National Centers For Environmental Prediction/National Center For Atmospheric Research Research Articles

Use of an optimum interpolation method to construct a high-resolution global ocean surface vector wind dataset from active scatterometers and passive radiometers

ABSTRACTThis study presents a new 0.25° gridded 6-hourly global ocean surface wind vector dataset from 2000 to 2015 produced by blending satellite wind retrievals from five active scatterometers (QuikSCAT, ASCAT-A, ASCAT-B, OSCAT, and HY-2A), nine passive radiometers (four SSM/I sensors, two SSMIS sensors, TMI, AMSR-E, and AMSR2) and one polarimetric radiometer (WindSat) with reanalysis from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) employing an optimum interpolation method (OIM). The accuracy of this wind product is determined through various comparisons with buoy measurements, NCEP/NCAR reanalysis and the cross-calibrated multi-platform (CCMP) winds. The comparisons indicate that OIM winds agree well with buoys, showing a root-mean-squared difference of 1.32 m s−1 for wind speed and 24.73° for wind direction over 0–30 m s−1 wind speed range. And the quality of OIM winds is improved significantly relative to NCEP/NCAR reanalysis and can be comparable with CCMP winds. Furthermore, OIM winds can reveal abundant small-scale features that are not visible in reanalysis data. In addition, the wind speed and direction retrievals of most satellites are proved to play an important role in generating the high-quality product, but the procedure for including HY-2A winds and WindSat wind directions should be further explored.

A Novel Spatiotemporal Statistical Downscaling Method for Hourly Rainfall

Finer spatiotemporal resolution rainfall data is essential for assessing hydrological impacts of climate change on medium and small basins. However, existing methods pay less attention to the inter-day correlation and diurnal cycle, which can strongly influence the hydrological cycle. To address this problem, we present a spatiotemporal downscaling method that is capable of reproducing the inter-day correlation, the diurnal cycle, and rainfall statistics on daily and hourly scales. The large-scale datasets, which we obtained from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis dataset (NNR) and general circulation model (GCM) outputs, and local rainfall data are analyzed to assess the impacts of climate change on rainfall. Our proposed method consists of two steps: spatial downscaling and temporal downscaling. We apply spatial downscaling first to obtain the relationship between large-scale datasets and daily rainfall at a site scale using a k-nearest neighbor method (KNN). Then, we conduct an hourly downscaling of daily rainfall in the second step using a genetic algorithm-based KNN (GAKNN) with the inter-day correlation and the diurnal cycle. Furthermore, we analyzed changes in rainfall statistics for the periods 2046–2065 and 2081–2100 under the A2, A1B, and B1 scenarios of the third generation Coupled Global Climate Model (CGCM3.1) and Bergen Climate Model version 2 (BCM2.0). An application of our proposed method to the Shihmen Reservoir basin (Taiwan) has shown that it could accurately reproduce local rainfall and its statistics on daily and hourly scales. Overall, the results demonstrated that the proposed spatiotemporal method is a powerful tool for downscaling hourly rainfall data from a large-scale dataset. The understanding of future changes of rainfall characteristics through our proposed method is also expected to assist the planning and management of water resources systems.

