Sun Wong

Closing the Global Water Vapor Budget with AIRS Water Vapor, MERRA Reanalysis, TRMM and GPCP Precipitation, and GSSTF Surface Evaporation

AbstractThe authors investigate if atmospheric water vapor from remote sensing retrievals obtained from the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit (AIRS) and the water vapor budget from the NASA Goddard Space Flight Center (GSFC) Modern Era Retrospective-analysis for Research and Applications (MERRA) are physically consistent with independently synthesized precipitation data from the Tropical Rainfall Measuring Mission (TRMM) or the Global Precipitation Climatology Project (GPCP) and evaporation data from the Goddard Satellite-based Surface Turbulent Fluxes (GSSTF). The atmospheric total water vapor sink (Σ) is estimated from AIRS water vapor retrievals with MERRA winds (AIRS–MERRA Σ) as well as directly from the MERRA water vapor budget (MERRA–MERRA Σ). The global geographical distributions as well as the regional wavelet amplitude spectra of Σ are then compared with those of TRMM or GPCP precipitation minus GSSTF surface evaporation (TRMM–GSSTF and GPCP–GSSTF P − E, respectively)....

Cloud-State-Dependent Sampling in AIRS Observations Based onCloudSatCloud Classification

AbstractThe precision, accuracy, and potential sampling biases of temperature T and water vapor q vertical profiles obtained by satellite infrared sounding instruments are highly cloud-state dependent and poorly quantified. The authors describe progress toward a comprehensive T and q climatology derived from the Atmospheric Infrared Sounder (AIRS) suite that is a function of cloud state based on collocated CloudSat observations. The AIRS sampling rates, biases, and center root-mean-square differences (CRMSD) are determined through comparisons of pixel-scale collocated ECMWF model analysis data. The results show that AIRS provides a realistic representation of most meteorological regimes in most geographical regions, including those dominated by high thin cirrus and shallow boundary layer clouds. The mean AIRS observational biases relative to the ECMWF analysis between the surface and 200 hPa are within ±1 K in T and from −1 to +0.5 g kg−1 in q. Biases because of cloud-state-dependent sampling dominate the...

The Apparent Water Vapor Sinks and Heat Sources Associated with the Intraseasonal Oscillation of the Indian Summer Monsoon

AbstractThe possibility of using remote sensing retrievals to estimate apparent water vapor sinks and heat sources is explored. The apparent water vapor sinks and heat sources are estimated from a combination of remote sensing, specific humidity, and temperature from the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit (AIRS) and wind fields from the National Aeronautics and Space Administration (NASA)’s Goddard Space Flight Center (GSFC)’s Modern Era Retrospective-Analysis for Research and Applications (MERRA). The intraseasonal oscillation (ISO) of the Indian summer monsoon is used as a test bed to evaluate the apparent water vapor sink and heat source. The ISO-related northward movement of the column-integrated apparent water vapor sink matches that of precipitation observed by the Tropical Rainfall Measuring Mission (TRMM) minus the MERRA surface evaporation, although the amplitude of the variation is underestimated by 50%. The diagnosed water vapor and heat budgets associated with convec...

Impact of increased water vapor on precipitation efficiency over northern Eurasia

This study investigates the relationships among water vapor, precipitation efficiency, precipitation amount, and air temperature anomalies on monthly time scales over northern Eurasia for winter and summer 2003–2010. Daily precipitation and temperature records at 505 historical stations, and atmospheric total precipitable water vapor and relative humidity data from Atmospheric Infrared Sounders, are used for analysis. Results show that higher atmospheric precipitable water associated with warmer temperature directly contributes to winter precipitation amount but has little impact on winter precipitation efficiency. However, accelerated decreasing relative humidity associated with higher temperature is the primary factor in the reduction of precipitation efficiency and precipitation amount regardless of higher precipitable water in summer. This study suggests that there are evident seasonal differences in precipitation trend associated with air temperature changes over the study region. Air temperature modifies a key atmospheric water variable that directly controls precipitation for that particular season.

Classification of atmospheric river events on the U.S. West Coast using a trajectory model

Author(s): Ryoo, JM; Waliser, DE; Waugh, DW; Wong, S; Fetzer, EJ; Fung, I | Abstract:

