ECMWF Re-Analysis Research Articles

The Diurnal Cycle of Precipitation according to Multiple Decades of Global Satellite Observations, Three CMIP6 Models, and the ECMWF Reanalysis

AbstractNASA Precipitation Measurement Mission observations are used to evaluate the diurnal cycle of precipitation from three CMIP6 models (NCAR-CESM2, CNRM-CM6.1, CNRM-ESM2.1) and the ERA5 reanalysis. NASA’s global-gridded IMERG product, which combines spaceborne microwave radiometer, infrared sensor, and ground-based gauge measurements, provides high-spatiotemporal-resolution (0.1° and half-hourly) estimates that are suitable for evaluating the diurnal cycle in models, as determined against the ground-based radar network over the conterminous United States. IMERG estimates are coarsened to the spatial and hourly resolution of the state-of-the-art CMIP6 and ERA5 products, and their diurnal cycles are compared across multiple decades of June–August in the 60°N–60°S domain (IMERG and ERA5: 2000–19; NCAR and CNRM: 1979–2008). Low-precipitation regions (and weak-amplitude regions when analyzing the diurnal phase) are excluded from analyses so as to assess only robust diurnal signals. Observations identify greater diurnal amplitudes over land (26%–134% of the precipitation mean; 5th–95th percentile) than over ocean (14%–66%). ERA5, NCAR, and CNRM underestimate amplitudes over ocean, and ERA5 overestimates over land. IMERG observes a distinct diurnal cycle only in certain regions, with precipitation peaking broadly between 1400 and 2100 LST over land (2100–0600 LST over mountainous and varying-terrain regions) and 0000 and 1200 LST over ocean. The simulated diurnal cycle is unrealistically early when compared with observations, particularly over land (NCAR-CESM2 AMIP: −1 h; ERA5: −2 h; CNRM-CM6.1 AMIP: −4 h on average) with nocturnal maxima not well represented over mountainous regions. Furthermore, ERA5’s representation of the diurnal cycle is too simplified, with less interannual variability in the time of maximum relative to observations over many regions.

Changes in regional wet heatwave in Eurasia during summer (1979–2017)

Wet heatwaves can have more impact on human health than hot dry heatwaves. However, changes in these have received little scientific attention. Using the ECMWF Reanalysis v5 reanalysis dataset, wet-bulb temperatures (T w) were used to investigate the spatial-temporal variation of wet heatwaves in Eurasia for 1979–2017. Wet heatwaves were defined as three day or longer periods when T w was above the 90th percentile of the summer distribution and characterized by amplitude, duration and frequency. Maximum values of amplitude, close to 31 °C, occur in the Indus–Ganges plain, the lower Yangtze valley, and the coasts of the Persian Gulf and Red Sea. Significant positive trends in the frequency and amplitude of wet heatwaves have occurred over most of Eurasia though with regional variations. Changes in heatwave amplitude (HWA) are largely driven by changes in summer mean T w. For Eurasia as a whole, increases in temperature contribute more than six times the impact of changes in relative humidity (RH) to changes in T w HWA. Changes in T w have a strong dependence on climatological RH with an increase in RH of 1% causing a T w increase of 0.2 °C in arid regions, and only increasing T w by 0.1 °C in humid regions. During T w heatwaves in Europe, parts of Tibet, India, East Asia and parts of the Arabian Peninsula both temperature and humidity contribute to the increase in T w, with temperature the dominant driver. During wet heatwaves in part of Russia, changes in humidity are weak and the increase in T w is mainly caused by an increase in temperature. In the Mediterranean and Central Asia, RH has fallen reducing the increase in T w from general warming.