An AOGCM based assessment of interseasonal variability in Pakistan

The interseasonal variability of two basic climatic parameters (precipitation and temperature) is assessed, over vulnerable and data sparse region of Pakistan (23° to 37°N and 60° to 75°E), for two Coupled Model Intercomparison Project 3 (CMIP3) based Atmospheric-Oceanic General Circulation Model (AOGCM) versions: CM2.0 and CM2.1 by Geophysical Fluid Dynamics Laboratory (GFDL), and two CMIP5 based AOGCM versions: CM2p1 and CM3.0. A recent historical 50-year period (1951–2000) is analyzed and compared with APHRODITE for precipitation and National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) re-analysis based gridded datasets for temperature for the following four seasons: DJF, MAM, JJA, and SON. The study area is divided into three regions: all Pakistan, northern Pakistan, and southern Pakistan. The interseasonal variability of the precipitation and the temperature are derived from all three (five) runs of CM2.0 (CM2.1) and from all ten (five) runs of CM 2p1 (CM3.0). The bias, root mean square error (RMSE), one-sigma standard deviation (SD) and correlation coefficient (CC) are used as assessing metrics. The following individual runs have positive CC with respect to APHRODITE at ≤1% Confidence Level (CL). On seasonal basis for CMIP5 based GFDL models during DJF: CM2p1R5 (for all Pakistan), CM2p1R5 (for northern Pakistan), and during MAM: CM2p1R5 (for southern Pakistan; this run has the lowest centered RMSE of 0.11 mm/day), whereas on annual basis: CM3.0R3 (for all Pakistan). However, out of these four runs, only CM2p1 (for southern Pakistan) has SD < SDobs (0.08 < 0.12 mm/day). There are 13 other runs for which the positive CC is at ≤5% CL, both relative to observed precipitation or temperature. Out of these 13 runs, only the average of runs of GFDL-CM2.1 in CMIP3 in JJA in southern Pakistan has SD < SDobs (0.56 < 0.59 °C) with a centered RMSE value of 0.65 °C. These characteristics of GFDL-CM2p1 runs are supported by their relatively better simulation of spatial distribution of 1000–850 hPa averaged layer wind patterns, relative to NCEP/NCAR 1000–850 hPa averaged wind patterns, over Pakistan, in respective seasons. A variance based bias adjustment when applied displays considerable interseasonal bias reduction both in precipitation and temperature in long term mean with no change in trend.

Assessment of changes in atmospheric dynamics and dust activity over southwest Asia using the Caspian Sea–Hindu Kush Index

ABSTRACTThis study examines the influence of the Caspian Sea–Hindu Kush Index (CasHKI) on local and synoptic meteorology as well as on dust emissions over southwest (SW) Asia by means of National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP‐NCAR) re‐analysed mean sea‐level pressure (MSLP), geopotential height at 700 hPa and surface meridional wind, along with meteorological data at Zabol, east Iran and Meteosat/Infrared Difference Dust Index (IDDI) retrievals. The analysis focuses on the summer period (June to September) of 2000–2014 and the winter period (November to March) of 1963–2014. The CasHKI values are mostly controlled by the MSLP anomalies over the Caspian Sea (CS) domain, varying from approximately −25 to +35 hPa in winter and from approximately−10 to +14 hPa in summer, but without a clear annual pattern. The CasHKI values are classified into four modes for each month depending on their intensity. In the summer months, the high CasHKI mode is associated with enhanced MSLP over central Asia and deepening of the Indo‐Pakistan thermal low associated with the Indian summer monsoon. At 700‐hPa level, the high CasHKI mode shows an enhancement of the Arabian ridge, expanding it to the north over Iran and the CS, with a concurrent strengthening of the Indian trough, leading to intensification of northerly winds along east Iran. This results in significant increase in dust activity over SW Asia, which is also apparent in the winter months. Furthermore, the intensification of the northerly flow associated with the high CasHKI modes drops the temperature and increases the relative humidity over Zabol, especially during winter. The SPRINTARS‐model simulations also show increased dust emissions and concentrations for the high CasHKI values, confirming that the CasHKI variations modulate the dust activity over SW Asia throughout the year.

Wind climatology of Toronto based on the NCEP/NCAR reanalysis 1 data and its potential relation to solar activity

This study represents a comprehensive analysis of the wind climatology for the Toronto area based on the daily National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis 1 data extracted for the period 1948–2014. The research is focused on investigating wind speed and wind direction distributions, long-term wind trends, and low-frequency wind spectrum. The results are given at the sigma-995 level. Westerlies are active in about 50% of the time in year. The strongest winds are coming in from 240° direction and the windiest seasons are winter and fall, followed by spring. A trend analysis shows that statistically significant and positive wind speed trends are present for both the omnidirectional mean annual wind speeds as well as for the winds associated with the most prevailing wind directions. Winter and fall winds had positive trends whereas negative wind speed trends in the summer and spring seasons are negligible. The spectral analysis of wind speed time series shows three distinguished peaks: (1) 2–4.5 days, (2) yearly, and (3) 11-year peak. The lowest frequency peak in the wind speed spectra is linked to the solar activity through the cross-correlation analysis and the relationship is discussed in details.

