Microwave Temperature and Humidity Profiler (MTHP) Data collected onboard the NSF/NCAR GV HIAPER aircraft from 7 April to 28 April 2022 as part of the TI3GER (Technological Innovation into Iodine and GV Environmental Research) field campaign. These data are available in a NETCDF4/HDF5 compatible format.

The High-resolution Urban Meteorology for Impacts Dataset, HUMID, will be useful for studies examining spatial variability of near surface meteorology and the impacts of urban heat islands across many disciplines including epidemiology, ecology, and climatology. We have explicitly included representation of spatial meteorological variability over urban areas in the contiguous United States (CONUS) as compared to other observation-only gridded meteorology products by employing the High-Resolution Land Data Assimilation System (HRLDAS), which accounts for the fine-scale impacts of spatiotemporally varying land surfaces on weather. Further, we include in situ meteorological observations such as local mesonets to bias correct the HRLDAS output, creating a model-observation fusion product. The data spans 1 January 1981 to 31 December 2018, covering all of CONUS at 1 km grid spacing. The dataset includes daily maximum, minimum, and mean values for a variety of temperature estimates such as 2 m temperature, skin temperature, urban temperatures, as well as specific humidity and surface energy budget terms. The full variable list with corresponding file and variable metadata is in this file [https://rda.ucar.edu/OS/web/datasets/d314008/docs/humid_dataset_readme.pdf].

Products from NCEP/NCAR Reanalysis Project (NNRP or R1) are archived in this dataset. The resolution of the global Reanalysis Model is T62 (209 km) with 28 vertical sigma levels. Results are available at 6 hour intervals. Although the initial plan is to reanalyze the data for a 40-year period (1957-1996), production has gone back to 1948 and going forward continuously. Future plans call for rerunning the entire period as next generation models are ready.

There are over 80 different variables, (including geopotential height, temperature, relative humidity, u- and v- wind components, etc.) in several different coordinate systems, such as 17 pressure level stack on 2.5 by 2.5 degree grids, 28 sigma level stack on 192 by 94 Gaussian grids, and 11 isentropic level stack on 2.5 by 2.5 degree grid. They are organized as different subgroups in the archive. In addition to analyses, diagnostic terms (for example: radiative heating, convective heating) and accumulative variables (like precipitation rate) are present. The input observations are archived with quality and usage flags in WMO BUFR format. Most of the project outputs are stored in WMO GRIB format. Other files, such as restart files and zonal statistics, are saved in IEEE format.

Some special periods are analyzed more than once to provide data for special research studies. For example, a special run of 1979 was made excluding most satellite inputs. This run could be used for evaluating the impact of satellite data on the analysis. During the TOGA COARE experiment period, special runs of reanalysis model without experimental data are archived under the TOGA COARE directory.

For details and problems, see NCEP/NCAR Reanalysis TOGA COARE [https://rda.ucar.edu/datasets/ds090.0/inventories/TOGA-COARE/]. Monthly means are on line at ds090.2 [https://rda.ucar.edu/datasets/ds090.2/]. The R1 forecasts are in ds090.1 [https://rda.ucar.edu/datasets/ds090.1/] dataset.

This dataset includes climate model output data from NCAR's Community Earth System Model (CESM) CMIP 5 runs, with output fields for the 3-D global atmosphere at six hourly intervals. A basic set of parameters is provided on 26 model hybrid level surfaces: specific humidity, temperature, wind components, and geopotential height to support regional modeling studies. Additional parameters are provided on single level grids to support analysis studies including surface temperature. Data are available in yearly time-series parameter archive files, and monthly synoptic time archive files. An interface is provided to give users the option to select parameter, temporal, and spatial subsets from the monthly synoptic time archive files. The data are a single 20th Century (1950-2005) simulation and three concomitant Representative Concentration Pathway (RCP) future scenarios spanning 2005-2100. These computer runs were completed in 2011.

NOTE: All RCP2.6 data has been removed due to corrupted data caused by a model bug. Users needing for WRF boundary conditions are recommended to use the bias corrected version of this dataset found in RDA dataset ds316.1, NCAR CESM Global Bias-corrected CMIP5 Output to Support WRF/MPAS Research.