The Diurnal Variation in Stratospheric Ozone from MACC Reanalysis, ERA-Interim, WACCM, and Earth Observation Data: Characteristics and Intercomparison

In this study, we compare the diurnal variation in stratospheric ozone of the MACC (Monitoring Atmospheric Composition and Climate) reanalysis, ECMWF Reanalysis Interim (ERA-Interim), and the free-running WACCM (Whole Atmosphere Community Climate Model). The diurnal variation of stratospheric ozone results from photochemical and dynamical processes depending on altitude, latitude, and season. MACC reanalysis and WACCM use similar chemistry modules and calculate a similar diurnal cycle in ozone when it is caused by a photochemical variation. The results of the two model systems are confirmed by observations of the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) experiment and three selected sites of the Network for Detection of Atmospheric Composition Change (NDACC) at Mauna Loa, Hawaii (tropics), Bern, Switzerland (midlatitudes), and Ny-Ålesund, Svalbard (high latitudes). On the other hand, the ozone product of ERA-Interim shows considerably less diurnal variation due to photochemical variations. The global maxima of diurnal variation occur at high latitudes in summer, e.g., near the Arctic NDACC site at Ny-Ålesund, Svalbard. The local OZORAM radiometer observes this effect in good agreement with MACC reanalysis and WACCM. The sensed diurnal variation at Ny-Ålesund is up to 8% (0.4 ppmv) due to photochemical variations in summer and negligible during the dynamically dominated winter. However, when dynamics play a major role for the diurnal ozone variation as in the lower stratosphere (100–20 hPa), the reanalysis models ERA-Interim and MACC which assimilate data from radiosondes and satellites outperform the free-running WACCM. Such a domain is the Antarctic polar winter where a surprising novel feature of diurnal variation is indicated by MACC reanalysis and ERA-Interim at the edge of the polar vortex. This effect accounts for up to 8% (0.4 ppmv) in both model systems. In summary, MACC reanalysis provides a global description of the diurnal variation of stratospheric ozone caused by dynamics and photochemical variations. This is of high interest for ozone trend analysis and other research which is based on merged satellite data or measurements at different local time.

Effects of Cropland Expansion on Temperature Extremes in Western India from 1982 to 2015

India has experienced extensive land cover and land use change (LCLUC). However, there is still limited empirical research regarding the impact of LCLUC on climate extremes in India. Here, we applied statistical methods to assess how cropland expansion has influenced temperature extremes in India from 1982 to 2015 using a new land cover and land use dataset and ECMWF Reanalysis V5 (ERA5) climate data. Our results show that during the last 34 years, croplands in western India increased by ~33.7 percentage points. This cropland expansion shows a significantly negative impact on the maxima of daily maximum temperature (TXx), while its impacts on the maxima of daily minimum temperature and the minima of daily maximum and minimum temperature are limited. It is estimated that if cropland expansion had not taken place in western India over the 1982 to 2015 period, TXx would likely have increased by 0.74 (±0.64) °C. The negative impact of croplands on reducing the TXx extreme is likely due to evaporative cooling from intensified evapotranspiration associated with croplands, resulting in increased latent heat flux and decreased sensible heat flux. This study underscores the important influences of cropland expansion on temperature extremes and can be applicable to other geographic regions experiencing LCLUC.

CMIP5 model performance of significant wave heights over the Indian Ocean using COWCLIP datasets

