The Saharan heat low (SHL) plays a pivotal role in the West African monsoon system in spring and summer. The recent trend in SHL activity has been analysed using two sets of numerical weather ...prediction (NWP) model reanalyses and Atmospheric Models Intercomparison Project simulations from 15 climate models performed in the framework of the 5th Coupled Models Intercomparison Project (CMIP5) exercise. A local increase of temperature in the Sahara during the 90s is found in the two sets of NWP models temperature. This increase is stronger within the SHL region than over the surrounding areas. Using different temporal filters (under 25 days, 25–100 days and above 300 days), we show that this is accompanied by a slight but widespread increase of temperature, and a change in the filtered signal under 25 days during the transition period of the 90s. We also show that SHL pulsations occurring at different time scales impact the West Africa climate on a variety of spatial scales, from the regional scale (for the high band pass) to the synoptic scale (for the low band pass signal). Despite a large variability in the temporal trends for 15 climate models from the CMIP5 project, the warming trend in the 90s is observed in the models ensemble mean. Nevertheless, large discrepancies are found between the NWP models reanalyses and the climate model simulations regarding the spatial and temporal evolutions of the SHL as well as its impact on West African climate at the different time scales. These comparisons also reveal that climate models represent the West African monsoon interactions with SHL pulsations quite differently. We provide recommendations to use some of them depending on the time scales of the processes at play (synoptic, seasonal, interannual) and based on key SHL metrics (location, mean intensity, global trend, interaction with the West African monsoon dynamics).
Intercomparison and evaluation of the global ocean surface mixed layer depth (MLD) fields estimated from a suite of major ocean syntheses are conducted. Compared with the reference MLDs calculated ...from individual profiles, MLDs calculated from monthly mean and gridded profiles show negative biases of 10–20 m in early spring related to the re-stratification process of relatively deep mixed layers. Vertical resolution of profiles also influences the MLD estimation. MLDs are underestimated by approximately 5–7 (14–16) m with the vertical resolution of 25 (50) m when the criterion of potential density exceeding the 10-m value by 0.03 kg m
−3
is used for the MLD estimation. Using the larger criterion (0.125 kg m
−3
) generally reduces the underestimations. In addition, positive biases greater than 100 m are found in wintertime subpolar regions when MLD criteria based on temperature are used. Biases of the reanalyses are due to both model errors and errors related to differences between the assimilation methods. The result shows that these errors are partially cancelled out through the ensemble averaging. Moreover, the bias in the ensemble mean field of the reanalyses is smaller than in the observation-only analyses. This is largely attributed to comparably higher resolutions of the reanalyses. The robust reproduction of both the seasonal cycle and interannual variability by the ensemble mean of the reanalyses indicates a great potential of the ensemble mean MLD field for investigating and monitoring upper ocean processes.
Sixteen monthly air–sea heat flux products from global ocean/coupled reanalyses are compared over 1993–2009 as part of the Ocean Reanalysis Intercomparison Project (ORA-IP). Objectives include ...assessing the global heat closure, the consistency of temporal variability, comparison with other flux products, and documenting errors against in situ flux measurements at a number of OceanSITES moorings. The ensemble of 16 ORA-IP flux estimates has a global positive bias over 1993–2009 of 4.2 ± 1.1 W m
−2
. Residual heat gain (i.e., surface flux + assimilation increments) is reduced to a small positive imbalance (typically, +1–2 W m
−2
). This compensation between surface fluxes and assimilation increments is concentrated in the upper 100 m. Implied steady meridional heat transports also improve by including assimilation sources, except near the equator. The ensemble spread in surface heat fluxes is dominated by turbulent fluxes (>40 W m
−2
over the western boundary currents). The mean seasonal cycle is highly consistent, with variability between products mostly <10 W m
−2
. The interannual variability has consistent signal-to-noise ratio (~2) throughout the equatorial Pacific, reflecting ENSO variability. Comparisons at tropical buoy sites (10°S–15°N) over 2007–2009 showed too little ocean heat gain (i.e., flux into the ocean) in ORA-IP (up to 1/3 smaller than buoy measurements) primarily due to latent heat flux errors in ORA-IP. Comparisons with the Stratus buoy (20°S, 85°W) over a longer period, 2001–2009, also show the ORA-IP ensemble has 16 W m
−2
smaller net heat gain, nearly all of which is due to too much latent cooling caused by differences in surface winds imposed in ORA-IP.