This dataset includes global bias-corrected climate model output data from version 1 of NCAR's Community Earth System Model (CESM1) that participated in phase 5 of the Coupled Model Intercomparison Experiment (CMIP5), which supported the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5). The dataset contains all the variables needed for the initial and boundary conditions for simulations with the Weather Research and Forecasting model (WRF) or the Model for Prediction Across Scales (MPAS), provided in the Intermediate File Format specific to WRF and MPAS. The data are interpolated to 26 pressure levels and are provided in files at six hourly intervals. The variables have been bias-corrected using the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA-Interim) fields for 1981-2005, following the method in Bruyere et al. (2013). Files are available for a 20th Century simulation (1951-2005) and three concomitant Representative Concentration Pathway (RCP) future scenarios (RCP4.5, RCP6.0 and RCP8.5) spanning 2006-2100.

DC3_MetNav_AircraftInSitu_NSF-GV-HIAPER_Data are in-situ meteorological and navigational data collected onboard the NSF/NCAR GV-HIAPER aircraft during the Deep Convective Clouds and Chemistry (DC3) field campaign. Data collection for this product is complete.

The Deep Convective Clouds and Chemistry (DC3) field campaign sought to understand the dynamical, physical, and lightning processes of deep, mid-latitude continental convective clouds and to define the impact of these clouds on upper tropospheric composition and chemistry. DC3 was conducted from May to June 2012 with a base location of Salina, Kansas. Observations were conducted in northeastern Colorado, west Texas to central Oklahoma, and northern Alabama in order to provide a wide geographic sample of storm types and boundary layer compositions, as well as to sample convection. DC3 had two primary science objectives. The first was to investigate storm dynamics and physics, lightning and its production of nitrogen oxides, cloud hydrometeor effects on wet deposition of species, surface emission variability, and chemistry in anvil clouds. Observations related to this objective focused on the early stages of active convection. The second objective was to investigate changes in upper tropospheric chemistry and composition after active convection. Observations related to this objective focused on the 12-48 hours following convection. This objective also served to explore seasonal change of upper tropospheric chemistry. In addition to using the NSF/NCAR Gulfstream-V (GV) aircraft, the NASA DC-8 was used during DC3 to provide in-situ measurements of the convective storm inflow and remotely-sensed measurements used for flight planning and column characterization. DC3 utilized ground-based radar networks spread across its observation area to measure the physical and kinematic characteristics of storms. Additional sampling strategies relied on lightning mapping arrays, radiosondes, and precipitation collection. Lastly, DC3 used data collected from various satellite instruments to achieve its goals, focusing on measurements from CALIOP onboard CALIPSO and CPL onboard CloudSat. In addition to providing an extensive set of data related to deep, mid-latitude continental convective clouds and analyzing their impacts on upper tropospheric composition and chemistry, DC3 improved models used to predict convective transport. DC3 improved knowledge of convection and chemistry, and provided information necessary to understanding the processes relating to ozone in the upper troposphere.

NCAR-NMC Upper Air is historical digital data set DSI-6309 archived at the National Climatic Data Center (NCDC). This is meteorological upper air data. This is a small, historical upper air data set that was created by the National Center for Atmospheric Research (NCAR) and the old National Meteorological Center (now the National Centers for Environmental Prediction (NCEP) in the National Weather Service (NWS)) and archived at the NCDC. Data is global for the 2 year period 1971-2. DSI-6309 was included in the much larger Comprehensive Aerological Data Set (CARDS) Upper Air data set, DSI-6305, which was quality controlled as it was assembled from many smaller data sets. DSI-6309 itself was not quality controlled at the NCDC. Most users should not request DSI-6309, but should instead opt for DSI-6305. Major parameters in upper air data sets are: pressure, temperature, relative humidity, and wind speed and direction.