Wind-generated surface gravity waves forms an integral part in modulating the air-sea exchange processes. Information of wave parameters is also very essential in planning marine- and coastal-related activities. It is now well recognized that wind-wave activity shows changing trends over the global ocean basins. Numerous studies have addressed the projected changes in significant wave height for the Indian Ocean (IO) region, and there is a need to conduct thorough performance evaluation of global climate models (GCMs) over this region for futuristic planning. With this motivation, the present study examined the performance of historical dynamical wave climate simulations generated under the Coordinated Ocean Wave Climate Projections (COWCLIP) experiment. The simulations utilized near-surface wind speed datasets from 8 CMIP5 (Fifth phase of Coupled Model Intercomparison Project) GCMs to force a spectral wave model. The skill level of individual GCM forced wave simulations and multi-model mean (MMM) in reproducing the significant wave height (SWH) over four different sub-domains in the IO was evaluated with reference to the ECMWF Reanalysis 5th Generation (ERA5) datasets. Several performance metrics such as the Taylor Skill, M-Score, Model Climate Performance Index (MCPI), and Model Variability Index (MVI) are employed to establish the skill level of model simulations. The study deciphers that model performance is highly reliant on the region and its characteristics. Representation of the historical wave climate over the Arabian Sea (AS) and the Bay of Bengal (BoB) regions is remarkable in the COWCLIP datasets. However, there are discrepancies noticed in SWH distribution over the South Indian Ocean (SIO) attributed to model limitations in adequately reproducing swell wave fields over that region. The MMM constructed using the best-performing models (MRI-CGCM3, ACCESS1.0, INMCM4, HadGEM2-ES, and BCC-CSM1.1) is found consistent at all the sub-domains. The study signifies that the performance evaluation of GCM forced wave simulations is crucial before employing them for practical applications. Best-performing models listed from this study can be used to establish futuristic scenarios of SWH in a changing climate for the IO region.

Impact of the Assimilation of INSAT-3D Sounder Retrieved Temperature and Humidity Profiles on Extreme Rainfall Event Forecast

In the present study, the impact of the assimilation of the Indian National Satellite (INSAT-3D) retrieved temperature and humidity profiles are evaluated during a heavy rainfall event. The Weather Research and Forecasting (WRF) and its three-dimensional variational (3D-Var) data assimilation system are used in this study. The extreme rainfall event which occurred during June 12th, 2017, to June 15th, 2017, over Bangladesh and adjoining region is taken as the case study. The analysis obtained after assimilation is compared with the European Centre for Medium-Range Weather Forecasts (ECMWF) re-analysis. Results shows quite good improvement in temperature and humidity profiles when compared with ECMWF re-analysis. The model predicted 72 h rainfall forecast is also found to improve on the assimilation of INSAT-3D retrieved temperature and humidity profiles. From the present study, it is observed that INSAT-3D data have large impact on the humidity profiles after assimilation.

Using a network of temperature lidars to identify temperature biases in the upper stratosphere in ECMWF reanalyses

Abstract. To advance our understanding of the stratosphere, high-quality observational datasets of the stratosphere are needed. It is commonplace that reanalysis datasets are used to conduct stratospheric studies. However, the accuracy of these reanalyses at these heights is hard to infer due to a lack of in situ measurements. Satellite measurements provide one source of temperature information. As some satellite information is already assimilated into reanalyses, the direct comparison of satellite temperatures to the reanalysis is not truly independent. Stratospheric lidars use Rayleigh scattering to measure density in the middle and upper atmosphere, allowing temperature profiles to be derived for altitudes from 30 km (where Mie scattering due to stratospheric aerosols becomes negligible) to 80–90 km (where the signal-to-noise ratio begins to drop rapidly). The Network for the Detection of Atmospheric Composition Change (NDACC) contains several lidars at different latitudes that have measured atmospheric temperatures since the 1970s, resulting in a long-running upper-stratospheric temperature dataset. These temperature datasets are useful for validating reanalysis datasets in the stratosphere, as they are not assimilated into reanalyses. Here, stratospheric temperature data from lidars in the Northern Hemisphere between 1990–2017 were compared with the European Centre for Medium-Range Weather Forecasts ERA-Interim and ERA5 reanalyses. To give confidence to any bias found, temperature data from NASA's EOS Microwave Limb Sounder were also compared to ERA-Interim and ERA5 at points over the lidar sites. In ERA-Interim a cold bias of −3 to −4 K between 10 and 1 hPa was found when compared to both measurement systems. Comparisons with ERA5 found a small bias of magnitude 1 K which varies between cold and warm bias with height between 10 and 1 hPa, indicating a good thermal representation of the middle atmosphere up to 1 hPa. A further comparison was undertaken looking at the temperature bias by year to see the effects of the assimilation of the Advanced Microwave Sounding Unit-A (AMSU-A) satellite data and the Constellation Observing System for Meteorology, Ionosphere, and Climate GPS Radio Occultation (COSMIC GPSRO) data on stratospheric temperatures within the aforementioned ERA analyses. It was found that ERA5 was sensitive to the introduction of COSMIC GPSRO in 2007 with the reduction of the cold bias above 1 hPa. In addition to this, the introduction of AMSU-A data caused variations in the temperature bias between 1–10 hPa between 1997–2008.

