W m-2. These estimated flux values only sometimes agree with nearby buoy data for the longwave fluxes and very rarely agree with the buoy shortwave fluxes, owing to spatial heterogeneity of the cloud field. Overall, the results provide new information about the precipitation processes of marine stratocumulus and its effects over an extended period of time for three subtropical locations.
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    Using total precipitable water anomaly as a forecast aid for heavy precipitation events
    (Colorado State University. Libraries, 2013) VandenBoogart, Lance M., author; Vonder Haar, Thomas H., advisor; Schumacher, Russ S., committee member; Ramirez, Jorge A., committee member; Kidder, Stanley Q., committee member
    Heavy precipitation events are of interest to weather forecasters, local government officials, and the Department of Defense. These events can cause flooding which endangers lives and property. Military concerns include decreased trafficability for military vehicles, which hinders both war- and peace-time missions. Even in data-rich areas such as the United States, it is difficult to determine when and where a heavy precipitation event will occur. The challenges are compounded in data-denied regions. The hypothesis that total precipitable water anomaly (TPWA) will be positive and increasing preceding heavy precipitation events is tested in order to establish an understanding of TPWA evolution. Results are then used to create a precipitation forecast aid. The operational, 16 km-gridded, 6-hourly TPWA product developed at the Cooperative Institute for Research in the Atmosphere (CIRA) compares a blended TPW product with a TPW climatology to give a percent of normal TPWA value. TPWA evolution is examined for 84 heavy precipitation events which occurred between August 2010 and November 2011. An algorithm which uses various TPWA thresholds derived from the 84 events is then developed and tested using dichotomous contingency table verification statistics to determine the extent to which satellite-based TPWA might be used to aid in forecasting precipitation over mesoscale domains. The hypothesis of positive and increasing TPWA preceding heavy precipitation events is supported by the analysis. Event-average TPWA rises for 36 hours and peaks at 154% of normal at the event time. The average precipitation event detected by the forecast algorithm is not of sufficient magnitude to be termed a "heavy" precipitation event; however, the algorithm adds skill to a climatological precipitation forecast. Probability of detection is low and false alarm ratios are large, thus qualifying the algorithm's current use as an aid rather than a deterministic forecast tool. The algorithm's ability to be easily modified and quickly run gives it potential for future use in precipitation forecasting.