A Hybrid Statistical Downscaling Method Based on the Classification of Rainfall Patterns

A hybrid statistical downscaling method based on the classification of rainfall patterns is presented which is capable of overcoming the poor representation of extreme events. The large-scale datasets, which are obtained from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis data and the global circulation models (GCMs) outputs, and the local daily rainfall data are analyzed to assess the impacts of climate change on rainfall. The proposed method is composed of two steps. The first step is the classification of daily rainfall patterns. The detrended fluctuation analysis (DFA) is introduced to define the extreme rainfall. Two classification models, extreme rainfall and wet rainfall, are developed to describe the relationship between large-scale weather factors and rainfall patterns using support vector machine (SVM). These two models are able to identify the three rainfall patterns (the extreme, the normal and the dry rainfall) of the daily weather factors. The second step is the estimation of daily rainfall. The improved self-organizing linear output map (ISOLO) is adopted to estimate the rainfall for the aforementioned three different rainfall patterns. The future rainfall changes are calculated for the periods 2046–2065 and 2081–2100 under the A2 and B1 scenarios. An application to Taiwan has shown that the proposed method provides reliable and accurate rainfall-pattern classification. In addition, the improvement of the estimation of daily rainfall is significant, especially for the extreme rainfall. In conclusion, the proposed method is effective to overcome the poor representation of extreme events and the impacts of climate change on rainfall are analyzed.

Statistical characterization of cloud-to-ground lightning data and meteorological modelling of cloud-to-ground lightning days for the warm season in the province of León (northwest Spain)

This study presents the characteristics of cloud-to-ground lightning in the province of León (Spain), based on data collected via the lightning detection network of the Spanish Meteorological Agency. A total of 146 081 flashes and 279 220 strokes were recorded between 2000 and 2010. Spatial analysis (total, negative and positive flash density, and mean peak currents of positive and negative flashes) was performed at a resolution of 1 km. The maximum density recorded for total negative and positive flashes was 2.0 flashes km−2 year−1; 2.3 for negative flashes only and 0.178 for positive flashes. There was a different spatial distribution for positive compared with negative flashes, resulting from meteorological mechanisms involved with their polarities. The density distribution corresponding to both total and negative flashes appears to be clearly associated with topography. Interestingly, there is a clear inverse spatial correlation between the density and peak current parameters, which has important implications for constructing risk maps of lightning activity. This correlation has been quantified and confirmed for both positive and negative flashes by two separate regression equations. In the second part of the present study, a statistical model was constructed to predict lightning in the province of León, using a quadratic discriminant function that encompasses three meteorological variables obtained from National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis: lifted index, K-index and precipitable water. To construct the model, data were used from May to September over 2002–2007, and then applied to an independent sample of years from 2008 to 2010. Results were verified using skill scores probability of detection, false alarm rate, critical success index and true skill statistic. Scores obtained for the samples were 0.79, 0.45, 0.48 and 0.53 (respectively) for model construction, and 0.78, 0.14, 0.69 and 0.65 (respectively) for application to the independent sample.

Polar Cyclone Identification from 4D Climate Data in a Knowledge-Driven Visualization System

Arctic cyclone activity has a significant association with Arctic warming and Arctic ice decline. Cyclones in the North Pole are more complex and less developed than those in tropical regions. Identifying polar cyclones proves to be a task of greater complexity. To tackle this challenge, a new method which utilizes pressure level data and velocity field is proposed to improve the identification accuracy. In addition, the dynamic, simulative cyclone visualized with a 4D (four-dimensional) wind field further validated the identification result. A knowledge-driven system is eventually constructed for visualizing and analyzing an atmospheric phenomenon (cyclone) in the North Pole. The cyclone is simulated with WebGL on in a web environment using particle tracing. To achieve interactive frame rates, the graphics processing unit (GPU) is used to accelerate the process of particle advection. It is concluded with the experimental results that: (1) the cyclone identification accuracy of the proposed method is 95.6% when compared with the NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis data; (2) the integrated knowledge-driven visualization system allows for streaming and rendering of millions of particles with an interactive frame rate to support knowledge discovery in the complex climate system of the Arctic region.