Evaluation of the Perspective of ERA-Interim and ERA5 Reanalyses for Calculation of Drought Indicators for Uzbekistan

The arid and semiarid regions of Uzbekistan are sensitive and vulnerable to climate change. However, the sparse and very unevenly distributed meteorological stations within the region provide limited data for studying the region’s climate variation. The aim of this work was to evaluate the performance of the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA)-Interim and ERA5 products for the fields of near-surface temperature, humidity, and precipitation over Uzbekistan from 1981 to 2018 using observations from 74 meteorological stations. Major results suggested that the reanalysis datasets match well with most of the observed climate records, especially in the plain areas. While ERA5, with a high spatial resolution of 0.1°, is able more accurately reproduce mountain ranges and valleys. Compared to ERA-Interim, the climatological biases in temperature, humidity, and total precipitation from ERA5 are clearly reduced, and the representation of inter-annual variability is improved over most regions of Uzbekistan. Both reanalyses show a high level of agreement with observations on the standardized precipitation evaporation index (SPEI) with a correlation coefficient of 0.7–0.8.Although both of these ECMWF products can be successfully implemented for the calculation of atmospheric drought indicators for Uzbekistan and adjacent regions of Central Asia, the newer and advanced ERA5 is preferred.

Gravity wave variations and contributions to stratospheric sudden warming using long-term ERA5 model output

This work analyzed ERA5 (ECMWF ReAnalysis) data from 1979 to 2018 to study changes in stratospheric gravity waves (GWs) associated with stratospheric sudden warming (SSWs). GW variations are examined by separating them into polar vortex split and displacement events. In general, GW amplitudes show enhancements prior to the wind reversal at 10 hPa and 60°N and reductions after the wind reversal. GW enhancements are larger during polar vortex split events compared to displacement events, likely due to the location of the polar vortex and background wind conditions. Locations of GW enhancements are different between split events and displacement events and these locations correlate with the locations of polar vortex edge where background wind is strong. GW drag (GWD) and Eliassen-Palm (EP) flux divergences are also analyzed to understand GW contributions to occurrences of SSWs. Our results indicate maximum GWD prior to SSWs are ~18% of the total drag, and timing of eastward zonal wind weakening is coincident with enhancements of westward GWD. These results indicate that although the main driver of SSWs are planetary waves, GWs can contribute to the occurrences of SSWs.

Drastic change in dynamics as Typhoon Lekima experiences an eyewall replacement cycle

Why does the 1909 typhoon, Lekima, become so destructive after making landfall in China? Using a newly developed mathematical apparatus, the multiscale window transform (MWT), and the MWT-based localized mutliscale energetics analysis and theory of canonical transfer, this study is intended to give a partial answer from a dynamical point of view. The ECMWF reanalysis fields are first reconstructed onto the background window, the TC-scale window, and the convection-scale window. A localized energetics analysis is then performed, which reveals to us distinctly different scenarios before and after August 8–9, 2019, when an eyewall replacement cycle takes place. Before that, the energy supply in the upper layer is mainly via a strong upper layer-limited baroclinic instability; the available potential energy thus-gained is then converted into the TC-scale kinetic energy, with a portion to fuel Lekima’s upper part, another portion carried downward via pressure work flux to maintain the cyclone’s lower part. After the eyewall replacement cycle, a drastic change in dynamics occurs. First, the pressure work is greatly increased in magnitude. A positive baroclinic transfer almost spreads throughout the troposphere, and so does barotropic transfer; in other words, the whole air column is now both barotropically and baroclinically unstable. These newly occurred instabilities help compensate the increasing consumption of the TC-scale kinetic energy, and hence help counteract the dissipation of Lekima after making landfalls.