The NCEP/NCAR Reanalysis project is using a state-of-the-art analysis/forecast system to perform data assimilation using past data from 1948 to the present. A large subset of this data is available from CDC in its original 4 times daily format and as daily averages. However, the data from 1948-1957 is a little different, in the regular (non-Gaussian) gridded data. That data was done at 8 times daily in the model, because the inputs available in that era were available at 3Z, 9Z, 15Z, and 21Z, whereas the 4x daily data has been available at 0Z, 6Z, 12Z, and 18Z. These latter times were forecasted and the combined result for this early era is 8x daily. The local ingestion process took only the 0Z, 6Z, 12Z, and 18Z forecasted values, and thus only those were used to make the daily time series and monthly means here. Please read the problem list before using the data. The NCEP/NCAR Reanalysis descriptions here are subdivided into separate data sets These are currently: Pressure Level Data Surface Data Surface Flux Data Other Flux Data Tropopause Level Data T62 Spectral Coefficients You can now search the NCEP/NCAR Reanalysis data by selecting one of these links: Search all of the NCEP/NCAR Reanalysis available at CDC. Search the NCEP/NCAR Reanalysis 4x daily data available at CDC. Search the NCEP/NCAR Reanalysis daily average data available at CDC. Search the CDC products derived from the NCEP/NCAR Reanalysis including monthly and long-term means.

 NOAAServer Codes: [POL 90 -90 180 -180] ; nodateline preview obtain

The Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) is an ongoing multiinstitutional, international effort addressing the response of biogeography and biogeochemistry to environmental variability in climate and other drivers in both space and time domains. The objectives of VEMAP are the intercomparison of biogeochemistry models and vegetation type distribution models (biogeography models) and determination of their sensitivity to changing climate, elevated atmospheric carbon dioxide concentrations, and other sources of altered forcing. Climate scenarios from eight climate change experiments are included in the data set. Seven of these experiments are from atmospheric general circulation model (GCM) 1xCO2 and 2xCO2 equilibrium runs. These GCMs were implemented with a simple "mixed-layer" ocean representation that includes ocean heat storage and vertical exchange of heat and moisture with the atmosphere, but omits or specifies (rather than calculates) horizontal ocean heat transport. The eighth scenario is from a limited-area nested regional climate model (RegCM) experiment for the U.S. which was supported by the Model Evaluation Consortium for Climate Assessment (MECCA). The CCC and GFDL R30 runs are among the high resolution GCM experiments reported in IPCC (1990). Changes in monthly mean temperature and relative humidity were represented as differences (2xCO2 climate value - 1xCO2 climate value) and those for monthly precipitation, solar radiation, vapor pressure, and horizontal wind speed as change ratios (2xCO2 climate value/1xCO2 climate value). GCM grid point change values were derived from archives at the National Center for Atmospheric Research (NCAR; Jenne 1992) and spatially interpolated to the 0.5 degree VEMAP grid. Wind speed changes are for the lowest model level. For GISS runs, we calculated winds from vector components and then determined the change ratio. Values from the 60-km RegCM grid were reprojected to the 0.5 degree grid. Vapor pressure (and relative humidity) were not available for the CCC run; relative humidity changes were not determined for the RegCM experiment. A key issue in the generation of altered climates based on climate model output is the strong possibility of physical inconsistencies in the new climates. Change ratios from the NCAR archive have an imposed upper limit of 5.0, providing some constraint on these changes. An exception is that the GISS wind speed change ratios do not have this limit imposed (most GISS wind speed change ratios were less than 5). For a discussion of the utility and limitations of using climate model experiment outputs for exploring ecological sensitivity to climate change, see Sulzman et al. (1995). The 8 climate model experiments are: CCC - Canadian Climate Centre (Boer, McFarlane, and Lazare 1992) GISS - Goddard Institute for Space Studies (Hansen et al. 1984) GFDL - Geophysical Fluid Dynamics Laboratory. Three experiments: (1) GFDL R15: R15 (4.5 degree by 7.5 degree grid) runs without Q- flux corrections (Manabe and Wetherald, 1987). (2) GFDL R15 Q-flux: R15 resolution (4.5 degree by 7.5 degree grid) runs with Q-flux corrections (Manabe and Wetherald 1990, Wetherald and Manabe 1990). (3) GFDL R30: R30 (2.22 degree by 3.75 degree grid) run with Q-flux corrections (Manabe and Wetherald 1990, Wetherald and Manabe 1990). OSU - Oregon State University (Schlesinger and Zhao 1989) UKMO - United Kingdom Meteorological Office (Wilson and Mitchell 1987) RegCM (MM4) - National Center for Atmospheric Research (NCAR) nested regional climate model (climate version of the Pennsylvania State University/NCAR mesoscale model MM4; Giorgi, Brodeur and Bates 1994). Conterminous U.S. simulations were on a 60-km interval grid and were driven by 1x and 2xCO2 equilibrium GCM runs (Thompson and Pollard 1995a, 1995b). 1x and 2xCO2 RegCM runs were each 3 years in length. Climate changes were based on averages for these runs. A complete users guide to the VEMAP Phase I database which includes more information about this data set can be found at ftp://daac.ornl.gov/data/vemap-1/comp/Phase_1_User_Guide.pdf. ORNL DAAC maintains additional information associated with the VEMAP Project. Data Citation: This data set should be cited as follows: Kittel, T. G. F., N. A. Rosenbloom, T. H. Painter, D. S. Schimel, H. H. Fisher, A. Grimsdell, VEMAP Participants, C. Daly, and E. R. Hunt, Jr. 2002. VEMAP Phase I Database, revised. Available on-line from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A.

