Global climatology and trends in convective environments from ERA5 and rawinsonde data

Globally, thunderstorms are responsible for a significant fraction of rainfall, and in the mid-latitudes often produce extreme weather, including large hail, tornadoes and damaging winds. Despite this importance, how the global frequency of thunderstorms and their accompanying hazards has changed over the past 4 decades remains unclear. Large-scale diagnostics applied to global climate models have suggested that the frequency of thunderstorms and their intensity is likely to increase in the future. Here, we show that according to ERA5 convective available potential energy (CAPE) and convective precipitation (CP) have decreased over the tropics and subtropics with simultaneous increases in 0–6 km wind shear (BS06). Conversely, rawinsonde observations paint a different picture across the mid-latitudes with increasing CAPE and significant decreases to BS06. Differing trends and disagreement between ERA5 and rawinsondes observed over some regions suggest that results should be interpreted with caution, especially for CAPE and CP across tropics where uncertainty is the highest and reliable long-term rawinsonde observations are missing.

Observing Possible Thermodynamic Controls on Tropical Marine Rainfall in Moist Environments

Radar and rawinsonde data from four ground-based observing stations in the tropical Indo-Pacific warm pool were used to identify possible associations of environmental state variables and their vertical profiles with radar-derived rain rate inside a mesoscale radar domain when the column-integrated relative humidity (CRH) exceeds 80%. At CRH exceeding 80%, a wide range—from near 0 to ~50 mm day−1—in rain rate is observed; therefore, tropospheric moisture was a necessary but insufficient condition for deep convection. This study seeks to identify possible factors that inhibit rainfall when the atmosphere is sufficiently moist to support large precipitation rates. The domain-mean rain rate was highly sensitive to the areal coverage of intense, convective rainfall that occurs. There were two fundamentally different instances in which convective area was low. One was when the radar domain is primarily occupied by weakly precipitating, stratiform echoes. The other was when the radar domain contained almost no precipitating echoes of any type. While the former was dependent upon the stage of the convective life cycle seen by radar, the latter was probably dependent upon the convective environment. Areal coverage of convective echoes was largely determined by the number of individual convective echoes rather than their sizes, so changes in the clear-air environment of updrafts might have governed how many updrafts grew into deep cumulonimbi. The most likely environmental influence on convective rainfall identified using rawinsonde data was 900–700-hPa lapse rate; however, processes occurring on spatial scales smaller than a radar domain were probably also important but not investigated.

Evaluation of Chinese Aircraft Meteorological Data Relay (AMDAR) Weather Reports

Aircraft Meteorological Data Relay (AMDAR) weather reports are a type of high spatiotemporal data currently widely used in weather monitoring and prediction. A recent Chinese AMDAR project began in 2003 has made rapid progress. However, the assessment and accuracy of these Chinese AMDAR reports have yet to be thoroughly discussed. A comparison of temperature and wind observations between Chinese AMDAR reports and rawinsonde data between 2004 and 2010 is conducted in this paper. Results demonstrate that the root-mean-square error (RMSE) between these two sets of data is 1.40°C for temperature, 3.56 m s−1 for wind speed, and 28° for wind direction. Because of the particularity of observation and inversion method, comparison results are not only affected by AMDAR measurement and reporting error but also by spatial and temporal representativeness, flight phases, and the environment. This evaluation helps create a complete estimation of the accuracy of Chinese AMDAR in order to assist with data assimilation.

The Impact of Dropwindsonde and Supplemental Rawinsonde Observations on Track Forecasts for Hurricane Irene (2011)

Because of the threat that Hurricane Irene (2011) posed to the United States, supplemental observations were collected for assimilation into operational numerical models in the hope of improving forecasts of the storm. Synoptic surveillance aircraft equipped with dropwindsondes were deployed twice daily over a 5-day period, and supplemental rawinsondes were launched from all upper-air sites in the continental United States east of the Rocky Mountains at 0600 and 1800 UTC, marking an unprecedented magnitude of coverage of special rawinsondes at the time. The impact of assimilating the supplemental observations on National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) model track forecasts of Irene was evaluated over the period that these observations were collected. The GFS track forecasts possessed small errors even in the absence of the supplemental observations, providing little room for improvement on average. The assimilation of the combined dropwindsonde and supplemental rawinsonde data provided small but statistically significant improvements in the 42–60-h range for GFS forecasts initialized at 0600 and 1800 UTC. The primary improvement from the dropwindsonde data was also within this time range, with an average improvement of 20% for 48-h forecasts. The rawinsonde data mostly improved the forecasts beyond 3 days by modest amounts. Both sets of observations provided small, additive improvements to the average cross-track errors. Investigations of individual forecasts identified corrections to the model analyses of the Atlantic subtropical ridge and an upstream midlatitude short-wave trough over the contiguous United States due to the assimilation of the extra data.

African Easterly Waves and Cyclonic Activity over the Eastern Atlantic: Composite and Case Studies

This study aims to understand the main differences over the African continent and the Eastern Atlantic Ocean between African Easterly Waves (AEWs) associated with Atlantic cyclones (developing AEWs) and non-developing AEWs. A statistical study showed that most of the named cyclones generated near the West African coast have a long lifecycle and all are associated with intense AEWs. Using NCEP/NCAR reanalyses, a composite study of the characteristics of developing AEWs is carried out and compared to those of non-developing AEWs. Developing AEWs exhibit the greatest baroclinic and barotropic conversions which are known to be the main processes involved in AEWs growth suggesting that these AEWs are stronger than the non-developing ones. Moreover, the developing AEWs are characterized by the existence of a relatively more unstable environment over West Africa and the Atlantic Ocean. A case study using rawinsonde data showed that the developing AEW is associated with dynamic and thermodynamic conditions conducive for deep convection and subsequent cyclogenesis compared to the non-developing AEW case.