The Effects of Lake Representation on the Regional Hydroclimate in the ECMWF Reanalyses

AbstractLakes are an integral part of the geosphere, but they are challenging to represent in Earth system models which either exclude lakes or prescribe properties without simulating lake dynamics. In ECMWF Interim reanalysis (ERA-Interim), lakes are represented by prescribing lake surface water temperatures (LSWT) from external data sources, while the newer generation ERA5 introduces the FLake parameterization scheme to the modelling system with different LSWT assimilation data sources. This study assesses the performance of these two reanalyses over three regions with the largest lakes in the world (Laurentian Great Lakes, African Great Lakes, and Lake Baikal) to understand the effects of their simulation differences on hydrometeorological variables. We find that differences in lake representation alter the associated hydrological and atmospheric processes and can affect regional hydroclimatic assessments. There are prominent differences in LSWT between the two datasets which influence the simulation of lake-effect snowstorms in the Laurentian winters and lake-land breeze circulation patterns in the African region. Generally, ERA5 has warmer LSWT in all three regions for most months (by 2-12 K) and its evaporation rates are up to twice the magnitudes in ERA-Interim. In the Laurentian lakes, ERA5 has strong biases in LSWT and evaporation magnitudes. Over Lake Baikal and the African Great Lakes, ERA5 LSWT magnitudes are closer to satellite-based datasets, albeit with warm bias (1-4 K), while ERA-Interim underestimates the magnitudes. ERA5 also simulates intense precipitation hotspots in lake proximity that are not visible in ERA-Interim and other observation-based datasets. Despite these limitations, ERA5 improves the simulation of lake-land circulation patterns across the African Great Lakes.

Characteristics and Synoptic Patterns of Regional Extreme Rainfall over the Central and Eastern Tibetan Plateau in Boreal Summer

In this research, the observation datasets from 106 gauge stations over the central and eastern areas of the Tibetan Plateau (TP) and the ERA (ECMWF Re-Analysis)-Interim reanalysis datasets in the summers of 1981–2016 are used to study the characteristics and synoptic patterns of extreme precipitation events over the TP. By using a modern statistical method, the abnormal circulation characteristics at high, middle, and low latitudes in the Northern Hemisphere during extreme precipitation events over the central-eastern Tibetan Plateau are discussed, and the physical mechanisms related to the extreme precipitation events are investigated. The results show that the largest amount of extreme precipitation is found in the southern and eastern areas of the TP, where the frequency of daily extreme rainfall events (exceeding 25 mm) and the frequency of all extreme precipitation events both show obvious quasi-biweekly oscillation. When the daily extreme precipitation event threshold over the TP is met and more than 5 stations show daily extreme precipitation at the same time, with at least three of them being adjacent to each other, this is determined as a regional extreme precipitation event. As such, 33 regional daily extreme precipitation events occur during the summer periods of 1981–2016. According to the influence system, the 33 regional extreme precipitation events can be divided into three types, namely the plateau trough type, the plateau shear line type, and the plateau vortex type. For the plateau trough type, the South Asian high is anomalously strong at 100 hPa. For the other two types, the South Asian high is slightly weaker than usual. For the plateau shear line type, the development of the dynamic disturbance is the strongest, reaching 200 hPa. In the plateau trough type and plateau vortex type, the water vapor is transported by the westerly belt and the southwesterly flow from the Bay of Bengal.