The NCAR Upper Air Database (UADB) contains global observations beginning in the 1920s and extends to a near current date. Upper air soundings from about 50 different sources have been consolidated into products that are well documented and provide the longest possible, duplicate-free, station time series. Historical sampling methods have been accounted for by creating two product lines, one with soundings that have wind (UADB-Wind) and another with temperature and humidity (UADB-TRH) measurements. This approach maximizes the amount of data consolidated, and when profiles have simultaneous temperature, humidity, and wind measurements, they are replicated in both products. The first consolidation step was compositing stations with identical WMO station numbers across all data sources. The UADB-TRH product has nearly 1100 stations that report for 20 years or more, and over 400 stations have time series of 50 years or longer. The UADB-Wind product has about 1600 stations that report for 20 years or more, and over 500 stations have soundings for at least 50 years. Next stations with different WMO station numbers, but that are located at identical latitudes and longitudes, or nearly so (within 40 kilometers) were combined, accounting for WMO station number changes and small position relocations. The result is that even longer station time series are created; extensions occur at over 240 and 250 locations in the UADB-TRH and UADB-Wind products, respectively. The composited and combined products are both available.

The Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) Phase 2 has developed a number of transient climate change scenarios based on coupled atmosphere-ocean general circulation model (AOGCM) transient climate experiments. The purpose of these scenarios is to reflect time-dependent changes in surface climate from AOGCMs in terms of both (1) long-term trends and (2) changes in multiyear (3-5 yr) to decadal variability patterns, such as El Nino/Southern Oscillation(ENSO). Development of the data set is reported in Kittel et al. (1997). Scenarios have been derived from transient greenhouse gas experiments with sulfate aerosols from the Canadian Climate Center (CCC) and the Hadley Centre (HADCM2; Mitchell et al. 1995, Johns et al. 1997) accessed via the Climate Impacts LINK Project, Climatic Research Unit, University of East Anglia. Scenarios were developed for the following variables: total incident solar radiation, minimum and maximum temperature, vapor pressure, precipitation, relative humidity and mean daily irradiance for the time periods January 1994 to approximately 2100. These data and the VEMAP 1 data (Kittel et al. 1995) were used to drive models in VEMAP Phase 2, the objectives of which are to compare time-dependent ecological responses of biogeochemical and coupled biogeochemical-biogeographical models to historical and projected transient forcings across the conterminous U.S. This data set of daily climate change scenarios was designed to be concatenated with the /VEMAP/vemap.html">VEMAP 2: U.S. Daily Climate, 1895-1993, Version 2 data set to create a single climate series from 1895 - ~2100. This data set is being made available for the U.S. National Assessment. Users are requested to confer with the NCAR VEMAP Data Group to ensure that the intended application of the data set is consistent with the generation and limitations of the data. For more information, refer to the VEMAP homepage. Data Citation The data set should be cited as follows: Kittel, T. G. F., N. A. Rosenbloom, C. Kaufman, J. A. Royle, C. Daly, H. H. Fisher, W. P. Gibson, S. Aulenbach, R. McKeown, D. S. Schimel, and VEMAP 2 Participants. 2000. VEMAP 2: U. S. Daily Climate Change Scenarios. Available on-line from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A.