In recent years, the frequency and severity of cloudburst considerably increased over southern rim of Himalayas due to hot climate that leads to loss of human lives and damage properties. The ...observed rainfall data shows that cloudburst events with heavy rainfall ∼ 100–200 mm/day are common over the Himalayan region during the summer monsoon period. It is very necessary to understand the mechanisms associated with such type of short span of high impact localised weather events over the regions where observations are limited. Therefore, one of best way to study the mechanism associated with the formation and development of cloudburst is using the available high resolution reanalysis datasets. An effort is made to understand the role of atmospheric conditions that control the evolution of cloudburst event by considering two reanalyses datasets such as high resolution IMDAA and ERA5 reanalyses. The present study analysed a cloudburst case that occurred on 3rd August 2012 at 10 pm with heavy rainfall of ∼ 100 mm in a very short span of time over the Uttarkashi district. Various dynamic and thermodynamic parameters are calculated from the two datasets with an aim of determining the best representation of severity of the cloudburst event. It is noticed that the evolution of dynamic and thermodynamic variables is well represented in the high resolution IMDAA dataset as compared to the ERA5 dataset. The amount and spatial distribution of rainfall from IMDAA reanalyses are well comparable with satellite estimated rainfall (GPM), having better correlation (0.60) with the observed rainfall as compared to the ERA5 (0.28). The rainfall time bias over the Uttarkashi district is larger in ERA5 reanalyses (∼ 5 h) than in the IMDAA (∼ 3 h). The ERA5 is not able to capture such type of localise high rainfall event due to its low resolution, compared to high resolution reanalyses (12 km) of IMDAA. The observations also indicate that the moisture flux from the Bay of Bengal (BoB) and Arabian Sea interacted with northwesterly dry air over Uttarkashi and the orographic uplifting resulted the cloudburst. Overall, results show that the eveolution and mechanism associated with the cloudburst is better represented in IMDAA than the ERA5. More cases are required to be studied to further support the findings of this study.
•Frequency and severity of the cloudburst significantly increased over southern rim of Himalayan region due to warm climate.•It is very essential to understand the mechanisms associated with cloudburst over the regions where observations are limited.•Therefore, high resolution reanalysis datasets is one of the best ways to study the mechanism associated with cloudburst.•Overall, the results show that evolution and mechanism associated with cloudburst is better represented in IMDAA than ERA5.
Observations from the historical meteorological observing network contain many artefacts of non‐climatic origin which must be accounted for prior to using these data in climate applications. ...State‐of‐the‐art homogenisation approaches use various flavours of pairwise comparison between a target station and candidate neighbour station series. Such approaches require an adequate number of neighbours of sufficient quality and comparability – a condition that is met for most station series since the mid‐20th Century. However, pairwise approaches have challenges where suitable neighbouring stations are sparse, as remains the case in vast regions of the globe and is common almost everywhere prior to the early 20th Century. Modern sparse‐input centennial reanalysis products continue to improve and offer a potential alternative to pairwise comparison, particularly where and when observations are sparse. They do not directly ingest or use land‐based surface temperature observations, so they are a formally independent estimate. This may be particularly helpful in cases where structurally similar changes exist across broad networks, which challenges current techniques in the absence of metadata. They also potentially offer a valuable methodologically distinct method, which would help explore structural uncertainty in homogenisation techniques. The present study compares the potential of spatially‐interpolated sparse‐input reanalysis products to neighbour‐based approaches to perform homogenisation of global monthly land surface air temperature records back to 1850 based upon the statistical properties of station‐minus‐reanalysis and station‐minus‐neighbour series. This shows that neighbour‐based approaches likely remain preferable in data dense regions and epochs. However, the most recent reanalysis product, NOAA‐CIRES‐DOE 20CRv3, is potentially preferable in cases where insufficient neighbours are available. This may in particular affect long‐term global average estimates where a small number of long‐term stations in data sparse regions will make substantial contributions to global estimates and may contain missed data artefacts in present homogenisation approaches.