Early 21st Century cyclone climatology: a 3D perspective.Basic Characterization

AbstractExtra‐tropical cyclones are a relevant feature in the climate at middle and high latitudes. Despite their importance, most studies typically focus only on cyclones identified at a single atmospheric level and on events close to the surface. This paper provides a new perspective on the Southern Hemisphere (SH) cyclone events based on the multilevel cyclone tracking algorithm STACKER. The algorithm, using relative vorticity, detects the raw tracks at single levels and objectively combines them to provide the 3D events and their evolutionary timeline. As a result, a 3D cyclone climatology, based on ECMWF Reanalysis ERA‐I data from 12 pressure levels in the troposphere and lowermost stratosphere is presented. To the best of our knowledge, this is the first analysis carried out throughout the troposphere and the lowermost extratropical/subpolar stratosphere in order to give a comprehensive picture of the cyclone events as physical entities throughout their lifetime. Cyclone properties analysed are track densities, translational velocity, vorticity and lifetimes. For the subtropical and extra‐tropical SH, results support many previous ideas about cyclone characteristics, but new insights are also obtained. A total of 58,231 multilevel cyclone events lasting at least 2 days were detected, with vertical structures spanning two or more levels. This means an average of 303 cyclone events of all types per month, between 2001 and 2017, disregarding seasonality. Results show that cyclones are most frequently detected at the lowest levels of 925 and 700 hPa. By considering that cyclonic systems can be grouped into families according to their vertical extent, results per month on average show that shallow systems are the most frequent events with approximately 248 systems detected, followed by 43 intermediary and 11 deep events. Shallow and deep systems have a large percentage of events with genesis at 925 and 700 hPa. Density statistics show that shallow events are present at all latitude ranges mostly poleward of 30°S with high‐ and medium‐intensities, while intermediate ones are mostly restricted to mid‐latitudes and deep events are mostly confined to sub‐polar and polar latitudes. Cyclones over Antarctica seem to be mostly intermediary and deep cyclones, with longer lifetimes and lower velocities.

Long-Term Assessment of Onshore and Offshore Wind Energy Potentials of Qatar

Exploitation of conventional energy resources has caused a deliberate increase in the emitted carbon in the atmosphere, which catalyzes global warming trends. This is a matter of concern, especially in Qatar, where fossil fuels (oil and gas) are largely relied upon for power production. The dependency on such resources could be gradually reduced by utilizing clean and renewable energy. Resource characterization is an important step to evaluate the potentiality of available renewable energy sources. Wind energy is one among them, which has not been assessed reliably so far in Qatar. We analyzed the wind energy potential along the onshore and offshore areas of Qatar using 40 years (1979–2018) of hourly wind data extracted from the ECMWF Reanalysis v5 (ERA5) database. Monthly, seasonal, annual, and decadal mean wind power densities have been derived. Reliability tests have been carried out at select onshore and offshore locations. Trends and inter-annual variability have been assessed. The study reveals that the available wind resources are generally moderate but consistent with no intense trends during the 40 year period. An inter-annual variability in wind power has been identified, which has secured links with the El Niño–Southern Oscillation (ENSO).

Performance of water vapour retrieval from MODIS and ECMWF and their validation with ground based GPS measurements over Varanasi

Water vapour is highly variable over tropical region and sensitive to weather condition, monsoon onset, green house effect, and pollution level in Ganga River. In the present study, variability in water vapour derived from Global Positioning System (GPS) over Varanasi (25°20′N, 82°59′E) during the period 2007–2010 has been studied. The GPS-derived water vapour (WV) has been compared with those retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) and ECMWF. The GPS-WV data concurrent to MODIS and ECMWF timing has been correlated to perform further analysis. To study the accuracy of water vapour retrieved from the MODIS and ECMWF, root mean square error (RMSE), absolute error (AE), correlation and standard deviation in it are computed with respect to GPS-derived water vapour. Analysis shows an annual correlation R2 = 86%, RMSE = 9.5 mm and AE (MODIS–GPS) = 7.0 mm in MODIS retrieval and annual correlation R2 = 86%, RMSE = 6.1 mm and AE (ECMWF–GPS) = 2.4 mm in ECMWF reanalysis retrieval. Correlation of ECMWF and MODIS datasets with the GPS datasets are found to vary significantly with seasons. The correlation is high during monsoon season and low during spring season. Water vapour is found to be an indicator for the onset of monsoon.