Downscaled North American Multi-Model Ensemble Forecast of Meteorological Variables for the Pacific Northwest Monthly retrospective hindcasts (1982-2010) and forecasts (2011-2020) of temperature and precipitation are acquired for the Pacific Northwest region of the United States from five models (CFSv2, NASA GEOS5v2, CanCM4i, GEM-NEMO, and NCAR-CCSM) participating in the North American Multi-Model Ensemble project (Kirtman et al., 2014). These models, detailed in Table 1 with more recent information available in (Becker et al., 2022), are initialized monthly to provide a forecast of 0-9 months at a 1.0̊ × 1.0̊ spatial resolution. The multi-model ensemble mean (ENSMEAN) is then generated for each initialization by simply averaging all considered models and their ensemble members. Monthly ENSMEAN forecast is bias-corrected and spatially downscaled to 1/24th degree using the methodology described in Wood et al. (2002) and Barbero et al. (2017) using historical meteorological data (gridMET; Abatzoglou, 2013) as the baseline. Then, the downscaled ENSMEAN data are temporally disaggregated to daily timescales using an analog approach. The closest analog month for the ENSMEAN forecast is found from the gridMET dataset by minimizing the root mean square error (RMSE) of monthly gridMET and forecast precipitation (excluding gridMET data for the target month). Other daily meteorological variables (such as maximum and minimum temperature, maximum and minimum relative humidity, wind speed, and specific humidity) are extracted from the same analog month to use as input for the coupled crop-hydrology model. As a last step to the analog approach, the process corrects the bias between the forecast and analog month to ensure that monthly mean temperature and accumulated precipitation match those of the original forecast. Table 1. List of NMME models used to create Ensemble Mean.

Model Model Expansion Ensemble Size References

NCEP- CFSv2 Climate Forecast System, version 2 24 (Saha et al., 2014)

NASA GEOS5v2 Goddard Earth Observing System, version 5 4 (Molod et al., 2020)

CanCM4i Fourth Generation Canadian Coupled Global Climate Model 10 (Merryfield et al., 2013)

GEM - NEMO Global Environmental Multiscale Model – Nucleus for European Modelling of the Ocean 10 (Lin et al., 2020)

NCAR - CCSM Community Climate System Model 10 (Kirtman & Min, 2009)

The dataset has *.mat files which are MATLAB data files. References

Abatzoglou, J. T. (2013). Development of gridded surface meteorological data for ecological applications and modelling. International Journal of Climatology, 33(1), 121–131. https://doi.org/10.1002/joc.3413

Barbero, R., Abatzoglou, J. T., & Hegewisch, K. C. (2017). Evaluation of Statistical Downscaling of North American Multimodel Ensemble Forecasts over the Western United States. Weather and Forecasting, 32(1), 327–341. https://doi.org/10.1175/WAF-D-16-0117.1

Becker, E. J., Kirtman, B. P., L’Heureux, M., Muñoz, Á. G., & Pegion, K. (2022). A Decade of the North American Multimodel Ensemble (NMME): Research, Application, and Future Directions. Bulletin of the American Meteorological Society, 103(3), E973–E995. https://doi.org/10.1175/BAMS-D-20-0327.1

Kirtman, B. P., & Min, D. (2009). Multimodel Ensemble ENSO Prediction with CCSM and CFS. Monthly Weather Review, 137(9), 2908–2930. https://doi.org/10.1175/2009MWR2672.1