Homogenisation of land surface air temperature records requires the availability of a high‐quality estimate of the true underlying climate series. State‐of‐the‐art techniques use neighbouring station comparisons, but these will struggle in regions and periods when the network is sparse. Sparse‐input centennial‐scale reanalyses are shown herein, for the first time with the advent of the new 20CRv3 product, to offer a potential alternative avenue.
Several researchers have postulated that, under a changing climate due to anthropogenic forcing, an intensification of the water cycle is already under way. This is usually related to increases in ...hydrological fluxes as precipitation (P), evapotranspiration (E), and river discharge (R). It is under debate, however, whether such observed or reconstructed flux changes are real and on what scales. Large‐scale increase or decrease of the flux deficit (P‐E‐R), i.e., flux changes that do not compensate, would lead to acceleration or deceleration of water storage anomalies potentially visible in Gravity Recovery and Climate Experiment (GRACE) data. In agreement with earlier studies, we do find such accelerations in global maps of gridded GRACE water storage anomalies over 2003–2012. However, these have been generally associated with interannual and decadal climate variability. Yet we show that even after carefully isolating and removing the contribution of El Niño that partially masks long‐term changes, using a new method, accelerations of up to 12 mm/yr2 remain in regions such as Australia, Turkey, and Northern India. We repeat our analysis with flux fields from two global atmospheric reanalyses that include land surface models (ERA‐Interim and MERRA‐Land). While agreeing well with GRACE on shorter time scales, they fall short in displaying long‐term trends corresponding to GRACE accelerations. We hypothesize that this may be due to time‐varying biases in the reanalysis fluxes as noticed in other studies. We conclude that even though its data record is short, GRACE provides new information that should be used to constrain future reanalyses toward a better representation of long‐term water cycle evolution.
Key Points
A new method for removing ENSO‐related interannual variability is presented
GRACE sees regions of distinct water storage acceleration, even after removing an “ENSO” mode
Atmospheric‐land surface reanalyses largely fail to reproduce corresponding flux trends
The clear knowledge of decadal variability of surface solar radiation (SSR) is of vitally significant for understanding hydrological and biological processes and climate prediction. However, existing ...studies have shown observed SSR over China may have large discrepancies and inhomogeneity in decadal variability due to sensitivity drift, inaccurate calibrations and instrument replacement. Therefore, a new procedure of station selection was proposed to eliminate errors and to derive “true” SSR values in this study. Afterward, two satellite retrieves of SSR, including Clouds and the Earth's Radiant Energy System‐energy balanced and filled product (CERES‐EBAF) (edition 4) and Global Energy and Water Cycle Experiment‐Surface Radiation Budget (GEWEX‐SRB) (Version 3.0), and three reanalysis products, including National Centers for Environmental Prediction‐National Center for Atmospheric Research (NCEP‐NCAR), national centers for environmental prediction‐/department of energy (NCEP‐DOE) and Modern‐Era Retrospective analysis for Research and Applications, version 2 (MERRA‐2) were evaluated using “true” SSR values at 39 homogeneous stations from the China Meteorological Administration and it was found that although all five products overestimated SSR, two satellite retrieves showed better accuracy with an overall R of 0.95, an root mean squared error (RMSE) of 20.4 W m−2 and mean absolute bias error (MAE) of 14.9 W m−2 for CERES‐EBAF and an overall R of 0.92, an RMSE of 27.7 W m−2 and MAE of 21.2 W m−2 for GEWEX‐SRB across China. Meanwhile, inter‐comparisons between trends of observations and trends of two satellite retrieves in this study showed that the new trends derived from two satellite retrieves (+0.78 W m−2 decade−1) were good agreement with trends of observation (+0.92 W m−2 decade−1) from 1994 to 2015. However, trends of SSR (+5.8 W m−2 decade−1) in situ measurements were still in disagreement with the trends of SSR (−3.7 W m−2 decade−1) derived from two satellite retrieves from 1984 to 1993 because of the sensitivity drift and instrument replacement in this period. The possible reasons for decadal variability of SSR in China were detected and it was found that variations in aerosol optical depth (AOD) and aerosol‐cloud interaction, rather than cloud, were suggested to be likely the main influencing factor of decadal variability of SSR across China from 1984 to 2015.