Datasets and approaches for the estimation of rainfall erosivity over Italy: A comprehensive comparison study and a new method

The paper considers a methodology to assess rainfall erosivity in Italy for the recent decades (1981–2010), building on datasets and materials freely available, such as those included within the Climate Data Store (CDS) of the Copernicus Climate Change Service (C3S). Twenty-one referenced empirical models to assess rainfall erosivity (R-factor) based on coarse rainfall data are tested and compared; then, a custom model is calibrated, with the support of seasonal rainfall pattern clustering by means of the Self-Organizing Map. Moreover, a large database of sub-hourly rainfall observations, covering the period 2002–2011, is collected and used for validation. Model performances are analysed at the point-scale of the rain gauges and at the spatial scale of different relevant gridded rainfall products: the fifth generation of ECMWF ReAnalysis (ERA5, ERA5-Land), the gridded European observational dataset (E-OBS), all included in the CDS, and SCIA-ISPRA (the Italian standard rainfall gridded dataset).New Hydrological Insights from the RegionThe proposed methodology provides four alternatives of spatially distributed rainfall erosivity datasets covering Italy with diverse levels of reliability. Analysis of results shows that the best performance is achieved by the combined use of the custom model and the SCIA-ISPRA dataset, followed by ERA5-Land, with the main source of error lying in the use of an empirical model instead of the rigorous model for R-factor estimation, and secondly in the use of gridded rainfall data instead of point-scale rainfall observations.

Evaluation of satellite/reanalysis precipitation products over Iran

ABSTRACT This study aims to evaluate the satellite- and model-based precipitation products against a relatively dense station network of Iran Meteorological Organization (IRIMO) from January 2015 to June 2018 at daily timescale over Iran. The evaluations are carried out based on continuous and categorical statistical metrics. First, we employed daily satellite soil moisture (SM) observations from the Advanced Microwave Scanning Radiometer 2 (AMSR2) for estimating rainfall through the use of the relatively new SM2RAIN approach (SM2R-AMSR2). Next, we validated rainfall estimations from satellite/reanalysis products including version 05 daily Global Precipitation Measurement (GPM) Integrated Multi-Satellite Retrievals for GPM (IMERG) Early (IMERG-DE), Late (IMERG-DL), and Final Daily (IMERG-DF) Runs and the European Centre for Medium-Range Weather Forecasts’ ReAnalysis Interim (ERA-Interim), ECMWF ReAnalysis 5th Generation (ERA5) and SM2R-AMSR2. Based on the probability density function (PDF), all satellite and model products capture more (less) precipitation events than the reference data set for precipitation under (upper) 5.0 mm day−1 threshold. Regarding the mean absolute error (MAE) and root-mean-square error (RMSE) quantities, the ERA5 product has the lowest error relative to other products. Also, the threat score (TS) indicates that this product has the highest accuracy. ERA-Interim and IMERG-DF had roughly similar performances. The results reveal the overall superiority of ERA5 data over other products as it has the highest correlation with observation and the best discrimination between occurrence and non-occurrence of the precipitation events. Also, the results of spatial correlations show that ERAs have a higher agreement with in situ observation when compare to satellite products, over the north to northwest of Iran, where rain is formed mainly by synoptic-scale systems.

Forecast skill of the Indian monsoon and its onset in the ECMWF seasonal forecasting system 5 (SEAS5)

Accurate forecasting of variations in Indian monsoon precipitation and progression on seasonal time scales remains a challenge for prediction centres. We examine prediction skill for the seasonal-mean Indian summer monsoon and its onset in the European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal forecasting system 5 (SEAS5). We analyse summer hindcasts initialised on 1st of May, with 51 ensemble members, for the 36-year period of 1981–2016. We evaluate the hindcasts against the Global Precipitation Climatology Project (GPCP) precipitation observations and the ECMWF reanalysis 5 (ERA5). The model has significant skill at forecasting dynamical features of the large-scale monsoon and local-scale monsoon onset tercile category one month in advance. SEAS5 shows higher skill for monsoon features calculated using large-scale indices compared to those at smaller scales. Our results also highlight possible model deficiencies in forecasting the all India monsoon rainfall.