Kirtman, B. P., Min, D., Infanti, J. M., Kinter, J. L., Paolino, D. A., Zhang, Q., Dool, H. van den, Saha, S., Mendez, M. P., Becker, E., Peng, P., Tripp, P., Huang, J., DeWitt, D. G., Tippett, M. K., Barnston, A. G., Li, S., Rosati, A., Schubert, S. D., … Wood, E. F. (2014). The North American Multimodel Ensemble: Phase-1 Seasonal-to-Interannual Prediction; Phase-2 toward Developing Intraseasonal Prediction. Bulletin of the American Meteorological Society, 95(4), 585–601. https://doi.org/10.1175/BAMS-D-12-00050.1

Lin, H., Merryfield, W. J., Muncaster, R., Smith, G. C., Markovic, M., Dupont, F., Roy, F., Lemieux, J.-F., Dirkson, A., Kharin, V. V., Lee, W.-S., Charron, M., & Erfani, A. (2020). The Canadian Seasonal to Interannual Prediction System Version 2 (CanSIPSv2). Weather and Forecasting, 35(4), 1317–1343. https://doi.org/10.1175/WAF-D-19-0259.1

Merryfield, W. J., Lee, W.-S., Boer, G. J., Kharin, V. V., Scinocca, J. F., Flato, G. M., Ajayamohan, R. S., Fyfe, J. C., Tang, Y., & Polavarapu, S. (2013). The Canadian Seasonal to Interannual Prediction System. Part I: Models and Initialization. Monthly Weather Review, 141(8), 2910–2945. https://doi.org/10.1175/MWR-D-12-00216.1

Molod, A., Hackert, E., Vikhliaev, Y., Zhao, B., Barahona, D., Vernieres, G., Borovikov, A., Kovach, R. M., Marshak, J., Schubert, S., Li, Z., Lim, Y.-K., Andrews, L. C., Cullather, R., Koster, R., Achuthavarier, D., Carton, J., Coy, L., Friere, J. L. M., … Pawson, S. (2020). GEOS-S2S Version 2: The GMAO High-Resolution Coupled Model and Assimilation System for Seasonal Prediction. Journal of Geophysical Research: Atmospheres, 125(5), e2019JD031767. https://doi.org/10.1029/2019JD031767

Saha, S., Moorthi, S., Wu, X., Wang, J., Nadiga, S., Tripp, P., Behringer, D., Hou, Y.-T., Chuang, H., Iredell, M., Ek, M., Meng, J., Yang, R., Mendez, M. P., Dool, H. van den, Zhang, Q., Wang, W., Chen, M., & Becker, E. (2014). The NCEP Climate Forecast System Version 2. Journal of Climate, 27(6), 2185–2208. https://doi.org/10.1175/JCLI-D-12-00823.1

Wood, A. W., Maurer, E. P., Kumar, A., & Lettenmaier, D. P. (2002). Long-range experimental hydrologic forecasting for the eastern United States. Journal of Geophysical Research: Atmospheres, 107(D20), ACL 6-1-ACL 6-15. https://doi.org/10.1029/2001JD000659

This data set includes airborne measurements obtained from the NCAR Research Aviation Facility (RAF) C-130 aircraft (Tail Number: N130AR) during the Coastally Trapped Waves (CTW) project. This dataset contains high rate navigation, state parameter, and microphysics flight-level data in NetCDF format.

This data set includes airborne measurements obtained from the Sabreliner aircraft (Tail Number N307D) during the Q80 project. This dataset contains low rate navigation, state parameter, and microphysics flight-level data in GENPRO-I format.