Assessing reference evapotranspiration estimation from reanalysis weather products. An application to the Iberian Peninsula

ABSTRACTComputing crop reference evapotranspiration (ETo) with the FAO Penman–Monteith method (PM‐ETo) requires maximum and minimum air temperature, shortwave radiation, relative air humidity and wind speed. These data are often not available, thus requiring alternative computation procedures. Although some proposed approximations may provide ETo values with small estimation errors, the physics of the ET processes may then not be well described. The use of reanalysis data, which is common in climate studies, represents an alternative to observation data for the weather variables referred above, when these are not available. This study focuses on the use of the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) blended reanalysis products with gridded data sets for the computation of PM‐ETo in the Iberian Peninsula. A monthly time step was adopted. The PM‐ETo time series computed with the blended reanalysis data sets were compared with those obtained using observations for 130 weather stations in the Iberian Peninsula. Results show that the PM‐ETo computed with blended reanalysis compares well with the series computed from observation data (average root mean square error, RMSE = 0.49 mm day−1). The weather variables derived from reanalysis were also compared with observation data. Results supported the quality of ETo computations because, overall, there was a good match between solar radiation (average RMSE = 1.76 MJm−2 day−1) and maximum temperature (average RMSE = 1.48 °C) derived from reanalysis and in situ observations. By contrast, the wind speed from reanalysis highly overestimated observations and this is likely a reason for the slight overestimation of ETo computed from reanalysis (percentage bias, PBIAS&gt;20% in 89% of cases). In addition, the reanalysis products are apparently influenced by modelled warming, which contributes to overestimation of the minimum temperature and, to a lesser extent, of the relative humidity. The spatial pattern of accuracy indicators reveals that poorer results correspond to the southern and south‐eastern coastal areas of Iberia, where climate is semi‐arid. The compatibility of the PM‐ETo computed with monthly inputs and of the daily ETo cumulated to the month using the PM‐ETo equation was confirmed, thus allowing to extend conclusions of this study to daily computations. Alternative reanalysis products were also assessed. Tests for ERA‐Interim reanalysis products revealed overestimation of ETo and those for NCEP/NCAR Reanalysis II have shown large underestimation. Results suggest that the blended reanalysis products are suitable for the estimation of ETo in Iberia since they integrate an appropriate correction of radiation and temperature, which proved essential for the good estimation results obtained.

On the climatological probability of the vertical propagation of stationary planetary waves

Abstract. We introduce a diagnostic tool to assess a climatological framework of the optimal propagation conditions for stationary planetary waves. Analyzing 50 winters using NCEP/NCAR (National Center for Environmental Prediction/National Center for Atmospheric Research) reanalysis data we derive probability density functions (PDFs) of positive vertical wave number as a function of zonal and meridional wave numbers. We contrast this quantity with classical climatological means of the vertical wave number. Introducing a membership value function (MVF) based on fuzzy logic, we objectively generate a modified set of PDFs (mPDFs) and demonstrate their superior performance compared to the climatological mean of vertical wave number and the original PDFs. We argue that mPDFs allow an even better understanding of how background conditions impact wave propagation in a climatological sense. As expected, probabilities are decreasing with increasing zonal wave numbers. In addition we discuss the meridional wave number dependency of the PDFs which is usually neglected, highlighting the contribution of meridional wave numbers 2 and 3 in the stratosphere. We also describe how mPDFs change in response to strong vortex regime (SVR) and weak vortex regime (WVR) conditions, with increased probabilities of the wave propagation during WVR than SVR in the stratosphere. We conclude that the mPDFs are a convenient way to summarize climatological information about planetary wave propagation in reanalysis and climate model data.