Assessment and calibration of MODIS precipitable water vapor products based on GPS network over China

The ground-based GPS provides a promising way to assess and calibrate precipitable water vapor (PWV) products from the Moderate-Resolution Imaging Spectrometer (MODIS) which has high spatial resolution and near global coverage. This study utilized PWV at about 260 ground-based GPS stations from the Crustal Movement Observation Network of China (CMONOC) from 2015 to 2018 to comprehensively assess the MODIS Near Infrared (NIR) PWV products as well as the latest ECMWF reanalysis, ERA5. Results reveal a general underestimate of MODIS PWV compared to GPS over China, with mean bias of 1.32 mm (GPS-MODIS), compared to −0.28 mm for ERA5 (GPS-ERA5). Taking GPS PWV as references, the average MODIS PWV error root mean square (RMS) is about 5.35 mm, with correlation coefficient (R) of ~90% between GPS and MODIS PWV, compared to the RMS of 1.73 mm and R of ~98% for ERA5. PWV differences between MODIS and GPS also show clear seasonal and climate type dependency over China. A refined linear MODIS PWV calibration model taking into account of climate region difference was then developed and examined. The calibrated MODIS PWV at more than 800 independent GPS stations from China Meteorological Administration (CMA) in the year of 2016 show obvious improvements, with RMS reduced by about 14.7, 17.7, 20.9, 2.5 and 11.3% in tropical monsoon (TM), subtropical monsoon (SM), midlatitude monsoon (MM), humid continental (HC) and plateau (PL) climate region, respectively. Compared to the unified calibration model which does not distinguish the climate regions, the RMS values after calibration using the refined model are reduced by 10.5, 8.3, 9.1, and 11.9% in TM, SM, MM and Plateau climate (PL) region, respectively. In addition, bias values are reduced from 2.01, 3.42, 1.50 and 0.84 mm to 1.64, 0.33, 0.68 and −0.06 mm in TM, SM, MM, PL region, respectively.

Contributions of Local and Remote Atmospheric Moisture Fluxes to East China Precipitation Estimated from CRA-40 Reanalysis

China Meteorological Administration (CMA) recently released its 40-yr (1979–2018) global Chinese reanalysis (CRA-40) dataset. To assess performance of the CRA-40 data in quantifying the regional water cycle, contributions of local and remote atmospheric moisture fluxes to precipitation in East China derived from CRA-40 are compared with those derived from the ECMWF reanalysis version 5 (ERA-5). Observed precipitation and evaporation data are also used for validation. As for mean precipitation, CRA-40 matches the observation better in winter and spring than in summer, with a larger wet bias (1.41 mm day−1) in summer than that in ERA-5 (0.97 mm day−1), particularly over South China. The conservation of atmospheric water vapor over East China measured by CRA-40 is comparable to that of ERA-5. Both reanalyses show a dominant role of the remote moisture transport in the East China precipitation. In comparison, the annual precipitation induced by the moisture influx from the west of the study domain in CRA-40 is 80 mm less than that in ERA-5. The recycling ratio of annual mean precipitation in CRA-40 is approximately 21.1%, slightly larger than that in ERA-5 (20.1%). The maximum difference of each hydrological component between the two datasets appears in the summer horizontal moisture influx (3.57 × 107 kg s−1; ERA-5 is larger) and winter runoff (1.84 × 107 kg s−1; CRA-40 is larger). CRA-40 shows better performance than ERA-5 in capturing the interannual variability of precipitation over East China, as evinced by a higher correlation coefficient with the observation (0.77 versus 0.33). The trend of summer precipitation since 2011 is better reproduced in CRA-40. Both reanalyses show prominent contribution of the southern moisture influx to the interannual variation of precipitation. This study demonstrates the reliability of CRA-40 in representing the hydrological cycle over East China and provides a useful reference for future application of CRA-40 in water cycle studies.