Cloud‐induced uncertainties in AIRS and ECMWF temperature and specific humidity

The uncertainties of the Atmospheric Infrared Sounder (AIRS) Level 2 version 6 specific humidity (q) and temperature (T) retrievals are quantified as functions of cloud types by comparison against Integrated Global Radiosonde Archive radiosonde measurements. The cloud types contained in an AIRS/Advanced Microwave Sounding Unit footprint are identified by collocated Moderate Resolution Imaging Spectroradiometer retrieved cloud optical depth (COD) and cloud top pressure. We also report results of similar validation of q and T from European Centre for Medium-Range Weather Forecasts (ECMWF) forecasts (EC) and retrievals from the AIRS Neural Network (NNW), which are used as the initial state for AIRS V6 physical retrievals. Differences caused by the variation in the measurement locations and times are estimated using EC, and all the comparisons of data sets against radiosonde measurements are corrected by these estimated differences. We report in detail the validation results for AIRS GOOD quality control, which is used for the AIRS Level 3 climate products. AIRS GOOD quality q reduces the dry biases inherited from the NNW in the middle troposphere under thin clouds but enhances dry biases in thick clouds throughout the troposphere (reaching −30% at 850 hPa near deep convective clouds), likely because the information contained in AIRS retrievals is obtained in cloud-cleared areas or above clouds within the field of regard. EC has small moist biases (~5–10%), which are within the uncertainty of radiosonde measurements, in thin and high clouds. Temperature biases of all data are within ±1 K at altitudes above the 700 hPa level but increase with decreasing altitude. Cloud-cleared retrievals lead to large AIRS cold biases (reaching about −2 K) in the lower troposphere for large COD, enhancing the cold biases inherited from the NNW. Consequently, AIRS GOOD quality T root-mean-squared errors (RMSEs) are slightly smaller than the NNW errors in thin clouds (1.5–2.5 K) but slightly larger than the NNW errors for thick COD (reaching 3.5 K near the surface). The AIRS BEST quality control retains retrievals with uncertainties closer to those of the NNW. The AIRS error estimates reported in the L2 product tend to underestimate the precision (RMSE) implied by comparisons to the radiosonde measurements and do not reflect the observed cloud dependency of uncertainties.

Observation-Based Longwave Cloud Radiative Kernels Derived from the A-Train

AbstractThe authors present a new method to derive both the broadband and spectral longwave observation-based cloud radiative kernels (CRKs) using cloud radiative forcing (CRF) and cloud fraction (CF) for different cloud types using multisensor A-Train observations and MERRA data collocated on the pixel scale. Both observation-based CRKs and model-based CRKs derived from the Fu–Liou radiative transfer model are shown. Good agreement between observation- and model-derived CRKs is found for optically thick clouds. For optically thin clouds, the observation-based CRKs show a larger radiative sensitivity at TOA to cloud-cover change than model-derived CRKs. Four types of possible uncertainties in the observed CRKs are investigated: 1) uncertainties in Moderate Resolution Imaging Spectroradiometer cloud properties, 2) the contributions of clear-sky changes to the CRF, 3) the assumptions regarding clear-sky thresholds in the observations, and 4) the assumption of a single-layer cloud. The observation-based CRKs...

Increasing Daily Precipitation Intensity Associated with Warmer Air Temperatures over Northern Eurasia

AbstractThis study uses 45 years of observational records from 517 historical surface weather stations over northern Eurasia to examine changing precipitation characteristics associated with increasing air temperatures. Results suggest that warming air temperatures over northern Eurasia have been accompanied by higher precipitation intensity but lower frequency and little change in annual precipitation total. An increase in daily precipitation intensity of around 1%–3% per each degree of air temperature increase is found for all seasons as long as a station’s seasonal mean air temperature is below about 15°–16°C. This threshold temperature may be location dependent. At temperatures above this threshold, precipitation intensity switches to decreasing with increasing air temperature, possibly related to decreasing water vapor associated with extreme high temperatures. Furthermore, the major atmospheric circulation of the Arctic Oscillation, Scandinavian pattern, east Atlantic–western Eurasian pattern, and p...

Increasing atmospheric water vapor and higher daily precipitation intensity over northern Eurasia

Increasing daily precipitation intensity is strongly associated with increasing water vapor in the atmosphere over northern Eurasia based on this study of 35 years of daily precipitation, specific humidity, and air temperature observations at 152 stations. The apparently linear relationship is consistent across all four seasons at interannual and longer time scales, and holds after temperature variation have been controlled. The study further reveals that this relationship is accompanied by increases in precipitation totals from heavy events (above the 70th percentile) and decreases in light ones (below the 30th percentile). Results suggest that increased atmospheric water vapor is the direct link to more frequent intense events of precipitation and increased risk of flooding under a warming climate via increasing precipitation intensity.

Validation of MODIS cloud mask and multilayer flag using CloudSat‐CALIPSO cloud profiles and a cross‐reference of their cloud classifications

Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 cloud observations (MYD06) at 1 km are collocated with daytime CloudSat-Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) (C-C) cloud vertical structures (2B-CLDCLASS-LIDAR). For 2007–2010, over 267 million C-C cloud profiles are used to (1) validate MODIS cloud mask and cloud multilayer flag and (2) cross-reference between C-C cloud types and MODIS cloud regimes defined by joint histograms of cloud top pressure (CTP) and cloud optical depth (τ). Globally, of total observations, C-C reports 27.1% clear and 72.9% cloudy, whereas MODIS reports 30.0% confidently clear and 58.7% confidently cloudy, with the rest 7.1% as probably clear and 4.2% as probably cloudy. Agreement between MODIS and C-C is 77.8%, with 20.9% showing both clear and 56.9% showing both cloudy. The 9.1% of observations are clear in MODIS but cloudy in C-C, indicating clouds missed by MODIS; 1.8% of observations are cloudy in MODIS but clear in C-C, likely due to aerosol/dust or surface snow layers misidentified by MODIS. C-C reports 47.4/25.5% single-layer/multilayer clouds, while MODIS reports 26.7/14.0%. For C-C single-layer clouds, ~90% of tropical MODIS high (CTP   23) clouds are recognized as deep convective in C-C. Approximately 70% of MODIS low-level (CTP > 680 hPa) clouds are classified as stratocumulus in C-C regardless of region and optical thickness. No systematic relationship exists between MODIS middle-level (680 < CTP < 440 hPa) clouds and C-C cloud types, largely due to different definitions adopted.