Zonal shift of the South Asian High on the subseasonal time‐scale and its relation to the summer rainfall anomaly in China

By using daily National Centers for Environmental Prediction‐National Center for Atmospheric Research (NCEP‐NCAR) reanalysis and observed rainfall data, we investigated the east–west shift of the South Asian High (SAH) on the subseasonal time‐scale and its relationship with the rainfall anomaly in China. It is found that the zonal shift of the SAH at 200 hPa displays a dominant periodicity of 10–50 days, with two preferred locations, one over the northeast Tibetan Plateau (eastern location) and the other over the northeast Iranian Plateau (western location). The zonal shift of the SAH is closely related to the southward movement of intraseasonal perturbations originating in middle latitudes. A vorticity budget analysis reveals that the advection of mean vorticity by the perturbation of meridional wind primarily contributes to the vorticity tendency over both the eastern and western locations. The zonal shift of the SAH closely connects to the summer rainfall anomalies over China. An eastern (a western) location of the SAH corresponds to generally positive (negative) rainfall anomalies in northwestern China and negative (positive) anomalies in southern China. A further diagnosis reveals that the strengthening of the intraseasonal perturbation during the southward journey in the eastern location is attributed to a positive convection–circulation feedback. On the one hand, a positive geopotential height anomaly in the upper troposphere and associated upper‐level divergence induce anomalous ascending motion and condensational heating in the middle troposphere. On the other hand, the positive heating anomaly increases mid‐tropospheric temperature and strengthens upper‐level geopotential height. The southward propagation leads to the zonal shift of the SAH.

Climatology and temporal evolution of the atmospheric semidiurnal tide in present‐day reanalyses

AbstractThe solar semidiurnal atmospheric tide (S2) was extracted from seven reanalysis data sets, including current data sets, such as CFSR (Climate Forecast System Reanalysis), MERRA (Modern‐Era Retrospective Analysis for Research and Applications), ERA‐Interim (ECMWF Reanalysis), and 20CR (Twentieth Century Reanalysis), and older frozen products, such as NCEP/NCAR (National Center for Environmental Prediction/National Center for Atmospheric Research), ERA‐40 (ECMWF Reanalysis), and JRA‐25 (Japanese 25 year Reanalysis). In this calculation, we emphasized the temporal variation of the tide. We also calculated the tidal error, which was sizable at high latitudes and over short averaging periods and large for 20CR at all latitudes. Because of the four standard daily samples, the interpolation scheme of van den Dool et al. (1997) was used when necessary. We found this method to be accurate for zonally averaged tides only. Comparing the climatology from the MERRA and CFSR S2 with a recent empirical tide model showed that MERRA better represented the geographical structure of the tide, especially its phase. We found a bias in the phase in all of the reanalysis data sets except for MERRA. The temporal evolution of the tide was inconsistent between the different data sets, although similar seasonal variations were observed. The seasonal cycle was also better depicted in MERRA. The S2 calculated from MERRA and satellite precipitation measurements from TRMM (Tropical Rainfall Measuring Mission) presented results that were inconsistent with the hypothesis in which rainfall latent heat release represents S2 forcing and functions as a source of S2 seasonal variability.

Study of the relationship between African ITCZ variability and an extreme heat wave on Egypt in summer 2015

An extreme heat wave hit Egypt in summer 2015. Abnormal hot weather conditions existed over Egypt for the entire summer season. The present paper investigates the relationship between the intertropical convergence zone (ITCZ) over Africa and a scorching heat wave that existed over Egypt in summer 2015. The National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis data of mean surface air temperature for the domain of Egypt for the summer season from 1948 to 2015 were used in this study. In addition, data of the daily maximum and daily minimum temperature used for the summer season of the year 2015 were also used. Time cross-section analysis of the daily operational data of geopotential height at level 500 hPa over Egypt from 1 June to 31 August 2015 was done. Moreover, the African ITCZ, both the western and the eastern ITCZ, data for summer of 2015 were used for the said period. The time series, time cross-section, anomaly, and correlation coefficient techniques were used to analyze the datasets. The results revealed that a new climate change record of heat wave over Egypt existed in summer 2015. Moreover, there is an outstanding significant positive correlation between the abrupt shift of African ITCZ position and heat wave occurrence over Egypt in summer 2015. In particular, the southerly movement of the eastern African ITCZ controls the weather over Egypt and led to the extreme heat wave in summer 2015.