Annual anomalies series of SSR from satellite‐derived or reanalysis‐derived (blue) and ground‐based (red) data.
The intertropical convergence zone (ITCZ) is usually analyzed in terms of the precipitation field. This study presents a new climatology of the ITCZ based on winds from ERA Interim reanalyses for the ...period 1990–2009. The central latitude of the ITCZ is defined as the zero crossing of the meridional wind averaged over 10 model levels below 900 hPa. Results of the zonal averaging of the meridional wind and wind convergence are compared with the zonally averaged precipitation from the ERA Interim and TRMM data sets. Collocation properties of precipitation maxima and the central latitude of the ITCZ are discussed for different land and ocean regions. It is found that the location of the ITCZ in wind and precipitation fields coincides over the Atlantic and east Pacific. Over other regions and especially over the tropical continents, the fields on average do not coincide.
Key Points
ERA Interim reanalyses provide good description of tropical surface winds
Comparison between ITCZ defined by precipitation and winds is performed
Collocation is found in East Pacific and Atlantic only
This paper presents some improvements of a probabilistic quantitative precipitation forecasting method based on analogues, formerly developed on small basins located in South-Eastern France. The ...scope is extended to large scale basins mainly influenced by frontal systems, considering a case study area related to the Saône river, a large basin in eastern France. For a given target situation, this method consists in searching for the most similar situations observed in a historical meteorological archive. Precipitation amounts observed during analogous situations are then collected to derive an empirical predictive distribution function, i.e. the probabilistic estimation of the precipitation amount expected for the target day. The former version of this forecasting method (Bontron, 2004) has been improved by introducing two innovative variables: temperature, that allows taking seasonal effects into account and vertical velocity, which enables a better characterization of the vertical atmospheric motion. The new algorithm is first applied in a perfect prognosis context (target situations come from a meteorological reanalysis) and then in an operational forecasting context (target situations come from weather forecasts) for a three years period. Results show that this approach yields useful forecasts, with a lower false alarm rate and improved performances from the present day D to day D+2.
•A precipitation forecast method based on analogues is adapted to a large river basin.•Temperature is introduced to take into account seasonal effects on precipitation.•Vertical velocity is introduced to better characterise large-scale vertical motion.•The upgraded analogue method is then applied in operational forecasting context.•A substantial increase in skill is obtained until the lead-time of three days.
We assess the correspondence between precipitation products from atmospheric reanalyses (ERA‐40, NCEP‐1, and NCEP‐2), the Climate Prediction Center (CPC) Merged Analyses of Precipitation (CMAP‐1 and ...CMAP‐2), and the Global Precipitation Climatology Project Version 2 (GPCP‐2) with adjusted observational precipitation (AOP) from China for 1979–2001 and also for ERA‐40 and NCEP‐1 over 1958–1978. In general, we conclude that CMAP‐1 and GPCP‐2 agree more closely with AOP than the reanalysis products do, although ERA‐40 data agree more closely with AOP than NCEP data. The percentages of precipitation differences (PPDs) across China between annual ERA‐40, NCEP‐1, NCEP‐2, CMAP‐1, CMAP‐2, and GPCP‐2 data and AOP are −12, 22, 14, −8, −7, and −15%, respectively, for 1979–2001. Although relatively small biases are evident for China as a whole, maximum PPDs, usually occurring around the Qinghai‐Tibetan Plateau, can exceed 1000%, indicating a strong terrain dependence of gridded precipitation data. GPCP‐2, although characterized by greater underestimation for most of China compared with CMAP‐1, exhibits a smaller biases range and hence may be better than CMAP‐1. Compared with the NCEP‐1 system, NCEP‐2 represents an improvement as NCEP‐2 precipitation agrees more closely with AOP than NCEP‐1 data. However, the coherence of NCEP‐2 precipitation needs further improvement. In addition, we find worse consistency and accuracy and larger positive biases in some parts of China for CMAP‐2 versus CMAP‐1, illustrating an advantage of including reanalysis data in CMAP, as CMAP‐1 does. CMAP‐1 could be further improved if they used the more skillful ERA‐40 precipitation instead of the NCEP/NCAR data.
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