Impacts of Assimilation of Satellite and Rawinsonde Observations on Southern Hemisphere Baroclinic Wave Activity in the NCEP–NCAR Reanalysis

In this study, the impacts of the assimilation of satellite and rawinsonde observations on Southern Hemisphere (SH) baroclinic wave activity in the NCEP–NCAR reanalysis are examined by comparing analyses made with and without the assimilation of satellite data (SAT and NOSAT, respectively) for the year 1979, as well as by comparing analyses to the corresponding first guesses from 1958 to 1999. Comparing the eddy kinetic energy (EKE) computed based on the SAT and NOSAT analyses, it is found that the assimilation of satellite data generally decreases the EKE in the SH, which is the opposite of the findings for the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) in previous studies. The decrease of EKE by satellite data in the NCEP–NCAR reanalysis can be traced back to a low bias in retrieved satellite temperature (SATEMP) variance. The eddy available potential energy (EPE) is decreased even more than the EKE with the assimilation of SATEMP, making the waves more barotropic in the SAT analysis. The EKE analysis increment, that is, the difference between the EKE based on analysis and first guess, is a good quantity to indicate the impacts of all observations assimilated. In the NOSAT analysis, positive EKE analysis increments are found around the SH rawinsonde stations, indicating that the assimilation of rawinsonde data increases EKE significantly from the first guess. This also suggests that the NCEP–NCAR first guess is probably biased low. Positive analysis increments around the rawinsonde stations become even larger in the SAT analysis compared with the NOSAT, suggesting that with the assimilation of low-biased SATEMP data, the EKE in the analysis (the initial condition for next time) and hence the first guess is reduced, therefore the rawinsonde observations have to further increase the EKE from the first guess. The patterns of EKE increment from the presatellite (1958–77) and satellite (1979–99) eras show high degrees of similarities to the NOSAT and SAT reanalysis patterns, respectively, lending further support to these findings. The impact of the assimilation of satellite data on the trend of SH baroclinic wave activity is discussed. Positive trends in the SH EKE are found in both the NCEP–NCAR and ERA-40 reanalyses during 1958–99. After taking the impacts of satellite data into account, the EKE trend in the NCEP–NCAR reanalysis gets stronger, while that in the ERA-40 is largely weakened, which adds complications to assessing the real trend in SH baroclinic wave activity. Comparisons among the variances based on the two reanalyses, NCEP–NCAR first guess, SATEMP, and rawinsonde observations are presented to substantiate some of the findings discussed above, such as the low bias in energy in NCEP–NCAR first guess and SATEMP variance.

A Two-Season Impact Study of Four Satellite Data Types and Rawinsonde Data in the NCEP Global Data Assimilation System

Extended-length observing system experiments (OSEs) during two seasons are used to quantify the contributions made to forecast quality by conventional rawinsonde data and four types of remotely sensed satellite data. The impact is measured by comparing the analysis and forecast results from an assimilation–forecast system using all data types with those excluding a particular observing system. The impact of the particular observing system is assessed by comparing the forecast results over extended periods. For these observing system experiments, forecast results are compared through 168 h for periods covering more than a month during both the summer and winter seasons of each hemisphere. The assimilation–forecast system used for these experiments is the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS) and the Global Forecast System (GFS). The case studies chosen consist of periods during January–February 2003 and August–September 2003. During these periods, a T254L64 layer version of NCEP’s global spectral model was used. The control run utilized all data types routinely assimilated in the GDAS. The experimental runs individually denied data from the Advanced Microwave Sounding Unit (AMSU), the High-Resolution Infrared Radiation Sounder (HIRS), geostationary satellite atmospheric motion vectors (GEO winds), in situ rawinsondes (raobs), and surface winds derived from the Quick Scatterometer (QuikSCAT). Differences between the control and denial experiment forecasts are accumulated over the two 45-day periods and are analyzed to demonstrate the impact of these data types. Anomaly correlations (ACs), forecast impacts (FIs), and hurricane track forecasts are evaluated for all experimental runs during both seasons. The anomaly correlations used the standard NCEP software suite and are partitioned into subsections covering the polar caps (60°–90°) and midlatitudes (20°–80°) of each hemisphere and the tropical region (20°N–20°S). Anomaly correlations of geopotential heights are shown at several pressure levels in the polar regions and midlatitudes. The root-mean-square error (RMSE) for 850- and 200-hPa wind vector differences are shown for the tropical region. The geographical distributions of forecast impacts on geopotential heights are also examined. The influence these data types have on tropical cyclone track forecasts are shown for both the Atlantic and Pacific basins and again are computed using standard algorithms developed and maintained at NCEP. The results demonstrate a positive impact from all data types with AMSU and rawinsonde data providing the largest anomaly correlation improvements in all zonal regions examined. Smaller forecast improvements are noticed from each of the other data types. In the Atlantic basin, each of the four satellite data types provides nearly equal improvement to the tropical cyclone track forecasts; however, GEO winds provide the largest improvement to track forecasts in the Pacific basin.