Investigation of permanent aerosol source regions over Asia using multi-year MODIS observations

This work examines the permanent aerosol source regions over Asia by analyzing 7-years data of aerosol optical thickness (AOT) product from MODerate Imaging Spectroradiometer (MODIS) onboard Aqua and Terra satellites. The analysis is carried out by taking the average AOT map during the years 2002-2008 over the region in different seasons, in which the permanent source regions will appear pronounced whereas the locations influenced by transport or any emissions that last for shorter time period will be smoothened. The results show four such main permanent source regions. Angstrom Exponent (AE) aerosol product is used to infer about the possible type and size of aerosols over the source regions. The average AOT trends over the source regions in different seasons during 2002-2008 are examined and the results are discussed based on the corresponding variations of meteorological parameters derived from National Center for Environmental Prediction - National Center for Atmospheric Research (NCEP-NCAR) reanalysis data. In addition, the trends in AOT variation during the period 2002-2008 over certain selected stations over the area are also discussed.

Inter‐hemispheric and inter‐zonal moisture transports and monsoon regimes

ABSTRACTThe principal objectives here are to quantify the strengths of global monsoon circulations in terms of cross‐equatorial moisture transport and to verify its behaviour during two extreme years of precipitation over the Amazon Basin. The National Centers for Environmental Prediction / National Center for Atmospheric Research (NCEP/NCAR) Reanalysis data sets for the period 1950–2012 are used in this study and the results are compared with calculations from ERA‐Interim data. During the South Asian summer monsoon (JJA), the transport is 82.1 × 107 kg s−1 between 30° and 90°E from the Southern Hemisphere (SH) to the Northern Hemisphere (NH) and reverses to 41.4 × 107 kg s−1 from NH to SH in northern winter (DJF). Over South America between 30° and 90°W, the values are 31.4 × 107 kg s−1 in DJF from NH to SH and 21.5 × 107 kg s−1 in JJA from SH to NH. Although there is no wind reversal from summer to winter seasons over the South American monsoon region, the moisture transport across the equator reverses. The transports during a weak and a strong monsoon in the Amazon Basin are distinctly different suggesting that the cross‐equatorial moisture transport can be used as a Monsoon Intensity Index (MII). For the South American monsoon, the DJF index is 28.5 × 107 kg s−1 in the dry year 2004–2005 and 45.1 × 107 kg s−1 in the wet year 2011–2012 as against the climatological value of 31.4 × 107 kg s−1. There is an indication of an inverse relation between the MIIs over the Amazon Basin and the Australian sectors. The annual mean moisture transport across the equator is from SH to NH and is equivalent to three Amazon River discharges.

Ocean-atmosphere dynamics changes associated with prominent ocean surface turbulent heat fluxes trends during 1958–2013

Three prominent features of ocean surface turbulent heat fluxes (THF) trends during 1958–2013 are identified based on the Objectively Analyzed air-sea Fluxes (OAFlux) data set. The associated ocean-atmosphere dynamics changes are further investigated based on the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis. First, the THF are enhanced over the mid-latitude expansions of the subtropical western boundary currents (WBCs). An intensified oceanic heat transport, forced by stronger near-surface zonal wind, is likely to be the cause of such THF tendency. Second, the THF are reduced over the tropical eastern Pacific Ocean, which is primarily caused by the decreasing near-surface wind speed and sea surface temperature (SST), associated with a local coupled ocean-atmosphere cooling mode. Finally, the THF are reduced over the northern tropical Atlantic Ocean, which is attributed to the decreasing air-sea humidity and temperature differences as a result of the convergence of near-surface air and the divergence of ocean currents (upwelling).

Projecting changes in Tanzania rainfall for the 21st century

A non-homogeneous hidden Markov model (NHMM) is developed using a 40-year record (1950–1990) of daily rainfall at 11 stations in Tanzania and National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) re-analysis atmospheric fields of a number of meteorological variables. The following atmospheric fields, temperature at 1000 hPa, geo-potential height at 1000 hPa, meridional winds and zonal winds at 850 hPa, and zonal winds at the equator from 10 to 1000 hPa, in a region defined by 25°S–25°N and 25°–75°E are identified as appropriate predictors for the downscaling of the seasonal regime of daily rainfall in Tanzania. The NHMM is used to predict future rainfall patterns under a comparatively high greenhouse gas emissions scenario [Representative Concentration Pathway 8.5 (RCP8.5)], using predictors from the CMCC-CMS (Centro Mediterraneo sui Cambiamenti Climatici) simulations from 1950 to 2100. Instead of pre-specifying a fixed rainy season, the model considers seasonality of precipitation to be determined by the 21st century simulations of the atmospheric variables used as predictors. The future downscaled precipitation simulations for the RCP8.5 scenario indicate that in the 21st century Tanzania may experience: (1) a slight decrease in the number of wet days and seasonal rainfall in MAM and JJAS, but not in OND; (2) a reduction of annual total rainfall; and (3) an intensification of the frequency and intensity of extreme rainfall, as identified by 90th, 95th, and 99th percentiles.