This data set contains meteorological and radiometric data from the National Center for Atmospheric Research (NCAR) Sabreliner aircraft that was collected during the 1986 First ISCCP Regional Experiment (FIRE) Cirrus Intensive Field-Observation (IFO). The NCAR Sabreliner research aircraft is a Rockwell International Sabreliner Model 60 aircraft, a low-wind twin-jet monoplane. The NCAR instrumentation that measured the data described above consisted of: 1. Aircraft Position, Velocity and Attitude -- Litton LTN-51 INS (Inertial Navigation System) 2. Static Pressure -- Rosemount Model 1201F1 Pressure Transducer (Fuselage Port) 3. Temperatures -- Rosemount Type 102 Non-dieced and Dieced Sensors (with Rosemount Model 510BH Amplifiers) 4. Dew Point and Humidity -- EG&G Model 137-C3 Dew Point Hygrometers -- NCAR Model LA-3 Lyman-alpha Hygrometer 5. Flow Angle Sensors -- Rosemount Model 858 Gust Probe -- Rosemount Model 1221FVL Differential Pressure Transducer 6. Cloud Physics -- Rosemount 871A Icing Rate Detector 7. Radiation Irradiances -- Shortwave Radiation (.3 - 2.8 microns): Research Aviation Facility (RAF) Modified Epply Model PSP Pyranometers -- Near Infrared Radiation (.7 - 2.8 microns): RAF Modified Epply Model Precision Spectral Pyranometer (PSP) Pyranometers -- Infrared Radiation (4 - 50 microns): RAF Modified Epply Model Precision Infrared Radiometer (PIR) Pyrgeometers

This data set includes airborne measurements obtained from the NSF/NCAR HIAPER GV aircraft (Tail Number N677F) during the ORCAS (The O2/N2 Ratio and CO2 Airborne Southern Ocean Study) project. This dataset contains low rate navigation, state parameter, and microphysics flight-level data in ICARTT format.