An assessment of the Jenkinson and Collison synoptic classification to a continental mid-latitude location

A weather-type catalogue based on the Jenkinson and Collison method was developed for an area in south-west Russia for the period 1961–2010. Gridded sea level pressure data was obtained from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis. The resulting catalogue was analysed for frequency of individual types and groups of weather types to characterise long-term atmospheric circulation in this region. Overall, the most frequent type is anticyclonic (A) (23.3 %) followed by cyclonic (C) (11.9 %); however, there are some key seasonal patterns with westerly circulation being significantly more common in winter than summer. The utility of this synoptic classification is evaluated by modelling daily rainfall amounts. A low level of error is found using a simple model based on the prevailing weather type. Finally, characteristics of the circulation classification are compared to those for the original JC British Isles catalogue and a much more equal distribution of flow types is seen in the former classification.

Validation of the Suomi NPP VIIRS Ice Surface Temperature Environmental Data Record

Continuous monitoring of the surface temperature is critical to understanding and forecasting Arctic climate change; as surface temperature integrates changes in the surface energy budget. The sea-ice surface temperature (IST) has been measured with optical and thermal infrared sensors for many years. With the IST Environmental Data Record (EDR) available from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (NPP) and future Joint Polar Satellite System (JPSS) satellites; we can continue to monitor and investigate Arctic climate change. This work examines the quality of the VIIRS IST EDR. Validation is performed through comparisons with multiple datasets; including NASA IceBridge measurements; air temperature from Arctic drifting ice buoys; Moderate Resolution Imaging Spectroradiometer (MODIS) IST; MODIS IST simultaneous nadir overpass (SNO); and surface air temperature from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis. Results show biases of −0.34; −0.12; 0.16; −3.20; and −3.41 K compared to an aircraft-mounted downward-looking pyrometer; MODIS; MODIS SNO; drifting buoy; and NCEP/NCAR reanalysis; respectively; root-mean-square errors of 0.98; 1.02; 0.95; 4.89; and 6.94 K; and root-mean-square errors with the bias removed of 0.92; 1.01; 0.94; 3.70; and 6.04 K. Based on the IceBridge and MODIS results; the VIIRS IST uncertainty (RMSE) meets or exceeds the JPSS system requirement of 1.0 K. The product can therefore be considered useful for meteorological and climatological applications.

Changes in clustered extreme precipitation events in South China and associated atmospheric circulations

ABSTRACTPrevious studies have documented that the summer precipitation over South China (SC) has experienced a prominent inter‐decadal increase in 1992/1993, and the possible mechanism has been well revealed. The aim of this study is to investigate the changes in extreme precipitation and clustered extreme precipitation events in recent decades using station observations and the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis data. The results indicate that extreme precipitation also experienced a significant inter‐decadal increase around 1992/1993. Significant changes can also be found in the associated atmospheric circulations, such as the western North Pacific subtropical high (WNPSH) and the westerly jet stream over East Asia. In addition, the water vapour transport (WVT) related to extreme precipitation differed from mean conditions. For extreme precipitation events, the WVT from the Northwest Pacific and Indian Oceans was much stronger when compared with mean precipitation. When extreme precipitation events were clustered, the increased WVT mainly originated from the South China Sea and Northwest Pacific Ocean. Further analysis indicates that the WVT increased from the Indian Ocean but decreased from the Northwest Pacific after 1992/1993; this finding explains the significant increase in the clustered extreme precipitation events over SC after 1992/1993. In addition, the atmospheric stratification has become more unstable since 1992/1993.