The First ISCCP Regional Experiments have been designed to improve data products and cloud/radiation parameterizations used in general circulation models (GCMs). Specifically, the goals of FIRE are (1) to seek the basic understanding of the interaction of physical processes in determining life cycles of cirrus and marine stratocumulus systems and the radiative properties of these clouds during their life cycles and (2) to investigate the interrelationships between ISCCP data, GCM parameterizations, and higher space and time resolution cloud data. To-date, four intensive field-observation periods were planned and executed: a cirrus IFO (October 13 - November 2, 1986); a marine stratocumulus IFO off the southwestern coast of California (June 29 - July 20, 1987); a second cirrus IFO in southeastern Kansas (November 13 - December 7, 1991); and a second marine stratocumulus IFO in the eastern North Atlantic Ocean (June 1 - June 28, 1992). Each mission combined coordinated satellite, airborne, and surface observations with modeling studies to investigate the cloud properties and physical processes of the cloud systems. The microphysical parameters in the data set were derived from 2D probe data collected by the NCAR aircraft during FIRE II. The 2D-C data are converted to size spectra according to the guidelines given in Heymsfield and Baumgardner (1985, Bull. Amer. Meteoro. Soc.), where one element is added to the size of a particle along the the flight direction to account for the probe's intrinsic start-up time. Size is determined as the maximum dimension ($D_{max}$) along the flight direction or optical array axis. The nominal size resolution for the Sabreliner 2D probe is 50 microns/per shadowed optical array element, for the King Air is 25 microns/bin. Sample area (SA) is derived using the depth of field estimates reported by Knollenberg (1970). Particles are binned into 32 size categories, nonuniformly spaced with higher resolution in the smaller classes. Particles within each size bin are subdivided into 10 ``area ratio (AR)'' bins, where AR represents the ratio of particle area to the area of discs of diameter $D_{max}$. The microphysical parameters in the data set were derived from 2D probe data collected by the NCAR Sabreliner during FIRE II. The derivation of the microphysical parameters is outlined in the later reference to Heymsfield (1977). The vertical velocity is the steady-state velocity in cm s-1 to keep the relative humidity at it's currently measured value. Differential growth rate represents the growth rate of the particle population of different sizes at the current relative humidity. The Total differential growth rate is the sum of the growth rate in all channels. The assumptions used for the IWC calculations are reported in Heymsfield; also, generic size to mass equations are used. Precipitation rate is calculated from particle size and terminal velocity data, integrated over the size spectrum. Concentration data are as derived above. Number of crystal-crystal collisions are derived from the data reported by Hindman and the crystal terminal velocities. Water vapor density andsupersaturation information in this data set should not be used--it is unreliable. Curve fits to the data using least squares methods are provided. VARIABLE DESCRIPTION UNITS ------------------------------------------------------------------------------- IT1, ITMEASUREMENT TIME INTERVAL HH/MM/SS PS STATIC PRESSURE mb TEMP AMBIENT TEMPERATURE degreesC ALT PRESSURE ALTITUDE m USTAR VERTICAL VELOCITY NEEDED TO KEEP THE cm/s RELATIVE HUMIDITY CONSTANT DBARM MEDIAN PARTICLE MASS WEIGHTED DIAMETER cm DMAX MAXIMUM PARTICLE DIAMETER cm W1 DIFFUSIONAL GROWTH RATE IN CHANNEL 1 g/sec W2 DIFFUSIONAL GROWTH RATE IN CHANNEL 2 g/sec W3 DIFFUSIONAL GROWTH RATE IN CHANNEL 3 g/sec W4 DIFFUSIONAL GROWTH RATE IN CHANNEL 4 g/sec WTOT TOTAL DIFFUSTIONAL GROWTH RATE g/sec DT8 DEPLETION TIME (8 micron droplets) sec DT12 DEPLETION TIME (12 micron droplets) sec TMASS1 IWC IN CHANNEL 1 g/m^3 TMASS2 IWC IN CHANNEL 2 g/m^3 DPTC DEW POINT TEMPERATURE (EG&G) degrees C RH RELATIVE HUMIDITY (EG&G) % RIWC ICE WATER CONTENT g/m^3 XM1 ICE WATER CONTENT BASED ON SNOW HABIT g/m^3 XM2 ICE WATER CONTENT BASED ON SMALL g/m^3 SNOW HABIT XM3 ICE WATER CONTENT BASED ON LARGE g/m^3 SNOW HABIT R PRECIPITATION RATE mm/hr DBZ RADAR REFLECTIVITY FACTOR decibels VBAR MEAN REFLECTIVITY WEIGHTED WITH THE cm/s TERMINAL VELOCITY TTCONC TOTAL PARTICLE CONCENTRATION #/L CBIN1 PARTICLE CONCENTRATION WITHIN THE #/L RANGE LE 200 CBIN2 PARTICLE CONCENTRATION WITHIN THE 200-500 #/L RANGE CBIN3 PARTICLE CONCENTRATION WITHIN THE 500-800 #/L RANGE CBIN4 PARTICLE CONCENTRATION WITHIN THE #/L RANGE GT 800 CE8 COLLECTION EFFICIENCY (8 micron none droplets) CE12 COLLECTION EFFICIENCY (12 micron none droplets) TMASS3 IWC IN CHANNEL 3 g/m^3 TMASS4 IWC IN CHANNEL 4 g/m^3 TIMP # OF CRYSTAL-CRYSTAL COLUMNS sec^(1-) RHORH WATER VAPOR DENSITY g/cm^3 SI SUPERSATURATION WITH RESPECT TO ICE % SW SUPERSATURATION WITH RESPECT TO WATER % LAMBDA COEFFICIENTS USED TO FIT THE EQUATION #/cm^3 NZERO N=N0EXP(-LAMBDAD) #/L/mm RSQ COEFFICIENT OF THE FIT ICP PROBE TYPE (C OR P) none

This data set includes airborne measurements obtained from the L-188 Electra aircraft (Tail Number N308D) during the STREX project. This dataset contains high rate navigation, state parameter, and microphysics flight-level data in GENPRO-I format.

This data set includes airborne measurements obtained from the QueenAir, A-80 aircraft (Tail Number N304D) during the MAF project. This dataset contains high rate navigation, state parameter, and microphysics flight-level data in GENPRO-I format.

This data set includes airborne measurements obtained from the QueenAir, A-80 aircraft (Tail Number N304D) during the MIC-78 project. This dataset contains high rate (primarily 10sps) navigation, state parameter, and microphysics flight-level data in GENPRO-I format.